WorldWideScience

Sample records for observer based estimation

  1. Observer-Based Human Knee Stiffness Estimation.

    Science.gov (United States)

    Misgeld, Berno J E; Luken, Markus; Riener, Robert; Leonhardt, Steffen

    2017-05-01

    We consider the problem of stiffness estimation for the human knee joint during motion in the sagittal plane. The new stiffness estimator uses a nonlinear reduced-order biomechanical model and a body sensor network (BSN). The developed model is based on a two-dimensional knee kinematics approach to calculate the angle-dependent lever arms and the torques of the muscle-tendon-complex. To minimize errors in the knee stiffness estimation procedure that result from model uncertainties, a nonlinear observer is developed. The observer uses the electromyogram (EMG) of involved muscles as input signals and the segmental orientation as the output signal to correct the observer-internal states. Because of dominating model nonlinearities and nonsmoothness of the corresponding nonlinear functions, an unscented Kalman filter is designed to compute and update the observer feedback (Kalman) gain matrix. The observer-based stiffness estimation algorithm is subsequently evaluated in simulations and in a test bench, specifically designed to provide robotic movement support for the human knee joint. In silico and experimental validation underline the good performance of the knee stiffness estimation even in the cases of a knee stiffening due to antagonistic coactivation. We have shown the principle function of an observer-based approach to knee stiffness estimation that employs EMG signals and segmental orientation provided by our own IPANEMA BSN. The presented approach makes realtime, model-based estimation of knee stiffness with minimal instrumentation possible.

  2. Robust Estimation for a CSTR Using a High Order Sliding Mode Observer and an Observer-Based Estimator

    Directory of Open Access Journals (Sweden)

    Esteban Jiménez-Rodríguez

    2016-12-01

    Full Text Available This paper presents an estimation structure for a continuous stirred-tank reactor, which is comprised of a sliding mode observer-based estimator coupled with a high-order sliding-mode observer. The whole scheme allows the robust estimation of the state and some parameters, specifically the concentration of the reactive mass, the heat of reaction and the global coefficient of heat transfer, by measuring the temperature inside the reactor and the temperature inside the jacket. In order to verify the results, the convergence proof of the proposed structure is done, and numerical simulations are presented with noiseless and noisy measurements, suggesting the applicability of the posed approach.

  3. ON ESTIMATING FORCE-FREENESS BASED ON OBSERVED MAGNETOGRAMS

    International Nuclear Information System (INIS)

    Zhang, X. M.; Zhang, M.; Su, J. T.

    2017-01-01

    It is a common practice in the solar physics community to test whether or not measured photospheric or chromospheric vector magnetograms are force-free, using the Maxwell stress as a measure. Some previous studies have suggested that magnetic fields of active regions in the solar chromosphere are close to being force-free whereas there is no consistency among previous studies on whether magnetic fields of active regions in the solar photosphere are force-free or not. Here we use three kinds of representative magnetic fields (analytical force-free solutions, modeled solar-like force-free fields, and observed non-force-free fields) to discuss how measurement issues such as limited field of view (FOV), instrument sensitivity, and measurement error could affect the estimation of force-freeness based on observed magnetograms. Unlike previous studies that focus on discussing the effect of limited FOV or instrument sensitivity, our calculation shows that just measurement error alone can significantly influence the results of estimates of force-freeness, due to the fact that measurement errors in horizontal magnetic fields are usually ten times larger than those in vertical fields. This property of measurement errors, interacting with the particular form of a formula for estimating force-freeness, would result in wrong judgments of the force-freeness: a truly force-free field may be mistakenly estimated as being non-force-free and a truly non-force-free field may be estimated as being force-free. Our analysis calls for caution when interpreting estimates of force-freeness based on measured magnetograms, and also suggests that the true photospheric magnetic field may be further away from being force-free than it currently appears to be.

  4. PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS

    Directory of Open Access Journals (Sweden)

    Y. Dehbi

    2017-09-01

    Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  5. Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

    Science.gov (United States)

    Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

    2017-09-01

    This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  6. Estimating Evapotranspiration Using an Observation Based Terrestrial Water Budget

    Science.gov (United States)

    Rodell, Matthew; McWilliams, Eric B.; Famiglietti, James S.; Beaudoing, Hiroko K.; Nigro, Joseph

    2011-01-01

    Evapotranspiration (ET) is difficult to measure at the scales of climate models and climate variability. While satellite retrieval algorithms do exist, their accuracy is limited by the sparseness of in situ observations available for calibration and validation, which themselves may be unrepresentative of 500m and larger scale satellite footprints and grid pixels. Here, we use a combination of satellite and ground-based observations to close the water budgets of seven continental scale river basins (Mackenzie, Fraser, Nelson, Mississippi, Tocantins, Danube, and Ubangi), estimating mean ET as a residual. For any river basin, ET must equal total precipitation minus net runoff minus the change in total terrestrial water storage (TWS), in order for mass to be conserved. We make use of precipitation from two global observation-based products, archived runoff data, and TWS changes from the Gravity Recovery and Climate Experiment satellite mission. We demonstrate that while uncertainty in the water budget-based estimates of monthly ET is often too large for those estimates to be useful, the uncertainty in the mean annual cycle is small enough that it is practical for evaluating other ET products. Here, we evaluate five land surface model simulations, two operational atmospheric analyses, and a recent global reanalysis product based on our results. An important outcome is that the water budget-based ET time series in two tropical river basins, one in Brazil and the other in central Africa, exhibit a weak annual cycle, which may help to resolve debate about the strength of the annual cycle of ET in such regions and how ET is constrained throughout the year. The methods described will be useful for water and energy budget studies, weather and climate model assessments, and satellite-based ET retrieval optimization.

  7. Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis

    Science.gov (United States)

    Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel

    2013-01-01

    This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007

  8. Longitudinal tire force estimation based on sliding mode observer

    Energy Technology Data Exchange (ETDEWEB)

    El Hadri, A.; Cadiou, J.C.; M' Sirdi, N.K. [Versailles Univ., Paris (France). Lab. de Robotique; Beurier, G.; Delanne, Y. [Lab. Central des Ponts, Centre de Nantes (France)

    2001-07-01

    This paper presents an estimation method for vehicle longitudinal dynamics, particularly the tractive/braking force. The estimation can be used to detect a critical driving situation to improve security. It can be used also in several vehicle control systems. The main characteristics of the vehicle longitudinal dynamics were taken into account in the model used to design an observer and computer simulations. The state variables are the angular wheel velocity, vehicle velocity and the longitudinal tire force. The proposed differential equation of the tractive/braking force is derived using the concept of relaxation length. The observer designed is based on the sliding mode approach using only the angular wheel velocity measurement. The proposed method of estimation is verified through a one-wheel simulation model with a ''Magic formula'' tire model. Simulations results show an excellent reconstruction of the tire force. (orig.)

  9. A statistic to estimate the variance of the histogram-based mutual information estimator based on dependent pairs of observations

    NARCIS (Netherlands)

    Moddemeijer, R

    In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimate the variance of the histogram based mutual information estimator has been derived earlier. We present such a statistic for dependent pairs. To derive this statistic it is necessary to avail of a

  10. Asymptotic theory of generalized estimating equations based on jack-knife pseudo-observations

    DEFF Research Database (Denmark)

    Overgaard, Morten; Parner, Erik Thorlund; Pedersen, Jan

    2017-01-01

    A general asymptotic theory of estimates from estimating functions based on jack-knife pseudo-observations is established by requiring that the underlying estimator can be expressed as a smooth functional of the empirical distribution. Using results in p-variation norms, the theory is applied...

  11. Observer Based Fault Detection and Moisture Estimating in Coal Mill

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Mataji, Babak

    2008-01-01

    In this paper an observer-based method for detecting faults and estimating moisture content in the coal in coal mills is presented. Handling of faults and operation under special conditions, such as high moisture content in the coal, are of growing importance due to the increasing...... requirements to the general performance of power plants. Detection  of faults and moisture content estimation are consequently of high interest in the handling of the problems caused by faults and moisture content. The coal flow out of the mill is the obvious variable to monitor, when detecting non-intended drops in the coal...... flow out of the coal mill. However, this variable is not measurable. Another estimated variable is the moisture content, which is only "measurable" during steady-state operations of the coal mill. Instead, this paper suggests a method where these unknown variables are estimated based on a simple energy...

  12. Iterative Observer-based Estimation Algorithms for Steady-State Elliptic Partial Differential Equation Systems

    KAUST Repository

    Majeed, Muhammad Usman

    2017-07-19

    Steady-state elliptic partial differential equations (PDEs) are frequently used to model a diverse range of physical phenomena. The source and boundary data estimation problems for such PDE systems are of prime interest in various engineering disciplines including biomedical engineering, mechanics of materials and earth sciences. Almost all existing solution strategies for such problems can be broadly classified as optimization-based techniques, which are computationally heavy especially when the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time-like. In this regard, first, an iterative observer algorithm is developed that sweeps over regular-shaped domains and solves boundary estimation problems for steady-state Laplace equation. It is well-known that source and boundary estimation problems for the elliptic PDEs are highly sensitive to noise in the data. For this, an optimal iterative observer algorithm, which is a robust counterpart of the iterative observer, is presented to tackle the ill-posedness due to noise. The iterative observer algorithm and the optimal iterative algorithm are then used to solve source localization and estimation problems for Poisson equation for noise-free and noisy data cases respectively. Next, a divide and conquer approach is developed for three-dimensional domains with two congruent parallel surfaces to solve the boundary and the source data estimation problems for the steady-state Laplace and Poisson kind of systems respectively. Theoretical results are shown using a functional analysis framework, and consistent numerical simulation results are presented for several test cases using finite difference discretization schemes.

  13. Distributed estimation based on observations prediction in wireless sensor networks

    KAUST Repository

    Bouchoucha, Taha

    2015-03-19

    We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.

  14. Adjustable Parameter-Based Distributed Fault Estimation Observer Design for Multiagent Systems With Directed Graphs.

    Science.gov (United States)

    Zhang, Ke; Jiang, Bin; Shi, Peng

    2017-02-01

    In this paper, a novel adjustable parameter (AP)-based distributed fault estimation observer (DFEO) is proposed for multiagent systems (MASs) with the directed communication topology. First, a relative output estimation error is defined based on the communication topology of MASs. Then a DFEO with AP is constructed with the purpose of improving the accuracy of fault estimation. Based on H ∞ and H 2 with pole placement, multiconstrained design is given to calculate the gain of DFEO. Finally, simulation results are presented to illustrate the feasibility and effectiveness of the proposed DFEO design with AP.

  15. Iterative Observer-based Estimation Algorithms for Steady-State Elliptic Partial Differential Equation Systems

    KAUST Repository

    Majeed, Muhammad Usman

    2017-01-01

    the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time

  16. An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations

    Science.gov (United States)

    Jeong, U; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

    2016-01-01

    An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

  17. Distributed estimation based on observations prediction in wireless sensor networks

    KAUST Repository

    Bouchoucha, Taha; Ahmed, Mohammed F A; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process

  18. Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations

    Directory of Open Access Journals (Sweden)

    Samuel A. Andam‑Akorful

    2013-07-01

    Full Text Available The measurement of total basin discharge along coastal regions is necessary for understanding the hydrological and oceanographic issues related to the water and energy cycles. However, only the observed streamflow (gauge-based observation is used to estimate the total fluxes from the river basin to the ocean, neglecting the portion of discharge that infiltrates to underground and directly discharges into the ocean. Hence, the aim of this study is to assess the total discharge of the Yangtze River (Chang Jiang basin. In this study, we explore the potential response of total discharge to changes in precipitation (from the Tropical Rainfall Measuring Mission—TRMM, evaporation (from four versions of the Global Land Data Assimilation—GLDAS, namely, CLM, Mosaic, Noah and VIC, and water-storage changes (from the Gravity Recovery and Climate Experiment—GRACE by using the terrestrial water budget method. This method has been validated by comparison with the observed streamflow, and shows an agreement with a root mean square error (RMSE of 14.30 mm/month for GRACE-based discharge and 20.98 mm/month for that derived from precipitation minus evaporation (P − E. This improvement of approximately 32% indicates that monthly terrestrial water-storage changes, as estimated by GRACE, cannot be considered negligible over Yangtze basin. The results for the proposed method are more accurate than the results previously reported in the literature.

  19. Estimation of the neuronal activation using fMRI data: An observer-based approach

    KAUST Repository

    Laleg-Kirati, Taous-Meriem

    2013-06-01

    This paper deals with the estimation of the neuronal activation and some unmeasured physiological information using the Blood Oxygenation Level Dependent (BOLD) signal measured using functional Magnetic Resonance Imaging (fMRI). We propose to use an observer-based approach applied to the balloon hemodynamic model. The latter describes the relation between the neural activity and the BOLD signal. The balloon model can be expressed in a nonlinear state-space representation where the states, the parameters and the input (neuronal activation), are unknown. This study focuses only on the estimation of the hidden states and the neuronal activation. The model is first linearized around the equilibrium and an observer is applied to this linearized version. Numerical results performed on synthetic data are presented.

  20. Estimating atmospheric visibility using synergy of MODIS data and ground-based observations

    Science.gov (United States)

    Komeilian, H.; Mohyeddin Bateni, S.; Xu, T.; Nielson, J.

    2015-05-01

    Dust events are intricate climatic processes, which can have adverse effects on human health, safety, and the environment. In this study, two data mining approaches, namely, back-propagation artificial neural network (BP ANN) and supporting vector regression (SVR), were used to estimate atmospheric visibility through the synergistic use of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B (L1B) data and ground-based observations at fourteen stations in the province of Khuzestan (southwestern Iran), during 2009-2010. Reflectance and brightness temperature in different bands (from MODIS) along with in situ meteorological data were input to the models to estimate atmospheric visibility. The results show that both models can accurately estimate atmospheric visibility. The visibility estimates from the BP ANN network had a root-mean-square error (RMSE) and Pearson's correlation coefficient (R) of 0.67 and 0.69, respectively. The corresponding RMSE and R from the SVR model were 0.59 and 0.71, implying that the SVR approach outperforms the BP ANN.

  1. Kalman filter data assimilation: targeting observations and parameter estimation.

    Science.gov (United States)

    Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

    2014-06-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

  2. Kalman filter data assimilation: Targeting observations and parameter estimation

    International Nuclear Information System (INIS)

    Bellsky, Thomas; Kostelich, Eric J.; Mahalov, Alex

    2014-01-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation

  3. Observation-based estimation of aerosol-induced reduction of planetary boundary layer height

    Science.gov (United States)

    Zou, Jun; Sun, Jianning; Ding, Aijun; Wang, Minghuai; Guo, Weidong; Fu, Congbin

    2017-09-01

    Radiative aerosols are known to influence the surface energy budget and hence the evolution of the planetary boundary layer. In this study, we develop a method to estimate the aerosol-induced reduction in the planetary boundary layer height (PBLH) based on two years of ground-based measurements at a site, the Station for Observing Regional Processes of the Earth System (SORPES), at Nanjing University, China, and radiosonde data from the meteorological station of Nanjing. The observations show that increased aerosol loads lead to a mean decrease of 67.1 W m-2 for downward shortwave radiation (DSR) and a mean increase of 19.2 W m-2 for downward longwave radiation (DLR), as well as a mean decrease of 9.6 Wm-2 for the surface sensible heat flux (SHF) in the daytime. The relative variations of DSR, DLR and SHF are shown as a function of the increment of column mass concentration of particulate matter (PM2.5). High aerosol loading can significantly increase the atmospheric stability in the planetary boundary layer during both daytime and nighttime. Based on the statistical relationship between SHF and PM2.5 column mass concentrations, the SHF under clean atmospheric conditions (same as the background days) is derived. In this case, the derived SHF, together with observed SHF, are then used to estimate changes in the PBLH related to aerosols. Our results suggest that the PBLH decreases more rapidly with increasing aerosol loading at high aerosol loading. When the daytime mean column mass concentration of PM2.5 reaches 200 mg m-2, the decrease in the PBLH at 1600 LST (local standard time) is about 450 m.

  4. Structural observability analysis and EKF based parameter estimation of building heating models

    Directory of Open Access Journals (Sweden)

    D.W.U. Perera

    2016-07-01

    Full Text Available Research for enhanced energy-efficient buildings has been given much recognition in the recent years owing to their high energy consumptions. Increasing energy needs can be precisely controlled by practicing advanced controllers for building Heating, Ventilation, and Air-Conditioning (HVAC systems. Advanced controllers require a mathematical building heating model to operate, and these models need to be accurate and computationally efficient. One main concern associated with such models is the accurate estimation of the unknown model parameters. This paper presents the feasibility of implementing a simplified building heating model and the computation of physical parameters using an off-line approach. Structural observability analysis is conducted using graph-theoretic techniques to analyze the observability of the developed system model. Then Extended Kalman Filter (EKF algorithm is utilized for parameter estimates using the real measurements of a single-zone building. The simulation-based results confirm that even with a simple model, the EKF follows the state variables accurately. The predicted parameters vary depending on the inputs and disturbances.

  5. Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

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    Yuqi Guo

    2017-08-01

    Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.

  6. An assessment of the performance of global rainfall estimates without ground-based observations

    Directory of Open Access Journals (Sweden)

    C. Massari

    2017-09-01

    Full Text Available Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets. In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS, showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth of the aforementioned products without using a ground benchmark data set. The analysis is carried out during the period 2007–2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern

  7. Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

    Science.gov (United States)

    Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

    2018-01-01

    Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

  8. Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations

    Directory of Open Access Journals (Sweden)

    Bradley C. Reed

    2013-02-01

    Full Text Available Winter annual plants in southwestern North America influence fire regimes, provide forage, and help prevent erosion. Exotic annuals may also threaten native species. Monitoring winter annuals is difficult because of their ephemeral nature, making the development of a satellite monitoring tool valuable. We mapped winter annual aboveground biomass in the Desert Southwest from satellite observations, evaluating 18 algorithms using time-series vegetation indices (VI. Field-based biomass estimates were used to calibrate and evaluate each algorithm. Winter annual biomass was best estimated by calculating a base VI across the period of record and subtracting it from the peak VI for each winter season (R2 = 0.92. The normalized difference vegetation index (NDVI derived from 8-day reflectance data provided the best estimate of winter annual biomass. It is important to account for the timing of peak vegetation when relating field-based estimates to satellite VI data, since post-peak field estimates may indicate senescent biomass which is inaccurately represented by VI-based estimates. Images generated from the best-performing algorithm show both spatial and temporal variation in winter annual biomass. Efforts to manage this variable resource would be enhanced by a tool that allows the monitoring of changes in winter annual resources over time.

  9. The influence of selection on the evolutionary distance estimated from the base changes observed between homologous nucleotide sequences.

    Science.gov (United States)

    Otsuka, J; Kawai, Y; Sugaya, N

    2001-11-21

    In most studies of molecular evolution, the nucleotide base at a site is assumed to change with the apparent rate under functional constraint, and the comparison of base changes between homologous genes is thought to yield the evolutionary distance corresponding to the site-average change rate multiplied by the divergence time. However, this view is not sufficiently successful in estimating the divergence time of species, but mostly results in the construction of tree topology without a time-scale. In the present paper, this problem is investigated theoretically by considering that observed base changes are the results of comparing the survivals through selection of mutated bases. In the case of weak selection, the time course of base changes due to mutation and selection can be obtained analytically, leading to a theoretical equation showing how the selection has influence on the evolutionary distance estimated from the enumeration of base changes. This result provides a new method for estimating the divergence time more accurately from the observed base changes by evaluating both the strength of selection and the mutation rate. The validity of this method is verified by analysing the base changes observed at the third codon positions of amino acid residues with four-fold codon degeneracy in the protein genes of mammalian mitochondria; i.e. the ratios of estimated divergence times are fairly well consistent with a series of fossil records of mammals. Throughout this analysis, it is also suggested that the mutation rates in mitochondrial genomes are almost the same in different lineages of mammals and that the lineage-specific base-change rates indicated previously are due to the selection probably arising from the preference of transfer RNAs to codons.

  10. Observer variability in estimating numbers: An experiment

    Science.gov (United States)

    Erwin, R.M.

    1982-01-01

    Census estimates of bird populations provide an essential framework for a host of research and management questions. However, with some exceptions, the reliability of numerical estimates and the factors influencing them have received insufficient attention. Independent of the problems associated with habitat type, weather conditions, cryptic coloration, ete., estimates may vary widely due only to intrinsic differences in observers? abilities to estimate numbers. Lessons learned in the field of perceptual psychology may be usefully applied to 'real world' problems in field ornithology. Based largely on dot discrimination tests in the laboratory, it was found that numerical abundance, density of objects, spatial configuration, color, background, and other variables influence individual accuracy in estimating numbers. The primary purpose of the present experiment was to assess the effects of observer, prior experience, and numerical range on accuracy in estimating numbers of waterfowl from black-and-white photographs. By using photographs of animals rather than black dots, I felt the results could be applied more meaningfully to field situations. Further, reinforcement was provided throughout some experiments to examine the influence of training on accuracy.

  11. Age estimation in forensic anthropology: quantification of observer error in phase versus component-based methods.

    Science.gov (United States)

    Shirley, Natalie R; Ramirez Montes, Paula Andrea

    2015-01-01

    The purpose of this study was to assess observer error in phase versus component-based scoring systems used to develop age estimation methods in forensic anthropology. A method preferred by forensic anthropologists in the AAFS was selected for this evaluation (the Suchey-Brooks method for the pubic symphysis). The Suchey-Brooks descriptions were used to develop a corresponding component-based scoring system for comparison. Several commonly used reliability statistics (kappa, weighted kappa, and the intraclass correlation coefficient) were calculated to assess observer agreement between two observers and to evaluate the efficacy of each of these statistics for this study. The linear weighted kappa was determined to be the most suitable measure of observer agreement. The results show that a component-based system offers the possibility for more objective scoring than a phase system as long as the coding possibilities for each trait do not exceed three states of expression, each with as little overlap as possible. © 2014 American Academy of Forensic Sciences.

  12. Observer-based estimation of stator-winding faults in delta-connected induction motors

    DEFF Research Database (Denmark)

    Skovemose Kallesøe, Carsten; Izadi-Zamanabadi, Roozbeh; Vadstrup, Pierre

    2007-01-01

    This paper addresses the subject of interturn short circuit estimation in the stator of a delta-connected induction motor. In this paper, an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved...... in the short circuit, and an expression of the current in the short circuit. Moreover, the currents are made available even though a fault has occurred in the motor. To be able to develop this observer, a model that is particularly suitable for the chosen observer design, is also derived. The effeciency...... of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate interturn short-circuit faults....

  13. Estimating Stochastic Volatility Models using Prediction-based Estimating Functions

    DEFF Research Database (Denmark)

    Lunde, Asger; Brix, Anne Floor

    to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from......In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared...... to correctly account for the noise are investigated. Our Monte Carlo study shows that the estimator based on PBEFs outperforms the GMM estimator, both in the setting with and without MMS noise. Finally, an empirical application investigates the possible challenges and general performance of applying the PBEF...

  14. Estimation of soft sediment thickness in Kuala Lumpur based on microtremor observation data

    Science.gov (United States)

    Chiew, Chang Chyau; Cheah, Yi Ben; Tan, Chin Guan; Lau, Tze Liang

    2017-10-01

    Seismic site effect is one of the major concerns in earthquake engineering. Soft ground tends to amplify the seismic wave in surficial geological layers. The determination of soft ground thickness on the surface layers of the earth is an important input for seismic hazard assessment. This paper presents an easy and convenient approach to estimate the soft sediment thickness at the site using microtremor observation technique. A total number of 133 survey points were conducted in selected sites around Kuala Lumpur area using a microtremor measuring instrument, but only 103 survey points contributed to the seismic microzonation and sediment thickness plots. The bedrock of Kuala Lumpur area is formed by Kenny Hill Formation, limestone, granite, and the Hawthornden Schist; however, the thickness of surface soft ground formed by alluvial deposits, mine tailings, and residual soils remains unknown. Hence, the predominant frequency of the ground in each site was determined based on Nakamura method. A total number of 14 sites with known depth to bedrock from the supply of geotechnical reports in the study area were determined. An empirical correlation was developed to relate the ground predominant frequency and soft ground thickness. This correlation may contribute to local soil underlying the subsurface of Kuala Lumpur area. The finding provides an important relationship for engineers to estimate the soft ground thickness in Kuala Lumpur area based on the dynamic characteristics of the ground measured from microtremor observation.

  15. Enhanced online model identification and state of charge estimation for lithium-ion battery with a FBCRLS based observer

    International Nuclear Information System (INIS)

    Wei, Zhongbao; Meng, Shujuan; Xiong, Binyu; Ji, Dongxu; Tseng, King Jet

    2016-01-01

    Highlights: • Integrated online model identification and SOC estimate is explored. • Noise variances are online estimated in a data-driven way. • Identification bias caused by noise corruption is attenuated. • SOC is online estimated with high accuracy and fast convergence. • Algorithm comparison shows the superiority of proposed method. - Abstract: State of charge (SOC) estimators with online identified battery model have proven to have high accuracy and better robustness due to the timely adaption of time varying model parameters. In this paper, we show that the common methods for model identification are intrinsically biased if both the current and voltage sensors are corrupted with noises. The uncertainties in battery model further degrade the accuracy and robustness of SOC estimate. To address this problem, this paper proposes a novel technique which integrates the Frisch scheme based bias compensating recursive least squares (FBCRLS) with a SOC observer for enhanced model identification and SOC estimate. The proposed method online estimates the noise statistics and compensates the noise effect so that the model parameters can be extracted without bias. The SOC is further estimated in real time with the online updated and unbiased battery model. Simulation and experimental studies show that the proposed FBCRLS based observer effectively attenuates the bias on model identification caused by noise contamination and as a consequence provides more reliable estimate on SOC. The proposed method is also compared with other existing methods to highlight its superiority in terms of accuracy and convergence speed.

  16. View Estimation Based on Value System

    Science.gov (United States)

    Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru

    Estimation of a caregiver's view is one of the most important capabilities for a child to understand the behavior demonstrated by the caregiver, that is, to infer the intention of behavior and/or to learn the observed behavior efficiently. We hypothesize that the child develops this ability in the same way as behavior learning motivated by an intrinsic reward, that is, he/she updates the model of the estimated view of his/her own during the behavior imitated from the observation of the behavior demonstrated by the caregiver based on minimizing the estimation error of the reward during the behavior. From this view, this paper shows a method for acquiring such a capability based on a value system from which values can be obtained by reinforcement learning. The parameters of the view estimation are updated based on the temporal difference error (hereafter TD error: estimation error of the state value), analogous to the way such that the parameters of the state value of the behavior are updated based on the TD error. Experiments with simple humanoid robots show the validity of the method, and the developmental process parallel to young children's estimation of its own view during the imitation of the observed behavior of the caregiver is discussed.

  17. Observation-based Quantitative Uncertainty Estimation for Realtime Tsunami Inundation Forecast using ABIC and Ensemble Simulation

    Science.gov (United States)

    Takagawa, T.

    2016-12-01

    An ensemble forecasting scheme for tsunami inundation is presented. The scheme consists of three elemental methods. The first is a hierarchical Bayesian inversion using Akaike's Bayesian Information Criterion (ABIC). The second is Montecarlo sampling from a probability density function of multidimensional normal distribution. The third is ensamble analysis of tsunami inundation simulations with multiple tsunami sources. Simulation based validation of the model was conducted. A tsunami scenario of M9.1 Nankai earthquake was chosen as a target of validation. Tsunami inundation around Nagoya Port was estimated by using synthetic tsunami waveforms at offshore GPS buoys. The error of estimation of tsunami inundation area was about 10% even if we used only ten minutes observation data. The estimation accuracy of waveforms on/off land and spatial distribution of maximum tsunami inundation depth is demonstrated.

  18. Observers for vehicle tyre/road forces estimation: experimental validation

    Science.gov (United States)

    Doumiati, M.; Victorino, A.; Lechner, D.; Baffet, G.; Charara, A.

    2010-11-01

    The motion of a vehicle is governed by the forces generated between the tyres and the road. Knowledge of these vehicle dynamic variables is important for vehicle control systems that aim to enhance vehicle stability and passenger safety. This study introduces a new estimation process for tyre/road forces. It presents many benefits over the existing state-of-art works, within the dynamic estimation framework. One of these major contributions consists of discussing in detail the vertical and lateral tyre forces at each tyre. The proposed method is based on the dynamic response of a vehicle instrumented with potentially integrated sensors. The estimation process is separated into two principal blocks. The role of the first block is to estimate vertical tyre forces, whereas in the second block two observers are proposed and compared for the estimation of lateral tyre/road forces. The different observers are based on a prediction/estimation Kalman filter. The performance of this concept is tested and compared with real experimental data using a laboratory car. Experimental results show that the proposed approach is a promising technique to provide accurate estimation. Thus, it can be considered as a practical low-cost solution for calculating vertical and lateral tyre/road forces.

  19. Distributed Fusion Estimation for Multisensor Multirate Systems with Stochastic Observation Multiplicative Noises

    Directory of Open Access Journals (Sweden)

    Peng Fangfang

    2014-01-01

    Full Text Available This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms.

  20. Optimal State Estimation for Discrete-Time Markov Jump Systems with Missing Observations

    Directory of Open Access Journals (Sweden)

    Qing Sun

    2014-01-01

    Full Text Available This paper is concerned with the optimal linear estimation for a class of direct-time Markov jump systems with missing observations. An observer-based approach of fault detection and isolation (FDI is investigated as a detection mechanic of fault case. For systems with known information, a conditional prediction of observations is applied and fault observations are replaced and isolated; then, an FDI linear minimum mean square error estimation (LMMSE can be developed by comprehensive utilizing of the correct information offered by systems. A recursive equation of filtering based on the geometric arguments can be obtained. Meanwhile, a stability of the state estimator will be guaranteed under appropriate assumption.

  1. Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

    Directory of Open Access Journals (Sweden)

    Dachuan Li

    2015-04-01

    Full Text Available This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO approach was developed to estimate the MAV’s relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV’s states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments.

  2. A comparative study of kalman filtering based observer and sliding mode observer for state of charge estimation

    Science.gov (United States)

    Ben Sassi, Hicham; Errahimi, Fatima; Es-Sbai, Najia; Alaoui, Chakib

    2018-05-01

    Nowadays, electric mobility is starting to define society and is becoming more and more irreplaceable and essential to daily activities. Safe and durable battery is of a great significance for this type of mobility, hence the increasing interest of research activity oriented to battery studies, in order to assure safe operating mode and to control the battery in case of any abnormal functioning conditions that could damage the battery if not properly managed. Lithium-ion technology is considered the most suitable existing technology for electrical storage, because of their interesting features such as their relatively long cycle life, lighter weight, their high energy density, However, there is a lot of work that is still needed to be done in order to assure safe operating lithium-ion batteries, starting with their internal status monitoring, cell balancing within a battery pack, and thermal management. Tasks that are accomplished by the battery management system (BMS) which uses the state of charge (SOC) as an indicator of the internal charge level of the battery, in order to avoid unpredicted system interruption. Since the state of charge is an inner state of a the battery which cannot be directly measured, a powerful estimation technique is inevitable, in this paper we investigate the performances of tow estimation strategies; kalman filtering based observers and sliding mode observers, both strategies are compared in terms of accuracy, design requirement, and overall performances.

  3. Health Parameter Estimation with Second-Order Sliding Mode Observer for a Turbofan Engine

    Directory of Open Access Journals (Sweden)

    Xiaodong Chang

    2017-07-01

    Full Text Available In this paper the problem of health parameter estimation in an aero-engine is investigated by using an unknown input observer-based methodology, implemented by a second-order sliding mode observer (SOSMO. Unlike the conventional state estimator-based schemes, such as Kalman filters (KF and sliding mode observers (SMO, the proposed scheme uses a “reconstruction signal” to estimate health parameters modeled as artificial inputs, and is not only applicable to long-time health degradation, but reacts much quicker in handling abrupt fault cases. In view of the inevitable uncertainties in engine dynamics and modeling, a weighting matrix is created to minimize such effect on estimation by using the linear matrix inequalities (LMI. A big step toward uncertainty modeling is taken compared with our previous SMO-based work, in that uncertainties are considered in a more practical form. Moreover, to avoid chattering in sliding modes, the super-twisting algorithm (STA is employed in observer design. Various simulations are carried out, based on the comparisons between the KF-based scheme, the SMO-based scheme in our earlier research, and the proposed method. The results consistently demonstrate the capabilities and advantages of the proposed approach in health parameter estimation.

  4. Observationally constrained estimates of carbonaceous aerosol radiative forcing.

    Science.gov (United States)

    Chung, Chul E; Ramanathan, V; Decremer, Damien

    2012-07-17

    Carbonaceous aerosols (CA) emitted by fossil and biomass fuels consist of black carbon (BC), a strong absorber of solar radiation, and organic matter (OM). OM scatters as well as absorbs solar radiation. The absorbing component of OM, which is ignored in most climate models, is referred to as brown carbon (BrC). Model estimates of the global CA radiative forcing range from 0 to 0.7 Wm(-2), to be compared with the Intergovernmental Panel on Climate Change's estimate for the pre-Industrial to the present net radiative forcing of about 1.6 Wm(-2). This study provides a model-independent, observationally based estimate of the CA direct radiative forcing. Ground-based aerosol network data is integrated with field data and satellite-based aerosol observations to provide a decadal (2001 through 2009) global view of the CA optical properties and direct radiative forcing. The estimated global CA direct radiative effect is about 0.75 Wm(-2) (0.5 to 1.0). This study identifies the global importance of BrC, which is shown to contribute about 20% to 550-nm CA solar absorption globally. Because of the inclusion of BrC, the net effect of OM is close to zero and the CA forcing is nearly equal to that of BC. The CA direct radiative forcing is estimated to be about 0.65 (0.5 to about 0.8) Wm(-2), thus comparable to or exceeding that by methane. Caused in part by BrC absorption, CAs have a net warming effect even over open biomass-burning regions in Africa and the Amazon.

  5. Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

    International Nuclear Information System (INIS)

    Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.

    2008-01-01

    This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.

  6. Observer Based Estimation of Stator Winding Faults in Delta-connected Induction Motors, a LMI Approach

    DEFF Research Database (Denmark)

    Kallesøe, Carsten; Vadstrup, Pierre; Rasmussen, Henrik

    2006-01-01

    This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....

  7. Fine-tuning satellite-based rainfall estimates

    Science.gov (United States)

    Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

    2018-05-01

    Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

  8. An observer-theoretic approach to estimating neutron flux distribution

    International Nuclear Information System (INIS)

    Park, Young Ho; Cho, Nam Zin

    1989-01-01

    State feedback control provides many advantages such as stabilization and improved transient response. However, when the state feedback control is considered for spatial control of a nuclear reactor, it requires complete knowledge of the distributions of the system state variables. This paper describes a method for estimating the flux spatial distribution using only limited flux measurements. It is based on the Luenberger observer in control theory, extended to the distributed parameter systems such as the space-time reactor dynamics equation. The results of the application of the method to simple reactor models showed that the flux distribution is estimated by the observer very efficiently using information from only a few sensors

  9. Estimation of time averages from irregularly spaced observations - With application to coastal zone color scanner estimates of chlorophyll concentration

    Science.gov (United States)

    Chelton, Dudley B.; Schlax, Michael G.

    1991-01-01

    The sampling error of an arbitrary linear estimate of a time-averaged quantity constructed from a time series of irregularly spaced observations at a fixed located is quantified through a formalism. The method is applied to satellite observations of chlorophyll from the coastal zone color scanner. The two specific linear estimates under consideration are the composite average formed from the simple average of all observations within the averaging period and the optimal estimate formed by minimizing the mean squared error of the temporal average based on all the observations in the time series. The resulting suboptimal estimates are shown to be more accurate than composite averages. Suboptimal estimates are also found to be nearly as accurate as optimal estimates using the correct signal and measurement error variances and correlation functions for realistic ranges of these parameters, which makes it a viable practical alternative to the composite average method generally employed at present.

  10. Visibility-based angular power spectrum estimation in low-frequency radio interferometric observations

    NARCIS (Netherlands)

    Choudhuri, Samir; Bharadwaj, Somnath; Ghosh, Abhik; Ali, Sk. Saiyad

    2014-01-01

    We present two estimators to quantify the angular power spectrum of the sky signal directly from the visibilities measured in radio interferometric observations. This is relevant for both the foregrounds and the cosmological 21-cm signal buried therein. The discussion here is restricted to the

  11. Estimating Global Impervious Surface based on Social-economic Data and Satellite Observations

    Science.gov (United States)

    Zeng, Z.; Zhang, K.; Xue, X.; Hong, Y.

    2016-12-01

    Impervious surface areas around the globe are expanding and significantly altering the surface energy balance, hydrology cycle and ecosystem services. Many studies have underlined the importance of impervious surface, r from hydrological modeling to contaminant transport monitoring and urban development estimation. Therefore accurate estimation of the global impervious surface is important for both physical and social sciences. Given the limited coverage of high spatial resolution imagery and ground survey, using satellite remote sensing and geospatial data to estimate global impervious areas is a practical approach. Based on the previous work of area-weighted imperviousness for north branch of the Chicago River provided by HDR, this study developed a method to determine the percentage of impervious surface using latest global land cover categories from multi-source satellite observations, population density and gross domestic product (GDP) data. Percent impervious surface at 30-meter resolution were mapped. We found that 1.33% of the CONUS (105,814 km2) and 0.475% of the land surface (640,370km2) are impervious surfaces. To test the utility and practicality of the proposed method, National Land Cover Database (NLCD) 2011 percent developed imperviousness for the conterminous United States was used to evaluate our results. The average difference between the derived imperviousness from our method and the NLCD data across CONUS is 1.14%, while difference between our results and the NLCD data are within ±1% over 81.63% of the CONUS. The distribution of global impervious surface map indicates that impervious surfaces are primarily concentrated in China, India, Japan, USA and Europe where are highly populated and/or developed. This study proposes a straightforward way of mapping global imperviousness, which can provide useful information for hydrologic modeling and other applications.

  12. Basic Earth's Parameters as estimated from VLBI observations

    Directory of Open Access Journals (Sweden)

    Ping Zhu

    2017-11-01

    Full Text Available The global Very Long Baseline Interferometry observation for measuring the Earth rotation's parameters was launched around 1970s. Since then the precision of the measurements is continuously improving by taking into account various instrumental and environmental effects. The MHB2000 nutation model was introduced in 2002, which is constructed based on a revised nutation series derived from 20 years VLBI observations (1980–1999. In this work, we firstly estimated the amplitudes of all nutation terms from the IERS-EOP-C04 VLBI global solutions w.r.t. IAU1980, then we further inferred the BEPs (Basic Earth's Parameters by fitting the major nutation terms. Meanwhile, the BEPs were obtained from the same nutation time series using a BI (Bayesian Inversion. The corrections to the precession rate and the estimated BEPs are in an agreement, independent of which methods have been applied.

  13. An adaptive observer for on-line tool wear estimation in turning, Part I: Theory

    Science.gov (United States)

    Danai, Kourosh; Ulsoy, A. Galip

    1987-04-01

    On-line sensing of tool wear has been a long-standing goal of the manufacturing engineering community. In the absence of any reliable on-line tool wear sensors, a new model-based approach for tool wear estimation has been proposed. This approach is an adaptive observer, based on force measurement, which uses both parameter and state estimation techniques. The design of the adaptive observer is based upon a dynamic state model of tool wear in turning. This paper (Part I) presents the model, and explains its use as the basis for the adaptive observer design. This model uses flank wear and crater wear as state variables, feed as the input, and the cutting force as the output. The suitability of the model as the basis for adaptive observation is also verified. The implementation of the adaptive observer requires the design of a state observer and a parameter estimator. To obtain the model parameters for tuning the adaptive observer procedures for linearisation of the non-linear model are specified. The implementation of the adaptive observer in turning and experimental results are presented in a companion paper (Part II).

  14. A robust observer based on H∞ filtering with parameter uncertainties combined with Neural Networks for estimation of vehicle roll angle

    Science.gov (United States)

    Boada, Beatriz L.; Boada, Maria Jesus L.; Vargas-Melendez, Leandro; Diaz, Vicente

    2018-01-01

    Nowadays, one of the main objectives in road transport is to decrease the number of accident victims. Rollover accidents caused nearly 33% of all deaths from passenger vehicle crashes. Roll Stability Control (RSC) systems prevent vehicles from untripped rollover accidents. The lateral load transfer is the main parameter which is taken into account in the RSC systems. This parameter is related to the roll angle, which can be directly measured from a dual-antenna GPS. Nevertheless, this is a costly technique. For this reason, roll angle has to be estimated. In this paper, a novel observer based on H∞ filtering in combination with a neural network (NN) for the vehicle roll angle estimation is proposed. The design of this observer is based on four main criteria: to use a simplified vehicle model, to use signals of sensors which are installed onboard in current vehicles, to consider the inaccuracy in the system model and to attenuate the effect of the external disturbances. Experimental results show the effectiveness of the proposed observer.

  15. Estimation of High-Frequency Earth-Space Radio Wave Signals via Ground-Based Polarimetric Radar Observations

    Science.gov (United States)

    Bolen, Steve; Chandrasekar, V.

    2002-01-01

    Expanding human presence in space, and enabling the commercialization of this frontier, is part of the strategic goals for NASA's Human Exploration and Development of Space (HEDS) enterprise. Future near-Earth and planetary missions will support the use of high-frequency Earth-space communication systems. Additionally, increased commercial demand on low-frequency Earth-space links in the S- and C-band spectra have led to increased interest in the use of higher frequencies in regions like Ku and Ka-band. Attenuation of high-frequency signals, due to a precipitating medium, can be quite severe and can cause considerable disruptions in a communications link that traverses such a medium. Previously, ground radar measurements were made along the Earth-space path and compared to satellite beacon data that was transmitted to a ground station. In this paper, quantitative estimation of the attenuation along the propagation path is made via inter-comparisons of radar data taken from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and ground-based polarimetric radar observations. Theoretical relationships between the expected specific attenuation (k) of spaceborne measurements with ground-based measurements of reflectivity (Zh) and differential propagation phase shift (Kdp) are developed for various hydrometeors that could be present along the propagation path, which are used to estimate the two-way path-integrated attenuation (PIA) on the PR return echo. Resolution volume matching and alignment of the radar systems is performed, and a direct comparison of PR return echo with ground radar attenuation estimates is made directly on a beam-by-beam basis. The technique is validated using data collected from the TExas and Florida UNderflights (TEFLUN-B) experiment and the TRMM large Biosphere-Atmosphere experiment in Amazonia (LBA) campaign. Attenuation estimation derived from this method can be used for strategiC planning of communication systems for

  16. HOTELLING'S T2 CONTROL CHARTS BASED ON ROBUST ESTIMATORS

    Directory of Open Access Journals (Sweden)

    SERGIO YÁÑEZ

    2010-01-01

    Full Text Available Under the presence of multivariate outliers, in a Phase I analysis of historical set of data, the T 2 control chart based on the usual sample mean vector and sample variance covariance matrix performs poorly. Several alternative estimators have been proposed. Among them, estimators based on the minimum volume ellipsoid (MVE and the minimum covariance determinant (MCD are powerful in detecting a reasonable number of outliers. In this paper we propose a T 2 control chart using the biweight S estimators for the location and dispersion parameters when monitoring multivariate individual observations. Simulation studies show that this method outperforms the T 2 control chart based on MVE estimators for a small number of observations.

  17. A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data

    Science.gov (United States)

    Barnes, J. R.

    1993-01-01

    Theoretical and modeling studies indicate that small-scale drag due to breaking gravity waves is likely to be of considerable importance for the circulation in the middle atmospheric region (approximately 40-100 km altitude) on Mars. Recent earth-based spectroscopic observations have provided evidence for the existence of circulation features, in particular, a warm winter polar region, associated with gravity wave drag. Since the Mars Observer PMIRR experiment will obtain temperature profiles extending from the surface up to about 80 km altitude, it will be extensively sampling middle atmospheric regions in which gravity wave drag may play a dominant role. Estimating the drag then becomes crucial to the estimation of the atmospheric winds from the PMIRR-observed temperatures. An interative diagnostic model based upon one previously developed and tested with earth satellite temperature data will be applied to the PMIRR measurements to produce estimates of the small-scale zonal drag and three-dimensional wind fields in the Mars middle atmosphere. This model is based on the primitive equations, and can allow for time dependence (the time tendencies used may be based upon those computed in a Fast Fourier Mapping procedure). The small-scale zonal drag is estimated as the residual in the zonal momentum equation; the horizontal winds having first been estimated from the meridional momentum equation and the continuity equation. The scheme estimates the vertical motions from the thermodynamic equation, and thus needs estimates of the diabatic heating based upon the observed temperatures. The latter will be generated using a radiative model. It is hoped that the diagnostic scheme will be able to produce good estimates of the zonal gravity wave drag in the Mars middle atmosphere, estimates that can then be used in other diagnostic or assimilation efforts, as well as more theoretical studies.

  18. Estimation in Discretely Observed Diffusions Killed at a Threshold

    DEFF Research Database (Denmark)

    Bibbona, Enrico; Ditlevsen, Susanne

    2013-01-01

    are modelled as discretely observed diffusions which are killed when the threshold is reached. Statistical inference is often based on a misspecified likelihood ignoring the presence of the threshold causing severe bias, e.g. the bias incurred in the drift parameters of the Ornstein–Uhlenbeck model...... for biological relevant parameters can be up to 25–100 per cent. We compute or approximate the likelihood function of the killed process. When estimating from a single trajectory, considerable bias may still be present, and the distribution of the estimates can be heavily skewed and with a huge variance...

  19. Estimating the Grain Size Distribution of Mars based on Fragmentation Theory and Observations

    Science.gov (United States)

    Charalambous, C.; Pike, W. T.; Golombek, M.

    2017-12-01

    We present here a fundamental extension to the fragmentation theory [1] which yields estimates of the distribution of particle sizes of a planetary surface. The model is valid within the size regimes of surfaces whose genesis is best reflected by the evolution of fragmentation phenomena governed by either the process of meteoritic impacts, or by a mixture with aeolian transportation at the smaller sizes. The key parameter of the model, the regolith maturity index, can be estimated as an average of that observed at a local site using cratering size-frequency measurements, orbital and surface image-detected rock counts and observations of sub-mm particles at landing sites. Through validation of ground truth from previous landed missions, the basis of this approach has been used at the InSight landing ellipse on Mars to extrapolate rock size distributions in HiRISE images down to 5 cm rock size, both to determine the landing safety risk and the subsequent probability of obstruction by a rock of the deployed heat flow mole down to 3-5 m depth [2]. Here we focus on a continuous extrapolation down to 600 µm coarse sand particles, the upper size limit that may be present through aeolian processes [3]. The parameters of the model are first derived for the fragmentation process that has produced the observable rocks via meteorite impacts over time, and therefore extrapolation into a size regime that is affected by aeolian processes has limited justification without further refinement. Incorporating thermal inertia estimates, size distributions observed by the Spirit and Opportunity Microscopic Imager [4] and Atomic Force and Optical Microscopy from the Phoenix Lander [5], the model's parameters in combination with synthesis methods are quantitatively refined further to allow transition within the aeolian transportation size regime. In addition, due to the nature of the model emerging in fractional mass abundance, the percentage of material by volume or mass that resides

  20. Consistent estimate of ocean warming, land ice melt and sea level rise from Observations

    Science.gov (United States)

    Blazquez, Alejandro; Meyssignac, Benoît; Lemoine, Jean Michel

    2016-04-01

    Based on the sea level budget closure approach, this study investigates the consistency of observed Global Mean Sea Level (GMSL) estimates from satellite altimetry, observed Ocean Thermal Expansion (OTE) estimates from in-situ hydrographic data (based on Argo for depth above 2000m and oceanic cruises below) and GRACE observations of land water storage and land ice melt for the period January 2004 to December 2014. The consistency between these datasets is a key issue if we want to constrain missing contributions to sea level rise such as the deep ocean contribution. Numerous previous studies have addressed this question by summing up the different contributions to sea level rise and comparing it to satellite altimetry observations (see for example Llovel et al. 2015, Dieng et al. 2015). Here we propose a novel approach which consists in correcting GRACE solutions over the ocean (essentially corrections of stripes and leakage from ice caps) with mass observations deduced from the difference between satellite altimetry GMSL and in-situ hydrographic data OTE estimates. We check that the resulting GRACE corrected solutions are consistent with original GRACE estimates of the geoid spherical harmonic coefficients within error bars and we compare the resulting GRACE estimates of land water storage and land ice melt with independent results from the literature. This method provides a new mass redistribution from GRACE consistent with observations from Altimetry and OTE. We test the sensibility of this method to the deep ocean contribution and the GIA models and propose best estimates.

  1. Adaptive Observer-Based Fault-Tolerant Control Design for Uncertain Systems

    Directory of Open Access Journals (Sweden)

    Huaming Qian

    2015-01-01

    Full Text Available This study focuses on the design of the robust fault-tolerant control (FTC system based on adaptive observer for uncertain linear time invariant (LTI systems. In order to improve robustness, rapidity, and accuracy of traditional fault estimation algorithm, an adaptive fault estimation algorithm (AFEA using an augmented observer is presented. By utilizing a new fault estimator model, an improved AFEA based on linear matrix inequality (LMI technique is proposed to increase the performance. Furthermore, an observer-based state feedback fault-tolerant control strategy is designed, which guarantees the stability and performance of the faulty system. Moreover, the adaptive observer and the fault-tolerant controller are designed separately, whose performance can be considered, respectively. Finally, simulation results of an aircraft application are presented to illustrate the effectiveness of the proposed design methods.

  2. An efficient algebraic approach to observability analysis in state estimation

    Energy Technology Data Exchange (ETDEWEB)

    Pruneda, R.E.; Solares, C.; Conejo, A.J. [University of Castilla-La Mancha, 13071 Ciudad Real (Spain); Castillo, E. [University of Cantabria, 39005 Santander (Spain)

    2010-03-15

    An efficient and compact algebraic approach to state estimation observability is proposed. It is based on transferring rows to columns and vice versa in the Jacobian measurement matrix. The proposed methodology provides a unified approach to observability checking, critical measurement identification, determination of observable islands, and selection of pseudo-measurements to restore observability. Additionally, the observability information obtained from a given set of measurements can provide directly the observability obtained from any subset of measurements of the given set. Several examples are used to illustrate the capabilities of the proposed methodology, and results from a large case study are presented to demonstrate the appropriate computational behavior of the proposed algorithms. Finally, some conclusions are drawn. (author)

  3. An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations.

    Science.gov (United States)

    Feng, Fei; Li, Xianglan; Yao, Yunjun; Liang, Shunlin; Chen, Jiquan; Zhao, Xiang; Jia, Kun; Pintér, Krisztina; McCaughey, J Harry

    2016-01-01

    Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types.

  4. Spacecraft Angular Rates Estimation with Gyrowheel Based on Extended High Gain Observer

    Directory of Open Access Journals (Sweden)

    Xiaokun Liu

    2016-04-01

    Full Text Available A gyrowheel (GW is a kind of electronic electric-mechanical servo system, which can be applied to a spacecraft attitude control system (ACS as both an actuator and a sensor simultaneously. In order to solve the problem of two-dimensional spacecraft angular rate sensing as a GW outputting three-dimensional control torque, this paper proposed a method of an extended high gain observer (EHGO with the derived GW mathematical model to implement the spacecraft angular rate estimation when the GW rotor is working at large angles. For this purpose, the GW dynamic equation is firstly derived with the second kind Lagrange method, and the relationship between the measurable and unmeasurable variables is built. Then, the EHGO is designed to estimate and calculate spacecraft angular rates with the GW, and the stability of the designed EHGO is proven by the Lyapunov function. Moreover, considering the engineering application, the effect of measurement noise in the tilt angle sensors on the estimation accuracy of the EHGO is analyzed. Finally, the numerical simulation is performed to illustrate the validity of the method proposed in this paper.

  5. A Study on Parametric Wave Estimation Based on Measured Ship Motions

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Iseki, Toshio

    2011-01-01

    The paper studies parametric wave estimation based on the ‘wave buoy analogy’, and data and results obtained from the training ship Shioji-maru are compared with estimates of the sea states obtained from other measurements and observations. Furthermore, the estimating characteristics of the param......The paper studies parametric wave estimation based on the ‘wave buoy analogy’, and data and results obtained from the training ship Shioji-maru are compared with estimates of the sea states obtained from other measurements and observations. Furthermore, the estimating characteristics...... of the parametric model are discussed by considering the results of a similar estimation concept based on Bayesian modelling. The purpose of the latter comparison is not to favour the one estimation approach to the other but rather to highlight some of the advantages and disadvantages of the two approaches....

  6. Estimation of snowpack matching ground-truth data and MODIS satellite-based observations by using regression kriging

    Science.gov (United States)

    Juan Collados-Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David

    2016-04-01

    The estimation of Snow Water Equivalent (SWE) is essential for an appropriate assessment of the available water resources in Alpine catchment. The hydrologic regime in these areas is dominated by the storage of water in the snowpack, which is discharged to rivers throughout the melt season. An accurate estimation of the resources will be necessary for an appropriate analysis of the system operation alternatives using basin scale management models. In order to obtain an appropriate estimation of the SWE we need to know the spatial distribution snowpack and snow density within the Snow Cover Area (SCA). Data for these snow variables can be extracted from in-situ point measurements and air-borne/space-borne remote sensing observations. Different interpolation and simulation techniques have been employed for the estimation of the cited variables. In this paper we propose to estimate snowpack from a reduced number of ground-truth data (1 or 2 campaigns per year with 23 observation point from 2000-2014) and MODIS satellite-based observations in the Sierra Nevada Mountain (Southern Spain). Regression based methodologies has been used to study snowpack distribution using different kind of explicative variables: geographic, topographic, climatic. 40 explicative variables were considered: the longitude, latitude, altitude, slope, eastness, northness, radiation, maximum upwind slope and some mathematical transformation of each of them [Ln(v), (v)^-1; (v)^2; (v)^0.5). Eight different structure of regression models have been tested (combining 1, 2, 3 or 4 explicative variables). Y=B0+B1Xi (1); Y=B0+B1XiXj (2); Y=B0+B1Xi+B2Xj (3); Y=B0+B1Xi+B2XjXl (4); Y=B0+B1XiXk+B2XjXl (5); Y=B0+B1Xi+B2Xj+B3Xl (6); Y=B0+B1Xi+B2Xj+B3XlXk (7); Y=B0+B1Xi+B2Xj+B3Xl+B4Xk (8). Where: Y is the snow depth; (Xi, Xj, Xl, Xk) are the prediction variables (any of the 40 variables); (B0, B1, B2, B3) are the coefficients to be estimated. The ground data are employed to calibrate the multiple regressions. In

  7. Lévy matters IV estimation for discretely observed Lévy processes

    CERN Document Server

    Belomestny, Denis; Genon-Catalot, Valentine; Masuda, Hiroki; Reiß, Markus

    2015-01-01

    The aim of this volume is to provide an extensive account of the most recent advances in statistics for discretely observed Lévy processes. These days, statistics for stochastic processes is a lively topic, driven by the needs of various fields of application, such as finance, the biosciences, and telecommunication. The three chapters of this volume are completely dedicated to the estimation of Lévy processes, and are written by experts in the field. The first chapter by Denis Belomestny and Markus Reiß treats the low frequency situation, and estimation methods are based on the empirical characteristic function. The second chapter by Fabienne Comte and Valery Genon-Catalon is dedicated to non-parametric estimation mainly covering the high-frequency data case. A distinctive feature of this part is the construction of adaptive estimators, based on deconvolution or projection or kernel methods. The last chapter by Hiroki Masuda considers the parametric situation. The chapters cover the main aspects of the est...

  8. Atmospheric evaporative demand observations, estimates and driving factors in Spain (1961-2011)

    KAUST Repository

    Azorin-Molina, Cesar

    2015-04-01

    We analyzed the spatio-temporal evolution of evaporation observations from Piché atmometers (1961-2011; 56 stations) and Pan evaporimeters (1984-2011; 21 stations) across Spain, and compared both measurements with evaporation estimates obtained by four physical models: i.e., Food and Agricultural Organization-56 Penman-Monteith, Food and Agricultural Organization-Pan, PenPan and Penman, based on climate data. In this study we observed a positive and statistically significant correlation between Piché and Pan evaporation measurements during the common period (1984-2011; 19 stations), mainly in summer. When evaporation observations and estimates were compared, we detected positive and statistically significant correlations with the four methods, except for winter. Among the four physical models, the FAO-Pan showed the best fitting to both Piché and Pan evaporation measurements; the PenPan model overestimated evaporation rates; and the FAO-Penman-Monteith and Penman methods underestimated evaporation observations. We also observed a better spatial agreement between Pan evaporation and estimates than that obtained by Piché measurements. Annual and seasonal trends of evaporation estimates show a statistically significant increase for 1961-2011, which do not agree with long-term Piché evaporation trends; e.g. a discontinuity was found around the 1980s. Radiative and aerodynamic driving factors suggest that this discontinuity, and the observed evaporation trends across Spain could be associated with the abrupt increase in air temperature observed during last few decades (i.e., global warming). Further investigations using available Piché evaporation observations for other regions are needed to better understand physical components influencing long-term trends of evaporation.

  9. Atmospheric evaporative demand observations, estimates and driving factors in Spain (1961-2011)

    KAUST Repository

    Azorin-Molina, Cesar; Vicente-Serrano, Sergio M.; Sanchez-Lorenzo, Arturo; McVicar, Tim R.; Morá n-Tejeda, Enrique; Revuelto, Jesú s; El Kenawy, Ahmed M.; Martí n-Herná ndez, Natalia; Tomà s, M.

    2015-01-01

    We analyzed the spatio-temporal evolution of evaporation observations from Piché atmometers (1961-2011; 56 stations) and Pan evaporimeters (1984-2011; 21 stations) across Spain, and compared both measurements with evaporation estimates obtained by four physical models: i.e., Food and Agricultural Organization-56 Penman-Monteith, Food and Agricultural Organization-Pan, PenPan and Penman, based on climate data. In this study we observed a positive and statistically significant correlation between Piché and Pan evaporation measurements during the common period (1984-2011; 19 stations), mainly in summer. When evaporation observations and estimates were compared, we detected positive and statistically significant correlations with the four methods, except for winter. Among the four physical models, the FAO-Pan showed the best fitting to both Piché and Pan evaporation measurements; the PenPan model overestimated evaporation rates; and the FAO-Penman-Monteith and Penman methods underestimated evaporation observations. We also observed a better spatial agreement between Pan evaporation and estimates than that obtained by Piché measurements. Annual and seasonal trends of evaporation estimates show a statistically significant increase for 1961-2011, which do not agree with long-term Piché evaporation trends; e.g. a discontinuity was found around the 1980s. Radiative and aerodynamic driving factors suggest that this discontinuity, and the observed evaporation trends across Spain could be associated with the abrupt increase in air temperature observed during last few decades (i.e., global warming). Further investigations using available Piché evaporation observations for other regions are needed to better understand physical components influencing long-term trends of evaporation.

  10. Effective wind speed estimation: Comparison between Kalman Filter and Takagi-Sugeno observer techniques.

    Science.gov (United States)

    Gauterin, Eckhard; Kammerer, Philipp; Kühn, Martin; Schulte, Horst

    2016-05-01

    Advanced model-based control of wind turbines requires knowledge of the states and the wind speed. This paper benchmarks a nonlinear Takagi-Sugeno observer for wind speed estimation with enhanced Kalman Filter techniques: The performance and robustness towards model-structure uncertainties of the Takagi-Sugeno observer, a Linear, Extended and Unscented Kalman Filter are assessed. Hence the Takagi-Sugeno observer and enhanced Kalman Filter techniques are compared based on reduced-order models of a reference wind turbine with different modelling details. The objective is the systematic comparison with different design assumptions and requirements and the numerical evaluation of the reconstruction quality of the wind speed. Exemplified by a feedforward loop employing the reconstructed wind speed, the benefit of wind speed estimation within wind turbine control is illustrated. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Observation- and model-based estimates of particulate dry nitrogen deposition to the oceans

    Directory of Open Access Journals (Sweden)

    A. R. Baker

    2017-07-01

    expected to be more robust than TM4, while TM4 gives access to speciated parameters (NO3− and NH4+ that are more relevant to the observed parameters and which are not available in ACCMIP. Dry deposition fluxes (CalDep were calculated from the observed concentrations using estimates of dry deposition velocities. Model–observation ratios (RA, n, weighted by grid-cell area and number of observations, were used to assess the performance of the models. Comparison in the three study regions suggests that TM4 overestimates NO3− concentrations (RA, n =  1.4–2.9 and underestimates NH4+ concentrations (RA, n =  0.5–0.7, with spatial distributions in the tropical Atlantic and northern Indian Ocean not being reproduced by the model. In the case of NH4+ in the Indian Ocean, this discrepancy was probably due to seasonal biases in the sampling. Similar patterns were observed in the various comparisons of CalDep to ModDep (RA, n =  0.6–2.6 for NO3−, 0.6–3.1 for NH4+. Values of RA, n for NHx CalDep–ModDep comparisons were approximately double the corresponding values for NH4+ CalDep–ModDep comparisons due to the significant fraction of gas-phase NH3 deposition incorporated in the TM4 and ACCMIP NHx model products. All of the comparisons suffered due to the scarcity of observational data and the large uncertainty in dry deposition velocities used to derive deposition fluxes from concentrations. These uncertainties have been a major limitation on estimates of the flux of material to the oceans for several decades. Recommendations are made for improvements in N deposition estimation through changes in observations, modelling and model–observation comparison procedures. Validation of modelled dry deposition requires effective comparisons to observable aerosol-phase species' concentrations, and this cannot be achieved if model products only report dry deposition flux over the ocean.

  12. Estimating Coastal Turbidity using MODIS 250 m Band Observations

    Science.gov (United States)

    Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.

    2004-01-01

    Terra MODIS 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where reflectance is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on MODIS observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing reflectance in the MODIS 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing reflectance are based on accepted inherent optical properties of sediment types known to be prevalent in the U.S. Gulf of Mexico coastal zone. We present our findings for the Atchafalaya Bay region of the Louisiana Coast, in the form of processed imagery over the annual cycle. We also apply our algorithm to selected sites worldwide with a goal of extending the utility of our approach to the global direct broadcast community.

  13. Estimation of Missing Observations in Two-Level Split-Plot Designs

    DEFF Research Database (Denmark)

    Almimi, Ashraf A.; Kulahci, Murat; Montgomery, Douglas C.

    2008-01-01

    Inserting estimates for the missing observations from split-plot designs restores their balanced or orthogonal structure and alleviates the difficulties in the statistical analysis. In this article, we extend a method due to Draper and Stoneman to estimate the missing observations from unreplicated...... two-level factorial and fractional factorial split-plot (FSP and FFSP) designs. The missing observations, which can either be from the same whole plot, from different whole plots, or comprise entire whole plots, are estimated by equating to zero a number of specific contrast columns equal...... to the number of the missing observations. These estimates are inserted into the design table and the estimates for the remaining effects (or alias chains of effects as the case with FFSP designs) are plotted on two half-normal plots: one for the whole-plot effects and the other for the subplot effects...

  14. Design and Experiment of Nonlinear Observer with Adaptive Gains for Battery State of Charge Estimation

    Directory of Open Access Journals (Sweden)

    Linhui Zhao

    2017-12-01

    Full Text Available State of charge (SOC is an important evaluation index for lithium-ion batteries (LIBs in electric vehicles (EVs. This paper proposes a nonlinear observer with a new adaptive gain structure for SOC estimation based on a second-order RC model. It is able to dynamically adjust the gains and obtain a better balance between convergence speed and estimation accuracy with less computational time. A sufficient condition is derived to guarantee the uniform asymptotic stability of the observer, and its robustness with respect to disturbances and uncertainties is analyzed with the help of input-to-state stability (ISS theory. A selection guide of the observer gains in practical application is presented. The estimation accuracy and convergence rate of the observer are evaluated and compared with those of extended Kalman filter (EKF based on multi-temperature datasets from two different types of LIB cells. The robustness against different disturbances and uncertainties that may appear in a real vehicle is validated and discussed in detail. The experimental results show that the proposed observer is capable of achieving better performance with less computational time in comparison to EKF for different types of LIB cells under various working conditions. The observer is also capable of estimating SOC accurately for real life conditions according to the validation results of datasets from a battery management system (BMS in an EV battery pack. Furthermore, the observer is simple enough, and is suitable for implementation on embedded hardware for LIB cells of EVs.

  15. Projected metastable Markov processes and their estimation with observable operator models

    International Nuclear Information System (INIS)

    Wu, Hao; Prinz, Jan-Hendrik; Noé, Frank

    2015-01-01

    The determination of kinetics of high-dimensional dynamical systems, such as macromolecules, polymers, or spin systems, is a difficult and generally unsolved problem — both in simulation, where the optimal reaction coordinate(s) are generally unknown and are difficult to compute, and in experimental measurements, where only specific coordinates are observable. Markov models, or Markov state models, are widely used but suffer from the fact that the dynamics on a coarsely discretized state spaced are no longer Markovian, even if the dynamics in the full phase space are. The recently proposed projected Markov models (PMMs) are a formulation that provides a description of the kinetics on a low-dimensional projection without making the Markovianity assumption. However, as yet no general way of estimating PMMs from data has been available. Here, we show that the observed dynamics of a PMM can be exactly described by an observable operator model (OOM) and derive a PMM estimator based on the OOM learning

  16. Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment

    International Nuclear Information System (INIS)

    Wengert, G.J.; Helbich, T.H.; Woitek, R.; Kapetas, P.; Clauser, P.; Baltzer, P.A.; Vogl, W.D.; Weber, M.; Meyer-Baese, A.; Pinker, Katja

    2016-01-01

    To evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. Eighty women with no imaging abnormalities (BI-RADS 1 and 2) were included in this institutional review board (IRB)-approved prospective study. All women underwent un-enhanced breast MRI. Four radiologists independently assessed FGT with MRI by subjective visual estimation according to BI-RADS. Automated observer-independent quantitative measurement of FGT with MRI was performed using a previously described measurement system. Inter-/intra-observer agreements of qualitative and quantitative FGT measurements were assessed using Cohen's kappa (k). Inexperienced readers achieved moderate inter-/intra-observer agreement and experienced readers a substantial inter- and perfect intra-observer agreement for subjective visual estimation of FGT. Practice and experience reduced observer-dependency. Automated observer-independent quantitative measurement of FGT was successfully performed and revealed only fair to moderate agreement (k = 0.209-0.497) with subjective visual estimations of FGT. Subjective visual estimation of FGT with MRI shows moderate intra-/inter-observer agreement, which can be improved by practice and experience. Automated observer-independent quantitative measurements of FGT are necessary to allow a standardized risk evaluation. (orig.)

  17. Inter- and intra-observer agreement of BI-RADS-based subjective visual estimation of amount of fibroglandular breast tissue with magnetic resonance imaging: comparison to automated quantitative assessment

    Energy Technology Data Exchange (ETDEWEB)

    Wengert, G.J.; Helbich, T.H.; Woitek, R.; Kapetas, P.; Clauser, P.; Baltzer, P.A. [Medical University of Vienna/ Vienna General Hospital, Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Vienna (Austria); Vogl, W.D. [Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Wien (Austria); Weber, M. [Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Division of General and Pediatric Radiology, Wien (Austria); Meyer-Baese, A. [State University of Florida, Department of Scientific Computing in Medicine, Tallahassee, FL (United States); Pinker, Katja [Medical University of Vienna/ Vienna General Hospital, Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Vienna (Austria); State University of Florida, Department of Scientific Computing in Medicine, Tallahassee, FL (United States); Memorial Sloan-Kettering Cancer Center, Department of Radiology, Molecular Imaging and Therapy Services, New York City, NY (United States)

    2016-11-15

    To evaluate the inter-/intra-observer agreement of BI-RADS-based subjective visual estimation of the amount of fibroglandular tissue (FGT) with magnetic resonance imaging (MRI), and to investigate whether FGT assessment benefits from an automated, observer-independent, quantitative MRI measurement by comparing both approaches. Eighty women with no imaging abnormalities (BI-RADS 1 and 2) were included in this institutional review board (IRB)-approved prospective study. All women underwent un-enhanced breast MRI. Four radiologists independently assessed FGT with MRI by subjective visual estimation according to BI-RADS. Automated observer-independent quantitative measurement of FGT with MRI was performed using a previously described measurement system. Inter-/intra-observer agreements of qualitative and quantitative FGT measurements were assessed using Cohen's kappa (k). Inexperienced readers achieved moderate inter-/intra-observer agreement and experienced readers a substantial inter- and perfect intra-observer agreement for subjective visual estimation of FGT. Practice and experience reduced observer-dependency. Automated observer-independent quantitative measurement of FGT was successfully performed and revealed only fair to moderate agreement (k = 0.209-0.497) with subjective visual estimations of FGT. Subjective visual estimation of FGT with MRI shows moderate intra-/inter-observer agreement, which can be improved by practice and experience. Automated observer-independent quantitative measurements of FGT are necessary to allow a standardized risk evaluation. (orig.)

  18. Observer-Based Fuel Control Using Oxygen Measurement

    DEFF Research Database (Denmark)

    Andersen, Palle; Bendtsen, Jan Dimon; Mortensen, Jan Henrik

    is constructed and validated against data obtained at the plant. A Kalman filter based on measurements of combustion air flow led into the furnace and oxygen concentration in the flue gas is designed to estimate the actual coal flow. With this estimate, it becomes possible to close an inner loop around the coal......This report describes an attempt to improve the existing control af coal mills used at the Danish power plant Nordjyllandsværket Unit 3. The coal mills are not equipped with coal flow sensors; thus an observer-based approach is investigated. A nonlinear differential equation model of the boiler...

  19. Model-based estimation for dynamic cardiac studies using ECT.

    Science.gov (United States)

    Chiao, P C; Rogers, W L; Clinthorne, N H; Fessler, J A; Hero, A O

    1994-01-01

    The authors develop a strategy for joint estimation of physiological parameters and myocardial boundaries using ECT (emission computed tomography). They construct an observation model to relate parameters of interest to the projection data and to account for limited ECT system resolution and measurement noise. The authors then use a maximum likelihood (ML) estimator to jointly estimate all the parameters directly from the projection data without reconstruction of intermediate images. They also simulate myocardial perfusion studies based on a simplified heart model to evaluate the performance of the model-based joint ML estimator and compare this performance to the Cramer-Rao lower bound. Finally, the authors discuss model assumptions and potential uses of the joint estimation strategy.

  20. Underwater navigation using diffusion-based trajectory observers

    DEFF Research Database (Denmark)

    Jouffroy, Jerome; Opderbecke, Jan

    2007-01-01

    This paper addresses the issue of estimating underwater vehicle trajectories using gyro-Doppler (body-fixed velocities) and acoustic positioning signals (earth-fixed positions). The approach consists of diffusion-based observers processing a whole trajectory segment at a time, allowing the consid...

  1. Rain cell-based identification of the vertical profile of reflectivity as observed by weather radar and its use for precipitation uncertainty estimation

    Science.gov (United States)

    Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.

    2012-04-01

    The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.

  2. Comparing Three Approaches of Evapotranspiration Estimation in Mixed Urban Vegetation: Field-Based, Remote Sensing-Based and Observational-Based Methods

    Directory of Open Access Journals (Sweden)

    Hamideh Nouri

    2016-06-01

    Full Text Available Despite being the driest inhabited continent, Australia has one of the highest per capita water consumptions in the world. In addition, instead of having fit-for-purpose water supplies (using different qualities of water for different applications, highly treated drinking water is used for nearly all of Australia’s urban water supply needs, including landscape irrigation. The water requirement of urban landscapes, particularly urban parklands, is of growing concern. The estimation of evapotranspiration (ET and subsequently plant water requirements in urban vegetation needs to consider the heterogeneity of plants, soils, water, and climate characteristics. This research contributes to a broader effort to establish sustainable irrigation practices within the Adelaide Parklands in Adelaide, South Australia. In this paper, two practical ET estimation approaches are compared to a detailed Soil Water Balance (SWB analysis over a one year period. One approach is the Water Use Classification of Landscape Plants (WUCOLS method, which is based on expert opinion on the water needs of different classes of landscape plants. The other is a remote sensing approach based on the Enhanced Vegetation Index (EVI from Moderate Resolution Imaging Spectroradiometer (MODIS sensors on the Terra satellite. Both methods require knowledge of reference ET calculated from meteorological data. The SWB determined that plants consumed 1084 mm·yr−1 of water in ET with an additional 16% lost to drainage past the root zone, an amount sufficient to keep salts from accumulating in the root zone. ET by MODIS EVI was 1088 mm·yr−1, very close to the SWB estimate, while WUCOLS estimated the total water requirement at only 802 mm·yr−1, 26% lower than the SWB estimate and 37% lower than the amount actually added including the drainage fraction. Individual monthly ET by MODIS was not accurate, but these errors were cancelled out to give good agreement on an annual time step. We

  3. Model-based estimation for dynamic cardiac studies using ECT

    International Nuclear Information System (INIS)

    Chiao, P.C.; Rogers, W.L.; Clinthorne, N.H.; Fessler, J.A.; Hero, A.O.

    1994-01-01

    In this paper, the authors develop a strategy for joint estimation of physiological parameters and myocardial boundaries using ECT (Emission Computed Tomography). The authors construct an observation model to relate parameters of interest to the projection data and to account for limited ECT system resolution and measurement noise. The authors then use a maximum likelihood (ML) estimator to jointly estimate all the parameters directly from the projection data without reconstruction of intermediate images. The authors also simulate myocardial perfusion studies based on a simplified heart model to evaluate the performance of the model-based joint ML estimator and compare this performance to the Cramer-Rao lower bound. Finally, model assumptions and potential uses of the joint estimation strategy are discussed

  4. Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators

    Science.gov (United States)

    Parmenter, R.R.; Yates, Terry L.; Anderson, D.R.; Burnham, K.P.; Dunnum, J.L.; Franklin, A.B.; Friggens, M.T.; Lubow, B.C.; Miller, M.; Olson, G.S.; Parmenter, Cheryl A.; Pollard, J.; Rexstad, E.; Shenk, T.M.; Stanley, T.R.; White, Gary C.

    2003-01-01

    blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web-based uniform and half-normal models in program DISTANCE, and the grid-based models Mb and Mbh in program CAPTURE (with AÌ‚ adjusted by species-specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web-based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid-based DÌ‚ analyses using full MMDM values for WÌ‚ area adjustments required a number of theoretical assumptions of uncertain validity, and we therefore viewed their empirical successes with caution. Finally, density estimates from the independent analysts were highly variable, but estimates from web-based approaches had smaller mean square errors and better achieved confidence-interval coverage of D than did grid-based approaches. Our results support the contention that web-based approaches for density estimation of small-mammal populations are both theoretically and empirically superior to grid-based approaches, even when sample size is far less than often recommended. In view of the increasing need for standardized environmental measures for comparisons among ecosystems and through time, analytical models based on distance sampling appear to offer accurate density estimation approaches for research

  5. Robust Fault Estimation Design for Discrete-Time Nonlinear Systems via A Modified Fuzzy Fault Estimation Observer.

    Science.gov (United States)

    Xie, Xiang-Peng; Yue, Dong; Park, Ju H

    2018-02-01

    The paper provides relaxed designs of fault estimation observer for nonlinear dynamical plants in the Takagi-Sugeno form. Compared with previous theoretical achievements, a modified version of fuzzy fault estimation observer is implemented with the aid of the so-called maximum-priority-based switching law. Given each activated switching status, the appropriate group of designed matrices can be provided so as to explore certain key properties of the considered plants by means of introducing a set of matrix-valued variables. Owing to the reason that more abundant information of the considered plants can be updated in due course and effectively exploited for each time instant, the conservatism of the obtained result is less than previous theoretical achievements and thus the main defect of those existing methods can be overcome to some extent in practice. Finally, comparative simulation studies on the classical nonlinear truck-trailer model are given to certify the benefits of the theoretic achievement which is obtained in our study. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Kernel density estimation-based real-time prediction for respiratory motion

    International Nuclear Information System (INIS)

    Ruan, Dan

    2010-01-01

    Effective delivery of adaptive radiotherapy requires locating the target with high precision in real time. System latency caused by data acquisition, streaming, processing and delivery control necessitates prediction. Prediction is particularly challenging for highly mobile targets such as thoracic and abdominal tumors undergoing respiration-induced motion. The complexity of the respiratory motion makes it difficult to build and justify explicit models. In this study, we honor the intrinsic uncertainties in respiratory motion and propose a statistical treatment of the prediction problem. Instead of asking for a deterministic covariate-response map and a unique estimate value for future target position, we aim to obtain a distribution of the future target position (response variable) conditioned on the observed historical sample values (covariate variable). The key idea is to estimate the joint probability distribution (pdf) of the covariate and response variables using an efficient kernel density estimation method. Then, the problem of identifying the distribution of the future target position reduces to identifying the section in the joint pdf based on the observed covariate. Subsequently, estimators are derived based on this estimated conditional distribution. This probabilistic perspective has some distinctive advantages over existing deterministic schemes: (1) it is compatible with potentially inconsistent training samples, i.e., when close covariate variables correspond to dramatically different response values; (2) it is not restricted by any prior structural assumption on the map between the covariate and the response; (3) the two-stage setup allows much freedom in choosing statistical estimates and provides a full nonparametric description of the uncertainty for the resulting estimate. We evaluated the prediction performance on ten patient RPM traces, using the root mean squared difference between the prediction and the observed value normalized by the

  7. Refining estimates of prescription durations by using observed covariates in pharmacoepidemiological databases

    DEFF Research Database (Denmark)

    Støvring, Henrik; Pottegård, Anton; Hallas, Jesper

    2017-01-01

    , patient sex and patient age as covariates. Results: The estimated prescription durations increased with redeemed amount and age. Women generally had longer prescription durations, which increased more with age than men. For 70-year-old women redeeming 300+ pills, we predicted a 95th percentile...... of the inter-arrival density of 225 (95%CI: 201, 249) days. For 50-year-old men redeeming 100 pills, the corresponding prediction was 97 (88, 106) days. Conclusions: The algorithm allows estimation of prescription durations based on the reverse WTD, which can depend upon observed covariates. Statistical...

  8. Quantifying Surface Energy Flux Estimation Uncertainty Using Land Surface Temperature Observations

    Science.gov (United States)

    French, A. N.; Hunsaker, D.; Thorp, K.; Bronson, K. F.

    2015-12-01

    Remote sensing with thermal infrared is widely recognized as good way to estimate surface heat fluxes, map crop water use, and detect water-stressed vegetation. When combined with net radiation and soil heat flux data, observations of sensible heat fluxes derived from surface temperatures (LST) are indicative of instantaneous evapotranspiration (ET). There are, however, substantial reasons LST data may not provide the best way to estimate of ET. For example, it is well known that observations and models of LST, air temperature, or estimates of transport resistances may be so inaccurate that physically based model nevertheless yield non-meaningful results. Furthermore, using visible and near infrared remote sensing observations collected at the same time as LST often yield physically plausible results because they are constrained by less dynamic surface conditions such as green fractional cover. Although sensitivity studies exist that help identify likely sources of error and uncertainty, ET studies typically do not provide a way to assess the relative importance of modeling ET with and without LST inputs. To better quantify model benefits and degradations due to LST observational inaccuracies, a Bayesian uncertainty study was undertaken using data collected in remote sensing experiments at Maricopa, Arizona. Visible, near infrared and thermal infrared data were obtained from an airborne platform. The prior probability distribution of ET estimates were modeled using fractional cover, local weather data and a Penman-Monteith mode, while the likelihood of LST data was modeled from a two-source energy balance model. Thus the posterior probabilities of ET represented the value added by using LST data. Results from an ET study over cotton grown in 2014 and 2015 showed significantly reduced ET confidence intervals when LST data were incorporated.

  9. A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions.

    Science.gov (United States)

    Aralis, Hilary; Brookmeyer, Ron

    2017-01-01

    Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition intensities of the underlying continuous-time process. When transition intensities depend on the time elapsed in the current state and back transitions between states are possible, this intermittent observation process presents difficulties in estimation due to intractability of the likelihood function. In this manuscript, we present an iterative stochastic expectation-maximization algorithm that relies on a simulation-based approximation to the likelihood function and implement this algorithm using rejection sampling. In a simulation study, we demonstrate the feasibility and performance of the proposed procedure. We then demonstrate application of the algorithm to a study of dementia, the Nun Study, consisting of intermittently-observed elderly subjects in one of four possible states corresponding to intact cognition, impaired cognition, dementia, and death. We show that the proposed stochastic expectation-maximization algorithm substantially reduces bias in model parameter estimates compared to an alternative approach used in the literature, minimal path estimation. We conclude that in estimating intermittently observed semi-Markov models, the proposed approach is a computationally feasible and accurate estimation procedure that leads to substantial improvements in back transition estimates.

  10. Empirical observations offer improved estimates of forest floor carbon content across in the United States

    Science.gov (United States)

    Perry, C. H.; Domke, G. M.; Walters, B. F.; Smith, J. E.; Woodall, C. W.

    2014-12-01

    The Forest Inventory and Analysis (FIA) program of the United States Forest Service reports official estimates of national forest floor carbon (FFC) stocks and stock change to national and international parties, the US Environmental Protection Agency (USEPA) and the United Nations Framework Convention on Climate Change (UNFCCC), respectively. These estimates of national FFC stocks are derived from plot-level predictions of FFC density. We suspect the models used to predict plot-level FFC density are less than ideal for several reasons: (a) they are based upon local studies that may not reflect FFC dynamics at the national scale, (b) they are relatively insensitive to climate change, and (c) they reduce the natural variability of the data leading to misplaced confidence in the estimates. However, FIA has measured forest floor attributes since 2001 on a systematic 1/16th subset of a nation-wide array of inventory plots (7 800 of 125 000 plots). Here we address the efficacy of replacing plot-level model predictions with empirical observations of FFC density while assessing the impact of imputing FFC density values to the full plot network on national stock estimates. First, using an equivalence testing framework, we found model predictions of FFC density to differ significantly from the observations in all regions and forest types; the mean difference across all plots was 21 percent (1.81 Mg·ha-1). Furthermore, the model predictions were biased towards the lower end of extant FFC density observations, underestimating it while greatly truncating the range relative to the observations. Second, the optimal imputation approach (k-Nearest Neighbor, k-NN) resulted in values that were equivalent to observations of FFC density across a range of simulated missingness and maintained the high variability seen in the observations. We used the k-NN approach to impute FFC density values to the 94 percent of FIA inventory plots without soil measurements. Third, using the imputed

  11. Estimating tropical vertical motion profile shapes from satellite observations

    Science.gov (United States)

    Back, L. E.; Handlos, Z.

    2013-12-01

    The vertical structure of tropical deep convection strongly influences interactions with larger scale circulations and climate. This research focuses on investigating this vertical structure and its relationship with mesoscale tropical weather states. We test the hypothesis that vertical motion shape varies in association with weather state type. We estimate mean state vertical motion profile shapes for six tropical weather states defined using cloud top pressure and optical depth properties from the International Satellite Cloud Climatology Project. The relationship between vertical motion and the dry static energy budget are utilized to set up a regression analysis that empirically determines two modes of variability in vertical motion from reanalysis data. We use these empirically determined modes, this relationship and surface convergence to estimate vertical motion profile shape from observations of satellite retrievals of rainfall and surface convergence. We find that vertical motion profile shapes vary systematically between different tropical weather states. The "isolated systems" regime exhibits a more ''bottom-heavy'' profile shape compared to the convective/thick cirrus and vigorous deep convective regimes, with maximum upward vertical motion occurring in the lower troposphere rather than the middle to upper troposphere. The variability we observe with our method does not coincide with that expected based on conventional ideas about how stratiform rain fraction and vertical motion are related.

  12. Estimating daily climatologies for climate indices derived from climate model data and observations

    Science.gov (United States)

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

    2015-01-01

    Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

  13. Yield Estimation for Semipalatinsk Underground Nuclear Explosions Using Seismic Surface-wave Observations at Near-regional Distances

    Science.gov (United States)

    Adushkin, V. V.

    - A statistical procedure is described for estimating the yields of underground nuclear tests at the former Soviet Semipalatinsk test site using the peak amplitudes of short-period surface waves observed at near-regional distances (Δ Semipalatinsk explosions, including the Soviet JVE explosion of September 14, 1988, and it is demonstrated that it provides seismic estimates of explosion yield which are typically within 20% of the yields determined for these same explosions using more accurate, non-seismic techniques based on near-source observations.

  14. Observer-Based Fault Estimation and Accomodation for Dynamic Systems

    CERN Document Server

    Zhang, Ke; Shi, Peng

    2013-01-01

    Due to the increasing security and reliability demand of actual industrial process control systems, the study on fault diagnosis and fault tolerant control of dynamic systems has received considerable attention. Fault accommodation (FA) is one of effective methods that can be used to enhance system stability and reliability, so it has been widely and in-depth investigated and become a hot topic in recent years. Fault detection is used to monitor whether a fault occurs, which is the first step in FA. On the basis of fault detection, fault estimation (FE) is utilized to determine online the magnitude of the fault, which is a very important step because the additional controller is designed using the fault estimate. Compared with fault detection, the design difficulties of FE would increase a lot, so research on FE and accommodation is very challenging. Although there have been advancements reported on FE and accommodation for dynamic systems, the common methods at the present stage have design difficulties, whi...

  15. Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

    Science.gov (United States)

    Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

    2015-05-01

    Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

    Science.gov (United States)

    Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

    2008-01-01

    In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

  17. Spatio-Temporal Audio Enhancement Based on IAA Noise Covariance Matrix Estimates

    DEFF Research Database (Denmark)

    Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

    2014-01-01

    A method for estimating the noise covariance matrix in a mul- tichannel setup is proposed. The method is based on the iter- ative adaptive approach (IAA), which only needs short seg- ments of data to estimate the covariance matrix. Therefore, the method can be used for fast varying signals....... The method is based on an assumption of the desired signal being harmonic, which is used for estimating the noise covariance matrix from the covariance matrix of the observed signal. The noise co- variance estimate is used in the linearly constrained minimum variance (LCMV) filter and compared...

  18. A-Train Aerosol Observations Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-Sky Estimates

    Science.gov (United States)

    Redemann, J.; Livingston, J.; Shinozuka, Y.; Kacenelenbogen, M.; Russell, P.; LeBlanc, S.; Vaughan, M.; Ferrare, R.; Hostetler, C.; Rogers, R.; hide

    2014-01-01

    We have developed a technique for combining CALIOP aerosol backscatter, MODIS spectral AOD (aerosol optical depth), and OMI AAOD (absorption aerosol optical depth) retrievals for the purpose of estimating full spectral sets of aerosol radiative properties, and ultimately for calculating the 3-D distribution of direct aerosol radiative forcing. We present results using one year of data collected in 2007 and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the recently released MODIS Collection 6 data for aerosol optical depths derived with the dark target and deep blue algorithms has extended the coverage of the multi-sensor estimates towards higher latitudes. We compare the spatio-temporal distribution of our multi-sensor aerosol retrievals and calculations of seasonal clear-sky aerosol radiative forcing based on the aerosol retrievals to values derived from four models that participated in the latest AeroCom model intercomparison initiative. We find significant inter-model differences, in particular for the aerosol single scattering albedo, which can be evaluated using the multi-sensor A-Train retrievals. We discuss the major challenges that exist in extending our clear-sky results to all-sky conditions. On the basis of comparisons to suborbital measurements, we present some of the limitations of the MODIS and CALIOP retrievals in the presence of adjacent or underlying clouds. Strategies for meeting these challenges are discussed.

  19. Estimating Tropical Cyclone Precipitation from Station Observations

    Institute of Scientific and Technical Information of China (English)

    REN Fumin; WANG Yongmei; WANG Xiaoling; LI Weijing

    2007-01-01

    In this paper, an objective technique for estimating the tropical cyclone (TC) precipitation from station observations is proposed. Based on a comparison between the Original Objective Method (OOM) and the Expert Subjective Method (ESM), the Objective Synoptic Analysis Technique (OSAT) for partitioning TC precipitation was developed by analyzing the western North Pacific (WNP) TC historical track and the daily precipitation datasets. Being an objective way of the ESM, OSAT overcomes the main problems in OOM,by changing two fixed parameters in OOM, the thresholds for the distance of the absolute TC precipitation (D0) and the TC size (D1), into variable parameters.Case verification for OSAT was also carried out by applying CMORPH (Climate Prediction Center MORPHing technique) daily precipitation measurements, which is NOAA's combined satellite precipitation measurement system. This indicates that OSAT is capable of distinguishing simultaneous TC precipitation rain-belts from those associated with different TCs or with middle-latitude weather systems.

  20. Fuzzy Sliding Mode Observer with Grey Prediction for the Estimation of the State-of-Charge of a Lithium-Ion Battery

    Directory of Open Access Journals (Sweden)

    Daehyun Kim

    2015-11-01

    Full Text Available We propose a state-of-charge (SOC estimation method for Li-ion batteries that combines a fuzzy sliding mode observer (FSMO with grey prediction. Unlike the existing methods based on a conventional first-order sliding mode observer (SMO and an adaptive gain SMO, the proposed method eliminates chattering in SOC estimation. In this method, which uses a fuzzy inference system, the gains of the SMO are adjusted according to the predicted future error and present estimation error of the terminal voltage. To forecast the future error value, a one-step-ahead terminal voltage prediction is obtained using a grey predictor. The proposed estimation method is validated through two types of discharge tests (a pulse discharge test and a random discharge test. The SOC estimation results are compared to the results of the conventional first-order SMO-based and the adaptive gain SMO-based methods. The experimental results show that the proposed method not only reduces chattering, but also improves estimation accuracy.

  1. Observer-based Coal Mill Control using Oxygen Measurements

    DEFF Research Database (Denmark)

    Andersen, Palle; Bendtsen, Jan Dimon; S., Tom

    2006-01-01

    This paper proposes a novel approach to coal flow estimation in pulverized coal mills, which utilizes measurements of oxygen content in the flue gas. Pulverized coal mills are typically not equipped with sensors that detect the amount of coal injected into the furnace. This makes control...... of the coal flow difficult, causing stability problems and limits the plant's load following capabilities. To alleviate this problem without having to rely on expensive flow measurement equipment, a novel observer-based approach is investigated. A Kalman filter based on measurements of combustion air flow led...... into the furnace and oxygen concentration in the flue gas is designed to estimate the actual coal flow injected into the furnace. With this estimate, it becomes possible to close an inner loop around the coal mill itself, thus giving a better disturbance rejection capability. The approach is validated against...

  2. Weibull Parameters Estimation Based on Physics of Failure Model

    DEFF Research Database (Denmark)

    Kostandyan, Erik; Sørensen, John Dalsgaard

    2012-01-01

    Reliability estimation procedures are discussed for the example of fatigue development in solder joints using a physics of failure model. The accumulated damage is estimated based on a physics of failure model, the Rainflow counting algorithm and the Miner’s rule. A threshold model is used...... for degradation modeling and failure criteria determination. The time dependent accumulated damage is assumed linearly proportional to the time dependent degradation level. It is observed that the deterministic accumulated damage at the level of unity closely estimates the characteristic fatigue life of Weibull...

  3. Tyre effective radius and vehicle velocity estimation: a variable structure observer solution

    International Nuclear Information System (INIS)

    El Tannoury, C.; Plestan, F.; Moussaoui, S.; ROMANi, N. RENAULT

    2011-01-01

    This paper proposes an application of a variable structure observer for wheel effective radius and velocity of automotive vehicles. This observer is based on high order sliding approach allowing robustness and finite time convergence. Its originality consists in assuming a nonlinear relation between the slip ratio and the friction coefficient and providing an estimation of both variables, wheel radius and vehicle velocity, from measurement of wheel angular velocity and torque. These signals being available on major modern vehicle CAN (Controller Area Network) buses, this system does not require additional sensors. A simulation example is given to illustrate the relevance of this approach.

  4. Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer

    Directory of Open Access Journals (Sweden)

    Yuan Zou

    2010-09-01

    Full Text Available In order to safely and efficiently use the power as well as to extend the lifetime of the traction battery pack, accurate estimation of State of Charge (SoC is very important and necessary. This paper presents an adaptive observer-based technique for estimating SoC of a lithium-ion battery pack used in an electric vehicle (EV. The RC equivalent circuit model in ADVISOR is applied to simulate the lithium-ion battery pack. The parameters of the battery model as a function of SoC, are identified and optimized using the numerically nonlinear least squares algorithm, based on an experimental data set. By means of the optimized model, an adaptive Luenberger observer is built to estimate online the SoC of the lithium-ion battery pack. The observer gain is adaptively adjusted using a stochastic gradient approach so as to reduce the error between the estimated battery output voltage and the filtered battery terminal voltage measurement. Validation results show that the proposed technique can accurately estimate SoC of the lithium-ion battery pack without a heavy computational load.

  5. Geographic information system-coupling sediment delivery distributed modeling based on observed data.

    Science.gov (United States)

    Lee, S E; Kang, S H

    2014-01-01

    Spatially distributed sediment delivery (SEDD) models are of great interest in estimating the expected effect of changes on soil erosion and sediment yield. However, they can only be applied if the model can be calibrated using observed data. This paper presents a geographic information system (GIS)-based method to calculate the sediment discharge from basins to coastal areas. For this, an SEDD model, with a sediment rating curve method based on observed data, is proposed and validated. The model proposed here has been developed using the combined application of the revised universal soil loss equation (RUSLE) and a spatially distributed sediment delivery ratio, within Model Builder of ArcGIS's software. The model focuses on spatial variability and is useful for estimating the spatial patterns of soil loss and sediment discharge. The model consists of two modules, a soil erosion prediction component and a sediment delivery model. The integrated approach allows for relatively practical and cost-effective estimation of spatially distributed soil erosion and sediment delivery, for gauged or ungauged basins. This paper provides the first attempt at estimating sediment delivery ratio based on observed data in the monsoon region of Korea.

  6. Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

    Science.gov (United States)

    Guzinski, R.; Anderson, M. C.; Kustas, W. P.; Nieto, H.; Sandholt, I.

    2013-07-01

    The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish

  7. Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations

    Directory of Open Access Journals (Sweden)

    R. Guzinski

    2013-07-01

    Full Text Available The Dual Temperature Difference (DTD model, introduced by Norman et al. (2000, uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the

  8. Diffusion-Based Trajectory Observers with Variance Constraints

    DEFF Research Database (Denmark)

    Alcocer, Alex; Jouffroy, Jerome; Oliveira, Paulo

    Diffusion-based trajectory observers have been recently proposed as a simple and efficient framework to solve diverse smoothing problems in underwater navigation. For instance, to obtain estimates of the trajectories of an underwater vehicle given position fixes from an acoustic positioning system...... of smoothing and is determined by resorting to trial and error. This paper presents a methodology to choose the observer gain by taking into account a priori information on the variance of the position measurement errors. Experimental results with data from an acoustic positioning system are presented...

  9. Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

    Science.gov (United States)

    Shrivastava, Akash; Mohanty, A. R.

    2018-03-01

    This paper proposes a model-based method to estimate single plane unbalance parameters (amplitude and phase angle) in a rotor using Kalman filter and recursive least square based input force estimation technique. Kalman filter based input force estimation technique requires state-space model and response measurements. A modified system equivalent reduction expansion process (SEREP) technique is employed to obtain a reduced-order model of the rotor system so that limited response measurements can be used. The method is demonstrated using numerical simulations on a rotor-disk-bearing system. Results are presented for different measurement sets including displacement, velocity, and rotational response. Effects of measurement noise level, filter parameters (process noise covariance and forgetting factor), and modeling error are also presented and it is observed that the unbalance parameter estimation is robust with respect to measurement noise.

  10. A fast pulse phase estimation method for X-ray pulsar signals based on epoch folding

    Directory of Open Access Journals (Sweden)

    Xue Mengfan

    2016-06-01

    Full Text Available X-ray pulsar-based navigation (XPNAV is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint probability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC and nonlinear least squares (NLS estimators, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML estimators.

  11. Estimation of solar radiation from Australian meterological observations

    International Nuclear Information System (INIS)

    Moriarty, W.W.

    1991-01-01

    A carefully prepared set of Australian radiation and meteorological data was used to develop a system for estimating hourly or instantaneous broad band direct, diffuse and global radiation from meteorological observations. For clear sky conditions relationships developed elsewhere were adapted to Australian data. For cloudy conditions the clouds were divided into two groups, high clouds and opaque (middle and low) clouds, and corrections were made to compensate for the bias due to reporting practices for almost clear and almost overcast skies. Careful consideration was given to the decrease of visible sky toward the horizon caused by the vertical extent of opaque clouds. Equations relating cloud and other meteorological observations to the direct and diffuse radiation contained four unknown quantities, functions of cloud amount and of solar elevation, which were estimated from the data. These were the proportions of incident solar radiation passed on as direct and as diffuse radiation by high clouds, and as diffuse radiation by opaque clouds, and a factor to describe the elevation dependence of the fraction of sky not obscured by opaque clouds. When the resulting relationships were used to estimate global, direct and diffuse radiation on a horizontal surface, the results were good, especially for global radiation. Some discrepancies between estimates and measurements of diffuse and direct radiation were probably due to erroneously high measurements of diffuse radiation

  12. A Note on the Large Sample Properties of Estimators Based on Generalized Linear Models for Correlated Pseudo-observations

    DEFF Research Database (Denmark)

    Jacobsen, Martin; Martinussen, Torben

    2016-01-01

    Pseudo-values have proven very useful in censored data analysis in complex settings such as multi-state models. It was originally suggested by Andersen et al., Biometrika, 90, 2003, 335 who also suggested to estimate standard errors using classical generalized estimating equation results. These r......Pseudo-values have proven very useful in censored data analysis in complex settings such as multi-state models. It was originally suggested by Andersen et al., Biometrika, 90, 2003, 335 who also suggested to estimate standard errors using classical generalized estimating equation results....... These results were studied more formally in Graw et al., Lifetime Data Anal., 15, 2009, 241 that derived some key results based on a second-order von Mises expansion. However, results concerning large sample properties of estimates based on regression models for pseudo-values still seem unclear. In this paper......, we study these large sample properties in the simple setting of survival probabilities and show that the estimating function can be written as a U-statistic of second order giving rise to an additional term that does not vanish asymptotically. We further show that previously advocated standard error...

  13. Observation-based estimate of the Fukushima radionuclide in the North Pacific

    Science.gov (United States)

    Yoshida, Sachiko; Jayne, Steven; Macdonald, Alison; Buesseler, Ken; Rypina, Irina

    2014-05-01

    Contaminated waters from Fukushima nuclear power plant (FNPP) were discharged directly into the North Pacific Ocean in March 2011. Coastal current system in this region and time scale of the water exchange with the open ocean is not well understood, however both observational evidence and numerical model simulation results indicate relatively rapid advection of contaminants eastward into the highly energetic mixed water region in the confluence of the Kuroshio and Oyashio. Surface drifters deployed near the FNPP in early summer 2011 show trajectories crossing the North Pacific generally following the large scale ocean circulation after one year. Previously obtained cesium (Cs) samples from multiple cruises near FNPP and off shore region between 2011 and 2013 are collected and evaluated to diagnose the propagating Cs signal crossing North Pacific Ocean. In this presentation, we use radionuclides of Fukushima origin as a tracer to understand the North Pacific circulation and mixing process after two years of release. Large numbers of the observation are repeatedly took place near shore where Cs shows still relatively higher about 10-30 Bq/m3 in 2013. Temperature-salinity (T-S) properties for the available hydrographic data indicate that the majority of the samples were obtained in the region where the water is highly influenced by the warm-salty Kuroshio origin water. Depth profiles of 35N section in March-May 2013 cruise of the U.S. Climate Variability and Predictability and Carbon (CLIVAR) repeat Hydrography sections are examined to track the radionuclide penetration into the subsurface ocean and the subduction pathways along isopycnal surfaces. Available large drifter datasets that accumulated over decades of field work can guide us in estimating the spread of these radionuclides. By applying an innovative statistical analysis to the drifter data, we investigate the spreading of radionuclides in the Pacific Ocean over 5-year time scales.

  14. Ensemble Kalman Filtering with Residual Nudging: An Extension to State Estimation Problems with Nonlinear Observation Operators

    KAUST Repository

    Luo, Xiaodong

    2014-10-01

    The ensemble Kalman filter (EnKF) is an efficient algorithm for many data assimilation problems. In certain circumstances, however, divergence of the EnKF might be spotted. In previous studies, the authors proposed an observation-space-based strategy, called residual nudging, to improve the stability of the EnKF when dealing with linear observation operators. The main idea behind residual nudging is to monitor and, if necessary, adjust the distances (misfits) between the real observations and the simulated ones of the state estimates, in the hope that by doing so one may be able to obtain better estimation accuracy. In the present study, residual nudging is extended and modified in order to handle nonlinear observation operators. Such extension and modification result in an iterative filtering framework that, under suitable conditions, is able to achieve the objective of residual nudging for data assimilation problems with nonlinear observation operators. The 40-dimensional Lorenz-96 model is used to illustrate the performance of the iterative filter. Numerical results show that, while a normal EnKF may diverge with nonlinear observation operators, the proposed iterative filter remains stable and leads to reasonable estimation accuracy under various experimental settings.

  15. An optimal pole-matching observer design for estimating tyre-road friction force

    Science.gov (United States)

    Faraji, Mohammad; Johari Majd, Vahid; Saghafi, Behrooz; Sojoodi, Mahdi

    2010-10-01

    In this paper, considering the dynamical model of tyre-road contacts, we design a nonlinear observer for the on-line estimation of tyre-road friction force using the average lumped LuGre model without any simplification. The design is the extension of a previously offered observer to allow a muchmore realistic estimation by considering the effect of the rolling resistance and a term related to the relative velocity in the observer. Our aim is not to introduce a new friction model, but to present a more accurate nonlinear observer for the assumed model. We derive linear matrix equality conditions to obtain an observer gain with minimum pole mismatch for the desired observer error dynamic system. We prove the convergence of the observer for the non-simplified model. Finally, we compare the performance of the proposed observer with that of the previously mentioned nonlinear observer, which shows significant improvement in the accuracy of estimation.

  16. Estimates of the field-aligned current density in current-carrying filaments using auroral zone ground-based observations

    Directory of Open Access Journals (Sweden)

    M. A. Danielides

    Full Text Available We described the ground signatures of dynamic substorm features as observed by the imaging riometer, magnetometers and all-sky camera (ASC at Kilpisjärvi, Finland on 5 and 25 October 1999 during the late evening hours. The magnetometer data was consistent with the motion of up-ward field-aligned currents (FACs associated with absorption patches moving within the field of view of the riometer. We used riometer data in order to estimate the intensity of FACs associated with these local current-carrying filaments. It is shown that during these events, the estimated FAC intensity exceeds a threshold value that corresponds to the excitation of the low-frequency turbulence in the upper ionosphere. As a result, a quasi-oscillating regime of anomalous resistivity on the auroral field lines can give rise to the burst-like electron acceleration responsible for simultaneously observed auroral forms and bursts of Pi1B pulsations.

    Key words. Ionosphere (active experiments; auroral ionosphere; electric fields and currents

  17. Genetic algorithm-based improved DOA estimation using fourth-order cumulants

    Science.gov (United States)

    Ahmed, Ammar; Tufail, Muhammad

    2017-05-01

    Genetic algorithm (GA)-based direction of arrival (DOA) estimation is proposed using fourth-order cumulants (FOC) and ESPRIT principle which results in Multiple Invariance Cumulant ESPRIT algorithm. In the existing FOC ESPRIT formulations, only one invariance is utilised to estimate DOAs. The unused multiple invariances (MIs) must be exploited simultaneously in order to improve the estimation accuracy. In this paper, a fitness function based on a carefully designed cumulant matrix is developed which incorporates MIs present in the sensor array. Better DOA estimation can be achieved by minimising this fitness function. Moreover, the effectiveness of Newton's method as well as GA for this optimisation problem has been illustrated. Simulation results show that the proposed algorithm provides improved estimation accuracy compared to existing algorithms, especially in the case of low SNR, less number of snapshots, closely spaced sources and high signal and noise correlation. Moreover, it is observed that the optimisation using Newton's method is more likely to converge to false local optima resulting in erroneous results. However, GA-based optimisation has been found attractive due to its global optimisation capability.

  18. BLACK HOLE MASS ESTIMATES BASED ON C IV ARE CONSISTENT WITH THOSE BASED ON THE BALMER LINES

    Energy Technology Data Exchange (ETDEWEB)

    Assef, R. J.; Denney, K. D.; Kochanek, C. S.; Peterson, B. M.; Kozlowski, S.; Dietrich, M.; Grier, C. J.; Khan, R. [Department of Astronomy, The Ohio State University, 140 W. 18th Ave., Columbus, OH 43210 (United States); Ageorges, N.; Buschkamp, P.; Gemperlein, H.; Hofmann, R. [Max-Planck-Institut fuer Extraterrestrische Physik, Giessenbachstr., D-85748 Garching (Germany); Barrows, R. S. [Arkansas Center for Space and Planetary Sciences, University of Arkansas, Fayetteville, AR 72701 (United States); Falco, E.; Kilic, M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Feiz, C.; Germeroth, A. [Landessternwarte, ZAH, Koenigstuhl 12, D-69117 Heidelberg (Germany); Juette, M.; Knierim, V. [Astron. Institut der Ruhr Univ. Bochum, Universitaetsstr. 150, D-44780 Bochum (Germany); Laun, W., E-mail: rjassef@astronomy.ohio-state.edu [Max-Planck-Institut fuer Astronomie, Koenigstuhl 17, D-69117 Heidelberg (Germany); and others

    2011-12-01

    Using a sample of high-redshift lensed quasars from the CASTLES project with observed-frame ultraviolet or optical and near-infrared spectra, we have searched for possible biases between supermassive black hole (BH) mass estimates based on the C IV, H{alpha}, and H{beta} broad emission lines. Our sample is based upon that of Greene, Peng, and Ludwig, expanded with new near-IR spectroscopic observations, consistently analyzed high signal-to-noise ratio (S/N) optical spectra, and consistent continuum luminosity estimates at 5100 A. We find that BH mass estimates based on the full width at half-maximum (FWHM) of C IV show a systematic offset with respect to those obtained from the line dispersion, {sigma}{sub l}, of the same emission line, but not with those obtained from the FWHM of H{alpha} and H{beta}. The magnitude of the offset depends on the treatment of the He II and Fe II emission blended with C IV, but there is little scatter for any fixed measurement prescription. While we otherwise find no systematic offsets between C IV and Balmer line mass estimates, we do find that the residuals between them are strongly correlated with the ratio of the UV and optical continuum luminosities. This means that much of the dispersion in previous comparisons of C IV and H{beta} BH mass estimates are due to the continuum luminosities rather than to any properties of the lines. Removing this dependency reduces the scatter between the UV- and optical-based BH mass estimates by a factor of approximately two, from roughly 0.35 to 0.18 dex. The dispersion is smallest when comparing the C IV {sigma}{sub l} mass estimate, after removing the offset from the FWHM estimates, and either Balmer line mass estimate. The correlation with the continuum slope is likely due to a combination of reddening, host contamination, and object-dependent SED shapes. When we add additional heterogeneous measurements from the literature, the results are unchanged. Moreover, in a trial observation of a

  19. Estimating evaporative vapor generation from automobiles based on parking activities

    International Nuclear Information System (INIS)

    Dong, Xinyi; Tschantz, Michael; Fu, Joshua S.

    2015-01-01

    A new approach is proposed to quantify the evaporative vapor generation based on real parking activity data. As compared to the existing methods, two improvements are applied in this new approach to reduce the uncertainties: First, evaporative vapor generation from diurnal parking events is usually calculated based on estimated average parking duration for the whole fleet, while in this study, vapor generation rate is calculated based on parking activities distribution. Second, rather than using the daily temperature gradient, this study uses hourly temperature observations to derive the hourly incremental vapor generation rates. The parking distribution and hourly incremental vapor generation rates are then adopted with Wade–Reddy's equation to estimate the weighted average evaporative generation. We find that hourly incremental rates can better describe the temporal variations of vapor generation, and the weighted vapor generation rate is 5–8% less than calculation without considering parking activity. - Highlights: • We applied real parking distribution data to estimate evaporative vapor generation. • We applied real hourly temperature data to estimate hourly incremental vapor generation rate. • Evaporative emission for Florence is estimated based on parking distribution and hourly rate. - A new approach is proposed to quantify the weighted evaporative vapor generation based on parking distribution with an hourly incremental vapor generation rate

  20. Estimation of Longitudinal Force and Sideslip Angle for Intelligent Four-Wheel Independent Drive Electric Vehicles by Observer Iteration and Information Fusion.

    Science.gov (United States)

    Chen, Te; Chen, Long; Xu, Xing; Cai, Yingfeng; Jiang, Haobin; Sun, Xiaoqiang

    2018-04-20

    Exact estimation of longitudinal force and sideslip angle is important for lateral stability and path-following control of four-wheel independent driven electric vehicle. This paper presents an effective method for longitudinal force and sideslip angle estimation by observer iteration and information fusion for four-wheel independent drive electric vehicles. The electric driving wheel model is introduced into the vehicle modeling process and used for longitudinal force estimation, the longitudinal force reconstruction equation is obtained via model decoupling, the a Luenberger observer and high-order sliding mode observer are united for longitudinal force observer design, and the Kalman filter is applied to restrain the influence of noise. Via the estimated longitudinal force, an estimation strategy is then proposed based on observer iteration and information fusion, in which the Luenberger observer is applied to achieve the transcendental estimation utilizing less sensor measurements, the extended Kalman filter is used for a posteriori estimation with higher accuracy, and a fuzzy weight controller is used to enhance the adaptive ability of observer system. Simulations and experiments are carried out, and the effectiveness of proposed estimation method is verified.

  1. Iterative observer based method for source localization problem for Poisson equation in 3D

    KAUST Repository

    Majeed, Muhammad Usman

    2017-07-10

    A state-observer based method is developed to solve point source localization problem for Poisson equation in a 3D rectangular prism with available boundary data. The technique requires a weighted sum of solutions of multiple boundary data estimation problems for Laplace equation over the 3D domain. The solution of each of these boundary estimation problems involves writing down the mathematical problem in state-space-like representation using one of the space variables as time-like. First, system observability result for 3D boundary estimation problem is recalled in an infinite dimensional setting. Then, based on the observability result, the boundary estimation problem is decomposed into a set of independent 2D sub-problems. These 2D problems are then solved using an iterative observer to obtain the solution. Theoretical results are provided. The method is implemented numerically using finite difference discretization schemes. Numerical illustrations along with simulation results are provided.

  2. A non-stationary cost-benefit based bivariate extreme flood estimation approach

    Science.gov (United States)

    Qi, Wei; Liu, Junguo

    2018-02-01

    Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

  3. Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw; Anderson, M.C.; Kustas, W.P.

    2013-01-01

    The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature...... agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use....

  4. Estimating Terrestrial Wood Biomass from Observed Concentrations of Atmospheric Carbon Dioxide

    NARCIS (Netherlands)

    Schaefer, K. M.; Peters, W.; Carvalhais, N.; van der Werf, G.; Miller, J.

    2008-01-01

    We estimate terrestrial disequilibrium state and wood biomass from observed concentrations of atmospheric CO2 using the CarbonTracker system coupled to the SiBCASA biophysical model. Starting with a priori estimates of carbon flux from the land, ocean, and fossil fuels, CarbonTracker estimates net

  5. Estimation of interplate coupling along Nankai trough considering the block motion model based on onland GNSS and seafloor GPS/A observation data using MCMC method

    Science.gov (United States)

    Kimura, H.; Ito, T.; Tadokoro, K.

    2017-12-01

    Introduction In southwest Japan, Philippine sea plate is subducting under the overriding plate such as Amurian plate, and mega interplate earthquakes has occurred at about 100 years interval. There is no occurrence of mega interplate earthquakes in southwest Japan, although it has passed about 70 years since the last mega interplate earthquakes: 1944 and 1946 along Nankai trough, meaning that the strain has been accumulated at plate interface. Therefore, it is essential to reveal the interplate coupling more precisely for predicting or understanding the mechanism of next occurring mega interplate earthquake. Recently, seafloor geodetic observation revealed the detailed interplate coupling distribution in expected source region of Nankai trough earthquake (e.g., Yokota et al. [2016]). In this study, we estimated interplate coupling in southwest Japan, considering block motion model and using seafloor geodetic observation data as well as onland GNSS observation data, based on Markov Chain Monte Carlo (MCMC) method. Method Observed crustal deformation is assumed that sum of rigid block motion and elastic deformation due to coupling at block boundaries. We modeled this relationship as a non-linear inverse problem that the unknown parameters are Euler pole of each block and coupling at each subfault, and solved them simultaneously based on MCMC method. Input data we used in this study are 863 onland GNSS observation data and 24 seafloor GPS/A observation data. We made some block division models based on the map of active fault tracing and selected the best model based on Akaike's Information Criterion (AIC): that is consist of 12 blocks. Result We find that the interplate coupling along Nankai trough has heterogeneous spatial distribution, strong at the depth of 0 to 20km at off Tokai region, and 0 to 30km at off Shikoku region. Moreover, we find that observed crustal deformation at off Tokai region is well explained by elastic deformation due to subducting Izu Micro

  6. A novel method for state of charge estimation of lithium-ion batteries using a nonlinear observer

    Science.gov (United States)

    Xia, Bizhong; Chen, Chaoren; Tian, Yong; Sun, Wei; Xu, Zhihui; Zheng, Weiwei

    2014-12-01

    The state of charge (SOC) is important for the safety and reliability of battery operation since it indicates the remaining capacity of a battery. However, as the internal state of each cell cannot be directly measured, the value of the SOC has to be estimated. In this paper, a novel method for SOC estimation in electric vehicles (EVs) using a nonlinear observer (NLO) is presented. One advantage of this method is that it does not need complicated matrix operations, so the computation cost can be reduced. As a key step in design of the nonlinear observer, the state-space equations based on the equivalent circuit model are derived. The Lyapunov stability theory is employed to prove the convergence of the nonlinear observer. Four experiments are carried out to evaluate the performance of the presented method. The results show that the SOC estimation error converges to 3% within 130 s while the initial SOC error reaches 20%, and does not exceed 4.5% while the measurement suffers both 2.5% voltage noise and 5% current noise. Besides, the presented method has advantages over the extended Kalman filter (EKF) and sliding mode observer (SMO) algorithms in terms of computation cost, estimation accuracy and convergence rate.

  7. Ideal observer estimation and generalized ROC analysis for computer-aided diagnosis

    International Nuclear Information System (INIS)

    Edwards, Darrin C.

    2004-01-01

    The research presented in this dissertation represents an innovative application of computer-aided diagnosis and signal detection theory to the specific task of early detection of breast cancer in the context of screening mammography. A number of automated schemes have been developed in our laboratory to detect masses and clustered microcalcifications in digitized mammograms, on the one hand, and to classify known lesions as malignant or benign, on the other. The development of fully automated classification schemes is difficult, because the output of a detection scheme will contain false-positive detections in addition to detected malignant and benign lesions, resulting in a three-class classification task. Researchers have so far been unable to extend successful tools for analyzing two-class classification tasks, such as receiver operating characteristic (ROC) analysis, to three-class classification tasks. The goals of our research were to use Bayesian artificial neural networks to estimate ideal observer decision variables to both detect and classify clustered microcalcifications and mass lesions in mammograms, and to derive substantial theoretical results indicating potential avenues of approach toward the three-class classification task. Specifically, we have shown that an ideal observer in an N-class classification task achieves an optimal ROC hypersurface, just as the two-class ideal observer achieves an optimal ROC curve; and that an obvious generalization of a well-known two-class performance metric, the area under the ROC curve, is not useful as a performance metric in classification tasks with more than two classes. This work is significant for three reasons. First, it involves the explicit estimation of feature-based (as opposed to image-based) ideal observer decision variables in the tasks of detecting and classifying mammographic lesions. Second, it directly addresses the three-class classification task of distinguishing malignant lesions, benign

  8. Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

    KAUST Repository

    2016-08-29

    In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

  9. Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation

    KAUST Repository

    Unknown author

    2016-01-01

    In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.

  10. Multi-Pitch Estimation of Audio Recordings Using a Codebook-Based Approach

    DEFF Research Database (Denmark)

    Hansen, Martin Weiss; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

    2016-01-01

    ), and a codebook consisting of realistic amplitude vectors. A nonlinear least squares (NLS) cost function is formed based on the observed signal and a parametric model of the signal, for a set of fundamental frequency candidates. For each of these, amplitude estimates are computed. The magnitudes...... of these estimates are quantized according to a codebook, and an updated cost function is used to estimate the fundamental frequencies of the sources. The performance of the proposed estimator is evaluated using synthetic and real mixtures, and the results show that the proposed method is able to estimate multiple...

  11. Estimating the Economic Benefits of Regional Ocean Observing Systems

    National Research Council Canada - National Science Library

    Kite-Powell, Hauke L; Colgan, Charles S; Wellman, Katharine F; Pelsoci, Thomas; Wieand, Kenneth; Pendleton, Linwood; Kaiser, Mark J; Pulsipher, Allan G; Luger, Michael

    2005-01-01

    We develop a methodology to estimate the potential economic benefits from new investments in regional coastal ocean observing systems in US waters, and apply this methodology to generate preliminary...

  12. Estimation of the radial force using a disturbance force observer for a magnetically levitated centrifugal blood pump.

    Science.gov (United States)

    Pai, C N; Shinshi, T; Shimokohbe, A

    2010-01-01

    Evaluation of the hydraulic forces in a magnetically levitated (maglev) centrifugal blood pump is important from the point of view of the magnetic bearing design. Direct measurement is difficult due to the absence of a rotor shaft, and computational fluid dynamic analysis demands considerable computational resource and time. To solve this problem, disturbance force observers were developed, using the radial controlled magnetic bearing of a centrifugal blood pump, to estimate the radial forces on the maglev impeller. In order to design the disturbance observer, the radial dynamic characteristics of a maglev impeller were evaluated under different working conditions. It was observed that the working fluid affects the additional mass and damping, while the rotational speed affects the damping and stiffness of the maglev system. Based on these results, disturbance force observers were designed and implemented. The designed disturbance force observers present a bandwidth of 45 Hz. In non-pulsatile conditions, the magnitude of the estimated radial thrust increases in proportion to the flowrate, and the rotational speed has little effect on the force direction. At 5 l/min against 100 mmHg, the estimated radial thrust is 0.95 N. In pulsatile conditions, this method was capable of estimating the pulsatile radial thrust with good response.

  13. A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

    Science.gov (United States)

    Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

    2017-07-01

    Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100-200 % for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASC measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18 % difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36 % for the individual events. Use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122 % for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. More accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.

  14. NASA Software Cost Estimation Model: An Analogy Based Estimation Model

    Science.gov (United States)

    Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James

    2015-01-01

    The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K-­ nearest neighbor prediction model performance on the same data set.

  15. Observing Tsunamis in the Ionosphere Using Ground Based GPS Measurements

    Science.gov (United States)

    Galvan, D. A.; Komjathy, A.; Song, Y. Tony; Stephens, P.; Hickey, M. P.; Foster, J.

    2011-01-01

    Ground-based Global Positioning System (GPS) measurements of ionospheric Total Electron Content (TEC) show variations consistent with atmospheric internal gravity waves caused by ocean tsunamis following recent seismic events, including the Tohoku tsunami of March 11, 2011. We observe fluctuations correlated in time, space, and wave properties with this tsunami in TEC estimates processed using JPL's Global Ionospheric Mapping Software. These TEC estimates were band-pass filtered to remove ionospheric TEC variations with periods outside the typical range of internal gravity waves caused by tsunamis. Observable variations in TEC appear correlated with the Tohoku tsunami near the epicenter, at Hawaii, and near the west coast of North America. Disturbance magnitudes are 1-10% of the background TEC value. Observations near the epicenter are compared to estimates of expected tsunami-driven TEC variations produced by Embry Riddle Aeronautical University's Spectral Full Wave Model, an atmosphere-ionosphere coupling model, and found to be in good agreement. The potential exists to apply these detection techniques to real-time GPS TEC data, providing estimates of tsunami speed and amplitude that may be useful for future early warning systems.

  16. Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

    Science.gov (United States)

    MOHAMMED, M. A. SI; BOUSSADIA, H.; BELLAR, A.; ADNANE, A.

    2017-01-01

    This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.

  17. Cooperative Fault Tolerant Tracking Control for Multiagent Systems: An Intermediate Estimator-Based Approach.

    Science.gov (United States)

    Zhu, Jun-Wei; Yang, Guang-Hong; Zhang, Wen-An; Yu, Li

    2017-10-17

    This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some specified parameters. Finally, a simulation example of aircraft demonstrates the effectiveness of the designed tracking protocol.This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some

  18. Direct Aerosol Radiative Forcing from Combined A-Train Observations - Preliminary Comparisons with AeroCom Models and Pathways to Observationally Based All-sky Estimates

    Science.gov (United States)

    Redemann, J.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Russell, P. B.; LeBlanc, S. E.; Vaughan, M.; Ferrare, R. A.; Hostetler, C. A.; Rogers, R. R.; Burton, S. P.; Torres, O.; Remer, L. A.; Stier, P.; Schutgens, N.

    2014-12-01

    We describe a technique for combining CALIOP aerosol backscatter, MODIS spectral AOD (aerosol optical depth), and OMI AAOD (absorption aerosol optical depth) retrievals for the purpose of estimating full spectral sets of aerosol radiative properties, and ultimately for calculating the 3-D distribution of direct aerosol radiative forcing. We present results using one year of data collected in 2007 and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the recently released MODIS Collection 6 data for aerosol optical depths derived with the dark target and deep blue algorithms has extended the coverage of the multi-sensor estimates towards higher latitudes. Initial calculations of seasonal clear-sky aerosol radiative forcing based on our multi-sensor aerosol retrievals compare well with over-ocean and top of the atmosphere IPCC-2007 model-based results, and with more recent assessments in the "Climate Change Science Program Report: Atmospheric Aerosol Properties and Climate Impacts" (2009). For the first time, we present comparisons of our multi-sensor aerosol direct radiative forcing estimates to values derived from a subset of models that participated in the latest AeroCom initiative. We discuss the major challenges that exist in extending our clear-sky results to all-sky conditions. On the basis of comparisons to suborbital measurements, we present some of the limitations of the MODIS and CALIOP retrievals in the presence of adjacent or underlying clouds. Strategies for meeting these challenges are discussed.

  19. ESTIMATION OF GRASPING TORQUE USING ROBUST REACTION TORQUE OBSERVER FOR ROBOTIC FORCEPS

    OpenAIRE

    塚本, 祐介

    2015-01-01

    Abstract— In this paper, the estimation of the grasping torque of robotic forceps without the use of a force/torque sensor is discussed. To estimate the grasping torque when the robotic forceps driven by a rotary motor with a reduction gear grasps an object, a novel robust reaction torque observer is proposed. In the case where a conventional reaction force/torque observer is applied, the estimated torque includes not only the grasping torque, namely the reaction torque, but also t...

  20. Maxima estimate of non gaussian process from observation of time history samples

    International Nuclear Information System (INIS)

    Borsoi, L.

    1987-01-01

    The problem constitutes a formidable task but is essential for industrial applications: extreme value design, fatigue analysis, etc. Even for the linear Gaussian case, the process ergodicity does not prevent the observation duration to be long enough to make reliable estimates. As well known, this duration is closely related to the process autocorrelation. A subterfuge, which distorts a little the problem, consists in considering periodic random process and in adjusting the observation duration to a complete period. In the nonlinear case, the stated problem is as much important as time history simulation is presently the only practicable way for analysing structures. Thus it is always interesting to adjust a tractable model to rough time history observations. In some cases this can be done with a Gumble-Poisson model. Then the difficulty is to make reliable estimates of the parameters involved in the model. Unfortunately it seems that even the use of sophisticated Bayesian method does not permit to reduce as wanted the necessary observation duration. One of the difficulties lies in process ergodicity which is often assumed to be based on physical considerations but which is not always rigorously stated. An other difficulty is the confusion between hidden informations - which can be extracted - and missing informations - which cannot be extracted. Finally it must be recalled that the obligation of considering time histories long enough is not always embarrassing due to the current computer cost reduction. (orig./HP)

  1. Estimating surface soil moisture from SMAP observations using a Neural Network technique.

    Science.gov (United States)

    Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

    2018-01-01

    A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

  2. Channel Estimation in DCT-Based OFDM

    Science.gov (United States)

    Wang, Yulin; Zhang, Gengxin; Xie, Zhidong; Hu, Jing

    2014-01-01

    This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective multipath fading channel. Channel estimation has been proved to improve system throughput and performance by allowing for coherent demodulation. Pilot-aided methods are traditionally used to learn the channel response. Least square (LS) and mean square error estimators (MMSE) are investigated. We also study a compressed sensing (CS) based channel estimation, which takes the sparse property of wireless channel into account. Simulation results have shown that the CS based channel estimation is expected to have better performance than LS. However MMSE can achieve optimal performance because of prior knowledge of the channel statistic. PMID:24757439

  3. Fast Emission Estimates in China Constrained by Satellite Observations (Invited)

    Science.gov (United States)

    Mijling, B.; van der A, R.

    2013-12-01

    Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for an emerging economy such as China, where rapid economic growth changes emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. Constraining emissions from concentration measurements is, however, computationally challenging. Within the GlobEmission project of the European Space Agency (ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China, using the CHIMERE model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission estimates result in a better

  4. Accounting for correlated observations in an age-based state-space stock assessment model

    DEFF Research Database (Denmark)

    Berg, Casper Willestofte; Nielsen, Anders

    2016-01-01

    Fish stock assessment models often relyon size- or age-specific observations that are assumed to be statistically independent of each other. In reality, these observations are not raw observations, but rather they are estimates from a catch-standardization model or similar summary statistics base...... the independence assumption is rejected. Less fluctuating estimates of the fishing mortality is obtained due to a reduced process error. The improved model does not suffer from correlated residuals unlike the independent model, and the variance of forecasts is decreased....

  5. Surface Soil Moisture Memory Estimated from Models and SMAP Observations

    Science.gov (United States)

    He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D.

    2017-12-01

    Soil moisture memory(SMM), which is loosely defined as the time taken by soil to forget an anomaly, has been proved to be important in land-atmosphere interaction. There are many metrics to calculate the SMM timescale, for example, the timescale based on the time-series autocorrelation, the timescale ignoring the soil moisture time series and the timescale which only considers soil moisture increment. Recently, a new timescale based on `Water Cycle Fraction' (Kaighin et al., 2017), in which the impact of precipitation on soil moisture memory is considered, has been put up but not been fully evaluated in global. In this study, we compared the surface SMM derived from SMAP observations with that from land surface model simulations (i.e., the SMAP Nature Run (NR) provided by the Goddard Earth Observing System, version 5) (Rolf et al., 2014). Three timescale metrics were used to quantify the surface SMM as: T0 based on the soil moisture time series autocorrelation, deT0 based on the detrending soil moisture time series autocorrelation, and tHalf based on the Water Cycle Fraction. The comparisons indicate that: (1) there are big gaps between the T0 derived from SMAP and that from NR (2) the gaps get small for deT0 case, in which the seasonality of surface soil moisture was removed with a moving average filter; (3) the tHalf estimated from SMAP is much closer to that from NR. The results demonstrate that surface SMM can vary dramatically among different metrics, while the memory derived from land surface model differs from the one from SMAP observation. tHalf, with considering the impact of precipitation, may be a good choice to quantify surface SMM and have high potential in studies related to land atmosphere interactions. References McColl. K.A., S.H. Alemohammad, R. Akbar, A.G. Konings, S. Yueh, D. Entekhabi. The Global Distribution and Dynamics of Surface Soil Moisture, Nature Geoscience, 2017 Reichle. R., L. Qing, D.L. Gabrielle, A. Joe. The "SMAP_Nature_v03" Data

  6. Observations and estimates of wave-driven water level extremes at the Marshall Islands

    Science.gov (United States)

    Merrifield, M. A.; Becker, J. M.; Ford, M.; Yao, Y.

    2014-10-01

    Wave-driven extreme water levels are examined for coastlines protected by fringing reefs using field observations obtained in the Republic of the Marshall Islands. The 2% exceedence water level near the shoreline due to waves is estimated empirically for the study sites from breaking wave height at the outer reef and by combining separate contributions from setup, sea and swell, and infragravity waves, which are estimated based on breaking wave height and water level over the reef flat. Although each component exhibits a tidal dependence, they sum to yield a 2% exceedence level that does not. A hindcast based on the breaking wave height parameterization is used to assess factors leading to flooding at Roi-Namur caused by an energetic swell event during December 2008. Extreme water levels similar to December 2008 are projected to increase significantly with rising sea level as more wave and tide events combine to exceed inundation threshold levels.

  7. Estimating Field Scale Crop Evapotranspiration using Landsat and MODIS Satellite Observations

    Science.gov (United States)

    Wong, A.; Jin, Y.; Snyder, R. L.; Daniele, Z.; Gao, F.

    2016-12-01

    Irrigation accounts for 80% of human freshwater consumption, and most of it return to the atmosphere through Evapotranspiration (ET). Given the challenges of already-stressed water resources and ground water regulation in California, a cost-effective, timely, and consistent spatial estimate of crop ET, from the farm to watershed level, is becoming increasingly important. The Priestley-Taylor (PT) approach, calibrated with field data and driven by satellite observations, shows great promise for accurate ET estimates across diverse ecosystems. We here aim to improve the robustness of the PT approach in agricultural lands, to enable growers and farm managers to tailor irrigation management based on in-field spatial variability and in-season variation. We optimized the PT coefficients for each crop type with available ET measurements from eddy covariance towers and/or surface renewal stations at six crop fields (Alfalfa, Almond, Citrus, Corn, Pistachio and Rice) in California. Good agreement was found between satellite-based estimates and field measurements of net radiation, with a RMSE of less than 36 W m-2. The crop type specific optimization performed well, with a RMSE of 30 W m-2 and a correlation of 0.81 for predicted daily latent heat flux. The calibrated algorithm was used to estimate ET at 30 m resolution over the Sacramento-San Joaquin Delta region for 2015 water year. It captures well the seasonal dynamics and spatial distribution of ET in Sacramento-San Joaquin Delta. A continuous monitoring of the dynamics and spatial heterogeneity of canopy and consumptive water use at a field scale, will help the growers to be well prepared and informed to adaptively manage water, canopy, and grove density to maximize the yield with the least amount of water.

  8. Accuracy of self-reported drinking: observational verification of 'last occasion' drink estimates of young adults.

    Science.gov (United States)

    Northcote, Jeremy; Livingston, Michael

    2011-01-01

    As a formative step towards determining the accuracy of self-reported drinking levels commonly used for estimating population alcohol use, the validity of a 'last occasion' self-reporting approach is tested with corresponding field observations of participants' drinking quantity. This study is the first known attempt to validate the accuracy of self-reported alcohol consumption using data from a natural setting. A total of 81 young adults (aged 18-25 years) were purposively selected in Perth, Western Australia. Participants were asked to report the number of alcoholic drinks consumed at nightlife venues 1-2 days after being observed by peer-based researchers on 239 occasions. Complete observation data and self-report estimates were available for 129 sessions, which were fitted with multi-level models assessing the relationship between observed and reported consumption. Participants accurately estimated their consumption when engaging in light to moderate drinking (eight or fewer drinks in a single session), with no significant difference between the mean reported consumption and the mean observed consumption. In contrast, participants underestimated their own consumption by increasing amounts when engaging in heavy drinking of more than eight drinks. It is suggested that recent recall methods in self-report surveys are potentially reasonably accurate measures of actual drinking levels for light to moderate drinkers, but that underestimating of alcohol consumption increases with heavy consumption. Some of the possible reasons for underestimation of heavy drinking are discussed, with both cognitive and socio-cultural factors considered.

  9. Estimating Soil Hydraulic Parameters using Gradient Based Approach

    Science.gov (United States)

    Rai, P. K.; Tripathi, S.

    2017-12-01

    The conventional way of estimating parameters of a differential equation is to minimize the error between the observations and their estimates. The estimates are produced from forward solution (numerical or analytical) of differential equation assuming a set of parameters. Parameter estimation using the conventional approach requires high computational cost, setting-up of initial and boundary conditions, and formation of difference equations in case the forward solution is obtained numerically. Gaussian process based approaches like Gaussian Process Ordinary Differential Equation (GPODE) and Adaptive Gradient Matching (AGM) have been developed to estimate the parameters of Ordinary Differential Equations without explicitly solving them. Claims have been made that these approaches can straightforwardly be extended to Partial Differential Equations; however, it has been never demonstrated. This study extends AGM approach to PDEs and applies it for estimating parameters of Richards equation. Unlike the conventional approach, the AGM approach does not require setting-up of initial and boundary conditions explicitly, which is often difficult in real world application of Richards equation. The developed methodology was applied to synthetic soil moisture data. It was seen that the proposed methodology can estimate the soil hydraulic parameters correctly and can be a potential alternative to the conventional method.

  10. spa: Semi-Supervised Semi-Parametric Graph-Based Estimation in R

    Directory of Open Access Journals (Sweden)

    Mark Culp

    2011-04-01

    Full Text Available In this paper, we present an R package that combines feature-based (X data and graph-based (G data for prediction of the response Y . In this particular case, Y is observed for a subset of the observations (labeled and missing for the remainder (unlabeled. We examine an approach for fitting Y = Xβ + f(G where β is a coefficient vector and f is a function over the vertices of the graph. The procedure is semi-supervised in nature (trained on the labeled and unlabeled sets, requiring iterative algorithms for fitting this estimate. The package provides several key functions for fitting and evaluating an estimator of this type. The package is illustrated on a text analysis data set, where the observations are text documents (papers, the response is the category of paper (either applied or theoretical statistics, the X information is the name of the journal in which the paper resides, and the graph is a co-citation network, with each vertex an observation and each edge the number of times that the two papers cite a common paper. An application involving classification of protein location using a protein interaction graph and an application involving classification on a manifold with part of the feature data converted to a graph are also presented.

  11. Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

    Science.gov (United States)

    Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

    2017-12-06

    This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

  12. The Event Detection and the Apparent Velocity Estimation Based on Computer Vision

    Science.gov (United States)

    Shimojo, M.

    2012-08-01

    The high spatial and time resolution data obtained by the telescopes aboard Hinode revealed the new interesting dynamics in solar atmosphere. In order to detect such events and estimate the velocity of dynamics automatically, we examined the estimation methods of the optical flow based on the OpenCV that is the computer vision library. We applied the methods to the prominence eruption observed by NoRH, and the polar X-ray jet observed by XRT. As a result, it is clear that the methods work well for solar images if the images are optimized for the methods. It indicates that the optical flow estimation methods in the OpenCV library are very useful to analyze the solar phenomena.

  13. Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

    Science.gov (United States)

    Zhao, You-Qun; Li, Hai-Qing; Lin, Fen; Wang, Jian; Ji, Xue-Wu

    2017-07-01

    The accurate estimation of road friction coefficient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coefficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coefficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode surface. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels. The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time and resist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate.

  14. Precise Orbital and Geodetic Parameter Estimation using SLR Observations for ILRS AAC

    Directory of Open Access Journals (Sweden)

    Young-Rok Kim

    2013-12-01

    Full Text Available In this study, we present results of precise orbital geodetic parameter estimation using satellite laser ranging (SLR observations for the International Laser Ranging Service (ILRS associate analysis center (AAC. Using normal point observations of LAGEOS-1, LAGEOS-2, ETALON-1, and ETALON-2 in SLR consolidated laser ranging data format, the NASA/ GSFC GEODYN II and SOLVE software programs were utilized for precise orbit determination (POD and finding solutions of a terrestrial reference frame (TRF and Earth orientation parameters (EOPs. For POD, a weekly-based orbit determination strategy was employed to process SLR observations taken from 20 weeks in 2013. For solutions of TRF and EOPs, loosely constrained scheme was used to integrate POD results of four geodetic SLR satellites. The coordinates of 11 ILRS core sites were determined and daily polar motion and polar motion rates were estimated. The root mean square (RMS value of post-fit residuals was used for orbit quality assessment, and both the stability of TRF and the precision of EOPs by external comparison were analyzed for verification of our solutions. Results of post-fit residuals show that the RMS of the orbits of LAGEOS-1 and LAGEOS-2 are 1.20 and 1.12 cm, and those of ETALON-1 and ETALON-2 are 1.02 and 1.11 cm, respectively. The stability analysis of TRF shows that the mean value of 3D stability of the coordinates of 11 ILRS core sites is 7.0 mm. An external comparison, with respect to International Earth rotation and Reference systems Service (IERS 08 C04 results, shows that standard deviations of polar motion Xp and Yp are 0.754 milliarcseconds (mas and 0.576 mas, respectively. Our results of precise orbital and geodetic parameter estimation are reasonable and help advance research at ILRS AAC.

  15. State Estimation for a Biological Phosphorus Removal Process using an Asymptotic Observer

    DEFF Research Database (Denmark)

    Larose, Claude Alain; Jørgensen, Sten Bay

    2001-01-01

    This study investigated the use of an asymptotic observer for state estimation in a continuous biological phosphorus removal process. The estimated states are the concentration of heterotrophic, autotrophic, and phosphorus accumulating organisms, polyphosphate, glycogen and PHA. The reaction scheme...... if the convergence, driven by the dilution rate, was slow (from 15 to 60 days). The propagation of the measurement noise and a bias in the estimation of glycogen and PHA could be the result of the high condition number of one of the matrices used in the algorithm of the asymptotic observer for the aerated tanks....

  16. Estimating the size of non-observed economy in Croatia using the MIMIC approach

    Directory of Open Access Journals (Sweden)

    Vjekoslav Klarić

    2011-03-01

    Full Text Available This paper gives a quick overview of the approaches that have been used in the research of shadow economy, starting with the definitions of the terms “shadow economy” and “non-observed economy”, with the accent on the ISTAT/Eurostat framework. Several methods for estimating the size of the shadow economy and the non-observed economy are then presented. The emphasis is placed on the MIMIC approach, one of the methods used to estimate the size of the nonobserved economy. After a glance at the theory behind it, the MIMIC model is then applied to the Croatian economy. Considering the described characteristics of different methods, a previous estimate of the size of the non-observed economy in Croatia is chosen to provide benchmark values for the MIMIC model. Using those, the estimates of the size of non-observed economy in Croatia during the period 1998-2009 are obtained.

  17. The effect of correlated observations on the performance of distributed estimation

    KAUST Repository

    Ahmed, Mohammed; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim; Turkiyyah, George M.

    2013-01-01

    Estimating unknown signal in Wireless Sensor Networks (WSNs) requires sensor nodes to transmit their observations of the signal over a multiple access channel to a Fusion Center (FC). The FC uses the received observations, which is corrupted

  18. LOD estimation from DORIS observations

    Science.gov (United States)

    Stepanek, Petr; Filler, Vratislav; Buday, Michal; Hugentobler, Urs

    2016-04-01

    The difference between astronomically determined duration of the day and 86400 seconds is called length of day (LOD). The LOD could be also understood as the daily rate of the difference between the Universal Time UT1, based on the Earth rotation, and the International Atomic Time TAI. The LOD is estimated using various Satellite Geodesy techniques as GNSS and SLR, while absolute UT1-TAI difference is precisely determined by VLBI. Contrary to other IERS techniques, the LOD estimation using DORIS (Doppler Orbitography and Radiopositioning Integrated by satellite) measurement did not achieve a geodetic accuracy in the past, reaching the precision at the level of several ms per day. However, recent experiments performed by IDS (International DORIS Service) analysis centre at Geodetic Observatory Pecny show a possibility to reach accuracy around 0.1 ms per day, when not adjusting the cross-track harmonics in the Satellite orbit model. The paper presents the long term LOD series determined from the DORIS solutions. The series are compared with C04 as the reference. Results are discussed in the context of accuracy achieved with GNSS and SLR. Besides the multi-satellite DORIS solutions, also the LOD series from the individual DORIS satellite solutions are analysed.

  19. A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

    Science.gov (United States)

    Qin, Fangjun; Jiang, Sai; Zha, Feng

    2018-01-01

    In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms. PMID:29751538

  20. A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

    Directory of Open Access Journals (Sweden)

    Fangjun Qin

    2018-05-01

    Full Text Available In this paper, a sequential multiplicative extended Kalman filter (SMEKF is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms.

  1. Estimation of Stator winding faults in induction motors using an adaptive observer scheme

    DEFF Research Database (Denmark)

    Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik

    2004-01-01

    This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....

  2. Estimation of Stator Winding Faults in Induction Motors using an Adaptive Observer Scheme

    DEFF Research Database (Denmark)

    Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik

    2004-01-01

    This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....

  3. The effect of correlated observations on the performance of distributed estimation

    KAUST Repository

    Ahmed, Mohammed

    2013-12-01

    Estimating unknown signal in Wireless Sensor Networks (WSNs) requires sensor nodes to transmit their observations of the signal over a multiple access channel to a Fusion Center (FC). The FC uses the received observations, which is corrupted by observation noise and both channel fading and noise, to find the minimum Mean Square Error (MSE) estimate of the signal. In this paper, we investigate the effect of the source-node correlation (the correlation between sensor node observations and the source signal) and the inter-node correlation (the correlation between sensor node observations) on the performance of the Linear Minimum Mean Square Error (LMMSE) estimator for three correlation models in the presence of channel fading. First, we investigate the asymptotic behavior of the achieved distortion (i.e., MSE) resulting from both the observation and channel noise in a non-fading channel. Then, the effect of channel fading is considered and the corresponding distortion outage probability, the probability that the distortion exceeds a certain value, is found. By representing the distortion as a ratio of indefinite quadratic forms, a closed-form expression is derived for the outage probability that shows its dependency on the correlation. Finally, the new representation of the outage probability allows us to propose an iterative solution for the power allocation problem to minimize the outage probability under total and individual power constraints. Numerical simulations are provided to verify our analytic results. © 2013 IEEE.

  4. An Inverse Source Problem for a One-dimensional Wave Equation: An Observer-Based Approach

    KAUST Repository

    Asiri, Sharefa M.

    2013-05-25

    Observers are well known in the theory of dynamical systems. They are used to estimate the states of a system from some measurements. However, recently observers have also been developed to estimate some unknowns for systems governed by Partial differential equations. Our aim is to design an observer to solve inverse source problem for a one dimensional wave equation. Firstly, the problem is discretized in both space and time and then an adaptive observer based on partial field measurements (i.e measurements taken form the solution of the wave equation) is applied to estimate both the states and the source. We see the effectiveness of this observer in both noise-free and noisy cases. In each case, numerical simulations are provided to illustrate the effectiveness of this approach. Finally, we compare the performance of the observer approach with Tikhonov regularization approach.

  5. Visibility of St Lawrence belugas to aerial photography, estimated by direct observation

    Directory of Open Access Journals (Sweden)

    Michael CS Kingsley

    2002-07-01

    Full Text Available The depleted population of belugas (Delphinapterus leucas inhabiting the St Lawrence estuary, Canada, was monitored by periodic photographic aerial surveys. In order to correct counts made on aerial survey film and to obtain an estimate of the true size of the population, the diving behaviour and the visibility from the air of these animals was studied. A Secchi-disk turbidity survey in the belugas’ summer range showed that water clarity varied between 1.5 m and 11.6 m. By studying aerial photographs of sheet-plastic models of belugas that had been sunk to different depths below the surface, we found that models of white adults could be seen down to about the same depth as a Secchi disk, but no deeper. Smaller models of dark-grey juveniles could only be seen down to about 50% of Secchi-disk depth. By observing groups of belugas from a hovering helicopter and recording their disappearances and re-appearances, it was found that they were visible for 44.3% of the time, and that an appropriate correction for single photographs would be to multiply the photographic count by about 222% (SE 20%. For surveys in which there was overlap between adjacent frames, the estimated correction would be 209% (SE 16%. This correction factor was slightly conservative and gave an estimate of the true size of the population, based on a single survey, of 1,202 belugas (SE 189 in 1997. An estimate for 1997 based on smoothing 5 surveys 1988–1997 was 1,238 (SE 119.

  6. Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

    Science.gov (United States)

    Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley

    2017-01-01

    Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...

  7. Estimating the average treatment effect on survival based on observational data and using partly conditional modeling.

    Science.gov (United States)

    Gong, Qi; Schaubel, Douglas E

    2017-03-01

    Treatments are frequently evaluated in terms of their effect on patient survival. In settings where randomization of treatment is not feasible, observational data are employed, necessitating correction for covariate imbalances. Treatments are usually compared using a hazard ratio. Most existing methods which quantify the treatment effect through the survival function are applicable to treatments assigned at time 0. In the data structure of our interest, subjects typically begin follow-up untreated; time-until-treatment, and the pretreatment death hazard are both heavily influenced by longitudinal covariates; and subjects may experience periods of treatment ineligibility. We propose semiparametric methods for estimating the average difference in restricted mean survival time attributable to a time-dependent treatment, the average effect of treatment among the treated, under current treatment assignment patterns. The pre- and posttreatment models are partly conditional, in that they use the covariate history up to the time of treatment. The pre-treatment model is estimated through recently developed landmark analysis methods. For each treated patient, fitted pre- and posttreatment survival curves are projected out, then averaged in a manner which accounts for the censoring of treatment times. Asymptotic properties are derived and evaluated through simulation. The proposed methods are applied to liver transplant data in order to estimate the effect of liver transplantation on survival among transplant recipients under current practice patterns. © 2016, The International Biometric Society.

  8. Infinite-Dimensional Boundary Observer for Lithium-Ion Battery State Estimation

    DEFF Research Database (Denmark)

    Hasan, Agus; Jouffroy, Jerome

    2017-01-01

    This paper presents boundary observer design for state-of-charge (SOC) estimation of lithium-ion batteries. The lithium-ion battery dynamics are governed by thermal-electrochemical principles, which mathematically modeled by partial differential equations (PDEs). In general, the model is a reaction......-diffusion equation with time-dependent coefficients. A Luenberger observer is developed using infinite-dimensional backstepping method and uses only a single measurement at the boundary of the battery. The observer gains are computed by solving the observer kernel equation. A numerical example is performed to show...

  9. On the use of a regression model for trend estimates from ground-based atmospheric observations in the Southern hemisphere

    CSIR Research Space (South Africa)

    Bencherif, H

    2010-09-01

    Full Text Available The present reports on the use of a multi-regression model adapted at Reunion University for temperature and ozone trend estimates. Depending on the location of the observing site, the studied geophysical signal is broken down in form of a sum...

  10. Estimation of Regional Carbon Balance from Atmospheric Observations

    Science.gov (United States)

    Denning, S.; Uliasz, M.; Skidmore, J.

    2002-12-01

    Variations in the concentration of CO2 and other trace gases in time and space contain information about sources and sinks at regional scales. Several methods have been developed to quantitatively extract this information from atmospheric measurements. Mass-balance techniques depend on the ability to repeatedly sample the same mass of air, which involves careful attention to airmass trajectories. Inverse and adjoint techniques rely on decomposition of the source field into quasi-independent "basis functions" that are propagated through transport models and then used to synthesize optimal linear combinations that best match observations. A recently proposed method for regional flux estimation from continuous measurements at tall towers relies on time-mean vertical gradients, and requires careful trajectory analysis to map the estimates onto regional ecosystems. Each of these techniques is likely to be applied to measurements made during the North American Carbon Program. We have also explored the use of Bayesian synthesis inversion at regional scales, using a Lagrangian particle dispersion model driven by mesoscale transport fields. Influence functions were calculated for each hypothetical observation in a realistic diurnally-varying flow. These influence functions were then treated as basis functions for the purpose of separate inversions for daytime photosynthesis and 24-hour mean ecosystem respiration. Our results highlight the importance of estimating CO2 fluxes through the lateral boundaries of the model. Respiration fluxes were well constrained by one or two hypothetical towers, regardless of inflow fluxes. Time-varying assimilation fluxes were less well constrained, and much more dependent on knowledge of inflow fluxes. The small net difference between respiration and photosynthesis was the most difficult to determine, being extremely sensitive to knowledge of inflow fluxes. Finally, we explored the feasibility of directly incorporating mid-day concentration

  11. Disturbance observer based current controller for vector controlled IM drives

    DEFF Research Database (Denmark)

    Teodorescu, Remus; Dal, Mehmet

    2008-01-01

    induction motor (IM) drives. The control design, based on synchronously rotating d-q frame model of the machine, has a simple structure that combines the proportional portion of a conventional PI control and output of the observer. The observer is predicted to estimate the disturbances caused by parameters...... coupling effects and increase robustness against parameters change without requiring any other compensation strategies. The experimental implementation results are provided to demonstrate validity and performance of the proposed control scheme.......In order to increase the accuracy of the current control loop, usually, well known parameter compensation and/or cross decoupling techniques are employed for advanced ac drives. In this paper, instead of using these techniques an observer-based current controller is proposed for vector controlled...

  12. Nonlinear observer to estimate polarization phenomenon in membrane distillation

    Directory of Open Access Journals (Sweden)

    Khoukhi Billal

    2015-01-01

    Full Text Available This paper presents a bi-dimensional dynamic model of Direct Contact Membrane Desalination (DCMD process. Most of the MD configuration processes have been modeled as steady-state one-dimensional systems. Stationary two-dimensional MD models have been considered only in very few studies. In this work, a dynamic model of a DCMD process is developed. The model is implemented using Matlab/Simulink environment. Numerical simulations are conducted for different operational parameters at the module inlets such as the feed and permeate temperature or feed and permeate flow rate. The results are compared with experimental data published in the literature. The work presents also a feed forward control that compensates the possible decrease of the temperature gradient by increasing the flow rate. This work also deals with a development of nonlinear observer to estimate temperature polarization inside the membrane. The observer gives a good profile and longitudinal temperature estimations and shows a good prediction of pure water flux production.

  13. Register-based estimates of parents' coresidence in Sweden, 1969-2007

    Directory of Open Access Journals (Sweden)

    Elizabeth Thomson

    2013-12-01

    Full Text Available Background: Many of the dramatic changes in family formation and dissolution observed in wealthy countries over the past 60 years are tracked through vital statistics or censuses. The signature change in family behavior -- non-marital cohabitation -- is not, however, registered in most settings. Objective: We evaluate the quality of new register-based estimates of parents' union status at birth and of separation during the childrearing years. Methods: Parents of a common child are identified through the Multi-Generation Register that links each child to each parent and therefore each parent to each other. The Total Population Register identifies the property at which each parent is registered at the end of each year. We use the five-year censuses 1960-1990 as one standard of comparison because the censuses identify the dwelling unit for each parent on the census date. Results: Property-based estimates of parents' coresidence compare very well to census reports. Register-based estimates are virtually identical with those produced from the 1992 Swedish Fertility and Family Survey; differences between register estimates and those produced from the 1991 and 2000 Level of Living Survey can be explained by differences in measurement of marriage and cohabitation. Conclusions: Estimates of parents' cohabitation based on annual, property-level registration are of sufficient quality for their use in substantive analyses of union status at birth and parents' separation in Sweden. Comments: Although register-based estimates of parents' coresidence at a child's birth or afterwards can be generated only for a select group of countries, their use can be fruitful for understanding more general processes of family change. Centralized administrative registers exist in many countries but have not been made fully available for research therefore losing much of the potential value.

  14. Nonlinear Disturbance Observer Based Robust Tracking Control of Pneumatic Muscle

    Directory of Open Access Journals (Sweden)

    Youssif Mohamed Toum Elobaid

    2014-01-01

    Full Text Available Presently pneumatic muscles (PMs are used in various applications due to their simple construction, lightweight, and high force-to-weight ratio. However, pneumatic muscles are facing various problems due to their nonlinear characteristics and various uncertainties in real applications. To cope with the uncertainties and strong nonlinearity of a PM model, a nonlinear disturbance observer (NDO is designed to estimate the lumped disturbance. Based on the disturbance observer, the tracking control of PM is studied. Stability analysis based on Lyapunov method with respect to our proposed control law is discussed. The simulation results show the validity, effectiveness, and enhancing robustness of the proposed methods.

  15. Kalman filter-based EM-optical sensor fusion for needle deflection estimation.

    Science.gov (United States)

    Jiang, Baichuan; Gao, Wenpeng; Kacher, Daniel; Nevo, Erez; Fetics, Barry; Lee, Thomas C; Jayender, Jagadeesan

    2018-04-01

    In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.

  16. An extended set-value observer for position estimation using single range measurements

    DEFF Research Database (Denmark)

    Marcal, Jose; Jouffroy, Jerome; Fossen, Thor I.

    the observability of the system is briefly discussed and an extended set-valued observer is presented, with some discussion about the effect of the measurements noise on the final solution. This observer estimates bounds in the errors assuming that the exogenous signals are bounded, providing a safe region......The ability of estimating the position of an underwater vehicle from single range measurements is important in applications where one transducer marks an important geographical point, when there is a limitation in the size or cost of the vehicle, or when there is a failure in a system...... of transponders. The knowledge of the bearing of the vehicle and the range measurements from a single location can provide a solution which is sensitive to the trajectory that the vehicle is following, since there is no complete constraint on the position estimate with a single beacon. In this paper...

  17. Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

    Science.gov (United States)

    Peng, L.; Sheffield, J.; Li, D.

    2015-12-01

    Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

  18. Nonparametric estimation for censored mixture data with application to the Cooperative Huntington's Observational Research Trial.

    Science.gov (United States)

    Wang, Yuanjia; Garcia, Tanya P; Ma, Yanyuan

    2012-01-01

    This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions. Although both NPMLEs are commonly used, we show that one is inefficient and the other inconsistent. To overcome these deficiencies, we propose three classes of consistent nonparametric estimators which do not assume parametric density models and are easy to implement. They are based on the inverse probability weighting (IPW), augmented IPW (AIPW), and nonparametric imputation (IMP). The AIPW achieves the efficiency bound without additional modeling assumptions. Extensive simulation experiments demonstrate satisfactory performance of these estimators even when the data are heavily censored. We apply these estimators to the Cooperative Huntington's Observational Research Trial (COHORT), and provide age-specific estimates of the effect of mutation in the Huntington gene on mortality using a sample of family members. The close approximation of the estimated non-carrier survival rates to that of the U.S. population indicates small ascertainment bias in the COHORT family sample. Our analyses underscore an elevated risk of death in Huntington gene mutation carriers compared to non-carriers for a wide age range, and suggest that the mutation equally affects survival rates in both genders. The estimated survival rates are useful in genetic counseling for providing guidelines on interpreting the risk of death associated with a positive genetic testing, and in facilitating future subjects at risk

  19. Uniform stable observer for the disturbance estimation in two renewable energy systems.

    Science.gov (United States)

    Rubio, José de Jesús; Ochoa, Genaro; Balcazar, Ricardo; Pacheco, Jaime

    2015-09-01

    In this study, an observer for the states and disturbance estimation in two renewable energy systems is introduced. The restrictions of the gains in the proposed observer are found to guarantee its stability and the convergence of its error; furthermore, these results are utilized to obtain a good estimation. The introduced technique is applied for the states and disturbance estimation in a wind turbine and an electric vehicle. The wind turbine has a rotatory tower to catch the incoming air to be transformed in electricity and the electric vehicle has generators connected with its wheels to catch the vehicle movement to be transformed in electricity. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model

    Science.gov (United States)

    Hilker, Thomas; Galvão, Lênio Soares; Aragão, Luiz E. O. C.; de Moura, Yhasmin M.; do Amaral, Cibele H.; Lyapustin, Alexei I.; Wu, Jin; Albert, Loren P.; Ferreira, Marciel José; Anderson, Liana O.; dos Santos, Victor A. H. F.; Prohaska, Neill; Tribuzy, Edgard; Barbosa Ceron, João Vitor; Saleska, Scott R.; Wang, Yujie; de Carvalho Gonçalves, José Francisco; de Oliveira Junior, Raimundo Cosme; Cardoso Rodrigues, João Victor Figueiredo; Garcia, Maquelle Neves

    2017-06-01

    As a preparatory study for future hyperspectral missions that can measure canopy chemistry, we introduce a novel approach to investigate whether multi-angle Moderate Resolution Imaging Spectroradiometer (MODIS) data can be used to generate a preliminary database with long-term estimates of chlorophyll. MODIS monthly chlorophyll estimates between 2000 and 2015, derived from a fully coupled canopy reflectance model (ProSAIL), were inspected for consistency with eddy covariance fluxes, tower-based hyperspectral images and chlorophyll measurements. MODIS chlorophyll estimates from the inverse model showed strong seasonal variations across two flux-tower sites in central and eastern Amazon. Marked increases in chlorophyll concentrations were observed during the early dry season. Remotely sensed chlorophyll concentrations were correlated to field measurements (r2 = 0.73 and r2 = 0.98) but the data deviated from the 1:1 line with root mean square errors (RMSE) ranging from 0.355 μg cm-2 (Tapajós tower) to 0.470 μg cm-2 (Manaus tower). The chlorophyll estimates were consistent with flux tower measurements of photosynthetically active radiation (PAR) and net ecosystem productivity (NEP). We also applied ProSAIL to mono-angle hyperspectral observations from a camera installed on a tower to scale modeled chlorophyll pigments to MODIS observations (r2 = 0.73). Chlorophyll pigment concentrations (ChlA+B) were correlated to changes in the amount of young and mature leaf area per month (0.59 ≤ r2 ≤ 0.64). Increases in MODIS observed ChlA+B were preceded by increased PAR during the dry season (0.61 ≤ r2 ≤ 0.62) and followed by changes in net carbon uptake. We conclude that, at these two sites, changes in LAI, coupled with changes in leaf chlorophyll, are comparable with seasonality of plant productivity. Our results allowed the preliminary development of a 15-year time series of chlorophyll estimates over the Amazon to support canopy chemistry studies using future

  1. BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems.

    Science.gov (United States)

    Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M

    2017-11-25

    Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression

  2. Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

    Science.gov (United States)

    Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

    2012-01-01

    Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

  3. Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

    Science.gov (United States)

    Campbell, D A; Chkrebtii, O

    2013-12-01

    Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  4. Estimation of failure probability on real structure utilized by earthquake observation data

    International Nuclear Information System (INIS)

    Matsubara, Masayoshi

    1995-01-01

    The objective of this report is to propose the procedure which estimates the structural response on a real structure by utilizing earthquake observation data using Neural network system. We apply the neural network system to estimate the ground motion of the site by enormous earthquake data published from Japan Meteorological Agency. The proposed procedure has some possibility to estimate the correlation between earthquake and response adequately. (author)

  5. Earth observations for estimating greenhouse gas emissions from deforestation in developing countries

    International Nuclear Information System (INIS)

    DeFries, Ruth; Achard, Frederic; Brown, Sandra; Herold, Martin; Murdiyarso, Daniel; Schlamadinger, Bernhard; Souza, Carlos de

    2007-01-01

    In response to the United Nations Framework Convention on Climate Change (UNFCCC) process investigating the technical issues surrounding the ability to reduce greenhouse gas (GHG) emissions from deforestation in developing countries, this paper reviews technical capabilities for monitoring deforestation and estimating emissions. Implementation of policies to reduce emissions from deforestation require effective deforestation monitoring systems that are reproducible, provide consistent results, meet standards for mapping accuracy, and can be implemented at the national level. Remotely sensed data supported by ground observations are key to effective monitoring. Capacity in developing countries for deforestation monitoring is well-advanced in a few countries and is a feasible goal in most others. Data sources exist to determine base periods in the 1990s as historical reference points. Forest degradation (e.g. from high impact logging and fragmentation) also contribute to greenhouse gas emissions but it is more technically challenging to measure than deforestation. Data on carbon stocks, which are needed to estimate emissions, cannot currently be observed directly over large areas with remote sensing. Guidelines for carbon accounting from deforestation exist and are available in approved Intergovernmental Panel on Climate Change (IPCC) reports and can be applied at national scales in the absence of forest inventory or other data. Key constraints for implementing programs to monitor greenhouse gas emissions from deforestation are international commitment of resources to increase capacity, coordination of observations to ensure pan-tropical coverage, access to free or low-cost data, and standard and consensual protocols for data interpretation and analysis

  6. Generalized synchronization-based multiparameter estimation in modulated time-delayed systems

    Science.gov (United States)

    Ghosh, Dibakar; Bhattacharyya, Bidyut K.

    2011-09-01

    We propose a nonlinear active observer based generalized synchronization scheme for multiparameter estimation in time-delayed systems with periodic time delay. A sufficient condition for parameter estimation is derived using Krasovskii-Lyapunov theory. The suggested tool proves to be globally and asymptotically stable by means of Krasovskii-Lyapunov method. With this effective method, parameter identification and generalized synchronization of modulated time-delayed systems with all the system parameters unknown, can be achieved simultaneously. We restrict our study for multiple parameter estimation in modulated time-delayed systems with single state variable only. Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed technique. The block diagram of electronic circuit for multiple time delay system shows that the method is easily applicable in practical communication problems.

  7. Power system observability and dynamic state estimation for stability monitoring using synchrophasor measurements

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Kai; Qi, Junjian; Kang, Wei

    2016-08-01

    Growing penetration of intermittent resources such as renewable generations increases the risk of instability in a power grid. This paper introduces the concept of observability and its computational algorithms for a power grid monitored by the wide-area measurement system (WAMS) based on synchrophasors, e.g. phasor measurement units (PMUs). The goal is to estimate real-time states of generators, especially for potentially unstable trajectories, the information that is critical for the detection of rotor angle instability of the grid. The paper studies the number and siting of synchrophasors in a power grid so that the state of the system can be accurately estimated in the presence of instability. An unscented Kalman filter (UKF) is adopted as a tool to estimate the dynamic states that are not directly measured by synchrophasors. The theory and its computational algorithms are illustrated in detail by using a 9-bus 3-generator power system model and then tested on a 140-bus 48-generator Northeast Power Coordinating Council power grid model. Case studies on those two systems demonstrate the performance of the proposed approach using a limited number of synchrophasors for dynamic state estimation for stability assessment and its robustness against moderate inaccuracies in model parameters.

  8. Observing expertise-related actions leads to perfect time flow estimations.

    Directory of Open Access Journals (Sweden)

    Yin-Hua Chen

    Full Text Available The estimation of the time of exposure of a picture portraying an action increases as a function of the amount of movement implied in the action represented. This effect suggests that the perceiver creates an internal embodiment of the action observed as if internally simulating the entire movement sequence. Little is known however about the timing accuracy of these internal action simulations, specifically whether they are affected by the level of familiarity and experience that the observer has of the action. In this study we asked professional pianists to reproduce different durations of exposure (shorter or longer than one second of visual displays both specific (a hand in piano-playing action and non-specific to their domain of expertise (a hand in finger-thumb opposition and scrambled-pixels and compared their performance with non-pianists. Pianists outperformed non-pianists independently of the time of exposure of the stimuli; remarkably the group difference was particularly magnified by the pianists' enhanced accuracy and stability only when observing the hand in the act of playing the piano. These results for the first time provide evidence that through musical training, pianists create a selective and self-determined dynamic internal representation of an observed movement that allows them to estimate precisely its temporal duration.

  9. Sensorless control for permanent magnet synchronous motor using a neural network based adaptive estimator

    Science.gov (United States)

    Kwon, Chung-Jin; Kim, Sung-Joong; Han, Woo-Young; Min, Won-Kyoung

    2005-12-01

    The rotor position and speed estimation of permanent-magnet synchronous motor(PMSM) was dealt with. By measuring the phase voltages and currents of the PMSM drive, two diagonally recurrent neural network(DRNN) based observers, a neural current observer and a neural velocity observer were developed. DRNN which has self-feedback of the hidden neurons ensures that the outputs of DRNN contain the whole past information of the system even if the inputs of DRNN are only the present states and inputs of the system. Thus the structure of DRNN may be simpler than that of feedforward and fully recurrent neural networks. If the backpropagation method was used for the training of the DRNN the problem of slow convergence arise. In order to reduce this problem, recursive prediction error(RPE) based learning method for the DRNN was presented. The simulation results show that the proposed approach gives a good estimation of rotor speed and position, and RPE based training has requires a shorter computation time compared to backpropagation based training.

  10. Modulating Function-Based Method for Parameter and Source Estimation of Partial Differential Equations

    KAUST Repository

    Asiri, Sharefa M.

    2017-10-08

    Partial Differential Equations (PDEs) are commonly used to model complex systems that arise for example in biology, engineering, chemistry, and elsewhere. The parameters (or coefficients) and the source of PDE models are often unknown and are estimated from available measurements. Despite its importance, solving the estimation problem is mathematically and numerically challenging and especially when the measurements are corrupted by noise, which is often the case. Various methods have been proposed to solve estimation problems in PDEs which can be classified into optimization methods and recursive methods. The optimization methods are usually heavy computationally, especially when the number of unknowns is large. In addition, they are sensitive to the initial guess and stop condition, and they suffer from the lack of robustness to noise. Recursive methods, such as observer-based approaches, are limited by their dependence on some structural properties such as observability and identifiability which might be lost when approximating the PDE numerically. Moreover, most of these methods provide asymptotic estimates which might not be useful for control applications for example. An alternative non-asymptotic approach with less computational burden has been proposed in engineering fields based on the so-called modulating functions. In this dissertation, we propose to mathematically and numerically analyze the modulating functions based approaches. We also propose to extend these approaches to different situations. The contributions of this thesis are as follows. (i) Provide a mathematical analysis of the modulating function-based method (MFBM) which includes: its well-posedness, statistical properties, and estimation errors. (ii) Provide a numerical analysis of the MFBM through some estimation problems, and study the sensitivity of the method to the modulating functions\\' parameters. (iii) Propose an effective algorithm for selecting the method\\'s design parameters

  11. OMI Satellite and Ground-Based Pandora Observations and Their Application to Surface NO2 Estimations at Terrestrial and Marine Sites

    Science.gov (United States)

    Kollonige, Debra E.; Thompson, Anne M.; Josipovic, Miroslav; Tzortziou, Maria; Beukes, Johan P.; Burger, Roelof; Martins, Douglas K.; van Zyl, Pieter G.; Vakkari, Ville; Laakso, Lauri

    2018-01-01

    The Pandora spectrometer that uses direct-Sun measurements to derive total column amounts of gases provides an approach for (1) validation of satellite instruments and (2) monitoring of total column (TC) ozone (O3) and nitrogen dioxide (NO2). We use for the first time Pandora and Ozone Monitoring Instrument (OMI) observations to estimate surface NO2 over marine and terrestrial sites downwind of urban pollution and compared with in situ measurements during campaigns in contrasting regions: (1) the South African Highveld (at Welgegund, 26°34'10″S, 26°56'21″E, 1,480 m asl, 120 km southwest of the Johannesburg-Pretoria megacity) and (2) shipboard U.S. mid-Atlantic coast during the 2014 Deposition of Atmospheric Nitrogen to Coastal Ecosystems (DANCE) cruise. In both cases, there were no local NOx sources but intermittent regional pollution influences. For TC NO2, OMI and Pandora difference is 20%, with Pandora higher most times. Surface NO2 values estimated from OMI and Pandora columns are compared to in situ NO2 for both locations. For Welgegund, the planetary boundary layer (PBL) height, used in converting column to surface NO2 value, has been estimated by three methods: co-located Atmospheric Infrared Sounder (AIRS) observations; a model simulation; and radiosonde data from Irene, 150 km northeast of the site. AIRS PBL heights agree within 10% of radiosonde-derived values. Absolute differences between Pandora- and OMI-estimated surface NO2 and the in situ data are better at the terrestrial site ( 0.5 ppbv and 1 ppbv or greater, respectively) than under clean marine air conditions, with differences usually >3 ppbv. Cloud cover and PBL variability influence these estimations.

  12. A Vehicle Haptic Steering by Wire System Based on High Gain GPI Observers

    Directory of Open Access Journals (Sweden)

    A. Rodriguez-Angeles

    2014-01-01

    Full Text Available A vehicle steering by wire (SBW haptic system based on high gain generalized proportional integral (GPI observers is introduced. The observers are considered for the estimation of dynamic perturbations that are present at the tire and steering wheel. To ensure efficient tracking between the commanded steering wheel angle and the tire orientation angle, the estimated perturbations are on line canceled. As to provide a haptic interface with the driver, the estimated dynamic effects at the steering rack are fed back to the steering wheel, yielding a master-slave haptic system with bilateral communication. For implementation purposes few sensors and minimum knowledge of the dynamic model are required, which is a major advantage compared to other approaches. Only position tracking errors are fed back, while all other signals are estimated by the high gain GPI observers. The scheme is robust to uncertainty on the input gain and cancels dynamic perturbation effects such as friction and aligning forces on the tire. Experimental results are presented on a prototype platform.

  13. Supporting Analogy-based Effort Estimation with the Use of Ontologies

    Directory of Open Access Journals (Sweden)

    Joanna Kowalska

    2014-06-01

    Full Text Available The paper concerns effort estimation of software development projects, in particular, at the level of product delivery stages. It proposes a new approach to model project data to support expert-supervised analogy-based effort estimation. The data is modeled using Semantic Web technologies, such as Resource Description Framework (RDF and Ontology Language for the Web (OWL. Moreover, in the paper, we define a method of supervised case-based reasoning. The method enables to search for similar projects’ tasks at different levels of abstraction. For instance, instead of searching for a task performed by a specific person, one could look for tasks performed by people with similar capabilities. The proposed method relies on ontology that defines the core concepts and relationships. However, it is possible to introduce new classes and relationships, without the need of altering the search mechanisms. Finally, we implemented a prototype tool that was used to preliminary validate the proposed approach. We observed that the proposed approach could potentially help experts in estimating non-trivial tasks that are often underestimated.

  14. Effect of recent observations on Asian CO2 flux estimates by transport model inversions

    International Nuclear Information System (INIS)

    Maksyutov, Shamil; Patra, Prabir K.; Machida, Toshinobu; Mukai, Hitoshi; Nakazawa, Takakiyo; Inoue, Gen

    2003-01-01

    We use an inverse model to evaluate the effects of the recent CO 2 observations over Asia on estimates of regional CO 2 sources and sinks. Global CO 2 flux distribution is evaluated using several atmospheric transport models, atmospheric CO 2 observations and a 'time-independent' inversion procedure adopted in the basic synthesis inversion by the Transcom-3 inverse model intercomparison project. In our analysis we include airborne and tower observations in Siberia, continuous monitoring and airborne observations over Japan, and airborne monitoring on regular flights on Tokyo-Sydney route. The inclusion of the new data reduces the uncertainty of the estimated regional CO 2 fluxes for Boreal Asia (Siberia), Temperate Asia and South-East Asia. The largest effect is observed for the emission/sink estimate for the Boreal Asia region, where introducing the observations in Siberia reduces the source uncertainty by almost half. It also produces an uncertainty reduction for Boreal North America. Addition of the Siberian airborne observations leads to projecting extra sinks in Boreal Asia of 0.2 Pg C/yr, and a smaller change for Europe. The Tokyo-Sydney observations reduce and constrain the Southeast Asian source

  15. Formulating informative, data-based priors for failure probability estimation in reliability analysis

    International Nuclear Information System (INIS)

    Guikema, Seth D.

    2007-01-01

    Priors play an important role in the use of Bayesian methods in risk analysis, and using all available information to formulate an informative prior can lead to more accurate posterior inferences. This paper examines the practical implications of using five different methods for formulating an informative prior for a failure probability based on past data. These methods are the method of moments, maximum likelihood (ML) estimation, maximum entropy estimation, starting from a non-informative 'pre-prior', and fitting a prior based on confidence/credible interval matching. The priors resulting from the use of these different methods are compared qualitatively, and the posteriors are compared quantitatively based on a number of different scenarios of observed data used to update the priors. The results show that the amount of information assumed in the prior makes a critical difference in the accuracy of the posterior inferences. For situations in which the data used to formulate the informative prior is an accurate reflection of the data that is later observed, the ML approach yields the minimum variance posterior. However, the maximum entropy approach is more robust to differences between the data used to formulate the prior and the observed data because it maximizes the uncertainty in the prior subject to the constraints imposed by the past data

  16. Chaos suppression based on adaptive observer for a P-class of chaotic systems

    International Nuclear Information System (INIS)

    Rodriguez, Angel; Leon, Jesus de; Femat, Ricardo

    2007-01-01

    A feedback approach is presented to suppress chaos in a P-class of chaotic system. The approach is based on an adaptive observer; which provides estimated values of both the unmeasured states and the uncertain model parameters. A continuous-time feedback law is taken as suppressing force. The feedback law attains chaos suppression as the observer provides estimated values close to the actual state/parameter values along time. The proposed scheme is robust in the sense that suppression is achieved despite only some states are measured and uncertainties in parameters are compensated. Results are corroborated experimentally by implementation in chaotic circuits

  17. Chaos suppression based on adaptive observer for a P-class of chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, Angel [Universidad Autonoma de Nuevo Leon, Facultad de Ingenieria Mecanica y Electrica, Av. Pedro de Alba s/n Cd. Universitaria, CP 66450 San Nicolas de los Garza, NL (Mexico); Leon, Jesus de [Universidad Autonoma de Nuevo Leon, Facultad de Ingenieria Mecanica y Electrica, Av. Pedro de Alba s/n Cd. Universitaria, CP 66450 San Nicolas de los Garza, NL (Mexico); Femat, Ricardo [Division de Matematicas Aplicadas y Sistemas Computacionales, IPICyT, Camino a la Presa San Jose 2055 Col. Lomas 4a. Secc. CP 78216 San Luis Potosi, SLP (Mexico)]. E-mail: rfemat@ipicyt.edu.mx

    2007-05-15

    A feedback approach is presented to suppress chaos in a P-class of chaotic system. The approach is based on an adaptive observer; which provides estimated values of both the unmeasured states and the uncertain model parameters. A continuous-time feedback law is taken as suppressing force. The feedback law attains chaos suppression as the observer provides estimated values close to the actual state/parameter values along time. The proposed scheme is robust in the sense that suppression is achieved despite only some states are measured and uncertainties in parameters are compensated. Results are corroborated experimentally by implementation in chaotic circuits.

  18. Nonparametric estimation for censored mixture data with application to the Cooperative Huntington’s Observational Research Trial

    Science.gov (United States)

    Wang, Yuanjia; Garcia, Tanya P.; Ma, Yanyuan

    2012-01-01

    This work presents methods for estimating genotype-specific distributions from genetic epidemiology studies where the event times are subject to right censoring, the genotypes are not directly observed, and the data arise from a mixture of scientifically meaningful subpopulations. Examples of such studies include kin-cohort studies and quantitative trait locus (QTL) studies. Current methods for analyzing censored mixture data include two types of nonparametric maximum likelihood estimators (NPMLEs) which do not make parametric assumptions on the genotype-specific density functions. Although both NPMLEs are commonly used, we show that one is inefficient and the other inconsistent. To overcome these deficiencies, we propose three classes of consistent nonparametric estimators which do not assume parametric density models and are easy to implement. They are based on the inverse probability weighting (IPW), augmented IPW (AIPW), and nonparametric imputation (IMP). The AIPW achieves the efficiency bound without additional modeling assumptions. Extensive simulation experiments demonstrate satisfactory performance of these estimators even when the data are heavily censored. We apply these estimators to the Cooperative Huntington’s Observational Research Trial (COHORT), and provide age-specific estimates of the effect of mutation in the Huntington gene on mortality using a sample of family members. The close approximation of the estimated non-carrier survival rates to that of the U.S. population indicates small ascertainment bias in the COHORT family sample. Our analyses underscore an elevated risk of death in Huntington gene mutation carriers compared to non-carriers for a wide age range, and suggest that the mutation equally affects survival rates in both genders. The estimated survival rates are useful in genetic counseling for providing guidelines on interpreting the risk of death associated with a positive genetic testing, and in facilitating future subjects at risk

  19. Sliding mode control-based linear functional observers for discrete-time stochastic systems

    Science.gov (United States)

    Singh, Satnesh; Janardhanan, Sivaramakrishnan

    2017-11-01

    Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.

  20. Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

    Science.gov (United States)

    Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

    2017-12-01

    This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

  1. Adaptive nonparametric estimation for L\\'evy processes observed at low frequency

    OpenAIRE

    Kappus, Johanna

    2013-01-01

    This article deals with adaptive nonparametric estimation for L\\'evy processes observed at low frequency. For general linear functionals of the L\\'evy measure, we construct kernel estimators, provide upper risk bounds and derive rates of convergence under regularity assumptions. Our focus lies on the adaptive choice of the bandwidth, using model selection techniques. We face here a non-standard problem of model selection with unknown variance. A new approach towards this problem is proposed, ...

  2. Dictionary-based fiber orientation estimation with improved spatial consistency.

    Science.gov (United States)

    Ye, Chuyang; Prince, Jerry L

    2018-02-01

    Diffusion magnetic resonance imaging (dMRI) has enabled in vivo investigation of white matter tracts. Fiber orientation (FO) estimation is a key step in tract reconstruction and has been a popular research topic in dMRI analysis. In particular, the sparsity assumption has been used in conjunction with a dictionary-based framework to achieve reliable FO estimation with a reduced number of gradient directions. Because image noise can have a deleterious effect on the accuracy of FO estimation, previous works have incorporated spatial consistency of FOs in the dictionary-based framework to improve the estimation. However, because FOs are only indirectly determined from the mixture fractions of dictionary atoms and not modeled as variables in the objective function, these methods do not incorporate FO smoothness directly, and their ability to produce smooth FOs could be limited. In this work, we propose an improvement to Fiber Orientation Reconstruction using Neighborhood Information (FORNI), which we call FORNI+; this method estimates FOs in a dictionary-based framework where FO smoothness is better enforced than in FORNI alone. We describe an objective function that explicitly models the actual FOs and the mixture fractions of dictionary atoms. Specifically, it consists of data fidelity between the observed signals and the signals represented by the dictionary, pairwise FO dissimilarity that encourages FO smoothness, and weighted ℓ 1 -norm terms that ensure the consistency between the actual FOs and the FO configuration suggested by the dictionary representation. The FOs and mixture fractions are then jointly estimated by minimizing the objective function using an iterative alternating optimization strategy. FORNI+ was evaluated on a simulation phantom, a physical phantom, and real brain dMRI data. In particular, in the real brain dMRI experiment, we have qualitatively and quantitatively evaluated the reproducibility of the proposed method. Results demonstrate that

  3. Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

    Science.gov (United States)

    Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

    2011-01-01

    Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

  4. Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net.

    Science.gov (United States)

    Choi, Jin; Jo, Jung Hyun; Yim, Hong-Suh; Choi, Eun-Jung; Cho, Sungki; Park, Jang-Hyun

    2018-06-07

    An Optical Wide-field patroL-Network (OWL-Net) has been developed for maintaining Korean low Earth orbit (LEO) satellites' orbital ephemeris. The OWL-Net consists of five optical tracking stations. Brightness signals of reflected sunlight of the targets were detected by a charged coupled device (CCD). A chopper system was adopted for fast astrometric data sampling, maximum 50 Hz, within a short observation time. The astrometric accuracy of the optical observation data was validated with precise orbital ephemeris such as Consolidated Prediction File (CPF) data and precise orbit determination result with onboard Global Positioning System (GPS) data from the target satellite. In the optical observation simulation of the OWL-Net for 2017, an average observation span for a single arc of 11 LEO observation targets was about 5 min, while an average optical observation separation time was 5 h. We estimated the position and velocity with an atmospheric drag coefficient of LEO observation targets using a sequential-batch orbit estimation technique after multi-arc batch orbit estimation. Post-fit residuals for the multi-arc batch orbit estimation and sequential-batch orbit estimation were analyzed for the optical measurements and reference orbit (CPF and GPS data). The post-fit residuals with reference show few tens-of-meters errors for in-track direction for multi-arc batch and sequential-batch orbit estimation results.

  5. Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net

    Directory of Open Access Journals (Sweden)

    Jin Choi

    2018-06-01

    Full Text Available An Optical Wide-field patroL-Network (OWL-Net has been developed for maintaining Korean low Earth orbit (LEO satellites’ orbital ephemeris. The OWL-Net consists of five optical tracking stations. Brightness signals of reflected sunlight of the targets were detected by a charged coupled device (CCD. A chopper system was adopted for fast astrometric data sampling, maximum 50 Hz, within a short observation time. The astrometric accuracy of the optical observation data was validated with precise orbital ephemeris such as Consolidated Prediction File (CPF data and precise orbit determination result with onboard Global Positioning System (GPS data from the target satellite. In the optical observation simulation of the OWL-Net for 2017, an average observation span for a single arc of 11 LEO observation targets was about 5 min, while an average optical observation separation time was 5 h. We estimated the position and velocity with an atmospheric drag coefficient of LEO observation targets using a sequential-batch orbit estimation technique after multi-arc batch orbit estimation. Post-fit residuals for the multi-arc batch orbit estimation and sequential-batch orbit estimation were analyzed for the optical measurements and reference orbit (CPF and GPS data. The post-fit residuals with reference show few tens-of-meters errors for in-track direction for multi-arc batch and sequential-batch orbit estimation results.

  6. CYGNSS Surface Wind Observations and Surface Flux Estimates within Low-Latitude Extratropical Cyclones

    Science.gov (United States)

    Crespo, J.; Posselt, D. J.

    2017-12-01

    The Cyclone Global Navigation Satellite System (CYGNSS), launched in December 2016, aims to improve estimates of surface wind speeds over the tropical oceans. While CYGNSS's core mission is to provide better estimates of surface winds within the core of tropical cyclones, previous research has shown that the constellation, with its orbital inclination of 35°, also has the ability to observe numerous extratropical cyclones that form in the lower latitudes. Along with its high spatial and temporal resolution, CYGNSS can provide new insights into how extratropical cyclones develop and evolve, especially in the presence of thick clouds and precipitation. We will demonstrate this by presenting case studies of multiple extratropical cyclones observed by CYGNSS early on in its mission in both Northern and Southern Hemispheres. By using the improved estimates of surface wind speeds from CYGNSS, we can obtain better estimates of surface latent and sensible heat fluxes within and around extratropical cyclones. Surface heat fluxes, driven by surface winds and strong vertical gradients of water vapor and temperature, play a key role in marine cyclogenesis as they increase instability within the boundary layer and may contribute to extreme marine cyclogenesis. In the past, it has been difficult to estimate surface heat fluxes from space borne instruments, as these fluxes cannot be observed directly from space, and deficiencies in spatial coverage and attenuation from clouds and precipitation lead to inaccurate estimates of surface flux components, such as surface wind speeds. While CYGNSS only contributes estimates of surface wind speeds, we can combine this data with other reanalysis and satellite data to provide improved estimates of surface sensible and latent heat fluxes within and around extratropical cyclones and throughout the entire CYGNSS mission.

  7. State and force observers based on multibody models and the indirect Kalman filter

    Science.gov (United States)

    Sanjurjo, Emilio; Dopico, Daniel; Luaces, Alberto; Naya, Miguel Ángel

    2018-06-01

    The aim of this work is to present two new methods to provide state observers by combining multibody simulations with indirect extended Kalman filters. One of the methods presented provides also input force estimation. The observers have been applied to two mechanism with four different sensor configurations, and compared to other multibody-based observers found in the literature to evaluate their behavior, namely, the unscented Kalman filter (UKF), and the indirect extended Kalman filter with simplified Jacobians (errorEKF). The new methods have some more computational cost than the errorEKF, but still much less than the UKF. Regarding their accuracy, both are better than the errorEKF. The method with input force estimation outperforms also the UKF, while the method without force estimation achieves results almost identical to those of the UKF. All the methods have been implemented as a reusable MATLAB® toolkit which has been released as Open Source in https://github.com/MBDS/mbde-matlab.

  8. MODIS Based Estimation of Forest Aboveground Biomass in China.

    Directory of Open Access Journals (Sweden)

    Guodong Yin

    Full Text Available Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS dataset in a machine learning algorithm (the model tree ensemble, MTE. We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

  9. MODIS Based Estimation of Forest Aboveground Biomass in China

    Science.gov (United States)

    Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha−1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y−1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y−1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y−1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests. PMID:26115195

  10. MODIS Based Estimation of Forest Aboveground Biomass in China.

    Science.gov (United States)

    Yin, Guodong; Zhang, Yuan; Sun, Yan; Wang, Tao; Zeng, Zhenzhong; Piao, Shilong

    2015-01-01

    Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

  11. Optimal difference-based estimation for partially linear models

    KAUST Repository

    Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun

    2017-01-01

    Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.

  12. Optimal difference-based estimation for partially linear models

    KAUST Repository

    Zhou, Yuejin

    2017-12-16

    Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.

  13. Clutch pressure estimation for a power-split hybrid transmission using nonlinear robust observer

    Science.gov (United States)

    Zhou, Bin; Zhang, Jianwu; Gao, Ji; Yu, Haisheng; Liu, Dong

    2018-06-01

    For a power-split hybrid transmission, using the brake clutch to realize the transition from electric drive mode to hybrid drive mode is an available strategy. Since the pressure information of the brake clutch is essential for the mode transition control, this research designs a nonlinear robust reduced-order observer to estimate the brake clutch pressure. Model uncertainties or disturbances are considered as additional inputs, thus the observer is designed in order that the error dynamics is input-to-state stable. The nonlinear characteristics of the system are expressed as the lookup tables in the observer. Moreover, the gain matrix of the observer is solved by two optimization procedures under the constraints of the linear matrix inequalities. The proposed observer is validated by offline simulation and online test, the results have shown that the observer achieves significant performance during the mode transition, as the estimation error is within a reasonable range, more importantly, it is asymptotically stable.

  14. Traction control of an electric vehicle based on nonlinear observers

    Directory of Open Access Journals (Sweden)

    Diego A. Aligia

    2017-12-01

    Full Text Available A traction control strategy for a four-wheel electric vehicle is proposed in this paper. The strategy is based on nonlinear observers which allows estimating the maximum force that can be transmitted to the road. Knowledge of the maximum force allows controlling the slip of the driving wheels, preventing the wheel’s slippage in low-grip surfaces. The proposed strategy also allows to avoid the undesired yaw moment in the vehicle which occurs when road conditions on either side of it are dierent. This improves the eciency and the control of the vehicle, avoiding possible losses of stability that can result in risks for its occupants. Both the proposed observer and the control strategy are designed based on a dynamic rotational model of the wheel and a brush force model. Simulation results are obtained based on a complete vehicle model on the Simulink/CarSim platform.

  15. MODELING ATMOSPHERIC EMISSION FOR CMB GROUND-BASED OBSERVATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Errard, J.; Borrill, J. [Space Sciences Laboratory, University of California, Berkeley, CA 94720 (United States); Ade, P. A. R. [School of Physics and Astronomy, Cardiff University, Cardiff CF10 3XQ (United Kingdom); Akiba, Y.; Chinone, Y. [High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801 (Japan); Arnold, K.; Atlas, M.; Barron, D.; Elleflot, T. [Department of Physics, University of California, San Diego, CA 92093-0424 (United States); Baccigalupi, C.; Fabbian, G. [International School for Advanced Studies (SISSA), Trieste I-34014 (Italy); Boettger, D. [Department of Astronomy, Pontifica Universidad Catolica de Chile (Chile); Chapman, S. [Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, B3H 4R2 (Canada); Cukierman, A. [Department of Physics, University of California, Berkeley, CA 94720 (United States); Delabrouille, J. [AstroParticule et Cosmologie, Univ Paris Diderot, CNRS/IN2P3, CEA/Irfu, Obs de Paris, Sorbonne Paris Cité (France); Dobbs, M.; Gilbert, A. [Physics Department, McGill University, Montreal, QC H3A 0G4 (Canada); Ducout, A.; Feeney, S. [Department of Physics, Imperial College London, London SW7 2AZ (United Kingdom); Feng, C. [Department of Physics and Astronomy, University of California, Irvine (United States); and others

    2015-08-10

    Atmosphere is one of the most important noise sources for ground-based cosmic microwave background (CMB) experiments. By increasing optical loading on the detectors, it amplifies their effective noise, while its fluctuations introduce spatial and temporal correlations between detected signals. We present a physically motivated 3D-model of the atmosphere total intensity emission in the millimeter and sub-millimeter wavelengths. We derive a new analytical estimate for the correlation between detectors time-ordered data as a function of the instrument and survey design, as well as several atmospheric parameters such as wind, relative humidity, temperature and turbulence characteristics. Using an original numerical computation, we examine the effect of each physical parameter on the correlations in the time series of a given experiment. We then use a parametric-likelihood approach to validate the modeling and estimate atmosphere parameters from the polarbear-i project first season data set. We derive a new 1.0% upper limit on the linear polarization fraction of atmospheric emission. We also compare our results to previous studies and weather station measurements. The proposed model can be used for realistic simulations of future ground-based CMB observations.

  16. Process-based Cost Estimation for Ramjet/Scramjet Engines

    Science.gov (United States)

    Singh, Brijendra; Torres, Felix; Nesman, Miles; Reynolds, John

    2003-01-01

    Process-based cost estimation plays a key role in effecting cultural change that integrates distributed science, technology and engineering teams to rapidly create innovative and affordable products. Working together, NASA Glenn Research Center and Boeing Canoga Park have developed a methodology of process-based cost estimation bridging the methodologies of high-level parametric models and detailed bottoms-up estimation. The NASA GRC/Boeing CP process-based cost model provides a probabilistic structure of layered cost drivers. High-level inputs characterize mission requirements, system performance, and relevant economic factors. Design alternatives are extracted from a standard, product-specific work breakdown structure to pre-load lower-level cost driver inputs and generate the cost-risk analysis. As product design progresses and matures the lower level more detailed cost drivers can be re-accessed and the projected variation of input values narrowed, thereby generating a progressively more accurate estimate of cost-risk. Incorporated into the process-based cost model are techniques for decision analysis, specifically, the analytic hierarchy process (AHP) and functional utility analysis. Design alternatives may then be evaluated not just on cost-risk, but also user defined performance and schedule criteria. This implementation of full-trade study support contributes significantly to the realization of the integrated development environment. The process-based cost estimation model generates development and manufacturing cost estimates. The development team plans to expand the manufacturing process base from approximately 80 manufacturing processes to over 250 processes. Operation and support cost modeling is also envisioned. Process-based estimation considers the materials, resources, and processes in establishing cost-risk and rather depending on weight as an input, actually estimates weight along with cost and schedule.

  17. Estimating the size of non-observed economy in Croatia using the MIMIC approach

    OpenAIRE

    Vjekoslav Klaric

    2011-01-01

    This paper gives a quick overview of the approaches that have been used in the research of shadow economy, starting with the defi nitions of the terms “shadow economy” and “non-observed economy”, with the accent on the ISTAT/Eurostat framework. Several methods for estimating the size of the shadow economy and the non-observed economy are then presented. The emphasis is placed on the MIMIC approach, one of the methods used to estimate the size of the nonobserved economy. After a glance at the ...

  18. Forensic age estimation based on development of third molars: a staging technique for magnetic resonance imaging.

    Science.gov (United States)

    De Tobel, J; Phlypo, I; Fieuws, S; Politis, C; Verstraete, K L; Thevissen, P W

    2017-12-01

    The development of third molars can be evaluated with medical imaging to estimate age in subadults. The appearance of third molars on magnetic resonance imaging (MRI) differs greatly from that on radiographs. Therefore a specific staging technique is necessary to classify third molar development on MRI and to apply it for age estimation. To develop a specific staging technique to register third molar development on MRI and to evaluate its performance for age estimation in subadults. Using 3T MRI in three planes, all third molars were evaluated in 309 healthy Caucasian participants from 14 to 26 years old. According to the appearance of the developing third molars on MRI, descriptive criteria and schematic representations were established to define a specific staging technique. Two observers, with different levels of experience, staged all third molars independently with the developed technique. Intra- and inter-observer agreement were calculated. The data were imported in a Bayesian model for age estimation as described by Fieuws et al. (2016). This approach adequately handles correlation between age indicators and missing age indicators. It was used to calculate a point estimate and a prediction interval of the estimated age. Observed age minus predicted age was calculated, reflecting the error of the estimate. One-hundred and sixty-six third molars were agenetic. Five percent (51/1096) of upper third molars and 7% (70/1044) of lower third molars were not assessable. Kappa for inter-observer agreement ranged from 0.76 to 0.80. For intra-observer agreement kappa ranged from 0.80 to 0.89. However, two stage differences between observers or between staging sessions occurred in up to 2.2% (20/899) of assessments, probably due to a learning effect. Using the Bayesian model for age estimation, a mean absolute error of 2.0 years in females and 1.7 years in males was obtained. Root mean squared error equalled 2.38 years and 2.06 years respectively. The performance to

  19. A Kalman Filter for SINS Self-Alignment Based on Vector Observation.

    Science.gov (United States)

    Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Tong, Jinwu

    2017-01-29

    In this paper, a self-alignment method for strapdown inertial navigation systems based on the q -method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate.

  20. Efficiency of the estimators of multivariate distribution parameters from the one-dimensional observed frequencies

    International Nuclear Information System (INIS)

    Chernov, N.I.; Kurbatov, V.S.; Ososkov, G.A.

    1988-01-01

    Parameter estimation for multivariate probability distributions is studied in experiments where data are presented as one-dimensional hystograms. For this model a statistics defined as a quadratic form of the observed frequencies which has a limitig x 2 -distribution is proposed. The efficiency of the estimator minimizing the value of that statistics is proved whithin the class of all unibased estimates obtained via minimization of quadratic forms of observed frequencies. The elaborated method was applied to the physical problem of analysis of the secondary pion energy distribution in the isobar model of pion-nucleon interactions with the production of an additional pion. The numerical experiments showed that the accuracy of estimation is twice as much if comparing the conventional methods

  1. A cooperative control algorithm for camera based observational systems.

    Energy Technology Data Exchange (ETDEWEB)

    Young, Joseph G.

    2012-01-01

    Over the last several years, there has been considerable growth in camera based observation systems for a variety of safety, scientific, and recreational applications. In order to improve the effectiveness of these systems, we frequently desire the ability to increase the number of observed objects, but solving this problem is not as simple as adding more cameras. Quite often, there are economic or physical restrictions that prevent us from adding additional cameras to the system. As a result, we require methods that coordinate the tracking of objects between multiple cameras in an optimal way. In order to accomplish this goal, we present a new cooperative control algorithm for a camera based observational system. Specifically, we present a receding horizon control where we model the underlying optimal control problem as a mixed integer linear program. The benefit of this design is that we can coordinate the actions between each camera while simultaneously respecting its kinematics. In addition, we further improve the quality of our solution by coupling our algorithm with a Kalman filter. Through this integration, we not only add a predictive component to our control, but we use the uncertainty estimates provided by the filter to encourage the system to periodically observe any outliers in the observed area. This combined approach allows us to intelligently observe the entire region of interest in an effective and thorough manner.

  2. Discrete-time state estimation for stochastic polynomial systems over polynomial observations

    Science.gov (United States)

    Hernandez-Gonzalez, M.; Basin, M.; Stepanov, O.

    2018-07-01

    This paper presents a solution to the mean-square state estimation problem for stochastic nonlinear polynomial systems over polynomial observations confused with additive white Gaussian noises. The solution is given in two steps: (a) computing the time-update equations and (b) computing the measurement-update equations for the state estimate and error covariance matrix. A closed form of this filter is obtained by expressing conditional expectations of polynomial terms as functions of the state estimate and error covariance. As a particular case, the mean-square filtering equations are derived for a third-degree polynomial system with second-degree polynomial measurements. Numerical simulations show effectiveness of the proposed filter compared to the extended Kalman filter.

  3. Estimation of the measurement uncertainty in magnetic resonance velocimetry based on statistical models

    Energy Technology Data Exchange (ETDEWEB)

    Bruschewski, Martin; Schiffer, Heinz-Peter [Technische Universitaet Darmstadt, Institute of Gas Turbines and Aerospace Propulsion, Darmstadt (Germany); Freudenhammer, Daniel [Technische Universitaet Darmstadt, Institute of Fluid Mechanics and Aerodynamics, Center of Smart Interfaces, Darmstadt (Germany); Buchenberg, Waltraud B. [University Medical Center Freiburg, Medical Physics, Department of Radiology, Freiburg (Germany); Grundmann, Sven [University of Rostock, Institute of Fluid Mechanics, Rostock (Germany)

    2016-05-15

    Velocity measurements with magnetic resonance velocimetry offer outstanding possibilities for experimental fluid mechanics. The purpose of this study was to provide practical guidelines for the estimation of the measurement uncertainty in such experiments. Based on various test cases, it is shown that the uncertainty estimate can vary substantially depending on how the uncertainty is obtained. The conventional approach to estimate the uncertainty from the noise in the artifact-free background can lead to wrong results. A deviation of up to -75% is observed with the presented experiments. In addition, a similarly high deviation is demonstrated with the data from other studies. As a more accurate approach, the uncertainty is estimated directly from the image region with the flow sample. Two possible estimation methods are presented. (orig.)

  4. Estimation of the measurement uncertainty in magnetic resonance velocimetry based on statistical models

    Science.gov (United States)

    Bruschewski, Martin; Freudenhammer, Daniel; Buchenberg, Waltraud B.; Schiffer, Heinz-Peter; Grundmann, Sven

    2016-05-01

    Velocity measurements with magnetic resonance velocimetry offer outstanding possibilities for experimental fluid mechanics. The purpose of this study was to provide practical guidelines for the estimation of the measurement uncertainty in such experiments. Based on various test cases, it is shown that the uncertainty estimate can vary substantially depending on how the uncertainty is obtained. The conventional approach to estimate the uncertainty from the noise in the artifact-free background can lead to wrong results. A deviation of up to -75 % is observed with the presented experiments. In addition, a similarly high deviation is demonstrated with the data from other studies. As a more accurate approach, the uncertainty is estimated directly from the image region with the flow sample. Two possible estimation methods are presented.

  5. Improved control of distributed parameter systems using wireless sensor and actuator networks: An observer-based method

    International Nuclear Information System (INIS)

    Jiang Zheng-Xian; Cui Bao-Tong; Lou Xu-Yang; Zhuang Bo

    2017-01-01

    In this paper, the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method. Firstly, a centralized observer which makes use of the measurement information provided by the fixed sensors is designed to estimate the distributed parameter systems. The mobile agents, each of which is affixed with a controller and an actuator, can provide the observer-based control for the target systems. By using Lyapunov stability arguments, the stability for the estimation error system and distributed parameter control system is proved, meanwhile a guidance scheme for each mobile actuator is provided to improve the control performance. A numerical example is finally used to demonstrate the effectiveness and the advantages of the proposed approaches. (paper)

  6. Estimates of lightning NOx production from GOME satellite observations

    Directory of Open Access Journals (Sweden)

    K. F. Boersma

    2005-01-01

    Full Text Available Tropospheric NO2 column retrievals from the Global Ozone Monitoring Experiment (GOME satellite spectrometer are used to quantify the source strength and 3-D distribution of lightning produced nitrogen oxides (NOx=NO+NO2. A sharp increase of NO2 is observed at convective cloud tops with increasing cloud top height, consistent with a power-law behaviour with power 5±2. Convective production of clouds with the same cloud height are found to produce NO2 with a ratio 1.6/1 for continents compared to oceans. This relation between cloud properties and NO2 is used to construct a 10:30 local time global lightning NO2 production map for 1997. An extensive statistical comparison is conducted to investigate the capability of the TM3 chemistry transport model to reproduce observed patterns of lightning NO2 in time and space. This comparison uses the averaging kernel to relate modelled profiles of NO2 to observed NO2 columns. It exploits a masking scheme to minimise the interference of other NOx sources on the observed total columns. Simulations are performed with two lightning parameterizations, one relating convective preciptation (CP scheme to lightning flash distributions, and the other relating the fifth power of the cloud top height (H5 scheme to lightning distributions. The satellite-retrieved NO2 fields show significant correlations with the simulated lightning contribution to the NO2 concentrations for both parameterizations. Over tropical continents modelled lightning NO2 shows remarkable quantitative agreement with observations. Over the oceans however, the two model lightning parameterizations overestimate the retrieved NO2 attributed to lightning. Possible explanations for these overestimations are discussed. The ratio between satellite-retrieved NO2 and modelled lightning NO2 is used to rescale the original modelled lightning NOx production. Eight estimates of the lightning NOx production in 1997 are obtained from spatial and temporal

  7. An ELM-Based Approach for Estimating Train Dwell Time in Urban Rail Traffic

    Directory of Open Access Journals (Sweden)

    Wen-jun Chu

    2015-01-01

    Full Text Available Dwell time estimation plays an important role in the operation of urban rail system. On this specific problem, a range of models based on either polynomial regression or microsimulation have been proposed. However, the generalization performance of polynomial regression models is limited and the accuracy of existing microsimulation models is unstable. In this paper, a new dwell time estimation model based on extreme learning machine (ELM is proposed. The underlying factors that may affect urban rail dwell time are analyzed first. Then, the relationships among different factors are extracted and modeled by ELM neural networks, on basis of which an overall estimation model is proposed. At last, a set of observed data from Beijing subway is used to illustrate the proposed method and verify its overall performance.

  8. Observer-based linear parameter varying H∞ tracking control for hypersonic vehicles

    Directory of Open Access Journals (Sweden)

    Yiqing Huang

    2016-11-01

    Full Text Available This article aims to develop observer-based linear parameter varying output feedback H∞ tracking controller for hypersonic vehicles. Due to the complexity of an original nonlinear model of the hypersonic vehicle dynamics, a slow–fast loop linear parameter varying polytopic model is introduced for system stability analysis and controller design. Then, a state observer is developed by linear parameter varying technique in order to estimate the unmeasured attitude angular for slow loop system. Also, based on the designed linear parameter varying state observer, a kind of attitude tracking controller is presented to reduce tracking errors for all bounded reference attitude angular inputs. The closed-loop linear parameter varying system is proved to be quadratically stable by Lypapunov function technique. Finally, simulation results show that the developed linear parameter varying H∞ controller has good tracking capability for reference commands.

  9. SU-E-I-46: Sample-Size Dependence of Model Observers for Estimating Low-Contrast Detection Performance From CT Images

    International Nuclear Information System (INIS)

    Reiser, I; Lu, Z

    2014-01-01

    Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions included two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, σ(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task

  10. Monte Carlo-based tail exponent estimator

    Science.gov (United States)

    Barunik, Jozef; Vacha, Lukas

    2010-11-01

    In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.

  11. Size-based estimation of the status of fish stocks: simulation analysis and comparison with age-based estimations

    DEFF Research Database (Denmark)

    Kokkalis, Alexandros; Thygesen, Uffe Høgsbro; Nielsen, Anders

    , were investigated and our estimations were compared to the ICES advice. Only size-specific catch data were used, in order to emulate data limited situations. The simulation analysis reveals that the status of the stock, i.e. F/Fmsy, is estimated more accurately than the fishing mortality F itself....... Specific knowledge of the natural mortality improves the estimation more than having information about all other life history parameters. Our approach gives, at least qualitatively, an estimated stock status which is similar to the results of an age-based assessment. Since our approach only uses size...

  12. Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

    Science.gov (United States)

    Vecchia, Aldo V.

    2018-03-22

    This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.

  13. Cloud-based shaft torque estimation for electric vehicle equipped with integrated motor-transmission system

    Science.gov (United States)

    Zhu, Xiaoyuan; Zhang, Hui; Yang, Bo; Zhang, Guichen

    2018-01-01

    In order to improve oscillation damping control performance as well as gear shift quality of electric vehicle equipped with integrated motor-transmission system, a cloud-based shaft torque estimation scheme is proposed in this paper by using measurable motor and wheel speed signals transmitted by wireless network. It can help reduce computational burden of onboard controllers and also relief network bandwidth requirement of individual vehicle. Considering possible delays during signal wireless transmission, delay-dependent full-order observer design is proposed to estimate the shaft torque in cloud server. With these random delays modeled by using homogenous Markov chain, robust H∞ performance is adopted to minimize the effect of wireless network-induced delays, signal measurement noise as well as system modeling uncertainties on shaft torque estimation error. Observer parameters are derived by solving linear matrix inequalities, and simulation results using acceleration test and tip-in, tip-out test demonstrate the effectiveness of proposed shaft torque observer design.

  14. Mesospheric temperatures estimated from the meteor radar observations at Mohe, China

    Science.gov (United States)

    Liu, Libo; Liu, Huixin; Chen, Yiding; Le, Huijun

    2017-04-01

    In this work, we report the estimation of mesospheric temperatures at 90 km height from the observations of the VHF all-sky meteor radar operated at Mohe (53.5 °N, 122.3° E), China, since August 2011. The kinetic temperature profiles retrieved from the observations of Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) onboard the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics (TIMED) satellite are processed to provide the temperature (TSABER) and temperature gradient (dT/dh) at 90 km height. Based on the SABER temperature profile data an empirical dT/dh model is developed for the Mohe latitude. First, we derive the temperatures from the meteor decay times (Tmeteor) and the Mohe dT/dh model gives prior information of temperature gradients. Secondly, the full-width of half maximum (FWHM) of the meteor height profiles is calculated and further used to deduce the temperatures (TFWHM) based on the strong linear relationship between FWHM and TSABER. The temperatures at 90 km deduced from the decay times (Tmeteor) and from the meteor height distributions (TFWHM) at Mohe are validated/calibrated with TSABER. The temperatures present a considerable annual variation, being maximum in winter and minimum in summer. Harmonic analyses reveal that the temperatures have an annual variation consistent with TSABER. Our work suggests that the FWHM has a good performance in routine estimation of the temperatures. It should be pointed out that the slope of FWHM and TSABER is 10.1 at Mohe, which is different from that of 15.71 at King Sejong (62.2° S, 58.8° E) station. Acknowledgments The TIMED/SABER kinetic temperature (version 2.0) data are provided by the SABER team through http://saber.gats-inc.com/. The temperatures from the NRLMSISE-00 model are calculated using Aerospace Blockset toolbox of MATLAB (2016a). This research was supported by National Natural Science Foundation of China (41231065, 41321003). We acknowledge the use of meteor radar

  15. Estimating Large Area Forest Carbon Stocks—A Pragmatic Design Based Strategy

    Directory of Open Access Journals (Sweden)

    Andrew Haywood

    2017-03-01

    Full Text Available Reducing uncertainty in forest carbon estimates at local and regional scales has become increasingly important due to the centrality of the terrestrial carbon cycle in issues of climate change. In Victoria, Australia, public natural forests extend over 7.2 M ha and constitute a significant and important carbon stock. Recently, a wide range of approaches to estimate carbon stocks within these forests have been developed and applied. However, there are a number of data and estimation limitations associated with these studies. In response, over the last five years, the State of Victoria has implemented a pragmatic plot-based design consisting of pre-stratified permanent observational units located on a state-wide grid. Using the ground sampling grid, we estimated aboveground and belowground carbon stocks (including soil to 0.3 m depth in both National Parks and State Forests, across a wide range of bioregions. Estimates of carbon stocks and associated uncertainty were conducted using simple design based estimators. We detected significantly more carbon in total aboveground and belowground components in State Forests (408.9 t ha−1, 95% confidence interval 388.8–428.9 t ha−1 than National Parks (267.6 t ha−1, 251.9–283.3 t ha−1. We were also able to estimate forest carbon stocks (and associated uncertainty for 21 strata that represent all of Victoria’s bioregions and public tenures. It is anticipated that the lessons learnt from this study may support the discussion on planning and implementing low cost large area forest carbon stock sampling in other jurisdictions.

  16. Methane Emissions from Bangladesh: Bridging the Gap Between Ground-based and Space-borne Estimates

    Science.gov (United States)

    Peters, C.; Bennartz, R.; Hornberger, G. M.

    2015-12-01

    Gaining an understanding of methane (CH4) emission sources and atmospheric dispersion is an essential part of climate change research. Large-scale and global studies often rely on satellite observations of column CH4 mixing ratio whereas high-spatial resolution estimates rely on ground-based measurements. Extrapolation of ground-based measurements on, for example, rice paddies to broad region scales is highly uncertain because of spatio-temporal variability. We explore the use of ground-based river stage measurements and independent satellite observations of flooded area along with satellite measurements of CH4 mixing ratio to estimate the extent of methane emissions. Bangladesh, which comprises most of the Ganges Brahmaputra Meghna (GBM) delta, is a region of particular interest for studying spatio-temporal variation of methane emissions due to (1) broadscale rice cultivation and (2) seasonal flooding and atmospheric convection during the monsoon. Bangladesh and its deltaic landscape exhibit a broad range of environmental, economic, and social circumstances that are relevant to many nations in South and Southeast Asia. We explore the seasonal enhancement of CH4 in Bangladesh using passive remote sensing spectrometer CH4 products from the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) and the Atmospheric Infrared Sounder (AIRS). The seasonal variation of CH4 is compared to independent estimates of seasonal flooding from water gauge stations and space-based passive microwave water-to-land fractions from the Tropical Rainfall Measuring Mission Microwave Imager (TRMM-TMI). Annual cycles in inundation (natural and anthropogenic) and atmospheric CH4 concentrations show highly correlated seasonal signals. NOAA's HYSPLIT model is used to determine atmospheric residence time of ground CH4 fluxes. Using the satellite observations, we can narrow the large uncertainty in extrapolation of ground-based CH4 emission estimates from rice paddies

  17. Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall-runoff data and land slope

    Science.gov (United States)

    Deshmukh, Dhananjay Suresh; Chaube, Umesh Chandra; Ekube Hailu, Ambaye; Aberra Gudeta, Dida; Tegene Kassa, Melaku

    2013-06-01

    The CN represents runoff potential is estimated using three different methods for three watersheds namely Barureva, Sher and Umar watershed located in Narmada basin. Among three watersheds, Sher watershed has gauging site for the runoff measurements. The CN computed from the observed rainfall-runoff events is termed as CN(PQ), land use and land cover (LULC) is termed as CN(LU) and the CN based on land slope is termed as SACN2. The estimated annual CN(PQ) varies from 69 to 87 over the 26 years data period with median 74 and average 75. The range of CN(PQ) from 70 to 79 are most significant values and these truly represent the AMC II condition for the Sher watershed. The annual CN(LU) was computed for all three watersheds using GIS and the years are 1973, 1989 and 2000. Satellite imagery of MSS, TM and ETM+ sensors are available for these years and obtained from the Global Land Cover Facility Data Center of Maryland University USA. The computed CN(LU) values show rising trend with the time and this trend is attributed to expansion of agriculture area in all watersheds. The predicted values of CN(LU) with time (year) can be used to predict runoff potential under the effect of change in LULC. Comparison of CN(LU) and CN(PQ) values shows close agreement and it also validates the classification of LULC. The estimation of slope adjusted SA-CN2 shows the significant difference over conventional CN for the hilly forest lands. For the micro watershed planning, SCS-CN method should be modified to incorporate the effect of change in land use and land cover along with effect of land slope.

  18. Number of discernible colors for color-deficient observers estimated from the MacAdam limits.

    Science.gov (United States)

    Perales, Esther; Martínez-Verdú, Francisco Miguel; Linhares, João Manuel Maciel; Nascimento, Sérgio Miguel Cardoso

    2010-10-01

    We estimated the number of colors perceived by color normal and color-deficient observers when looking at the theoretic limits of object-color stimuli. These limits, the optimal color stimuli, were computed for a color normal observer and CIE standard illuminant D65, and the resultant colors were expressed in the CIELAB and DIN99d color spaces. The corresponding color volumes for abnormal color vision were computed using models simulating for normal trichromatic observers the appearance for dichromats and anomalous trichomats. The number of colors perceived in each case was then computed from the color volumes enclosed by the optimal colors also known as MacAdam limits. It was estimated that dichromats perceive less than 1% of the colors perceived by normal trichromats and that anomalous trichromats perceive 50%-60% for anomalies in the medium-wavelength-sensitive and 60%-70% for anomalies in the long-wavelength-sensitive cones. Complementary estimates obtained similarly for the spectral locus of monochromatic stimuli suggest less impairment for color-deficient observers, a fact that is explained by the two-dimensional nature of the locus.

  19. State and actuator fault estimation observer design integrated in a riderless bicycle stabilization system.

    Science.gov (United States)

    Brizuela Mendoza, Jorge Aurelio; Astorga Zaragoza, Carlos Manuel; Zavala Río, Arturo; Pattalochi, Leo; Canales Abarca, Francisco

    2016-03-01

    This paper deals with an observer design for Linear Parameter Varying (LPV) systems with high-order time-varying parameter dependency. The proposed design, considered as the main contribution of this paper, corresponds to an observer for the estimation of the actuator fault and the system state, considering measurement noise at the system outputs. The observer gains are computed by considering the extension of linear systems theory to polynomial LPV systems, in such a way that the observer reaches the characteristics of LPV systems. As a result, the actuator fault estimation is ready to be used in a Fault Tolerant Control scheme, where the estimated state with reduced noise should be used to generate the control law. The effectiveness of the proposed methodology has been tested using a riderless bicycle model with dependency on the translational velocity v, where the control objective corresponds to the system stabilization towards the upright position despite the variation of v along the closed-loop system trajectories. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

    Directory of Open Access Journals (Sweden)

    R. Manam

    2017-12-01

    Full Text Available In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

  1. Risk Probability Estimating Based on Clustering

    DEFF Research Database (Denmark)

    Chen, Yong; Jensen, Christian D.; Gray, Elizabeth

    2003-01-01

    of prior experiences, recommendations from a trusted entity or the reputation of the other entity. In this paper we propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models...... from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based...

  2. High-global warming potential F-gas emissions in California: comparison of ambient-based versus inventory-based emission estimates, and implications of refined estimates.

    Science.gov (United States)

    Gallagher, Glenn; Zhan, Tao; Hsu, Ying-Kuang; Gupta, Pamela; Pederson, James; Croes, Bart; Blake, Donald R; Barletta, Barbara; Meinardi, Simone; Ashford, Paul; Vetter, Arnie; Saba, Sabine; Slim, Rayan; Palandre, Lionel; Clodic, Denis; Mathis, Pamela; Wagner, Mark; Forgie, Julia; Dwyer, Harry; Wolf, Katy

    2014-01-21

    To provide information for greenhouse gas reduction policies, the California Air Resources Board (CARB) inventories annual emissions of high-global-warming potential (GWP) fluorinated gases, the fastest growing sector of greenhouse gas (GHG) emissions globally. Baseline 2008 F-gas emissions estimates for selected chlorofluorocarbons (CFC-12), hydrochlorofluorocarbons (HCFC-22), and hydrofluorocarbons (HFC-134a) made with an inventory-based methodology were compared to emissions estimates made by ambient-based measurements. Significant discrepancies were found, with the inventory-based emissions methodology resulting in a systematic 42% under-estimation of CFC-12 emissions from older refrigeration equipment and older vehicles, and a systematic 114% overestimation of emissions for HFC-134a, a refrigerant substitute for phased-out CFCs. Initial, inventory-based estimates for all F-gas emissions had assumed that equipment is no longer in service once it reaches its average lifetime of use. Revised emission estimates using improved models for equipment age at end-of-life, inventories, and leak rates specific to California resulted in F-gas emissions estimates in closer agreement to ambient-based measurements. The discrepancies between inventory-based estimates and ambient-based measurements were reduced from -42% to -6% for CFC-12, and from +114% to +9% for HFC-134a.

  3. Solar radiation estimation based on the insolation

    International Nuclear Information System (INIS)

    Assis, F.N. de; Steinmetz, S.; Martins, S.R.; Mendez, M.E.G.

    1998-01-01

    A series of daily global solar radiation data measured by an Eppley pyranometer was used to test PEREIRA and VILLA NOVA’s (1997) model to estimate the potential of radiation based on the instantaneous values measured at solar noon. The model also allows to estimate the parameters of PRESCOTT’s equation (1940) assuming a = 0,29 cosj. The results demonstrated the model’s validity for the studied conditions. Simultaneously, the hypothesis of generalizing the use of the radiation estimative formulas based on insolation, and using K = Ko (0,29 cosj + 0,50 n/N), was analysed and confirmed [pt

  4. An Approach for State Observation in Dynamical Systems Based on the Twisting Algorithm

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

    2013-01-01

    This paper discusses a novel approach for state estimation in dynamical systems, with the special focus on hydraulic valve-cylinder drives. The proposed observer structure is based on the framework of the so-called twisting algorithm. This algorithm utilizes the sign of the state being the target...

  5. Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J. [Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS foundation Trust, Sutton, London SM2 5PT (United Kingdom)

    2016-01-15

    Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison with normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking

  6. Corona magnetic field over sunspots estimated by m-wave observation

    International Nuclear Information System (INIS)

    Kurihara, Masahiro

    1974-01-01

    The shape of the magnetic field in corona was estimated from the observation of the type I storm occurred in the last decade of August, 1971. It was found from the observation with a 160 MHz interferometer at Mt. Nobeyama that at most three storm sources, which are called radio wave source, were produced. The radio wave sources were fixed above sunspots. The height of the radio wave sources was estimated to be 0.45 R from the photosphere. The sunspots under the radio wave sources can be classified to four sub-groups. Weakening of the magnetic field on the photosphere was found from the reduction of the area of some sub-group. The relation between the activity of type I storm and the intensity of the magnetic field of sunspots is qualitatively suggested. It is considered that the radio wave sources and the sunspots were connected by common magnetic force lines. The probable magnetic field in corona was presumed and is shown in a figure. An interesting point is that the direction of magnetic force lines inclined by about 30 0 outward to the vertical line to the photosphere surface. (Kato, T.)

  7. Empirically Driven Variable Selection for the Estimation of Causal Effects with Observational Data

    Science.gov (United States)

    Keller, Bryan; Chen, Jianshen

    2016-01-01

    Observational studies are common in educational research, where subjects self-select or are otherwise non-randomly assigned to different interventions (e.g., educational programs, grade retention, special education). Unbiased estimation of a causal effect with observational data depends crucially on the assumption of ignorability, which specifies…

  8. Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation

    Directory of Open Access Journals (Sweden)

    Yechen Qin

    2015-01-01

    Full Text Available A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II. A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.

  9. Evaluating detection and estimation capabilities of magnetometer-based vehicle sensors

    Science.gov (United States)

    Slater, David M.; Jacyna, Garry M.

    2013-05-01

    In an effort to secure the northern and southern United States borders, MITRE has been tasked with developing Modeling and Simulation (M&S) tools that accurately capture the mapping between algorithm-level Measures of Performance (MOP) and system-level Measures of Effectiveness (MOE) for current/future surveillance systems deployed by the the Customs and Border Protection Office of Technology Innovations and Acquisitions (OTIA). This analysis is part of a larger M&S undertaking. The focus is on two MOPs for magnetometer-based Unattended Ground Sensors (UGS). UGS are placed near roads to detect passing vehicles and estimate properties of the vehicle's trajectory such as bearing and speed. The first MOP considered is the probability of detection. We derive probabilities of detection for a network of sensors over an arbitrary number of observation periods and explore how the probability of detection changes when multiple sensors are employed. The performance of UGS is also evaluated based on the level of variance in the estimation of trajectory parameters. We derive the Cramer-Rao bounds for the variances of the estimated parameters in two cases: when no a priori information is known and when the parameters are assumed to be Gaussian with known variances. Sample results show that UGS perform significantly better in the latter case.

  10. Robust observer-based fault diagnosis for nonlinear systems using Matlab

    CERN Document Server

    Zhang, Jian; Nguang, Sing Kiong

    2016-01-01

    This book introduces several observer-based methods, including: • the sliding-mode observer • the adaptive observer • the unknown-input observer and • the descriptor observer method for the problem of fault detection, isolation and estimation, allowing readers to compare and contrast the different approaches. The authors present basic material on Lyapunov stability theory, H¥ control theory, sliding-mode control theory and linear matrix inequality problems in a self-contained and step-by-step manner. Detailed and rigorous mathematical proofs are provided for all the results developed in the text so that readers can quickly gain a good understanding of the material. MATLAB® and Simulink® codes for all the examples, which can be downloaded from http://extras.springer.com, enable students to follow the methods and illustrative examples easily. The systems used in the examples make the book highly relevant to real-world problems in industrial control engineering and include a seventh-order aircraft mod...

  11. Adaptive fuzzy bilinear observer based synchronization design for generalized Lorenz system

    International Nuclear Information System (INIS)

    Baek, Jaeho; Lee, Heejin; Kim, Seungwoo; Park, Mignon

    2009-01-01

    This Letter proposes an adaptive fuzzy bilinear observer (FBO) based synchronization design for generalized Lorenz system (GLS). The GLS can be described to TS fuzzy bilinear generalized Lorenz model (FBGLM) with their states immeasurable and their parameters unknown. We design an adaptive FBO based on TS FBGLM for synchronization. Lyapunov theory is employed to guarantee the stability of error dynamic system via linear matrix equalities (LMIs) and to derive the adaptive laws to estimate unknown parameters. Numerical example is given to demonstrate the validity of our proposed adaptive FBO approach for synchronization.

  12. Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation

    Directory of Open Access Journals (Sweden)

    Sekhar S Chandra

    2004-01-01

    Full Text Available We address the problem of estimating instantaneous frequency (IF of a real-valued constant amplitude time-varying sinusoid. Estimation of polynomial IF is formulated using the zero-crossings of the signal. We propose an algorithm to estimate nonpolynomial IF by local approximation using a low-order polynomial, over a short segment of the signal. This involves the choice of window length to minimize the mean square error (MSE. The optimal window length found by directly minimizing the MSE is a function of the higher-order derivatives of the IF which are not available a priori. However, an optimum solution is formulated using an adaptive window technique based on the concept of intersection of confidence intervals. The adaptive algorithm enables minimum MSE-IF (MMSE-IF estimation without requiring a priori information about the IF. Simulation results show that the adaptive window zero-crossing-based IF estimation method is superior to fixed window methods and is also better than adaptive spectrogram and adaptive Wigner-Ville distribution (WVD-based IF estimators for different signal-to-noise ratio (SNR.

  13. Accelerometer-based wireless body area network to estimate intensity of therapy in post-acute rehabilitation

    Directory of Open Access Journals (Sweden)

    Hamel Mathieu

    2008-09-01

    Full Text Available Abstract Background It has been suggested that there is a dose-response relationship between the amount of therapy and functional recovery in post-acute rehabilitation care. To this day, only the total time of therapy has been investigated as a potential determinant of this dose-response relationship because of methodological and measurement challenges. The primary objective of this study was to compare time and motion measures during real life physical therapy with estimates of active time (i.e. the time during which a patient is active physically obtained with a wireless body area network (WBAN of 3D accelerometer modules positioned at the hip, wrist and ankle. The secondary objective was to assess the differences in estimates of active time when using a single accelerometer module positioned at the hip. Methods Five patients (77.4 ± 5.2 y with 4 different admission diagnoses (stroke, lower limb fracture, amputation and immobilization syndrome were recruited in a post-acute rehabilitation center and observed during their physical therapy sessions throughout their stay. Active time was recorded by a trained observer using a continuous time and motion analysis program running on a Tablet-PC. Two WBAN configurations were used: 1 three accelerometer modules located at the hip, wrist and ankle (M3 and 2 one accelerometer located at the hip (M1. Acceleration signals from the WBANs were synchronized with the observations. Estimates of active time were computed based on the temporal density of the acceleration signals. Results A total of 62 physical therapy sessions were observed. Strong associations were found between WBANs estimates of active time and time and motion measures of active time. For the combined sessions, the intraclass correlation coefficient (ICC was 0.93 (P ≤ 0.001 for M3 and 0.79 (P ≤ 0.001 for M1. The mean percentage of differences between observation measures and estimates from the WBAN of active time was -8.7% ± 2.0% using

  14. Comparing NEXRAD Operational Precipitation Estimates and Raingage Observations of Intense Precipitation in the Missouri River Basin.

    Science.gov (United States)

    Young, C. B.

    2002-05-01

    Accurate observation of precipitation is critical to the study and modeling of land surface hydrologic processes. NEXRAD radar-based precipitation estimates are increasingly used in field experiments, hydrologic modeling, and water and energy budget studies due to their high spatial and temporal resolution, national coverage, and perceived accuracy. Extensive development and testing of NEXRAD precipitation algorithms have been carried out in the Southern Plains. Previous studies (Young et al. 2000, Young et al. 1999, Smith et al. 1996) indicate that NEXRAD operational products tend to underestimate precipitation at light rain rates. This study investigates the performance of NEXRAD precipitation estimates of high-intensity rainfall, focusing on flood-producing storms in the Missouri River Basin. NEXRAD estimates for these storms are compared with data from multiple raingage networks, including NWS recording and non-recording gages and ALERT raingage data for the Kansas City metropolitan area. Analyses include comparisons of gage and radar data at a wide range of temporal and spatial scales. Particular attention is paid to the October 4th, 1998, storm that produced severe flooding in Kansas City. NOTE: The phrase `NEXRAD operational products' in this abstract includes precipitation estimates generated using the Stage III and P1 algorithms. Both of these products estimate hourly accumulations on the (approximately) 4 km HRAP grid.

  15. Fast emission estimates in China and South Africa constrained by satellite observations

    Science.gov (United States)

    Mijling, Bas; van der A, Ronald

    2013-04-01

    Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for emerging economies such as China and South Africa, where rapid economic growth change emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. However, constraining emissions from observations of concentrations is computationally challenging. Within the GlobEmission project (part of the Data User Element programme of ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China and South Africa, using the CHIMERE chemical transport model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e

  16. Response-Based Estimation of Sea State Parameters

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2007-01-01

    of measured ship responses. It is therefore interesting to investigate how the filtering aspect, introduced by FRF, affects the final outcome of the estimation procedures. The paper contains a study based on numerical generated time series, and the study shows that filtering has an influence...... calculated by a 3-D time domain code and by closed-form (analytical) expressions, respectively. Based on comparisons with wave radar measurements and satellite measurements it is seen that the wave estimations based on closedform expressions exhibit a reasonable energy content, but the distribution of energy...

  17. Model Based Optimal Control, Estimation, and Validation of Lithium-Ion Batteries

    Science.gov (United States)

    Perez, Hector Eduardo

    This dissertation focuses on developing and experimentally validating model based control techniques to enhance the operation of lithium ion batteries, safely. An overview of the contributions to address the challenges that arise are provided below. Chapter 1: This chapter provides an introduction to battery fundamentals, models, and control and estimation techniques. Additionally, it provides motivation for the contributions of this dissertation. Chapter 2: This chapter examines reference governor (RG) methods for satisfying state constraints in Li-ion batteries. Mathematically, these constraints are formulated from a first principles electrochemical model. Consequently, the constraints explicitly model specific degradation mechanisms, such as lithium plating, lithium depletion, and overheating. This contrasts with the present paradigm of limiting measured voltage, current, and/or temperature. The critical challenges, however, are that (i) the electrochemical states evolve according to a system of nonlinear partial differential equations, and (ii) the states are not physically measurable. Assuming available state and parameter estimates, this chapter develops RGs for electrochemical battery models. The results demonstrate how electrochemical model state information can be utilized to ensure safe operation, while simultaneously enhancing energy capacity, power, and charge speeds in Li-ion batteries. Chapter 3: Complex multi-partial differential equation (PDE) electrochemical battery models are characterized by parameters that are often difficult to measure or identify. This parametric uncertainty influences the state estimates of electrochemical model-based observers for applications such as state-of-charge (SOC) estimation. This chapter develops two sensitivity-based interval observers that map bounded parameter uncertainty to state estimation intervals, within the context of electrochemical PDE models and SOC estimation. Theoretically, this chapter extends the

  18. Adaptive fuzzy observer based synchronization design and secure communications of chaotic systems

    International Nuclear Information System (INIS)

    Hyun, Chang-Ho; Kim, Jae-Hun; Kim, Euntai; Park, Mignon

    2006-01-01

    This paper proposes a synchronization design scheme based on an alternative indirect adaptive fuzzy observer and its application to secure communication of chaotic systems. It is assumed that their states are unmeasurable and their parameters are unknown. Chaotic systems and the structure of the fuzzy observer are represented by the Takagi-Sugeno fuzzy model. Using Lyapunov stability theory, an adaptive law is derived to estimate the unknown parameters and the stability of the proposed system is guaranteed. Through this process, the asymptotic synchronization of chaotic systems is achieved. The proposed observer is applied to secure communications of chaotic systems and some numerical simulation results show the validity of theoretical derivations and the performance of the proposed observer

  19. Robust linear discriminant analysis with distance based estimators

    Science.gov (United States)

    Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

    2017-11-01

    Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.

  20. Estimation of the neuronal activation using fMRI data: An observer-based approach

    KAUST Repository

    Laleg-Kirati, Taous-Meriem; Arabi, Hossein; Tadjine, Mohamed; Zayane, Chadia

    2013-01-01

    This paper deals with the estimation of the neuronal activation and some unmeasured physiological information using the Blood Oxygenation Level Dependent (BOLD) signal measured using functional Magnetic Resonance Imaging (fMRI). We propose to use

  1. Comparison of MRI-based estimates of articular cartilage contact area in the tibiofemoral joint.

    Science.gov (United States)

    Henderson, Christopher E; Higginson, Jill S; Barrance, Peter J

    2011-01-01

    Knee osteoarthritis (OA) detrimentally impacts the lives of millions of older Americans through pain and decreased functional ability. Unfortunately, the pathomechanics and associated deviations from joint homeostasis that OA patients experience are not well understood. Alterations in mechanical stress in the knee joint may play an essential role in OA; however, existing literature in this area is limited. The purpose of this study was to evaluate the ability of an existing magnetic resonance imaging (MRI)-based modeling method to estimate articular cartilage contact area in vivo. Imaging data of both knees were collected on a single subject with no history of knee pathology at three knee flexion angles. Intra-observer reliability and sensitivity studies were also performed to determine the role of operator-influenced elements of the data processing on the results. The method's articular cartilage contact area estimates were compared with existing contact area estimates in the literature. The method demonstrated an intra-observer reliability of 0.95 when assessed using Pearson's correlation coefficient and was found to be most sensitive to changes in the cartilage tracings on the peripheries of the compartment. The articular cartilage contact area estimates at full extension were similar to those reported in the literature. The relationships between tibiofemoral articular cartilage contact area and knee flexion were also qualitatively and quantitatively similar to those previously reported. The MRI-based knee modeling method was found to have high intra-observer reliability, sensitivity to peripheral articular cartilage tracings, and agreeability with previous investigations when using data from a single healthy adult. Future studies will implement this modeling method to investigate the role that mechanical stress may play in progression of knee OA through estimation of articular cartilage contact area.

  2. The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

    Science.gov (United States)

    Kelly, R. E. J.; Saberi, N.; Li, Q.

    2017-12-01

    With moderate to high spatial resolution (observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides SWE estimates that are independent of real or near real

  3. Bootstrap-Based Inference for Cube Root Consistent Estimators

    DEFF Research Database (Denmark)

    Cattaneo, Matias D.; Jansson, Michael; Nagasawa, Kenichi

    This note proposes a consistent bootstrap-based distributional approximation for cube root consistent estimators such as the maximum score estimator of Manski (1975) and the isotonic density estimator of Grenander (1956). In both cases, the standard nonparametric bootstrap is known...... to be inconsistent. Our method restores consistency of the nonparametric bootstrap by altering the shape of the criterion function defining the estimator whose distribution we seek to approximate. This modification leads to a generic and easy-to-implement resampling method for inference that is conceptually distinct...... from other available distributional approximations based on some form of modified bootstrap. We offer simulation evidence showcasing the performance of our inference method in finite samples. An extension of our methodology to general M-estimation problems is also discussed....

  4. Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  5. It counts who counts: an experimental evaluation of the importance of observer effects on spotlight count estimates

    DEFF Research Database (Denmark)

    Sunde, Peter; Jessen, Lonnie

    2013-01-01

    observers with respect to their ability to detect and estimate distance to realistic animal silhouettes at different distances. Detection probabilities were higher for observers experienced in spotlighting mammals than for inexperienced observers, higher for observers with a hunting background compared...... with non-hunters and decreased as function of age but were independent of sex or educational background. If observer-specific detection probabilities were applied to real counting routes, point count estimates from inexperienced observers without a hunting background would only be 43 % (95 % CI, 39...

  6. Multichannel Singular Spectrum Analysis in the Estimates of Common Environmental Effects Affecting GPS Observations

    Science.gov (United States)

    Gruszczynska, Marta; Rosat, Severine; Klos, Anna; Gruszczynski, Maciej; Bogusz, Janusz

    2018-03-01

    We described a spatio-temporal analysis of environmental loading models: atmospheric, continental hydrology, and non-tidal ocean changes, based on multichannel singular spectrum analysis (MSSA). We extracted the common annual signal for 16 different sections related to climate zones: equatorial, arid, warm, snow, polar and continents. We used the loading models estimated for a set of 229 ITRF2014 (International Terrestrial Reference Frame) International GNSS Service (IGS) stations and discussed the amount of variance explained by individual modes, proving that the common annual signal accounts for 16, 24 and 68% of the total variance of non-tidal ocean, atmospheric and hydrological loading models, respectively. Having removed the common environmental MSSA seasonal curve from the corresponding GPS position time series, we found that the residual station-specific annual curve modelled with the least-squares estimation has the amplitude of maximum 2 mm. This means that the environmental loading models underestimate the seasonalities observed by the GPS system. The remaining signal present in the seasonal frequency band arises from the systematic errors which are not of common environmental or geophysical origin. Using common mode error (CME) estimates, we showed that the direct removal of environmental loading models from the GPS series causes an artificial loss in the CME power spectra between 10 and 80 cycles per year. When environmental effect is removed from GPS series with MSSA curves, no influence on the character of spectra of CME estimates was noticed.

  7. Limited information estimation of the diffusion-based item response theory model for responses and response times.

    Science.gov (United States)

    Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten

    2016-05-01

    Psychological tests are usually analysed with item response models. Recently, some alternative measurement models have been proposed that were derived from cognitive process models developed in experimental psychology. These models consider the responses but also the response times of the test takers. Two such models are the Q-diffusion model and the D-diffusion model. Both models can be calibrated with the diffIRT package of the R statistical environment via marginal maximum likelihood (MML) estimation. In this manuscript, an alternative approach to model calibration is proposed. The approach is based on weighted least squares estimation and parallels the standard estimation approach in structural equation modelling. Estimates are determined by minimizing the discrepancy between the observed and the implied covariance matrix. The estimator is simple to implement, consistent, and asymptotically normally distributed. Least squares estimation also provides a test of model fit by comparing the observed and implied covariance matrix. The estimator and the test of model fit are evaluated in a simulation study. Although parameter recovery is good, the estimator is less efficient than the MML estimator. © 2016 The British Psychological Society.

  8. Observation of top quark pair production and estimation of W+jets background with ATLAS at the LHC

    CERN Document Server

    Radics, Bálint

    An analysis has been presented based on an integrated luminosity of 2.9 pb-1 of 7 TeV center-of-mass energy proton-proton collision data in ATLAS at the Large Hadron Collider. The data have been collected since March until September of 2010. Clear signals from W+ jets and Z+ jets events have been seen. The aim of the analysis is to observe top quark pair production in the collision data. Two analysis approaches have been used independently and yielded consistent result. The first approach allowed more multijet background in the data in order to estimate its rate reliably. The other approach introduced a discriminator selection to suppress the multijet background. The dominant background contributions in the signal region are W+jets and multijet production processes. The rates of these backgrounds in the signal region have been estimated with data-driven methods using signal-free, sideband regions as auxiliary measurements. The use of Monte Carlo simulation based normalizations were minimized as much as possib...

  9. Instantaneous Attitude Determination Based on Original Multi-antenna Observations Using Adaptively Robust Kalman Filtering

    Directory of Open Access Journals (Sweden)

    GAN Yu

    2015-09-01

    Full Text Available Attitude determination directly by carrier phase observation makes optimal use of observation and attitude constraints. The phase models based on misalignment angle and multiplicative quaternion error are derived. The state models for attitude estimation with and without external angular rate sensors are both erected. The attitude errors are estimated by adaptively robust filtering, in which the adaptive factors of ambiguity and attitude error are decided respectively following the idea of multi adaptive factor filtering. The factor of attitude is determined by a three-section function containing Ratio. Adaptively robust filtering makes the best use of constraint and historical information, fusing them in the calculation of float solution. As the accuracy of float solution and the structure of covariance matrix are improved greatly, the fix solution can be searched efficiently using LAMBDA (least-squares ambiguity decorrelation adjustment method merely, perfectly fulfilling the real-time requirement. Field test of a ship-based three-antenna attitude system is used to validate the proposed method. It is showed that direct attitude determination based on adaptively robust filtering has obvious advantages in efficiency and reliability.

  10. Statistical inference based on latent ability estimates

    NARCIS (Netherlands)

    Hoijtink, H.J.A.; Boomsma, A.

    The quality of approximations to first and second order moments (e.g., statistics like means, variances, regression coefficients) based on latent ability estimates is being discussed. The ability estimates are obtained using either the Rasch, oi the two-parameter logistic model. Straightforward use

  11. Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications

    Science.gov (United States)

    Qian, Xuewen; Deng, Honggui; He, Hailang

    2017-10-01

    Due to wide modulation bandwidth in optical communication, multipath channels may be non-sparse and deteriorate communication performance heavily. Traditional compressive sensing-based channel estimation algorithm cannot be employed in this kind of situation. In this paper, we propose a practical parametric channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based visual light communication (VLC) systems based on modified zero correlation code (ZCC) pair that has the impulse-like correlation property. Simulation results show that the proposed algorithm achieves better performances than existing least squares (LS)-based algorithm in both bit error ratio (BER) and frequency response estimation.

  12. Subspace Based Blind Sparse Channel Estimation

    DEFF Research Database (Denmark)

    Hayashi, Kazunori; Matsushima, Hiroki; Sakai, Hideaki

    2012-01-01

    The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by replacing the 2–norm minimization in the conventional subspace based method by the 1–norm minimization problem. Numerical results confirm that the proposed method can significantly improve...

  13. Fast LCMV-based Methods for Fundamental Frequency Estimation

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Glentis, George-Othon; Christensen, Mads Græsbøll

    2013-01-01

    peaks and require matrix inversions for each point in the search grid. In this paper, we therefore consider fast implementations of LCMV-based fundamental frequency estimators, exploiting the estimators' inherently low displacement rank of the used Toeplitz-like data covariance matrices, using...... with several orders of magnitude, but, as we show, further computational savings can be obtained by the adoption of an approximative IAA-based data covariance matrix estimator, reminiscent of the recently proposed Quasi-Newton IAA technique. Furthermore, it is shown how the considered pitch estimators can...... as such either the classic time domain averaging covariance matrix estimator, or, if aiming for an increased spectral resolution, the covariance matrix resulting from the application of the recent iterative adaptive approach (IAA). The proposed exact implementations reduce the required computational complexity...

  14. A Kalman-based Fundamental Frequency Estimation Algorithm

    DEFF Research Database (Denmark)

    Shi, Liming; Nielsen, Jesper Kjær; Jensen, Jesper Rindom

    2017-01-01

    Fundamental frequency estimation is an important task in speech and audio analysis. Harmonic model-based methods typically have superior estimation accuracy. However, such methods usually as- sume that the fundamental frequency and amplitudes are station- ary over a short time frame. In this pape...

  15. Estimating radar reflectivity - snowfall rate relationships and their uncertainties over Antarctica by combining disdrometer and radar observations

    Science.gov (United States)

    Souverijns, Niels; Gossart, Alexandra; Lhermitte, Stef; Gorodetskaya, Irina; Kneifel, Stefan; Maahn, Maximilian; Bliven, Francis; van Lipzig, Nicole

    2017-04-01

    The Antarctic Ice Sheet (AIS) is the largest ice body on earth, having a volume equivalent to 58.3 m global mean sea level rise. Precipitation is the dominant source term in the surface mass balance of the AIS. However, this quantity is not well constrained in both models and observations. Direct observations over the AIS are also not coherent, as they are sparse in space and time and acquisition techniques differ. As a result, precipitation observations stay mostly limited to continent-wide averages based on satellite radar observations. Snowfall rate (SR) at high temporal resolution can be derived from the ground-based radar effective reflectivity factor (Z) using information about snow particle size and shape. Here we present reflectivity snowfall rate relations (Z = aSRb) for the East Antarctic escarpment region using the measurements at the Princess Elisabeth (PE) station and an overview of their uncertainties. A novel technique is developed by combining an optical disdrometer (NASA's Precipitation Imaging Package; PIP) and a vertically pointing 24 GHz FMCW micro rain radar (Metek's MRR) in order to reduce the uncertainty in SR estimates. PIP is used to obtain information about snow particle characteristics and to get an estimate of Z, SR and the Z-SR relation. For PE, located 173 km inland, the relation equals Z = 18SR1.1. The prefactor (a) of the relation is sensitive to the median diameter of the particles. Larger particles, found closer to the coast, lead to an increase of the value of the prefactor. More inland locations, where smaller snow particles are found, obtain lower values for the prefactor. The exponent of the Z-SR relation (b) is insensitive to the median diameter of the snow particles. This dependence of the prefactor of the Z-SR relation to the particle size needs to be taken into account when converting radar reflectivities to snowfall rates over Antarctica. The uncertainty on the Z-SR relations is quantified using a bootstrapping approach

  16. Electric Drive Control with Rotor Resistance and Rotor Speed Observers Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    C. Ben Regaya

    2014-01-01

    Full Text Available Many scientific researchers have proposed the control of the induction motor without speed sensor. These methods have the disadvantage that the variation of the rotor resistance causes an error of estimating the motor speed. Thus, simultaneous estimation of the rotor resistance and the motor speed is required. In this paper, a scheme for estimating simultaneously the rotor resistance and the rotor speed of an induction motor using fuzzy logic has been developed. We present a method which is based on two adaptive observers using fuzzy logic without affecting each other and a simple algorithm in order to facilitate the determination of the optimal values of the controller gains. The control algorithm is proved by the simulation tests. The results analysis shows the characteristic robustness of the two observers of the proposed method even in the case of variation of the rotor resistance.

  17. On Drift Parameter Estimation in Models with Fractional Brownian Motion by Discrete Observations

    Directory of Open Access Journals (Sweden)

    Yuliya Mishura

    2014-06-01

    Full Text Available We study a problem of an unknown drift parameter estimation in a stochastic differen- tial equation driven by fractional Brownian motion. We represent the likelihood ratio as a function of the observable process. The form of this representation is in general rather complicated. However, in the simplest case it can be simplified and we can discretize it to establish the a. s. convergence of the discretized version of maximum likelihood estimator to the true value of parameter. We also investigate a non-standard estimator of the drift parameter showing further its strong consistency. 

  18. A new approach to estimate ice dynamic rates using satellite observations in East Antarctica

    Directory of Open Access Journals (Sweden)

    B. Kallenberg

    2017-05-01

    Full Text Available Mass balance changes of the Antarctic ice sheet are of significant interest due to its sensitivity to climatic changes and its contribution to changes in global sea level. While regional climate models successfully estimate mass input due to snowfall, it remains difficult to estimate the amount of mass loss due to ice dynamic processes. It has often been assumed that changes in ice dynamic rates only need to be considered when assessing long-term ice sheet mass balance; however, 2 decades of satellite altimetry observations reveal that the Antarctic ice sheet changes unexpectedly and much more dynamically than previously expected. Despite available estimates on ice dynamic rates obtained from radar altimetry, information about ice sheet changes due to changes in the ice dynamics are still limited, especially in East Antarctica. Without understanding ice dynamic rates, it is not possible to properly assess changes in ice sheet mass balance and surface elevation or to develop ice sheet models. In this study we investigate the possibility of estimating ice sheet changes due to ice dynamic rates by removing modelled rates of surface mass balance, firn compaction, and bedrock uplift from satellite altimetry and gravity observations. With similar rates of ice discharge acquired from two different satellite missions we show that it is possible to obtain an approximation of the rate of change due to ice dynamics by combining altimetry and gravity observations. Thus, surface elevation changes due to surface mass balance, firn compaction, and ice dynamic rates can be modelled and correlated with observed elevation changes from satellite altimetry.

  19. Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

    Science.gov (United States)

    Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

    2017-12-01

    Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

  20. Estimation of vegetation photosynthetic capacity from space-based measurements of chlorophyll fluorescence for terrestrial biosphere models.

    Science.gov (United States)

    Zhang, Yongguang; Guanter, Luis; Berry, Joseph A; Joiner, Joanna; van der Tol, Christiaan; Huete, Alfredo; Gitelson, Anatoly; Voigt, Maximilian; Köhler, Philipp

    2014-12-01

    Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (Vcmax ) is a key control parameter of photosynthetic capacity. Even though Vcmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space-borne measurements of sun-induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top-of-canopy SIF measurements from space are sensitive to Vcmax at the ecosystem level, and present an approach to invert Vcmax from SIF data. We use the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal Vcmax and SIF which are used to solve the inverse problem. We evaluate our Vcmax estimation method at six agricultural flux tower sites in the midwestern US using spaced-based SIF retrievals. Our Vcmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101 μmol m(-2)  s(-1) , respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying Vcmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed Vcmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time-resolved Vcmax estimates from SIF are used, with R(2) for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of

  1. Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

    Science.gov (United States)

    Poon, P.; Kinoshita, A. M.

    2017-12-01

    Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

  2. Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

    Science.gov (United States)

    Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

    Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

  3. Co-estimation of state-of-charge, capacity and resistance for lithium-ion batteries based on a high-fidelity electrochemical model

    International Nuclear Information System (INIS)

    Zheng, Linfeng; Zhang, Lei; Zhu, Jianguo; Wang, Guoxiu; Jiang, Jiuchun

    2016-01-01

    Highlights: • The numerical solution for an electrochemical model is presented. • Trinal PI observers are used to concurrently estimate SOC, capacity and resistance. • An iteration-approaching method is incorporated to enhance estimation performance. • The robustness against aging and temperature variations is experimentally verified. - Abstract: Lithium-ion batteries have been widely used as enabling energy storage in many industrial fields. Accurate modeling and state estimation play fundamental roles in ensuring safe, reliable and efficient operation of lithium-ion battery systems. A physics-based electrochemical model (EM) is highly desirable for its inherent ability to push batteries to operate at their physical limits. For state-of-charge (SOC) estimation, the continuous capacity fade and resistance deterioration are more prone to erroneous estimation results. In this paper, trinal proportional-integral (PI) observers with a reduced physics-based EM are proposed to simultaneously estimate SOC, capacity and resistance for lithium-ion batteries. Firstly, a numerical solution for the employed model is derived. PI observers are then developed to realize the co-estimation of battery SOC, capacity and resistance. The moving-window ampere-hour counting technique and the iteration-approaching method are also incorporated for the estimation accuracy improvement. The robustness of the proposed approach against erroneous initial values, different battery cell aging levels and ambient temperatures is systematically evaluated, and the experimental results verify the effectiveness of the proposed method.

  4. Facial Asymmetry-Based Age Group Estimation: Role in Recognizing Age-Separated Face Images.

    Science.gov (United States)

    Sajid, Muhammad; Taj, Imtiaz Ahmad; Bajwa, Usama Ijaz; Ratyal, Naeem Iqbal

    2018-04-23

    Face recognition aims to establish the identity of a person based on facial characteristics. On the other hand, age group estimation is the automatic calculation of an individual's age range based on facial features. Recognizing age-separated face images is still a challenging research problem due to complex aging processes involving different types of facial tissues, skin, fat, muscles, and bones. Certain holistic and local facial features are used to recognize age-separated face images. However, most of the existing methods recognize face images without incorporating the knowledge learned from age group estimation. In this paper, we propose an age-assisted face recognition approach to handle aging variations. Inspired by the observation that facial asymmetry is an age-dependent intrinsic facial feature, we first use asymmetric facial dimensions to estimate the age group of a given face image. Deeply learned asymmetric facial features are then extracted for face recognition using a deep convolutional neural network (dCNN). Finally, we integrate the knowledge learned from the age group estimation into the face recognition algorithm using the same dCNN. This integration results in a significant improvement in the overall performance compared to using the face recognition algorithm alone. The experimental results on two large facial aging datasets, the MORPH and FERET sets, show that the proposed age group estimation based on the face recognition approach yields superior performance compared to some existing state-of-the-art methods. © 2018 American Academy of Forensic Sciences.

  5. Remaining useful life estimation based on discriminating shapelet extraction

    International Nuclear Information System (INIS)

    Malinowski, Simon; Chebel-Morello, Brigitte; Zerhouni, Noureddine

    2015-01-01

    In the Prognostics and Health Management domain, estimating the remaining useful life (RUL) of critical machinery is a challenging task. Various research topics including data acquisition, fusion, diagnostics and prognostics are involved in this domain. This paper presents an approach, based on shapelet extraction, to estimate the RUL of equipment. This approach extracts, in an offline step, discriminative rul-shapelets from an history of run-to-failure data. These rul-shapelets are patterns that are selected for their correlation with the remaining useful life of the equipment. In other words, every selected rul-shapelet conveys its own information about the RUL of the equipment. In an online step, these rul-shapelets are compared to testing units and the ones that match these units are used to estimate their RULs. Therefore, RUL estimation is based on patterns that have been selected for their high correlation with the RUL. This approach is different from classical similarity-based approaches that attempt to match complete testing units (or only late instants of testing units) with training ones to estimate the RUL. The performance of our approach is evaluated on a case study on the remaining useful life estimation of turbofan engines and performance is compared with other similarity-based approaches. - Highlights: • A data-driven RUL estimation technique based on pattern extraction is proposed. • Patterns are extracted for their correlation with the RUL. • The proposed method shows good performance compared to other techniques

  6. Intra- and inter-observer reproducibility study of gestational age estimation using three common foetal biometric parameters: Experienced versus inexperienced sonographer

    International Nuclear Information System (INIS)

    Ohagwu, C.C.; Onoduagu, H.I.; Eze, C.U.; Ochie, K.; Ohagwu, C.I.

    2015-01-01

    Aim: To assess reproducibility of estimating gestational age (GA) of foetus using femur length (FL), biparietal diameter (BPD) and abdominal circumference (AC) within experienced and inexperienced sonographers and between the two. Patients and methods: Two sets of GA estimates each were obtained for FL, BPD and AC by the two observers in 20 normal singleton foetuses. The first estimates for the three biometric parameters were made by the experienced sonographer. Subsequently, the inexperienced sonographer, blind to the estimates of the first observer obtained his own estimates for the same biometric parameters. After a time interval of ten minutes the process was repeated for the second set of GA estimates. All the gestational age estimates were made following standard protocol. Statistical analysis was performed by Pearson's and intraclass correlations, coefficient of variation and Bland–Altman plots. Statistical inferences were drawn at p < 0.05. Results: The Pearson's and intraclass correlations of between GA estimates within and between both observers from measurement of FL, BPD and AC were very high and statistically significant (p < 0.05). Coefficient of variation for duplicate measurements for GA estimates within observers and between observers were quite negligible. Between observers, the first and second GA estimates from FL measurements showed the least variation. Estimates from BPD and AC measurements showed greater degree of variation between the observers. Conclusion: Reproducibility of GA estimation using FL, BPD and AC within experienced and inexperienced sonographers and between the two was excellent. Therefore, a fresh Nigerian radiography graduate with adequate exposure in obstetric ultrasound can correctly determine the gestational age of foetus in routine obstetric ultrasound without supervision

  7. Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

    Science.gov (United States)

    Lubey, D.; Scheeres, D.

    Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal

  8. Estimation of CO2 flux from targeted satellite observations: a Bayesian approach

    International Nuclear Information System (INIS)

    Cox, Graham

    2014-01-01

    We consider the estimation of carbon dioxide flux at the ocean–atmosphere interface, given weighted averages of the mixing ratio in a vertical atmospheric column. In particular we examine the dependence of the posterior covariance on the weighting function used in taking observations, motivated by the fact that this function is instrument-dependent, hence one needs the ability to compare different weights. The estimation problem is considered using a variational data assimilation method, which is shown to admit an equivalent infinite-dimensional Bayesian formulation. The main tool in our investigation is an explicit formula for the posterior covariance in terms of the prior covariance and observation operator. Using this formula, we compare weighting functions concentrated near the surface of the earth with those concentrated near the top of the atmosphere, in terms of the resulting covariance operators. We also consider the problem of observational targeting, and ask if it is possible to reduce the covariance in a prescribed direction through an appropriate choice of weighting function. We find that this is not the case—there exist directions in which one can never gain information, regardless of the choice of weight. (paper)

  9. Estimating time-based instantaneous total mortality rate based on the age-structured abundance index

    Science.gov (United States)

    Wang, Yingbin; Jiao, Yan

    2015-05-01

    The instantaneous total mortality rate ( Z) of a fish population is one of the important parameters in fisheries stock assessment. The estimation of Z is crucial to fish population dynamics analysis, abundance and catch forecast, and fisheries management. A catch curve-based method for estimating time-based Z and its change trend from catch per unit effort (CPUE) data of multiple cohorts is developed. Unlike the traditional catch-curve method, the method developed here does not need the assumption of constant Z throughout the time, but the Z values in n continuous years are assumed constant, and then the Z values in different n continuous years are estimated using the age-based CPUE data within these years. The results of the simulation analyses show that the trends of the estimated time-based Z are consistent with the trends of the true Z, and the estimated rates of change from this approach are close to the true change rates (the relative differences between the change rates of the estimated Z and the true Z are smaller than 10%). Variations of both Z and recruitment can affect the estimates of Z value and the trend of Z. The most appropriate value of n can be different given the effects of different factors. Therefore, the appropriate value of n for different fisheries should be determined through a simulation analysis as we demonstrated in this study. Further analyses suggested that selectivity and age estimation are also two factors that can affect the estimated Z values if there is error in either of them, but the estimated change rates of Z are still close to the true change rates. We also applied this approach to the Atlantic cod ( Gadus morhua) fishery of eastern Newfoundland and Labrador from 1983 to 1997, and obtained reasonable estimates of time-based Z.

  10. Estimating Soil and Vegetation Parameters using Synergies between Optical and Microwave Observations

    Science.gov (United States)

    Timmermans, J.; Gomez-Dans, J. L.; Lewis, P.; Loew, A.; Schlenz, F.; Mathieu, P. P.; Pounder, N. L.; Styles, J.

    2017-12-01

    The large amount of remote sensing data available provides a huge potential for various applications, such as crop monitoring. This potential has not been realized yet because inversion-algorithms mostly use a single sensor approach. Consequently, products that combine different low-level observations from different sensors are hard to find. The difficulty in a multi-sensor approach is that 1) different sensor types (microwave/ optical) require different radiative transfer (RT) models and 2) it require consistency between the models. The goal of this research was to investigate the synergistic potential of integrating optical (Opt) and passive microwave (PM) RT models within the Earth Observation Land Data Assimilation System (EOLDAS). EOLDAS uses a Bayesian data assimilation approach together with observation operators such as PROSAIL to estimate state variables. In order to use PM observations, the Community Microwave Emission Model was integrated into the system. Results show a high potential when both Opt and PM observations are used independently. Using only RapidEye only with SAIL RT model, LAI was estimated with R=0.68, with leaf water content and dry matter having lower correlations |R|<0.4. Results for retrieving soil temperature and leaf area index retrievals using only Elbarra observations were good with respectively R=[0.85, 0.79], and for soil moisture also very good with R=0.73 (focusing on dry-spells of at least 9 days only), and with R=0.89 and R=0.77 for respectively the trend and anomalies. Synergistically using Opt and MW observations also shows good potential. Results show that absolute errors decreased (with RMSE=1.22 and S=0.89), but with lower R=0.59; sparse optical observations only improved part of the temporal domain. This shows that PM observations provide good information for the overall trend of the retrieved LAI due to the regular acquisitions, while Opt observations provides better information of the absolute values of the LAI.

  11. A phase-space approach to atmospheric dynamics based on observational data. Theory and applications

    International Nuclear Information System (INIS)

    Wang Risheng.

    1994-01-01

    This thesis is an attempt to develop systematically a phase-space approach to the atmospheric dynamics based on the theoretical achievement and application experiences in nonlinear time-series analysis. In particular, it is concerned with the derivation of quantities for describing the geometrical structure of the observed dynamics in phase-space (dimension estimation) and the examination of the observed atmospheric fluctuations in the light of phase-space representation. The thesis is, therefore composed of three major parts, i.e. an general survey of the theory of statistical approaches to dynamic systems, the methodology designed for the present study and specific applications with respect to dimension estimation and to a phase-space analysis of the tropical stratospheric quasi-biennial oscillation. (orig./KW)

  12. Radiation dosimetry estimates of [{sup 18}F]-fluoroacetate based on biodistribution data of rats

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Jianping [Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai 200032 (China); Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032 (China); Zhang Yingjian, E-mail: yjzhang111@yahoo.com.cn [Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai 200032 (China); Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032 (China); Xu Junyan; Yang Zhongyi [Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai 200032 (China); Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032 (China)

    2012-01-15

    We estimated the dosimetry of [{sup 18}F]fluoroacetate (FAC) with the method established by MIRD based on biodistribution data of rats. We selected some important organs and computed their residence time, their absorbed doses and effective dose with the (%ID{sub Organ}) {sub human} data using OLINDA/EXM 1.1 program. We observed the highest absorbed doses in the heart wall (0.025 mGy/MBq) and the lowest in skin (0.0079 mGy/MBq). The total mean absorbed doses and the effective doses were 0.011 mGy/MBq and 0.014 mSv/MBq, respectively. A 370-MBq injection of FAC leads to an estimated effective dose of 5.2 mSv. The potential radiation risk associated with FAC/PET imaging is well within the accepted limits. - Highlights: Black-Right-Pointing-Pointer We demonstrate a proper model to estimate the absorbed dose and effective dose of normal human. Black-Right-Pointing-Pointer Dosimetry of [{sup 18}F]-Fluoroacetate was estimated in human based on biodistribution of rats. Black-Right-Pointing-Pointer A 370 MBq injection of [{sup 18}F]-Fluoroacetate leads to an estimated effective dose of 5.2 mSv.

  13. Estimation of the shape parameter of a generalized Pareto distribution based on a transformation to Pareto distributed variables

    OpenAIRE

    van Zyl, J. Martin

    2012-01-01

    Random variables of the generalized Pareto distribution, can be transformed to that of the Pareto distribution. Explicit expressions exist for the maximum likelihood estimators of the parameters of the Pareto distribution. The performance of the estimation of the shape parameter of generalized Pareto distributed using transformed observations, based on the probability weighted method is tested. It was found to improve the performance of the probability weighted estimator and performs good wit...

  14. Semiparametric Gaussian copula models : Geometry and efficient rank-based estimation

    NARCIS (Netherlands)

    Segers, J.; van den Akker, R.; Werker, B.J.M.

    2014-01-01

    We propose, for multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically efficient estimator for the Euclidean copula parameter. This estimator is defined as a one-step update of a rank-based pilot estimator in the direction of

  15. Coastal observing and forecasting system for the German Bight – estimates of hydrophysical states

    Directory of Open Access Journals (Sweden)

    W. Petersen

    2011-09-01

    Full Text Available A coastal observing system for Northern and Arctic Seas (COSYNA aims at construction of a long-term observatory for the German part of the North Sea, elements of which will be deployed as prototype modules in Arctic coastal waters. At present a coastal prediction system deployed in the area of the German Bight integrates near real-time measurements with numerical models in a pre-operational way and provides continuously state estimates and forecasts of coastal ocean state. The measurement suite contributing to the pre-operational set up includes in situ time series from stationary stations, a High-Frequency (HF radar system measuring surface currents, a FerryBox system and remote sensing data from satellites. The forecasting suite includes nested 3-D hydrodynamic models running in a data-assimilation mode, which are forced with up-to-date meteorological forecast data. This paper reviews the present status of the system and its recent upgrades focusing on developments in the field of coastal data assimilation. Model supported data analysis and state estimates are illustrated using HF radar and FerryBox observations as examples. A new method combining radial surface current measurements from a single HF radar with a priori information from a hydrodynamic model is presented, which optimally relates tidal ellipses parameters of the 2-D current field and the M2 phase and magnitude of the radials. The method presents a robust and helpful first step towards the implementation of a more sophisticated assimilation system and demonstrates that even using only radials from one station can substantially benefit state estimates for surface currents. Assimilation of FerryBox data based on an optimal interpolation approach using a Kalman filter with a stationary background covariance matrix derived from a preliminary model run which was validated against remote sensing and in situ data demonstrated the capabilities of the pre-operational system. Data

  16. Robust Non-Chattering Observer Based Sliding Control Concept for Electro-Hydraulic Drives

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

    2013-01-01

    This paper presents an observer-based sliding mode control concept with chattering reduction, generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD's). The proposed control concept requires only common data sheet information and no knowledge on load...... extensive knowledge on system parameters nor advanced control theory. In order to accomplish this task, an integral sliding mode controller designed for the control derivative employing state observation is proposed, based on a generalized reduced order model structure of a VCD with unmatched valve ow......- and cylinder asymmetries. It is shown that limited attention can be given to bounds on parameter estimates, that chattering is reduced and the number of tuning parameters is reduced to the level seen in conventional PID schemes. Furthermore, simulation results demonstrate a high level of robustness when...

  17. Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

    International Nuclear Information System (INIS)

    Barut, Murat

    2010-01-01

    This study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner; thus, it has superiority over the previous EKF schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good.

  18. Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

    Energy Technology Data Exchange (ETDEWEB)

    Barut, Murat, E-mail: muratbarut27@yahoo.co [Nigde University, Department of Electrical and Electronics Engineering, 51245 Nigde (Turkey)

    2010-10-15

    This study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner; thus, it has superiority over the previous EKF schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good.

  19. Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

    Science.gov (United States)

    Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

    2013-09-01

    In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

  20. A novel SURE-based criterion for parametric PSF estimation.

    Science.gov (United States)

    Xue, Feng; Blu, Thierry

    2015-02-01

    We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

  1. Model-based estimation of finite population total in stratified sampling

    African Journals Online (AJOL)

    The work presented in this paper concerns the estimation of finite population total under model – based framework. Nonparametric regression approach as a method of estimating finite population total is explored. The asymptotic properties of the estimators based on nonparametric regression are also developed under ...

  2. Adaptive observer for the joint estimation of parameters and input for a coupled wave PDE and infinite dimensional ODE system

    KAUST Repository

    Belkhatir, Zehor

    2016-08-05

    This paper deals with joint parameters and input estimation for coupled PDE-ODE system. The system consists of a damped wave equation and an infinite dimensional ODE. This model describes the spatiotemporal hemodynamic response in the brain and the objective is to characterize brain regions using functional Magnetic Resonance Imaging (fMRI) data. For this reason, we propose an adaptive estimator and prove the asymptotic convergence of the state, the unknown input and the unknown parameters. The proof is based on a Lyapunov approach combined with a priori identifiability assumptions. The performance of the proposed observer is illustrated through some simulation results.

  3. Comparing three approaches of evapotranspiration estimation in mixed urban vegetation; field-based, remote sensing-based and observational-based methods

    Science.gov (United States)

    Nouri, Hamideh; Glenn, Edward P.; Beecham, Simon; Chavoshi Boroujeni, Sattar; Sutton, Paul; Alaghmand, Sina; Nagler, Pamela L.; Noori, Behnaz

    2016-01-01

    Despite being the driest inhabited continent, Australia has one of the highest per capita water consumptions in the world. In addition, instead of having fit-for-purpose water supplies (using different qualities of water for different applications), highly treated drinking water is used for nearly all of Australia’s urban water supply needs, including landscape irrigation. The water requirement of urban landscapes, and particularly urban parklands, is of growing concern. The estimation of ET and subsequently plant water requirements in urban vegetation needs to consider the heterogeneity of plants, soils, water and climate characteristics. Accurate estimation of evapotranspiration (ET), which is the main component of a plant’s water requirement, in urban parks is highly desirable because this water maintains the health of green infrastructure and this in turn provides essential ecosystem services. This research contributes to a broader effort to establish sustainable irrigation practices within the Adelaide Parklands in Adelaide, South Australia.

  4. Teletactile System Based on Mechanical Properties Estimation

    Directory of Open Access Journals (Sweden)

    Mauro M. Sette

    2011-01-01

    Full Text Available Tactile feedback is a major missing feature in minimally invasive procedures; it is an essential means of diagnosis and orientation during surgical procedures. Previous works have presented a remote palpation feedback system based on the coupling between a pressure sensor and a general haptic interface. Here a new approach is presented based on the direct estimation of the tissue mechanical properties and finally their presentation to the operator by means of a haptic interface. The approach presents different technical difficulties and some solutions are proposed: the implementation of a fast Young’s modulus estimation algorithm, the implementation of a real time finite element model, and finally the implementation of a stiffness estimation approach in order to guarantee the system’s stability. The work is concluded with an experimental evaluation of the whole system.

  5. Design of Model-based Controller with Disturbance Estimation in Steer-by-wire System

    Directory of Open Access Journals (Sweden)

    Jung Sanghun

    2018-01-01

    Full Text Available The steer-by-wire system is a next generation steering control technology that has been actively studied because it has many advantages such as fast response, space efficiency due to removal of redundant mechanical elements, and high connectivity with vehicle chassis control, such as active steering. Steer-by-wire system has disturbance composed of tire friction torque and self-aligning torque. These disturbances vary widely due to the weight or friction coefficient change. Therefore, disturbance compensation logic is strongly required to obtain desired performance. This paper proposes model-based controller with disturbance compensation to achieve the robust control performance. Targeted steer-by-wire system is identified through the experiment and system identification method. Moreover, model-based controller is designed using the identified plant model. Disturbance of targeted steer-by-wire is estimated using disturbance observer(DOB, and compensate the estimated disturbance into control input. Experiment of various scenarios are conducted to validate the robust performance of proposed model-based controller.

  6. A Comparison of Evidence-Based Estimates and Empirical Benchmarks of the Appropriate Rate of Use of Radiation Therapy in Ontario

    International Nuclear Information System (INIS)

    Mackillop, William J.; Kong, Weidong; Brundage, Michael; Hanna, Timothy P.; Zhang-Salomons, Jina; McLaughlin, Pierre-Yves; Tyldesley, Scott

    2015-01-01

    Purpose: Estimates of the appropriate rate of use of radiation therapy (RT) are required for planning and monitoring access to RT. Our objective was to compare estimates of the appropriate rate of use of RT derived from mathematical models, with the rate observed in a population of patients with optimal access to RT. Methods and Materials: The rate of use of RT within 1 year of diagnosis (RT 1Y ) was measured in the 134,541 cases diagnosed in Ontario between November 2009 and October 2011. The lifetime rate of use of RT (RT LIFETIME ) was estimated by the multicohort utilization table method. Poisson regression was used to evaluate potential barriers to access to RT and to identify a benchmark subpopulation with unimpeded access to RT. Rates of use of RT were measured in the benchmark subpopulation and compared with published evidence-based estimates of the appropriate rates. Results: The benchmark rate for RT 1Y , observed under conditions of optimal access, was 33.6% (95% confidence interval [CI], 33.0%-34.1%), and the benchmark for RT LIFETIME was 41.5% (95% CI, 41.2%-42.0%). Benchmarks for RT LIFETIME for 4 of 5 selected sites and for all cancers combined were significantly lower than the corresponding evidence-based estimates. Australian and Canadian evidence-based estimates of RT LIFETIME for 5 selected sites differed widely. RT LIFETIME in the overall population of Ontario was just 7.9% short of the benchmark but 20.9% short of the Australian evidence-based estimate of the appropriate rate. Conclusions: Evidence-based estimates of the appropriate lifetime rate of use of RT may overestimate the need for RT in Ontario

  7. Determining the Uncertainties in Prescribed Burn Emissions Through Comparison of Satellite Estimates to Ground-based Estimates and Air Quality Model Evaluations in Southeastern US

    Science.gov (United States)

    Odman, M. T.; Hu, Y.; Russell, A. G.

    2016-12-01

    Prescribed burning is practiced throughout the US, and most widely in the Southeast, for the purpose of maintaining and improving the ecosystem, and reducing the wildfire risk. However, prescribed burn emissions contribute significantly to the of trace gas and particulate matter loads in the atmosphere. In places where air quality is already stressed by other anthropogenic emissions, prescribed burns can lead to major health and environmental problems. Air quality modeling efforts are under way to assess the impacts of prescribed burn emissions. Operational forecasts of the impacts are also emerging for use in dynamic management of air quality as well as the burns. Unfortunately, large uncertainties exist in the process of estimating prescribed burn emissions and these uncertainties limit the accuracy of the burn impact predictions. Prescribed burn emissions are estimated by using either ground-based information or satellite observations. When there is sufficient local information about the burn area, the types of fuels, their consumption amounts, and the progression of the fire, ground-based estimates are more accurate. In the absence of such information satellites remain as the only reliable source for emission estimation. To determine the level of uncertainty in prescribed burn emissions, we compared estimates derived from a burn permit database and other ground-based information to the estimates by the Biomass Burning Emissions Product derived from a constellation of NOAA and NASA satellites. Using these emissions estimates we conducted simulations with the Community Multiscale Air Quality (CMAQ) model and predicted trace gas and particulate matter concentrations throughout the Southeast for two consecutive burn seasons (2015 and 2016). In this presentation, we will compare model predicted concentrations to measurements at monitoring stations and evaluate if the differences are commensurate with our emission uncertainty estimates. We will also investigate if

  8. Estimating monthly temperature using point based interpolation techniques

    Science.gov (United States)

    Saaban, Azizan; Mah Hashim, Noridayu; Murat, Rusdi Indra Zuhdi

    2013-04-01

    This paper discusses the use of point based interpolation to estimate the value of temperature at an unallocated meteorology stations in Peninsular Malaysia using data of year 2010 collected from the Malaysian Meteorology Department. Two point based interpolation methods which are Inverse Distance Weighted (IDW) and Radial Basis Function (RBF) are considered. The accuracy of the methods is evaluated using Root Mean Square Error (RMSE). The results show that RBF with thin plate spline model is suitable to be used as temperature estimator for the months of January and December, while RBF with multiquadric model is suitable to estimate the temperature for the rest of the months.

  9. Design of Artificial Neural Network-Based pH Estimator

    Directory of Open Access Journals (Sweden)

    Shebel A. Alsabbah

    2010-10-01

    Full Text Available Taking into consideration the cost, size and drawbacks might be found with real hardware instrument for measuring pH values such that the complications of the wiring, installing, calibrating and troubleshooting the system, would make a person look for a cheaper, accurate, and alternative choice to perform the measuring operation, Where’s hereby, a feedforward artificial neural network-based pH estimator has to be proposed. The proposed estimator has been designed with multi- layer perceptrons. One input which is a measured base stream and two outputs represent pH values at strong base and strong/weak acids for a titration process. The created data base has been obtained with consideration of temperature variation. The final numerical results ensure the effectiveness and robustness of the design neural network-based pH estimator.

  10. Biogenic nonmethane hydrocarbon emissions estimated from tethered balloon observations

    Science.gov (United States)

    Davis, K. J.; Lenschow, D. H.; Zimmerman, P. R.

    1994-01-01

    A new technique for estimating surface fluxes of trace gases, the mixed-layer gradient technique, is used to calculate isoprene and terpene emissions from forests. The technique is applied to tethered balloon measurements made over the Amazon forest and a pine-oak forest in Alabama at altitudes up to 300 m. The observations were made during the dry season Amazon Boundary Layer Experiment (ABLE 2A) and the Rural Oxidants in the Southern Environment 1990 experiment (ROSE I). Results from large eddy simulations of scalar transport in the clear convective boundary layer are used to infer fluxes from the balloon profiles. Profiles from the Amazon give a mean daytime emission of 3630 +/- 1400 micrograms isoprene sq m/h, where the uncertainty represents the standard deviation of the mean of eight flux estimates. Twenty profiles from Alabama give emissions of 4470 +/- 3300 micrograms isoprene sq m/h, 1740 +/- 1060 micrograms alpha-pinene sq m/h, and 790 +/- 560 micrograms beta-pinene sq m/h, respectively. These results are in agreement with emissions derived from chemical budgets. The emissions may be overestimated because of uncertainty about how to incorporate the effects of the canopy on the mixed-layer gradients. The large variability in these emission estimates is probably due to the relatively short sampling times of the balloon profiles, though spatially heterogeneous emissions may also play a role. Fluxes derived using this technique are representative of an upwind footprint of several kilometers and are independent of hydrocarbon oxidation rate and mean advection.

  11. Earth Observation-Based Operational Estimation of Soil Moisture and Evapotranspiration for Agricultural Crops in Support of Sustainable Water Management

    Directory of Open Access Journals (Sweden)

    George P. Petropoulos

    2018-01-01

    Full Text Available Global information on the spatio-temporal variation of parameters driving the Earth’s terrestrial water and energy cycles, such as evapotranspiration (ET rates and surface soil moisture (SSM, is of key significance. The water and energy cycles underpin global food and water security and need to be fully understood as the climate changes. In the last few decades, Earth Observation (EO technology has played an increasingly important role in determining both ET and SSM. This paper reviews the state of the art in the use specifically of operational EO of both ET and SSM estimates. We discuss the key technical and operational considerations to derive accurate estimates of those parameters from space. The review suggests significant progress has been made in the recent years in retrieving ET and SSM operationally; yet, further work is required to optimize parameter accuracy and to improve the operational capability of services developed using EO data. Emerging applications on which ET/SSM operational products may be included in the context specifically in relation to agriculture are also highlighted; the operational use of those operational products in such applications remains to be seen.

  12. Estimating Surface Downward Shortwave Radiation over China Based on the Gradient Boosting Decision Tree Method

    Directory of Open Access Journals (Sweden)

    Lu Yang

    2018-01-01

    Full Text Available Downward shortwave radiation (DSR is an essential parameter in the terrestrial radiation budget and a necessary input for models of land-surface processes. Although several radiation products using satellite observations have been released, coarse spatial resolution and low accuracy limited their application. It is important to develop robust and accurate retrieval methods with higher spatial resolution. Machine learning methods may be powerful candidates for estimating the DSR from remotely sensed data because of their ability to perform adaptive, nonlinear data fitting. In this study, the gradient boosting regression tree (GBRT was employed to retrieve DSR measurements with the ground observation data in China collected from the China Meteorological Administration (CMA Meteorological Information Center and the satellite observations from the Advanced Very High Resolution Radiometer (AVHRR at a spatial resolution of 5 km. The validation results of the DSR estimates based on the GBRT method in China at a daily time scale for clear sky conditions show an R2 value of 0.82 and a root mean square error (RMSE value of 27.71 W·m−2 (38.38%. These values are 0.64 and 42.97 W·m−2 (34.57%, respectively, for cloudy sky conditions. The monthly DSR estimates were also evaluated using ground measurements. The monthly DSR estimates have an overall R2 value of 0.92 and an RMSE of 15.40 W·m−2 (12.93%. Comparison of the DSR estimates with the reanalyzed and retrieved DSR measurements from satellite observations showed that the estimated DSR is reasonably accurate but has a higher spatial resolution. Moreover, the proposed GBRT method has good scalability and is easy to apply to other parameter inversion problems by changing the parameters and training data.

  13. The estimation of body mass index and physical attractiveness is dependent on the observer's own body mass index.

    Science.gov (United States)

    Tovée, M J; Emery, J L; Cohen-Tovée, E M

    2000-01-01

    A disturbance in the evaluation of personal body mass and shape is a key feature of both anorexia and bulimia nervosa. However, it is uncertain whether overestimation is a causal factor in the development of these eating disorders or is merely a secondary effect of having a low body mass. Moreover, does this overestimation extend to the perception of other people's bodies? Since body mass is an important factor in the perception of physical attractiveness, we wanted to determine whether this putative overestimation of self body mass extended to include the perceived attractiveness of others. We asked 204 female observers (31 anorexic, 30 bulimic and 143 control) to estimate the body mass and rate the attractiveness of a set of 25 photographic images showing people of varying body mass index (BMI). BMI is a measure of weight scaled for height (kg m(- 2)). The observers also estimated their own BMI. Anorexic and bulimic observers systematically overestimated the body mass of both their own and other people's bodies, relative to controls, and they rated a significantly lower body mass to be optimally attractive. When the degree of overestimation is plotted against the BMI of the observer there is a strong correlation. Taken across all our observers, as the BMI of the observer declines, the overestimation of body mass increases. One possible explanation for this result is that the overestimation is a secondary effect caused by weight loss. Moreover, if the degree of body mass overestimation is taken into account, then there are no significant differences in the perceptions of attractiveness between anorexic and bulimic observers and control observers. Our results suggest a significant perceptual overestimation of BMI that is based on the observer's own BMI and not correlated with cognitive factors, and suggests that this overestimation in eating-disordered patients must be addressed directly in treatment regimes. PMID:11075712

  14. Simultaneous Estimation of Model State Variables and Observation and Forecast Biases Using a Two-Stage Hybrid Kalman Filter

    Science.gov (United States)

    Pauwels, V. R. N.; DeLannoy, G. J. M.; Hendricks Franssen, H.-J.; Vereecken, H.

    2013-01-01

    In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.

  15. Simultaneous estimation of model state variables and observation and forecast biases using a two-stage hybrid Kalman filter

    Directory of Open Access Journals (Sweden)

    V. R. N. Pauwels

    2013-09-01

    Full Text Available In this paper, we present a two-stage hybrid Kalman filter to estimate both observation and forecast bias in hydrologic models, in addition to state variables. The biases are estimated using the discrete Kalman filter, and the state variables using the ensemble Kalman filter. A key issue in this multi-component assimilation scheme is the exact partitioning of the difference between observation and forecasts into state, forecast bias and observation bias updates. Here, the error covariances of the forecast bias and the unbiased states are calculated as constant fractions of the biased state error covariance, and the observation bias error covariance is a function of the observation prediction error covariance. In a series of synthetic experiments, focusing on the assimilation of discharge into a rainfall-runoff model, it is shown that both static and dynamic observation and forecast biases can be successfully estimated. The results indicate a strong improvement in the estimation of the state variables and resulting discharge as opposed to the use of a bias-unaware ensemble Kalman filter. Furthermore, minimal code modification in existing data assimilation software is needed to implement the method. The results suggest that a better performance of data assimilation methods should be possible if both forecast and observation biases are taken into account.

  16. Random Decrement Based FRF Estimation

    DEFF Research Database (Denmark)

    Brincker, Rune; Asmussen, J. C.

    to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods...... that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation...

  17. Random Decrement Based FRF Estimation

    DEFF Research Database (Denmark)

    Brincker, Rune; Asmussen, J. C.

    1997-01-01

    to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods...... that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation...

  18. A Minimum Fuel Based Estimator for Maneuver and Natrual Dynamics Reconstruction

    Science.gov (United States)

    Lubey, D.; Scheeres, D.

    2013-09-01

    The vast and growing population of objects in Earth orbit (active and defunct spacecraft, orbital debris, etc.) offers many unique challenges when it comes to tracking these objects and associating the resulting observations. Complicating these challenges are the inaccurate natural dynamical models of these objects, the active maneuvers of spacecraft that deviate them from their ballistic trajectories, and the fact that spacecraft are tracked and operated by separate agencies. Maneuver detection and reconstruction algorithms can help with each of these issues by estimating mismodeled and unmodeled dynamics through indirect observation of spacecraft. It also helps to verify the associations made by an object correlation algorithm or aid in making those associations, which is essential when tracking objects in orbit. The algorithm developed in this study applies an Optimal Control Problem (OCP) Distance Metric approach to the problems of Maneuver Reconstruction and Dynamics Estimation. This was first developed by Holzinger, Scheeres, and Alfriend (2011), with a subsequent study by Singh, Horwood, and Poore (2012). This method estimates the minimum fuel control policy rather than the state as a typical Kalman Filter would. This difference ensures that the states are connected through a given dynamical model and allows for automatic covariance manipulation, which can help to prevent filter saturation. Using a string of measurements (either verified or hypothesized to correlate with one another), the algorithm outputs a corresponding string of adjoint and state estimates with associated noise. Post-processing techniques are implemented, which when applied to the adjoint estimates can remove noise and expose unmodeled maneuvers and mismodeled natural dynamics. Specifically, the estimated controls are used to determine spacecraft dependent accelerations (atmospheric drag and solar radiation pressure) using an adapted form of the Optimal Control based natural dynamics

  19. Optimization of observation plan based on the stochastic characteristics of the geodetic network

    Directory of Open Access Journals (Sweden)

    Pachelski Wojciech

    2016-06-01

    Full Text Available Optimal design of geodetic network is a basic subject of many engineering projects. An observation plan is a concluding part of the process. Any particular observation within the network has through adjustment a different contribution and impact on values and accuracy characteristics of unknowns. The problem of optimal design can be solved by means of computer simulation. This paper presents a new method of simulation based on sequential estimation of individual observations in a step-by-step manner, by means of the so-called filtering equations. The algorithm aims at satisfying different criteria of accuracy according to various interpretations of the covariance matrix. Apart of them, the optimization criterion is also amount of effort, defined as the minimum number of observations required.

  20. Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

    2015-12-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

  1. Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation.

    Science.gov (United States)

    Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin

    2014-03-01

    Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.

  2. Estimation of human core temperature from sequential heart rate observations

    International Nuclear Information System (INIS)

    Buller, Mark J; Tharion, William J; Cheuvront, Samuel N; Montain, Scott J; Kenefick, Robert W; Castellani, John; Latzka, William A; Hoyt, Reed W; Roberts, Warren S; Richter, Mark; Jenkins, Odest Chadwicke

    2013-01-01

    Core temperature (CT) in combination with heart rate (HR) can be a good indicator of impending heat exhaustion for occupations involving exposure to heat, heavy workloads, and wearing protective clothing. However, continuously measuring CT in an ambulatory environment is difficult. To address this problem we developed a model to estimate the time course of CT using a series of HR measurements as a leading indicator using a Kalman filter. The model was trained using data from 17 volunteers engaged in a 24 h military field exercise (air temperatures 24–36 °C, and 42%–97% relative humidity and CTs ranging from 36.0–40.0 °C). Validation data from laboratory and field studies (N = 83) encompassing various combinations of temperature, hydration, clothing, and acclimation state were examined using the Bland–Altman limits of agreement (LoA) method. We found our model had an overall bias of −0.03 ± 0.32 °C and that 95% of all CT estimates fall within ±0.63 °C (>52 000 total observations). While the model for estimating CT is not a replacement for direct measurement of CT (literature comparisons of esophageal and rectal methods average LoAs of ±0.58 °C) our results suggest it is accurate enough to provide practical indication of thermal work strain for use in the work place. (paper)

  3. Estimating misclassification error: a closer look at cross-validation based methods

    Directory of Open Access Journals (Sweden)

    Ounpraseuth Songthip

    2012-11-01

    Full Text Available Abstract Background To estimate a classifier’s error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV methods based on sampling without replacement. Monte Carlo (MC simulation studies aimed at estimating the true misclassification error conditional on the training set are commonly used to compare CV methods. We conducted an MC simulation study to compare a new method of bootstrap CV (BCV to k-fold CV for estimating clasification error. Findings For the low-dimensional conditions simulated, the modest positive bias of k-fold CV contrasted sharply with the substantial negative bias of the new BCV method. This behavior was corroborated using a real-world dataset of prognostic gene-expression profiles in breast cancer patients. Our simulation results demonstrate some extreme characteristics of variance and bias that can occur due to a fault in the design of CV exercises aimed at estimating the true conditional error of a classifier, and that appear not to have been fully appreciated in previous studies. Although CV is a sound practice for estimating a classifier’s generalization error, using CV to estimate the fixed misclassification error of a trained classifier conditional on the training set is problematic. While MC simulation of this estimation exercise can correctly represent the average bias of a classifier, it will overstate the between-run variance of the bias. Conclusions We recommend k-fold CV over the new BCV method for estimating a classifier’s generalization error. The extreme negative bias of BCV is too high a price to pay for its reduced variance.

  4. A Channelization-Based DOA Estimation Method for Wideband Signals

    Directory of Open Access Journals (Sweden)

    Rui Guo

    2016-07-01

    Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.

  5. State Estimation-based Transmission line parameter identification

    Directory of Open Access Journals (Sweden)

    Fredy Andrés Olarte Dussán

    2010-01-01

    Full Text Available This article presents two state-estimation-based algorithms for identifying transmission line parameters. The identification technique used simultaneous state-parameter estimation on an artificial power system composed of several copies of the same transmission line, using measurements at different points in time. The first algorithm used active and reactive power measurements at both ends of the line. The second method used synchronised phasor voltage and current measurements at both ends. The algorithms were tested in simulated conditions on the 30-node IEEE test system. All line parameters for this system were estimated with errors below 1%.

  6. US Air Force Base Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Hourly observations taken by U.S. Air Force personnel at bases in the United States and around the world. Foreign observations concentrated in the Middle East and...

  7. Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

    Science.gov (United States)

    Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.

    2018-02-01

    An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

  8. Investigation of error estimation method of observational data and comparison method between numerical and observational results toward V and V of seismic simulation

    International Nuclear Information System (INIS)

    Suzuki, Yoshio; Kawakami, Yoshiaki; Nakajima, Norihiro

    2017-01-01

    The method to estimate errors included in observational data and the method to compare numerical results with observational results are investigated toward the verification and validation (V and V) of a seismic simulation. For the method to estimate errors, 144 literatures for the past 5 years (from the year 2010 to 2014) in the structure engineering field and earthquake engineering field where the description about acceleration data is frequent are surveyed. As a result, it is found that some processes to remove components regarded as errors from observational data are used in about 30% of those literatures. Errors are caused by the resolution, the linearity, the temperature coefficient for sensitivity, the temperature coefficient for zero shift, the transverse sensitivity, the seismometer property, the aliasing, and so on. Those processes can be exploited to estimate errors individually. For the method to compare numerical results with observational results, public materials of ASME V and V Symposium 2012-2015, their references, and above 144 literatures are surveyed. As a result, it is found that six methods have been mainly proposed in existing researches. Evaluating those methods using nine items, advantages and disadvantages for those methods are arranged. The method is not well established so that it is necessary to employ those methods by compensating disadvantages and/or to search for a solution to a novel method. (author)

  9. Accurate position estimation methods based on electrical impedance tomography measurements

    Science.gov (United States)

    Vergara, Samuel; Sbarbaro, Daniel; Johansen, T. A.

    2017-08-01

    Electrical impedance tomography (EIT) is a technology that estimates the electrical properties of a body or a cross section. Its main advantages are its non-invasiveness, low cost and operation free of radiation. The estimation of the conductivity field leads to low resolution images compared with other technologies, and high computational cost. However, in many applications the target information lies in a low intrinsic dimensionality of the conductivity field. The estimation of this low-dimensional information is addressed in this work. It proposes optimization-based and data-driven approaches for estimating this low-dimensional information. The accuracy of the results obtained with these approaches depends on modelling and experimental conditions. Optimization approaches are sensitive to model discretization, type of cost function and searching algorithms. Data-driven methods are sensitive to the assumed model structure and the data set used for parameter estimation. The system configuration and experimental conditions, such as number of electrodes and signal-to-noise ratio (SNR), also have an impact on the results. In order to illustrate the effects of all these factors, the position estimation of a circular anomaly is addressed. Optimization methods based on weighted error cost functions and derivate-free optimization algorithms provided the best results. Data-driven approaches based on linear models provided, in this case, good estimates, but the use of nonlinear models enhanced the estimation accuracy. The results obtained by optimization-based algorithms were less sensitive to experimental conditions, such as number of electrodes and SNR, than data-driven approaches. Position estimation mean squared errors for simulation and experimental conditions were more than twice for the optimization-based approaches compared with the data-driven ones. The experimental position estimation mean squared error of the data-driven models using a 16-electrode setup was less

  10. Improving cluster-based missing value estimation of DNA microarray data.

    Science.gov (United States)

    Brás, Lígia P; Menezes, José C

    2007-06-01

    We present a modification of the weighted K-nearest neighbours imputation method (KNNimpute) for missing values (MVs) estimation in microarray data based on the reuse of estimated data. The method was called iterative KNN imputation (IKNNimpute) as the estimation is performed iteratively using the recently estimated values. The estimation efficiency of IKNNimpute was assessed under different conditions (data type, fraction and structure of missing data) by the normalized root mean squared error (NRMSE) and the correlation coefficients between estimated and true values, and compared with that of other cluster-based estimation methods (KNNimpute and sequential KNN). We further investigated the influence of imputation on the detection of differentially expressed genes using SAM by examining the differentially expressed genes that are lost after MV estimation. The performance measures give consistent results, indicating that the iterative procedure of IKNNimpute can enhance the prediction ability of cluster-based methods in the presence of high missing rates, in non-time series experiments and in data sets comprising both time series and non-time series data, because the information of the genes having MVs is used more efficiently and the iterative procedure allows refining the MV estimates. More importantly, IKNN has a smaller detrimental effect on the detection of differentially expressed genes.

  11. Parallel Factor-Based Model for Two-Dimensional Direction Estimation

    Directory of Open Access Journals (Sweden)

    Nizar Tayem

    2017-01-01

    Full Text Available Two-dimensional (2D Direction-of-Arrivals (DOA estimation for elevation and azimuth angles assuming noncoherent, mixture of coherent and noncoherent, and coherent sources using extended three parallel uniform linear arrays (ULAs is proposed. Most of the existing schemes have drawbacks in estimating 2D DOA for multiple narrowband incident sources as follows: use of large number of snapshots, estimation failure problem for elevation and azimuth angles in the range of typical mobile communication, and estimation of coherent sources. Moreover, the DOA estimation for multiple sources requires complex pair-matching methods. The algorithm proposed in this paper is based on first-order data matrix to overcome these problems. The main contributions of the proposed method are as follows: (1 it avoids estimation failure problem using a new antenna configuration and estimates elevation and azimuth angles for coherent sources; (2 it reduces the estimation complexity by constructing Toeplitz data matrices, which are based on a single or few snapshots; (3 it derives parallel factor (PARAFAC model to avoid pair-matching problems between multiple sources. Simulation results demonstrate the effectiveness of the proposed algorithm.

  12. Estimation of Thermal Sensation Based on Wrist Skin Temperatures

    Science.gov (United States)

    Sim, Soo Young; Koh, Myung Jun; Joo, Kwang Min; Noh, Seungwoo; Park, Sangyun; Kim, Youn Ho; Park, Kwang Suk

    2016-01-01

    Thermal comfort is an essential environmental factor related to quality of life and work effectiveness. We assessed the feasibility of wrist skin temperature monitoring for estimating subjective thermal sensation. We invented a wrist band that simultaneously monitors skin temperatures from the wrist (i.e., the radial artery and ulnar artery regions, and upper wrist) and the fingertip. Skin temperatures from eight healthy subjects were acquired while thermal sensation varied. To develop a thermal sensation estimation model, the mean skin temperature, temperature gradient, time differential of the temperatures, and average power of frequency band were calculated. A thermal sensation estimation model using temperatures of the fingertip and wrist showed the highest accuracy (mean root mean square error [RMSE]: 1.26 ± 0.31). An estimation model based on the three wrist skin temperatures showed a slightly better result to the model that used a single fingertip skin temperature (mean RMSE: 1.39 ± 0.18). When a personalized thermal sensation estimation model based on three wrist skin temperatures was used, the mean RMSE was 1.06 ± 0.29, and the correlation coefficient was 0.89. Thermal sensation estimation technology based on wrist skin temperatures, and combined with wearable devices may facilitate intelligent control of one’s thermal environment. PMID:27023538

  13. Multimodal Analysis of Estimated and Observed Social Competence in Preschoolers With/Without Behavior Problems

    Directory of Open Access Journals (Sweden)

    Talita Pereira Dias

    2013-05-01

    Full Text Available Social skills compete with behavior problems, and the combination of these aspects may cause differences in social competence. This study was aimed at assessing the differences and similarities in the social competence of 26 preschoolers resulting from: (1 groups which they belonged to, being one with social skills and three with behavior problems (internalizing, externalizing and mixed; (2 types of assessment, considering the estimates of mothers and teachers, as well as direct observation in a structured situation; (3 structured situations as demands for five categories of social skills. Children’s performance in each situation was assessed by judges and estimated by mothers and teachers. There was a similarity in the social competence estimated by mothers, teachers and in the performance observed. Only the teachers distinguished the groups (higher social competence in the group with social skills and lower in the internalizing and mixed groups. Assertiveness demands differentiated the groups. The methodological aspects were discussed, as well as the clinical and educational potential of the structured situations to promote social skills.

  14. Estimating Driving Performance Based on EEG Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Jung Tzyy-Ping

    2005-01-01

    Full Text Available The growing number of traffic accidents in recent years has become a serious concern to society. Accidents caused by driver's drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the driver's abilities of perception, recognition, and vehicle control abilities while sleepy. Preventing such accidents caused by drowsiness is highly desirable but requires techniques for continuously detecting, estimating, and predicting the level of alertness of drivers and delivering effective feedbacks to maintain their maximum performance. This paper proposes an EEG-based drowsiness estimation system that combines electroencephalogram (EEG log subband power spectrum, correlation analysis, principal component analysis, and linear regression models to indirectly estimate driver's drowsiness level in a virtual-reality-based driving simulator. Our results demonstrated that it is feasible to accurately estimate quantitatively driving performance, expressed as deviation between the center of the vehicle and the center of the cruising lane, in a realistic driving simulator.

  15. Estimating Allee dynamics before they can be observed: polar bears as a case study.

    Science.gov (United States)

    Molnár, Péter K; Lewis, Mark A; Derocher, Andrew E

    2014-01-01

    Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum

  16. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    2016-10-01

    The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

  17. Estimation of inhalation flow profile using audio-based methods to assess inhaler medication adherence

    Science.gov (United States)

    Lacalle Muls, Helena; Costello, Richard W.; Reilly, Richard B.

    2018-01-01

    Asthma and chronic obstructive pulmonary disease (COPD) patients are required to inhale forcefully and deeply to receive medication when using a dry powder inhaler (DPI). There is a clinical need to objectively monitor the inhalation flow profile of DPIs in order to remotely monitor patient inhalation technique. Audio-based methods have been previously employed to accurately estimate flow parameters such as the peak inspiratory flow rate of inhalations, however, these methods required multiple calibration inhalation audio recordings. In this study, an audio-based method is presented that accurately estimates inhalation flow profile using only one calibration inhalation audio recording. Twenty healthy participants were asked to perform 15 inhalations through a placebo Ellipta™ DPI at a range of inspiratory flow rates. Inhalation flow signals were recorded using a pneumotachograph spirometer while inhalation audio signals were recorded simultaneously using the Inhaler Compliance Assessment device attached to the inhaler. The acoustic (amplitude) envelope was estimated from each inhalation audio signal. Using only one recording, linear and power law regression models were employed to determine which model best described the relationship between the inhalation acoustic envelope and flow signal. Each model was then employed to estimate the flow signals of the remaining 14 inhalation audio recordings. This process repeated until each of the 15 recordings were employed to calibrate single models while testing on the remaining 14 recordings. It was observed that power law models generated the highest average flow estimation accuracy across all participants (90.89±0.9% for power law models and 76.63±2.38% for linear models). The method also generated sufficient accuracy in estimating inhalation parameters such as peak inspiratory flow rate and inspiratory capacity within the presence of noise. Estimating inhaler inhalation flow profiles using audio based methods may be

  18. Temperature Observation Time and Type Influence Estimates of Heat-Related Mortality in Seven U.S. Cities.

    Science.gov (United States)

    Davis, Robert E; Hondula, David M; Patel, Anjali P

    2016-06-01

    Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat-mortality relationships. We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method. Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series. In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature-mortality relationships were associated with maximum temperature, although mean temperature results were comparable. There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature-mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum

  19. Particle filter based MAP state estimation: A comparison

    NARCIS (Netherlands)

    Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha

    2009-01-01

    MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi

  20. Rate estimation in partially observed Markov jump processes with measurement errors

    OpenAIRE

    Amrein, Michael; Kuensch, Hans R.

    2010-01-01

    We present a simulation methodology for Bayesian estimation of rate parameters in Markov jump processes arising for example in stochastic kinetic models. To handle the problem of missing components and measurement errors in observed data, we embed the Markov jump process into the framework of a general state space model. We do not use diffusion approximations. Markov chain Monte Carlo and particle filter type algorithms are introduced, which allow sampling from the posterior distribution of t...

  1. Evidence-based research: understanding the best estimate

    Directory of Open Access Journals (Sweden)

    Bauer JG

    2016-09-01

    Full Text Available Janet G Bauer,1 Sue S Spackman,2 Robert Fritz,2 Amanjyot K Bains,3 Jeanette Jetton-Rangel3 1Advanced Education Services, 2Division of General Dentistry, 3Center of Dental Research, Loma Linda University School of Dentistry, Loma Linda, CA, USA Introduction: Best estimates of intervention outcomes are used when uncertainties in decision making are evidenced. Best estimates are often, out of necessity, from a context of less than quality evidence or needing more evidence to provide accuracy. Purpose: The purpose of this article is to understand the best estimate behavior, so that clinicians and patients may have confidence in its quantification and validation. Methods: To discover best estimates and quantify uncertainty, critical appraisals of the literature, gray literature and its resources, or both are accomplished. Best estimates of pairwise comparisons are calculated using meta-analytic methods; multiple comparisons use network meta-analysis. Manufacturers provide margins of performance of proprietary material(s. Lower margin performance thresholds or requirements (functional failure of materials are determined by a distribution of tests to quantify performance or clinical competency. The same is done for the high margin performance thresholds (estimated true value of success and clinician-derived critical values (material failure to function clinically. This quantification of margins and uncertainties assists clinicians in determining if reported best estimates are progressing toward true value as new knowledge is reported. Analysis: The best estimate of outcomes focuses on evidence-centered care. In stochastic environments, we are not able to observe all events in all situations to know without uncertainty the best estimates of predictable outcomes. Point-in-time analyses of best estimates using quantification of margins and uncertainties do this. Conclusion: While study design and methodology are variables known to validate the quality of

  2. Application of iterative method with dynamic weight based on observation equation's constant in NPP's surveying

    International Nuclear Information System (INIS)

    Chen Benfu; Guo Xianchun; Zou Zili

    2009-01-01

    It' s useful to identify the data with errors from the large number of observations during the process of adjustment to decrease the influence of the errors and to improve the quality of the final surveying result. Based on practical conditions of the nuclear power plant's plain control network, it has been given on how to simply calculate the threshold value which used to pre-weight each datum before adjustment calculation; it shows some superiorities in efficiency on data snooping and in quality of the final calculation compared with some traditional methods such as robust estimation, which process data with dynamic weight based the observation' s correction after each iteration. (authors)

  3. Estimating the top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data

    Science.gov (United States)

    Minnis, Patrick; Yost, Chris R.; Sun-Mack, Sunny; Chen, Yan

    2008-06-01

    The difference between cloud-top altitude Z top and infrared effective radiating height Z eff for optically thick ice clouds is examined using April 2007 data taken by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and the Moderate-Resolution Imaging Spectroradiometer (MODIS). For even days, the difference ΔZ between CALIPSO Z top and MODIS Z eff is 1.58 +/- 1.26 km. The linear fit between Z top and Z eff , applied to odd-day data, yields a difference of 0.03 +/- 1.21 km and can be used to estimate Z top from any infrared-based Z eff for thick ice clouds. Random errors appear to be due primarily to variations in cloud ice-water content (IWC). Radiative transfer calculations show that ΔZ corresponds to an optical depth of ~1, which based on observed ice-particle sizes yields an average cloud-top IWC of ~0.015 gm-3, a value consistent with in situ measurements. The analysis indicates potential for deriving cloud-top IWC using dual-satellite data.

  4. Estimation of Compaction Parameters Based on Soil Classification

    Science.gov (United States)

    Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.

    2018-02-01

    Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.

  5. Wind estimation around the shipwreck of Oriental Star based on field damage surveys and radar observations

    OpenAIRE

    Meng, Zhiyong; Yao, Dan; Bai, Lanqiang; Zheng, Yongguang; Xue, Ming; Zhang, Xiaoling; Zhao, Kun; Tian, Fuyou; Wang, Mingjun

    2016-01-01

    Based on observational analyses and on-site ground and aerial damage surveys, this work aims to reveal the weather phenomena?especially the wind situation?when Oriental Star capsized in the Yangtze River on June 1, 2015. Results demonstrate that the cruise ship capsized when it encountered strong winds at speeds of at least 31?m?s?1 near the apex of a bow echo embedded in a squall line. As suggested by the fallen trees within a 2-km radius around the wreck location, such strong winds were lik...

  6. [Differences between observed and estimated by hematocrit hemoglobin and its relevance in the diagnosis of anemia among coastal population in Venezuela: analysis of the second national study of human growth and development (SENACREDH)].

    Science.gov (United States)

    Flores-Torres, Jessica; Echeverría-Ortega, María; Arria-Bohorquez, Melissa; Hidalgo, Glida; Albano-Ramos, Carlos; Sanz, Rafael; Rodríguez-Morales, Alfonso J

    2011-03-01

    To evaluate the differences between the observed hemoglobin levels and those estimated based on hematocrit in the context of the 2nd National Study of Human Growth and Development of the Venezuelan Population (SENACREDH). 6,004 individuals were chosen by a probabilistic multistage cluster sampling representing 7,286,781 inhabitants from North Central Coastal area (Vargas, Carabobo, Capital District, Aragua and Miranda). Means of observed and estimated hemoglobin (hematocrit/3) were compared, using t test for related samples and linear regression. Mean difference between the values of observed and estimated hemoglobin was -0.3446 ±0.0002 (phemoglobin values. Regression models of hemoglobin on hematocrit showed an r2=0,87. In order to correct the estimation, we propose a new formula for calculating hemoglobin based on haematocrit values: estimated hemoglobin=(Haematocrit/3.135)+ 0.257. There is an overestimation of hemoglobin levels from hematocrit levels and therefore an underestimation of the prevalence of anemia; however, a high positive correlation between them was found, allowing modeling for achieving a better estimation of the hemoglobin from the hematocrit value.

  7. Estimating the parameters of stochastic differential equations using a criterion function based on the Kolmogorov-Smirnov statistic

    OpenAIRE

    McDonald, A. David; Sandal, Leif Kristoffer

    1998-01-01

    Estimation of parameters in the drift and diffusion terms of stochastic differential equations involves simulation and generally requires substantial data sets. We examine a method that can be applied when available time series are limited to less than 20 observations per replication. We compare and contrast parameter estimation for linear and nonlinear first-order stochastic differential equations using two criterion functions: one based on a Chi-square statistic, put forward by Hurn and Lin...

  8. A survey on OFDM channel estimation techniques based on denoising strategies

    Directory of Open Access Journals (Sweden)

    Pallaviram Sure

    2017-04-01

    Full Text Available Channel estimation forms the heart of any orthogonal frequency division multiplexing (OFDM based wireless communication receiver. Frequency domain pilot aided channel estimation techniques are either least squares (LS based or minimum mean square error (MMSE based. LS based techniques are computationally less complex. Unlike MMSE ones, they do not require a priori knowledge of channel statistics (KCS. However, the mean square error (MSE performance of the channel estimator incorporating MMSE based techniques is better compared to that obtained with the incorporation of LS based techniques. To enhance the MSE performance using LS based techniques, a variety of denoising strategies have been developed in the literature, which are applied on the LS estimated channel impulse response (CIR. The advantage of denoising threshold based LS techniques is that, they do not require KCS but still render near optimal MMSE performance similar to MMSE based techniques. In this paper, a detailed survey on various existing denoising strategies, with a comparative discussion of these strategies is presented.

  9. The estimation of soil parameters using observations on crop biophysical variables and the crop model STICS improve the predictions of agro environmental variables.

    Science.gov (United States)

    Varella, H.-V.

    2009-04-01

    Dynamic crop models are very useful to predict the behavior of crops in their environment and are widely used in a lot of agro-environmental work. These models have many parameters and their spatial application require a good knowledge of these parameters, especially of the soil parameters. These parameters can be estimated from soil analysis at different points but this is very costly and requires a lot of experimental work. Nevertheless, observations on crops provided by new techniques like remote sensing or yield monitoring, is a possibility for estimating soil parameters through the inversion of crop models. In this work, the STICS crop model is studied for the wheat and the sugar beet and it includes more than 200 parameters. After a previous work based on a large experimental database for calibrate parameters related to the characteristics of the crop, a global sensitivity analysis of the observed variables (leaf area index LAI and absorbed nitrogen QN provided by remote sensing data, and yield at harvest provided by yield monitoring) to the soil parameters is made, in order to determine which of them have to be estimated. This study was made in different climatic and agronomic conditions and it reveals that 7 soil parameters (4 related to the water and 3 related to the nitrogen) have a clearly influence on the variance of the observed variables and have to be therefore estimated. For estimating these 7 soil parameters, a Bayesian data assimilation method is chosen (because of available prior information on these parameters) named Importance Sampling by using observations, on wheat and sugar beet crop, of LAI and QN at various dates and yield at harvest acquired on different climatic and agronomic conditions. The quality of parameter estimation is then determined by comparing the result of parameter estimation with only prior information and the result with the posterior information provided by the Bayesian data assimilation method. The result of the

  10. Estimating a Global Hydrological Carrying Capacity Using GRACE Observed Water Stress

    Science.gov (United States)

    An, K.; Reager, J. T.; Famiglietti, J. S.

    2013-12-01

    Global population is expected to reach 9 billion people by the year 2050, causing increased demands for water and potential threats to human security. This study attempts to frame the overpopulation problem through a hydrological resources lens by hypothesizing that observed groundwater trends should be directly attributed to human water consumption. This study analyzes the relationships between available blue water, population, and cropland area on a global scale. Using satellite data from NASA's Gravity Recovery and Climate Experiment (GRACE) along with land surface model data from the Global Land Data Assimilation System (GLDAS), a global groundwater depletion trend is isolated, the validity of which has been verified in many regional studies. By using the inherent distributions of these relationships, we estimate the regional populations that have exceeded their local hydrological carrying capacity. Globally, these populations sum to ~3.5 billion people that are living in presently water-stressed or potentially water-scarce regions, and we estimate total cropland is exceeding a sustainable threshold by about 80 million km^2. Key study areas such as the North China Plain, northwest India, and Mexico City were qualitatively chosen for further analysis of regional water resources and policies, based on our distributions of water stress. These case studies are used to verify the groundwater level changes seen in the GRACE trend . Tfor the many populous, arid regions of the world that have already begun to experience the strains of high water demand.he many populous, arid regions of the world have already begun to experience the strains of high water demand. It will take a global cooperative effort of improving domestic and agricultural use efficiency, and summoning a political will to prioritize environmental issues to adapt to a thirstier planet. Global Groundwater Depletion Trend (Mar 2003-Dec 2011)

  11. vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

    Directory of Open Access Journals (Sweden)

    Demeter Lisa

    2010-05-01

    Full Text Available Abstract Background The replication rate (or fitness between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV. HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Results Based on a mathematical model and several statistical methods (least-squares approach and measurement error models, a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1. Conclusions Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at http://bis.urmc.rochester.edu/vFitness/.

  12. Estimation of human core temperature from sequential heart rate observations.

    Science.gov (United States)

    Buller, Mark J; Tharion, William J; Cheuvront, Samuel N; Montain, Scott J; Kenefick, Robert W; Castellani, John; Latzka, William A; Roberts, Warren S; Richter, Mark; Jenkins, Odest Chadwicke; Hoyt, Reed W

    2013-07-01

    Core temperature (CT) in combination with heart rate (HR) can be a good indicator of impending heat exhaustion for occupations involving exposure to heat, heavy workloads, and wearing protective clothing. However, continuously measuring CT in an ambulatory environment is difficult. To address this problem we developed a model to estimate the time course of CT using a series of HR measurements as a leading indicator using a Kalman filter. The model was trained using data from 17 volunteers engaged in a 24 h military field exercise (air temperatures 24-36 °C, and 42%-97% relative humidity and CTs ranging from 36.0-40.0 °C). Validation data from laboratory and field studies (N = 83) encompassing various combinations of temperature, hydration, clothing, and acclimation state were examined using the Bland-Altman limits of agreement (LoA) method. We found our model had an overall bias of -0.03 ± 0.32 °C and that 95% of all CT estimates fall within ±0.63 °C (>52 000 total observations). While the model for estimating CT is not a replacement for direct measurement of CT (literature comparisons of esophageal and rectal methods average LoAs of ±0.58 °C) our results suggest it is accurate enough to provide practical indication of thermal work strain for use in the work place.

  13. Estimating the seismotelluric current required for observable electromagnetic ground signals

    Directory of Open Access Journals (Sweden)

    J. Bortnik

    2010-08-01

    Full Text Available We use a relatively simple model of an underground current source co-located with the earthquake hypocenter to estimate the magnitude of the seismotelluric current required to produce observable ground signatures. The Alum Rock earthquake of 31 October 2007, is used as an archetype of a typical California earthquake, and the effects of varying the ground conductivity and length of the current element are examined. Results show that for an observed 30 nT pulse at 1 Hz, the expected seismotelluric current magnitudes fall in the range ~10–100 kA. By setting the detectability threshold to 1 pT, we show that even when large values of ground conductivity are assumed, magnetic signals are readily detectable within a range of 30 km from the epicenter. When typical values of ground conductivity are assumed, the minimum current required to produce an observable signal within a 30 km range was found to be ~1 kA, which is a surprisingly low value. Furthermore, we show that deep nulls in the signal power develop in the non-cardinal directions relative to the orientation of the source current, indicating that a magnetometer station located in those regions may not observe a signal even though it is well within the detectable range. This result underscores the importance of using a network of magnetometers when searching for preseismic electromagnetic signals.

  14. The impact of the ocean observing system on estimates of the California current circulation spanning three decades

    Science.gov (United States)

    Moore, Andrew M.; Jacox, Michael G.; Crawford, William J.; Laughlin, Bruce; Edwards, Christopher A.; Fiechter, Jérôme

    2017-08-01

    Data assimilation is now used routinely in oceanography on both regional and global scales for computing ocean circulation estimates and for making ocean forecasts. Regional ocean observing systems are also expanding rapidly, and observations from a wide array of different platforms and sensor types are now available. Evaluation of the impact of the observing system on ocean circulation estimates (and forecasts) is therefore of considerable interest to the oceanographic community. In this paper, we quantify the impact of different observing platforms on estimates of the California Current System (CCS) spanning a three decade period (1980-2010). Specifically, we focus attention on several dynamically related aspects of the circulation (coastal upwelling, the transport of the California Current and the California Undercurrent, thermocline depth and eddy kinetic energy) which in many ways describe defining characteristics of the CCS. The circulation estimates were computed using a 4-dimensional variational (4D-Var) data assimilation system, and our analyses also focus on the impact of the different elements of the control vector (i.e. the initial conditions, surface forcing, and open boundary conditions) on the circulation. While the influence of each component of the control vector varies between different metrics of the circulation, the impact of each observing system across metrics is very robust. In addition, the mean amplitude of the circulation increments (i.e. the difference between the analysis and background) remains relatively stable throughout the three decade period despite the addition of new observing platforms whose impact is redistributed according to the relative uncertainty of observations from each platform. We also consider the impact of each observing platform on CCS circulation variability associated with low-frequency climate variability. The low-frequency nature of the dominant climate modes in this region allows us to track through time the

  15. Normal estimation for pointcloud using GPU based sparse tensor voting

    OpenAIRE

    Liu , Ming; Pomerleau , François; Colas , Francis; Siegwart , Roland

    2012-01-01

    International audience; Normal estimation is the basis for most applications using pointcloud, such as segmentation. However, it is still a challenging problem regarding computational complexity and observation noise. In this paper, we propose a normal estimation method for pointcloud using results from tensor voting. Comparing with other approaches, we show it has smaller estimation error. Moreover, by varying the voting kernel size, we find it is a flexible approach for structure extraction...

  16. The influence of population characteristics on variation in general practice based morbidity estimations

    Directory of Open Access Journals (Sweden)

    van den Dungen C

    2011-11-01

    Full Text Available Abstract Background General practice based registration networks (GPRNs provide information on morbidity rates in the population. Morbidity rate estimates from different GPRNs, however, reveal considerable, unexplained differences. We studied the range and variation in morbidity estimates, as well as the extent to which the differences in morbidity rates between general practices and networks change if socio-demographic characteristics of the listed patient populations are taken into account. Methods The variation in incidence and prevalence rates of thirteen diseases among six Dutch GPRNs and the influence of age, gender, socio economic status (SES, urbanization level, and ethnicity are analyzed using multilevel logistic regression analysis. Results are expressed in median odds ratios (MOR. Results We observed large differences in morbidity rate estimates both on the level of general practices as on the level of networks. The differences in SES, urbanization level and ethnicity distribution among the networks' practice populations are substantial. The variation in morbidity rate estimates among networks did not decrease after adjusting for these socio-demographic characteristics. Conclusion Socio-demographic characteristics of populations do not explain the differences in morbidity estimations among GPRNs.

  17. A test of the ADV-based Reynolds flux method for in situ estimation of sediment settling velocity in a muddy estuary

    Science.gov (United States)

    Cartwright, Grace M.; Friedrichs, Carl T.; Smith, S. Jarrell

    2013-12-01

    Under conditions common in muddy coastal and estuarine environments, acoustic Doppler velocimeters (ADVs) can serve to estimate sediment settling velocity ( w s) by assuming a balance between upward turbulent Reynolds flux and downward gravitational settling. Advantages of this method include simple instrument deployment, lack of flow disturbance, and relative insensitivity to biofouling and water column stratification. Although this method is being used with increasing frequency in coastal and estuarine environments, to date it has received little direct ground truthing. This study compared in situ estimates of w s inferred by a 5-MHz ADV to independent in situ observations from a high-definition video settling column over the course of a flood tide in the bottom boundary layer of the York River estuary, Virginia, USA. The ADV-based measurements were found to agree with those of the settling column when the current speed at about 40 cm above the bed was greater than about 20 cm/s. This corresponded to periods when the estimated magnitude of the settling term in the suspended sediment continuity equation was four or more times larger than the time rate of change of concentration. For ADV observations restricted to these conditions, ADV-based estimates of w s (mean 0.48±0.04 mm/s) were highly consistent with those observed by the settling column (mean 0.45±0.02 mm/s). However, the ADV-based method for estimating w s was sensitive to the prescribed concentration of the non-settling washload, C wash. In an objective operational definition, C wash can be set equal to the lowest suspended solids concentration observed around slack water.

  18. Sliding mode based trajectory linearization control for hypersonic reentry vehicle via extended disturbance observer.

    Science.gov (United States)

    Xingling, Shao; Honglun, Wang

    2014-11-01

    This paper proposes a novel hybrid control framework by combing observer-based sliding mode control (SMC) with trajectory linearization control (TLC) for hypersonic reentry vehicle (HRV) attitude tracking problem. First, fewer control consumption is achieved using nonlinear tracking differentiator (TD) in the attitude loop. Second, a novel SMC that employs extended disturbance observer (EDO) to counteract the effect of uncertainties using a new sliding surface which includes the estimation error is integrated to address the tracking error stabilization issues in the attitude and angular rate loop, respectively. In addition, new results associated with EDO are examined in terms of dynamic response and noise-tolerant performance, as well as estimation accuracy. The key feature of the proposed compound control approach is that chattering free tracking performance with high accuracy can be ensured for HRV in the presence of multiple uncertainties under control constraints. Based on finite time convergence stability theory, the stability of the resulting closed-loop system is well established. Also, comparisons and extensive simulation results are presented to demonstrate the effectiveness of the control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Estimation of the flow resistances exerted in coronary arteries using a vessel length-based method.

    Science.gov (United States)

    Lee, Kyung Eun; Kwon, Soon-Sung; Ji, Yoon Cheol; Shin, Eun-Seok; Choi, Jin-Ho; Kim, Sung Joon; Shim, Eun Bo

    2016-08-01

    Flow resistances exerted in the coronary arteries are the key parameters for the image-based computer simulation of coronary hemodynamics. The resistances depend on the anatomical characteristics of the coronary system. A simple and reliable estimation of the resistances is a compulsory procedure to compute the fractional flow reserve (FFR) of stenosed coronary arteries, an important clinical index of coronary artery disease. The cardiac muscle volume reconstructed from computed tomography (CT) images has been used to assess the resistance of the feeding coronary artery (muscle volume-based method). In this study, we estimate the flow resistances exerted in coronary arteries by using a novel method. Based on a physiological observation that longer coronary arteries have more daughter branches feeding a larger mass of cardiac muscle, the method measures the vessel lengths from coronary angiogram or CT images (vessel length-based method) and predicts the coronary flow resistances. The underlying equations are derived from the physiological relation among flow rate, resistance, and vessel length. To validate the present estimation method, we calculate the coronary flow division over coronary major arteries for 50 patients using the vessel length-based method as well as the muscle volume-based one. These results are compared with the direct measurements in a clinical study. Further proving the usefulness of the present method, we compute the coronary FFR from the images of optical coherence tomography.

  20. Sliding observer-based demagnetisation fault-tolerant control in permanent magnet synchronous motors

    Directory of Open Access Journals (Sweden)

    Changfan Zhang

    2017-04-01

    Full Text Available This study proposes a fault-tolerant control method for permanent magnet synchronous motors (PMSMs based on the active flux linkage concept, which addresses permanent magnet (PM demagnetisation faults in PMSMs. First, a mathematical model for a PMSM is established based on active flux linkage, and then the effect of PM demagnetisation on the PMSM is analysed. Second, the stator current in the static coordinate is set as the state variable, an observer is designed based on a sliding-mode variable structure, and an equation for active flux linkage is established for dynamic estimation based on the equivalent control principle of sliding-mode variable structure. Finally, the active flux linkage for the next moment is predicted according to the operating conditions of the motor and the observed values of the current active flux linkage. The deadbeat control strategy is applied to eliminate errors in the active flux linkage and realise the objective of fault-tolerant control. A timely and effective control for demagnetisation faults is achieved using the proposed method, which validity and feasibility are verified by the simulation and experiment results.

  1. Crustal block motion model and interplate coupling along Ecuador-Colombia trench based on GNSS observation network

    Science.gov (United States)

    Ito, T.; Mora-Páez, H.; Peláez-Gaviria, J. R.; Kimura, H.; Sagiya, T.

    2017-12-01

    IntroductionEcuador-Colombia trench is located at the boundary between South-America plate, Nazca Plate and Caribrian plate. This region is very complexes such as subducting Caribrian plate and Nazca plate, and collision between Panama and northern part of the Andes mountains. The previous large earthquakes occurred along the subducting boundary of Nazca plate, such as 1906 (M8.8) and 1979 (M8.2). And also, earthquakes occurred inland, too. So, it is important to evaluate earthquake potentials for preparing huge damage due to large earthquake in near future. GNSS observation In the last decade, the GNSS observation was established in Columbia. The GNSS observation is called by GEORED, which is operated by servicing Geologico Colomiano. The purpose of GEORED is research of crustal deformation. The number of GNSS site of GEORED is consist of 60 continuous GNSS observation site at 2017 (Mora et al., 2017). The sampling interval of almost GNSS site is 30 seconds. These GNSS data were processed by PPP processing using GIPSY-OASYS II software. GEORED can obtain the detailed crustal deformation map in whole Colombia. In addition, we use 100 GNSS data at Ecuador-Peru region (Nocquet et al. 2014). Method We developed a crustal block movements model based on crustal deformation derived from GNSS observation. Our model considers to the block motion with pole location and angular velocity and the interplate coupling between each block boundaries, including subduction between the South-American plate and the Nazca plate. And also, our approach of estimation of crustal block motion and coefficient of interplate coupling are based on MCMC method. The estimated each parameter is obtained probably density function (PDF). Result We tested 11 crustal block models based on geological data, such as active fault trace at surface. The optimal number of crustal blocks is 11 for based on geological and geodetic data using AIC. We use optimal block motion model. And also, we estimate

  2. Variable disparity-motion estimation based fast three-view video coding

    Science.gov (United States)

    Bae, Kyung-Hoon; Kim, Seung-Cheol; Hwang, Yong Seok; Kim, Eun-Soo

    2009-02-01

    In this paper, variable disparity-motion estimation (VDME) based 3-view video coding is proposed. In the encoding, key-frame coding (KFC) based motion estimation and variable disparity estimation (VDE) for effectively fast three-view video encoding are processed. These proposed algorithms enhance the performance of 3-D video encoding/decoding system in terms of accuracy of disparity estimation and computational overhead. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm's PSNRs is 37.66 and 40.55 dB, and the processing time is 0.139 and 0.124 sec/frame, respectively.

  3. Correlation-Based Amplitude Estimation of Coincident Partials in Monaural Musical Signals

    Directory of Open Access Journals (Sweden)

    Jayme Garcia Arnal Barbedo

    2010-01-01

    Full Text Available This paper presents a method for estimating the amplitude of coincident partials generated by harmonic musical sources (instruments and vocals. It was developed as an alternative to the commonly used interpolation approach, which has several limitations in terms of performance and applicability. The strategy is based on the following observations: (a the parameters of partials vary with time; (b such a variation tends to be correlated when the partials belong to the same source; (c the presence of an interfering coincident partial reduces the correlation; and (d such a reduction is proportional to the relative amplitude of the interfering partial. Besides the improved accuracy, the proposed technique has other advantages over its predecessors: it works properly even if the sources have the same fundamental frequency, it is able to estimate the first partial (fundamental, which is not possible using the conventional interpolation method, it can estimate the amplitude of a given partial even if its neighbors suffer intense interference from other sources, it works properly under noisy conditions, and it is immune to intraframe permutation errors. Experimental results show that the strategy clearly outperforms the interpolation approach.

  4. Advances in estimation methods of vegetation water content based on optical remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

  5. State of charge estimation of lithium-ion batteries based on an improved parameter identification method

    International Nuclear Information System (INIS)

    Xia, Bizhong; Chen, Chaoren; Tian, Yong; Wang, Mingwang; Sun, Wei; Xu, Zhihui

    2015-01-01

    The SOC (state of charge) is the most important index of the battery management systems. However, it cannot be measured directly with sensors and must be estimated with mathematical techniques. An accurate battery model is crucial to exactly estimate the SOC. In order to improve the model accuracy, this paper presents an improved parameter identification method. Firstly, the concept of polarization depth is proposed based on the analysis of polarization characteristics of the lithium-ion batteries. Then, the nonlinear least square technique is applied to determine the model parameters according to data collected from pulsed discharge experiments. The results show that the proposed method can reduce the model error as compared with the conventional approach. Furthermore, a nonlinear observer presented in the previous work is utilized to verify the validity of the proposed parameter identification method in SOC estimation. Finally, experiments with different levels of discharge current are carried out to investigate the influence of polarization depth on SOC estimation. Experimental results show that the proposed method can improve the SOC estimation accuracy as compared with the conventional approach, especially under the conditions of large discharge current. - Highlights: • The polarization characteristics of lithium-ion batteries are analyzed. • The concept of polarization depth is proposed to improve model accuracy. • A nonlinear least square technique is applied to determine the model parameters. • A nonlinear observer is used as the SOC estimation algorithm. • The validity of the proposed method is verified by experimental results.

  6. Accurate Frequency Estimation Based On Three-Parameter Sine-Fitting With Three FFT Samples

    Directory of Open Access Journals (Sweden)

    Liu Xin

    2015-09-01

    Full Text Available This paper presents a simple DFT-based golden section searching algorithm (DGSSA for the single tone frequency estimation. Because of truncation and discreteness in signal samples, Fast Fourier Transform (FFT and Discrete Fourier Transform (DFT are inevitable to cause the spectrum leakage and fence effect which lead to a low estimation accuracy. This method can improve the estimation accuracy under conditions of a low signal-to-noise ratio (SNR and a low resolution. This method firstly uses three FFT samples to determine the frequency searching scope, then – besides the frequency – the estimated values of amplitude, phase and dc component are obtained by minimizing the least square (LS fitting error of three-parameter sine fitting. By setting reasonable stop conditions or the number of iterations, the accurate frequency estimation can be realized. The accuracy of this method, when applied to observed single-tone sinusoid samples corrupted by white Gaussian noise, is investigated by different methods with respect to the unbiased Cramer-Rao Low Bound (CRLB. The simulation results show that the root mean square error (RMSE of the frequency estimation curve is consistent with the tendency of CRLB as SNR increases, even in the case of a small number of samples. The average RMSE of the frequency estimation is less than 1.5 times the CRLB with SNR = 20 dB and N = 512.

  7. Assessing methane emission estimation methods based on atmospheric measurements from oil and gas production using LES simulations

    Science.gov (United States)

    Saide, P. E.; Steinhoff, D.; Kosovic, B.; Weil, J.; Smith, N.; Blewitt, D.; Delle Monache, L.

    2017-12-01

    There are a wide variety of methods that have been proposed and used to estimate methane emissions from oil and gas production by using air composition and meteorology observations in conjunction with dispersion models. Although there has been some verification of these methodologies using controlled releases and concurrent atmospheric measurements, it is difficult to assess the accuracy of these methods for more realistic scenarios considering factors such as terrain, emissions from multiple components within a well pad, and time-varying emissions representative of typical operations. In this work we use a large-eddy simulation (LES) to generate controlled but realistic synthetic observations, which can be used to test multiple source term estimation methods, also known as an Observing System Simulation Experiment (OSSE). The LES is based on idealized simulations of the Weather Research & Forecasting (WRF) model at 10 m horizontal grid-spacing covering an 8 km by 7 km domain with terrain representative of a region located in the Barnett shale. Well pads are setup in the domain following a realistic distribution and emissions are prescribed every second for the components of each well pad (e.g., chemical injection pump, pneumatics, compressor, tanks, and dehydrator) using a simulator driven by oil and gas production volume, composition and realistic operational conditions. The system is setup to allow assessments under different scenarios such as normal operations, during liquids unloading events, or during other prescribed operational upset events. Methane and meteorology model output are sampled following the specifications of the emission estimation methodologies and considering typical instrument uncertainties, resulting in realistic observations (see Figure 1). We will show the evaluation of several emission estimation methods including the EPA Other Test Method 33A and estimates using the EPA AERMOD regulatory model. We will also show source estimation

  8. Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

    Science.gov (United States)

    Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

    2017-10-03

    Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

  9. Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

    Science.gov (United States)

    Xie, Pingping; Joyce, Robert; Wu, Shaorong

    2015-04-01

    As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of

  10. In vivo estimation of normal amygdala volume from structural MRI scans with anatomical-based segmentation.

    Science.gov (United States)

    Siozopoulos, Achilleas; Thomaidis, Vasilios; Prassopoulos, Panos; Fiska, Aliki

    2018-02-01

    Literature includes a number of studies using structural MRI (sMRI) to determine the volume of the amygdala, which is modified in various pathologic conditions. The reported values vary widely mainly because of different anatomical approaches to the complex. This study aims at estimating of the normal amygdala volume from sMRI scans using a recent anatomical definition described in a study based on post-mortem material. The amygdala volume has been calculated in 106 healthy subjects, using sMRI and anatomical-based segmentation. The resulting volumes have been analyzed for differences related to hemisphere, sex, and age. The mean amygdalar volume was estimated at 1.42 cm 3 . The mean right amygdala volume has been found larger than the left, but the difference for the raw values was within the limits of the method error. No intersexual differences or age-related alterations have been observed. The study provides a method for determining the boundaries of the amygdala in sMRI scans based on recent anatomical considerations and an estimation of the mean normal amygdala volume from a quite large number of scans for future use in comparative studies.

  11. A process-based 222radon flux map for Europe and its comparison to long-term observations

    Science.gov (United States)

    Karstens, U.; Schwingshackl, C.; Schmithüsen, D.; Levin, I.

    2015-11-01

    Detailed 222radon (222Rn) flux maps are an essential pre-requisite for the use of radon in atmospheric transport studies. Here we present a high-resolution 222Rn flux map for Europe, based on a parameterization of 222Rn production and transport in the soil. The 222Rn exhalation rate is parameterized based on soil properties, uranium content, and modelled soil moisture from two different land-surface reanalysis data sets. Spatial variations in exhalation rates are primarily determined by the uranium content of the soil, but also influenced by soil texture and local water-table depth. Temporal variations are related to soil moisture variations as the molecular diffusion in the unsaturated soil zone depends on available air-filled pore space. The implemented diffusion parameterization was tested against campaign-based 222Rn soil profile measurements. Monthly 222Rn exhalation rates from European soils were calculated with a nominal spatial resolution of 0.083° × 0.083° and compared to long-term direct measurements of 222Rn exhalation rates in different areas of Europe. The two realizations of the 222Rn flux map, based on the different soil moisture data sets, both realistically reproduce the observed seasonality in the fluxes but yield considerable differences for absolute flux values. The mean 222Rn flux from soils in Europe is estimated to be 10 mBq m-2 s-1 (ERA-Interim/Land soil moisture) or 15 mBq m-2 s-1 (GLDAS (Global Land Data Assimilation System) Noah soil moisture) for the period 2006-2010. The corresponding seasonal variations with low fluxes in winter and high fluxes in summer range in the two realizations from ca. 7 to ca. 14 mBq m-2 s-1 and from ca. 11 to ca. 20 mBq m-2 s-1, respectively. These systematic differences highlight the importance of realistic soil moisture data for a reliable estimation of 222Rn exhalation rates. Comparison with observations suggests that the flux estimates based on the GLDAS Noah soil moisture model on average better

  12. A process-based 222radon flux map for Europe and its comparison to long-term observations

    International Nuclear Information System (INIS)

    Karstens, U.; Schwingshackl, C.; Schmithuesen, D.; Levin, I.

    2015-01-01

    Detailed 222 radon ( 222 Rn) flux maps are an essential pre-requisite for the use of radon in atmospheric transport studies. Here we present a high-resolution 222 Rn flux map for Europe, based on a parameterization of 222 Rn production and transport in the soil. The 222 Rn exhalation rate is parameterized based on soil properties, uranium content, and modelled soil moisture from two different land-surface reanalysis data sets. Spatial variations in exhalation rates are primarily determined by the uranium content of the soil, but also influenced by soil texture and local water-table depth. Temporal variations are related to soil moisture variations as the molecular diffusion in the unsaturated soil zone depends on available air-filled pore space. The implemented diffusion parameterization was tested against campaign-based 222 Rn soil profile measurements. Monthly 222 Rn exhalation rates from European soils were calculated with a nominal spatial resolution of 0.083 x 0.083 and compared to long-term direct measurements of 222 Rn exhalation rates in different areas of Europe. The two realizations of the 222 Rn flux map, based on the different soil moisture data sets, both realistically reproduce the observed seasonality in the fluxes but yield considerable differences for absolute flux values. The mean 222 Rn flux from soils in Europe is estimated to be 10 mBq m -2 s -1 (ERA-Interim/Land soil moisture) or 15 mBq m -2 s -1 (GLDAS (Global Land Data Assimilation System) Noah soil moisture) for the period 2006-2010. The corresponding seasonal variations with low fluxes in winter and high fluxes in summer range in the two realizations from ca. 7 to ca. 14 mBq m -2 s -1 and from ca. 11 to ca. 20 mBq m -2 s -1 , respectively. These systematic differences highlight the importance of realistic soil moisture data for a reliable estimation of 222 Rn exhalation rates. Comparison with observations suggests that the flux estimates based on the GLDAS Noah soil moisture model on

  13. Statistical inference for remote sensing-based estimates of net deforestation

    Science.gov (United States)

    Ronald E. McRoberts; Brian F. Walters

    2012-01-01

    Statistical inference requires expression of an estimate in probabilistic terms, usually in the form of a confidence interval. An approach to constructing confidence intervals for remote sensing-based estimates of net deforestation is illustrated. The approach is based on post-classification methods using two independent forest/non-forest classifications because...

  14. Fuzzy logic based ELF magnetic field estimation in substations

    International Nuclear Information System (INIS)

    Kosalay, I.

    2008-01-01

    This paper examines estimation of the extremely low frequency magnetic fields (MF) in the power substation. First, the results of the previous relevant research studies and the MF measurements in a sample power substation are presented. Then, a fuzzy logic model based on the geometric definitions in order to estimate the MF distribution is explained. Visual software, which has a three-dimensional screening unit, based on the fuzzy logic technique, has been developed. (authors)

  15. Line impedance estimation using model based identification technique

    DEFF Research Database (Denmark)

    Ciobotaru, Mihai; Agelidis, Vassilios; Teodorescu, Remus

    2011-01-01

    The estimation of the line impedance can be used by the control of numerous grid-connected systems, such as active filters, islanding detection techniques, non-linear current controllers, detection of the on/off grid operation mode. Therefore, estimating the line impedance can add extra functions...... into the operation of the grid-connected power converters. This paper describes a quasi passive method for estimating the line impedance of the distribution electricity network. The method uses the model based identification technique to obtain the resistive and inductive parts of the line impedance. The quasi...

  16. Robust Online State of Charge Estimation of Lithium-Ion Battery Pack Based on Error Sensitivity Analysis

    Directory of Open Access Journals (Sweden)

    Ting Zhao

    2015-01-01

    Full Text Available Accurate and reliable state of charge (SOC estimation is a key enabling technique for large format lithium-ion battery pack due to its vital role in battery safety and effective management. This paper tries to make three contributions to existing literatures through robust algorithms. (1 Observer based SOC estimation error model is established, where the crucial parameters on SOC estimation accuracy are determined by quantitative analysis, being a basis for parameters update. (2 The estimation method for a battery pack in which the inconsistency of cells is taken into consideration is proposed, ensuring all batteries’ SOC ranging from 0 to 1, effectively avoiding the battery overcharged/overdischarged. Online estimation of the parameters is also presented in this paper. (3 The SOC estimation accuracy of the battery pack is verified using the hardware-in-loop simulation platform. The experimental results at various dynamic test conditions, temperatures, and initial SOC difference between two cells demonstrate the efficacy of the proposed method.

  17. A fuel-based approach to estimating motor vehicle exhaust emissions

    Science.gov (United States)

    Singer, Brett Craig

    Motor vehicles contribute significantly to air pollution problems; accurate motor vehicle emission inventories are therefore essential to air quality planning. Current travel-based inventory models use emission factors measured from potentially biased vehicle samples and predict fleet-average emissions which are often inconsistent with on-road measurements. This thesis presents a fuel-based inventory approach which uses emission factors derived from remote sensing or tunnel-based measurements of on-road vehicles. Vehicle activity is quantified by statewide monthly fuel sales data resolved to the air basin level. Development of the fuel-based approach includes (1) a method for estimating cold start emission factors, (2) an analysis showing that fuel-normalized emission factors are consistent over a range of positive vehicle loads and that most fuel use occurs during loaded-mode driving, (3) scaling factors relating infrared hydrocarbon measurements to total exhaust volatile organic compound (VOC) concentrations, and (4) an analysis showing that economic factors should be considered when selecting on-road sampling sites. The fuel-based approach was applied to estimate carbon monoxide (CO) emissions from warmed-up vehicles in the Los Angeles area in 1991, and CO and VOC exhaust emissions for Los Angeles in 1997. The fuel-based CO estimate for 1991 was higher by a factor of 2.3 +/- 0.5 than emissions predicted by California's MVEI 7F model. Fuel-based inventory estimates for 1997 were higher than those of California's updated MVEI 7G model by factors of 2.4 +/- 0.2 for CO and 3.5 +/- 0.6 for VOC. Fuel-based estimates indicate a 20% decrease in the mass of CO emitted, despite an 8% increase in fuel use between 1991 and 1997; official inventory models predict a 50% decrease in CO mass emissions during the same period. Cold start CO and VOC emission factors derived from parking garage measurements were lower than those predicted by the MVEI 7G model. Current inventories

  18. A review of land-based greenhouse gas flux estimates in Indonesia

    Science.gov (United States)

    Austin, Kemen G.; Harris, Nancy L.; Wijaya, Arief; Murdiyarso, Daniel; Harvey, Tom; Stolle, Fred; Kasibhatla, Prasad S.

    2018-05-01

    This study examines underlying reasons for differences among land-based greenhouse gas flux estimates in Indonesia, where six national inventories reported average emissions of between 0.4 and 1.1 Gt CO2e yr‑1 over the 2000–2012 period. The large range among estimates is only somewhat smaller than Indonesia’s GHG mitigation commitment. To determine the reasons for these differences, we compared input data and estimation methods, including the definitions and assumptions used for setting accounting boundaries, including emitting activities, incorporating fluxes from various carbon pools, and handling legacy fluxes. We also tested the sensitivity of methodological differences by generating our own reference emissions estimate and iteratively modifying individual components of the inventory. We found that the largest changes stem from the inclusion of legacy GHG emissions due to peat drainage (which increased emissions by at least +94% compared to the reference), methane emissions due to peat fires (+35%), and GHG emissions from belowground biomass and necromass carbon pools (+61%), modifications to assumptions of the mass of fuel burnt in peat fire events (+88%), and accounting for regrowth following a deforestation event (‑31%). These differences cumulatively explain more than half of the observed difference among inventory estimates. Understanding the various approaches to emissions estimation, and how these influence the magnitude of component GHG fluxes, is an important first step towards reconciling GHG inventories. The Indonesian government’s success in achieving its mitigation goal will depend on its ability to measure progress and evaluate the effectiveness of abatement actions, for which reliable harmonized greenhouse gas inventories are an essential foundation.

  19. Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers

    Directory of Open Access Journals (Sweden)

    S. A. Archfield

    2013-01-01

    Full Text Available Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.

  20. Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers

    Science.gov (United States)

    Archfield, Stacey A.; Steeves, Peter A.; Guthrie, John D.; Ries, Kernell G.

    2013-01-01

    Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals) at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.

  1. 48 CFR 2452.216-70 - Estimated cost, base fee and award fee.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Estimated cost, base fee... Provisions and Clauses 2452.216-70 Estimated cost, base fee and award fee. As prescribed in 2416.406(e)(1), insert the following clause in all cost-plus-award-fee contracts: Estimated Cost, Base Fee and Award Fee...

  2. Spectrum estimation method based on marginal spectrum

    International Nuclear Information System (INIS)

    Cai Jianhua; Hu Weiwen; Wang Xianchun

    2011-01-01

    FFT method can not meet the basic requirements of power spectrum for non-stationary signal and short signal. A new spectrum estimation method based on marginal spectrum from Hilbert-Huang transform (HHT) was proposed. The procession of obtaining marginal spectrum in HHT method was given and the linear property of marginal spectrum was demonstrated. Compared with the FFT method, the physical meaning and the frequency resolution of marginal spectrum were further analyzed. Then the Hilbert spectrum estimation algorithm was discussed in detail, and the simulation results were given at last. The theory and simulation shows that under the condition of short data signal and non-stationary signal, the frequency resolution and estimation precision of HHT method is better than that of FFT method. (authors)

  3. Estimating wind-turbine-caused bird and bat fatality when zero carcasses are observed

    Science.gov (United States)

    Huso, Manuela M.P.; Dalthorp, Daniel; Dail, David; Madsen, Lisa

    2015-01-01

    Many wind-power facilities in the United States have established effective monitoring programs to determine turbine-caused fatality rates of birds and bats, but estimating the number of fatalities of rare species poses special difficulties. The loss of even small numbers of individuals may adversely affect fragile populations, but typically, few (if any) carcasses are observed during monitoring. If monitoring design results in only a small proportion of carcasses detected, then finding zero carcasses may give little assurance that the number of actual fatalities is small. Fatality monitoring at wind-power facilities commonly involves conducting experiments to estimate the probability (g) an individual will be observed, accounting for the possibilities that it falls in an unsearched area, is scavenged prior to detection, or remains undetected even when present. When g  ~0.45. Further, we develop extensions for temporal replication that can inform prior distributions of M and methods for combining information across several areas or time periods. We apply the method to data collected at a wind-power facility where scheduled searches yielded X = 0 raptor carcasses

  4. Estimating wind-turbine-caused bird and bat fatality when zero carcasses are observed.

    Science.gov (United States)

    Huso, Manuela M P; Dalthorp, Dan; Dail, David; Madsen, Lisa

    2015-07-01

    Many wind-power facilities in the United States have established effective monitoring programs to determine turbine-caused fatality rates of birds and bats, but estimating the number of fatalities of rare species poses special difficulties. The loss of even small numbers of individuals may adversely affect fragile populations, but typically, few (if any) carcasses are observed during monitoring. If monitoring design results in only a small proportion of carcasses detected, then finding zero carcasses may give little assurance that the number of actual fatalities is small. Fatality monitoring at wind-power facilities commonly involves conducting experiments to estimate the probability (g) an individual will be observed, accounting for the possibilities that it falls in an unsearched area, is scavenged prior to detection, or remains undetected even when present. When g -0.45. Further, we develop extensions for temporal replication that can inform prior distributions of M and methods for combining information across several areas or time periods. We apply the method to data collected at a wind-power facility where scheduled searches yielded X = 0 raptor carcasses.

  5. Accuracy of prehospital transport time estimation.

    Science.gov (United States)

    Wallace, David J; Kahn, Jeremy M; Angus, Derek C; Martin-Gill, Christian; Callaway, Clifton W; Rea, Thomas D; Chhatwal, Jagpreet; Kurland, Kristen; Seymour, Christopher W

    2014-01-01

    Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports. This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respectively. Transport time estimates were generated using three methods: linear arc distance, Google Maps, and ArcGIS Network Analyst. Estimation error, defined as the absolute difference between observed and estimated transport time, was assessed, as well as the proportion of estimated times that were within specified error thresholds. Based on the primary results, a regression estimate was used that incorporated population density, time of day, and season to assess improved accuracy. Finally, hospital catchment areas were compared using each method with a fixed drive time. The authors analyzed 29,935 prehospital transports to 44 hospitals. The mean (± standard deviation [±SD]) absolute error was 4.8 (±7.3) minutes using linear arc, 3.5 (±5.4) minutes using Google Maps, and 4.4 (±5.7) minutes using ArcGIS. All pairwise comparisons were statistically significant (p Google Maps, and 11.6 [±10.9] minutes for ArcGIS). Estimates were within 5 minutes of observed transport time for 79% of linear arc estimates, 86.6% of Google Maps estimates, and 81.3% of ArcGIS estimates. The regression-based approach did not substantially improve estimation. There were large differences in hospital catchment areas estimated by each method. Route-based transport time estimates demonstrate moderate accuracy. These methods can be valuable for informing a host of decisions related to the system organization and patient access to emergency medical care; however, they should be employed with sensitivity to their limitations.

  6. An optimal estimation algorithm to derive Ice and Ocean parameters from AMSR Microwave radiometer observations

    DEFF Research Database (Denmark)

    Pedersen, Leif Toudal; Tonboe, Rasmus T.; Høyer, Jacob

    channels as well as the combination of data from multiple sources such as microwave radiometry, scatterometry and numerical weather prediction. Optimal estimation is data assimilation without a numerical model for retrieving physical parameters from remote sensing using a multitude of available information......Global multispectral microwave radiometer measurements have been available for several decades. However, most current sea ice concentration algorithms still only takes advantage of a very limited subset of the available channels. Here we present a method that allows utilization of all available....... The methodology is observation driven and model innovation is limited to the translation between observation space and physical parameter space Over open water we use a semi-empirical radiative transfer model developed by Meissner & Wentz that estimates the multispectral AMSR brightness temperatures, i...

  7. Topology-Based Estimation of Missing Smart Meter Readings

    Directory of Open Access Journals (Sweden)

    Daisuke Kodaira

    2018-01-01

    Full Text Available Smart meters often fail to measure or transmit the data they record when measuring energy consumption, known as meter readings, owing to faulty measuring equipment or unreliable communication modules. Existing studies do not address successive and non-periodical missing meter readings. This paper proposes a method whereby missing readings observed at a node are estimated by using circuit theory principles that leverage the voltage and current data from adjacent nodes. A case study is used to demonstrate the ability of the proposed method to successfully estimate the missing readings over an entire day during which outages and unpredictable perturbations occurred.

  8. Estimating High-Frequency Based (Co-) Variances: A Unified Approach

    DEFF Research Database (Denmark)

    Voev, Valeri; Nolte, Ingmar

    We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...

  9. Head pose estimation algorithm based on deep learning

    Science.gov (United States)

    Cao, Yuanming; Liu, Yijun

    2017-05-01

    Head pose estimation has been widely used in the field of artificial intelligence, pattern recognition and intelligent human-computer interaction and so on. Good head pose estimation algorithm should deal with light, noise, identity, shelter and other factors robustly, but so far how to improve the accuracy and robustness of attitude estimation remains a major challenge in the field of computer vision. A method based on deep learning for pose estimation is presented. Deep learning with a strong learning ability, it can extract high-level image features of the input image by through a series of non-linear operation, then classifying the input image using the extracted feature. Such characteristics have greater differences in pose, while they are robust of light, identity, occlusion and other factors. The proposed head pose estimation is evaluated on the CAS-PEAL data set. Experimental results show that this method is effective to improve the accuracy of pose estimation.

  10. An operational weather radar-based Quantitative Precipitation Estimation and its application in catchment water resources modeling

    DEFF Research Database (Denmark)

    He, Xin; Vejen, Flemming; Stisen, Simon

    2011-01-01

    of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with ground surface observations. The method was applied to the Skjern River catchment...... in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate...... reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream discharge results. Also, groundwater recharge was shown to be sensitive...

  11. Numerosity estimation in visual stimuli in the absence of luminance-based cues.

    Directory of Open Access Journals (Sweden)

    Peter Kramer

    2011-02-01

    Full Text Available Numerosity estimation is a basic preverbal ability that humans share with many animal species and that is believed to be foundational of numeracy skills. It is notoriously difficult, however, to establish whether numerosity estimation is based on numerosity itself, or on one or more non-numerical cues like-in visual stimuli-spatial extent and density. Frequently, different non-numerical cues are held constant on different trials. This strategy, however, still allows numerosity estimation to be based on a combination of non-numerical cues rather than on any particular one by itself.Here we introduce a novel method, based on second-order (contrast-based visual motion, to create stimuli that exclude all first-order (luminance-based cues to numerosity. We show that numerosities can be estimated almost as well in second-order motion as in first-order motion.The results show that numerosity estimation need not be based on first-order spatial filtering, first-order density perception, or any other processing of luminance-based cues to numerosity. Our method can be used as an effective tool to control non-numerical variables in studies of numerosity estimation.

  12. A chaotic modulation scheme based on algebraic observability and sliding mode differentiators

    International Nuclear Information System (INIS)

    Cannas, Barbara; Cincotti, Silvano; Usai, Elio

    2005-01-01

    A chaotic communication technique for the transmission of secure information signals is presented. The proposed method allows the reconstruction of the system input (i.e., the information signal) from a scalar observable (i.e., the transmitted signal) and its derivatives. The approach is based on the concept of algebraic observability. A systematic procedure for the chaotic demodulation of the class of algebraic chaotic systems is described and discussed. The proposed procedure also allows one to directly identify a suitable 'response' system and the 'drive signal'. Moreover, it is shown that sliding differentiators can be used to reconstruct the time derivatives of the observable, and thus the information signal is recovered at the receiving end through some simple signal-processing operations such as multiplication, addition and subtraction. This allows the estimation of the system state and of the input signal (i.e., the information recovery) in a finite time

  13. Wind estimation around the shipwreck of Oriental Star based on field damage surveys and radar observations.

    Science.gov (United States)

    Meng, Zhiyong; Yao, Dan; Bai, Lanqiang; Zheng, Yongguang; Xue, Ming; Zhang, Xiaoling; Zhao, Kun; Tian, Fuyou; Wang, Mingjun

    Based on observational analyses and on-site ground and aerial damage surveys, this work aims to reveal the weather phenomena-especially the wind situation-when Oriental Star capsized in the Yangtze River on June 1, 2015. Results demonstrate that the cruise ship capsized when it encountered strong winds at speeds of at least 31 m s -1 near the apex of a bow echo embedded in a squall line. As suggested by the fallen trees within a 2-km radius around the wreck location, such strong winds were likely caused by microburst straight-line wind and/or embedded small vortices, rather than tornadoes.

  14. Chaos suppression via observer based active control scheme: Application to Duffing's oscillator

    International Nuclear Information System (INIS)

    Aguilar-Lopez, Ricardo; Martinez-Guerra, Rafael

    2007-01-01

    The aim of this paper is the synthesis of a robust control law for chaos suppression of a class of non-linear oscillator with affine control input. A robust state observer based active controller, which provides robustness against model uncertainties and noisy output measurements is proposed. The closed-loop stability for the underlying closed-loop system is done via the regulation and estimation errors dynamics. The performance of the proposed control law is illustrated with numerical simulations. The method is general and can be applied to various non-linear systems which satisfy the conditions required

  15. Decay in blood loss estimation skills after web-based didactic training.

    Science.gov (United States)

    Toledo, Paloma; Eosakul, Stanley T; Goetz, Kristopher; Wong, Cynthia A; Grobman, William A

    2012-02-01

    Accuracy in blood loss estimation has been shown to improve immediately after didactic training. The objective of this study was to evaluate retention of blood loss estimation skills 9 months after a didactic web-based training. Forty-four participants were recruited from a cohort that had undergone web-based training and testing in blood loss estimation. The web-based posttraining test, consisting of pictures of simulated blood loss, was repeated 9 months after the initial training and testing. The primary outcome was the difference in accuracy of estimated blood loss (percent error) at 9 months compared with immediately posttraining. At the 9-month follow-up, the median error in estimation worsened to -34.6%. Although better than the pretraining error of -47.8% (P = 0.003), the 9-month error was significantly less accurate than the immediate posttraining error of -13.5% (P = 0.01). Decay in blood loss estimation skills occurs by 9 months after didactic training.

  16. An accurate Kriging-based regional ionospheric model using combined GPS/BeiDou observations

    Science.gov (United States)

    Abdelazeem, Mohamed; Çelik, Rahmi N.; El-Rabbany, Ahmed

    2018-01-01

    In this study, we propose a regional ionospheric model (RIM) based on both of the GPS-only and the combined GPS/BeiDou observations for single-frequency precise point positioning (SF-PPP) users in Europe. GPS/BeiDou observations from 16 reference stations are processed in the zero-difference mode. A least-squares algorithm is developed to determine the vertical total electron content (VTEC) bi-linear function parameters for a 15-minute time interval. The Kriging interpolation method is used to estimate the VTEC values at a 1 ° × 1 ° grid. The resulting RIMs are validated for PPP applications using GNSS observations from another set of stations. The SF-PPP accuracy and convergence time obtained through the proposed RIMs are computed and compared with those obtained through the international GNSS service global ionospheric maps (IGS-GIM). The results show that the RIMs speed up the convergence time and enhance the overall positioning accuracy in comparison with the IGS-GIM model, particularly the combined GPS/BeiDou-based model.

  17. A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model

    International Nuclear Information System (INIS)

    Wei, Zhongbao; Zhao, Jiyun; Ji, Dongxu; Tseng, King Jet

    2017-01-01

    Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.

  18. Disease prevalence estimations based on contact registrations in general practice

    NARCIS (Netherlands)

    Hoogenveen, Rudolf; Westert, Gert; Dijkgraaf, Marcel; Schellevis, François; de Bakker, Dinny

    2002-01-01

    This paper describes how to estimate the prevalence of chronic diseases in a population using data from contact registrations in general practice with a limited time length. Instead of using only total numbers of observed patients adjusted for the length of the observation period, we propose the use

  19. Flood Damage and Loss Estimation for Iowa on Web-based Systems using HAZUS

    Science.gov (United States)

    Yildirim, E.; Sermet, M. Y.; Demir, I.

    2016-12-01

    Importance of decision support systems for flood emergency response and loss estimation increases with its social and economic impacts. To estimate the damage of the flood, there are several software systems available to researchers and decision makers. HAZUS-MH is one of the most widely used desktop program, developed by FEMA (Federal Emergency Management Agency), to estimate economic loss and social impacts of disasters such as earthquake, hurricane and flooding (riverine and coastal). HAZUS used loss estimation methodology and implements through geographic information system (GIS). HAZUS contains structural, demographic, and vehicle information across United States. Thus, it allows decision makers to understand and predict possible casualties and damage of the floods by running flood simulations through GIS application. However, it doesn't represent real time conditions because of using static data. To close this gap, an overview of a web-based infrastructure coupling HAZUS and real time data provided by IFIS (Iowa Flood Information System) is presented by this research. IFIS is developed by the Iowa Flood Center, and a one-stop web-platform to access community-based flood conditions, forecasts, visualizations, inundation maps and flood-related data, information, and applications. Large volume of real-time observational data from a variety of sensors and remote sensing resources (radars, rain gauges, stream sensors, etc.) and flood inundation models are staged on a user-friendly maps environment that is accessible to the general public. Providing cross sectional analyses between HAZUS-MH and IFIS datasets, emergency managers are able to evaluate flood damage during flood events easier and more accessible in real time conditions. With matching data from HAZUS-MH census tract layer and IFC gauges, economical effects of flooding can be observed and evaluated by decision makers. The system will also provide visualization of the data by using augmented reality for

  20. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  1. Estimating Zenith Tropospheric Delays from BeiDou Navigation Satellite System Observations

    Directory of Open Access Journals (Sweden)

    Xin Sui

    2013-04-01

    Full Text Available The GNSS derived Zenith Tropospheric Delay (ZTD plays today a very critical role in meteorological study and weather forecasts, as ZTDs of thousands of GNSS stations are operationally assimilated into numerical weather prediction models. Recently, the Chinese BeiDou Navigation Satellite System (BDS was officially announced to provide operational services around China and its neighborhood and it was demonstrated to be very promising for precise navigation and positioning. In this contribution, we concentrate on estimating ZTD using BDS observations to assess its capacity for troposphere remote sensing. A local network which is about 250 km from Beijing and comprised of six stations equipped with GPS- and BDS-capable receivers is utilized. Data from 5 to 8 November 2012 collected on the network is processed in network mode using precise orbits and in Precise Point Positioning mode using precise orbits and clocks. The precise orbits and clocks are generated from a tracking network with most of the stations in China and several stations around the world. The derived ZTDs are compared with that estimated from GPS data using the final products of the International GNSS Service (IGS. The comparison shows that the bias and the standard deviation of the ZTD differences are about 2 mm and 5 mm, respectively, which are very close to the differences of GPS ZTD estimated using different software packages.

  2. Robust Diagnosis Method Based on Parameter Estimation for an Interturn Short-Circuit Fault in Multipole PMSM under High-Speed Operation.

    Science.gov (United States)

    Lee, Jewon; Moon, Seokbae; Jeong, Hyeyun; Kim, Sang Woo

    2015-11-20

    This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates the q-axis inductance (Lq) of the faulty PMSM to solve this problem. The proposed method also estimates the faulty phase and the value of G, which serves as an index of the severity of the fault. The q-axis current is used to estimate the faulty phase, the values of G and Lq. For this reason, two open-loop observers and an optimization method based on a particle-swarm are implemented. The q-axis current of a healthy PMSM is estimated by the open-loop observer with the parameters of a healthy PMSM. The Lq estimation significantly compensates for the estimation errors in high-speed operation. The experimental results demonstrate that the proposed method can estimate the faulty phase, G, and Lq besides exhibiting robustness against parameter uncertainties.

  3. Covariance specification and estimation to improve top-down Green House Gas emission estimates

    Science.gov (United States)

    Ghosh, S.; Lopez-Coto, I.; Prasad, K.; Whetstone, J. R.

    2015-12-01

    The National Institute of Standards and Technology (NIST) operates the North-East Corridor (NEC) project and the Indianapolis Flux Experiment (INFLUX) in order to develop measurement methods to quantify sources of Greenhouse Gas (GHG) emissions as well as their uncertainties in urban domains using a top down inversion method. Top down inversion updates prior knowledge using observations in a Bayesian way. One primary consideration in a Bayesian inversion framework is the covariance structure of (1) the emission prior residuals and (2) the observation residuals (i.e. the difference between observations and model predicted observations). These covariance matrices are respectively referred to as the prior covariance matrix and the model-data mismatch covariance matrix. It is known that the choice of these covariances can have large effect on estimates. The main objective of this work is to determine the impact of different covariance models on inversion estimates and their associated uncertainties in urban domains. We use a pseudo-data Bayesian inversion framework using footprints (i.e. sensitivities of tower measurements of GHGs to surface emissions) and emission priors (based on Hestia project to quantify fossil-fuel emissions) to estimate posterior emissions using different covariance schemes. The posterior emission estimates and uncertainties are compared to the hypothetical truth. We find that, if we correctly specify spatial variability and spatio-temporal variability in prior and model-data mismatch covariances respectively, then we can compute more accurate posterior estimates. We discuss few covariance models to introduce space-time interacting mismatches along with estimation of the involved parameters. We then compare several candidate prior spatial covariance models from the Matern covariance class and estimate their parameters with specified mismatches. We find that best-fitted prior covariances are not always best in recovering the truth. To achieve

  4. Frequency Estimator Performance for a Software-Based Beacon Receiver

    Science.gov (United States)

    Zemba, Michael J.; Morse, Jacquelynne Rose; Nessel, James A.; Miranda, Felix

    2014-01-01

    As propagation terminals have evolved, their design has trended more toward a software-based approach that facilitates convenient adjustment and customization of the receiver algorithms. One potential improvement is the implementation of a frequency estimation algorithm, through which the primary frequency component of the received signal can be estimated with a much greater resolution than with a simple peak search of the FFT spectrum. To select an estimator for usage in a QV-band beacon receiver, analysis of six frequency estimators was conducted to characterize their effectiveness as they relate to beacon receiver design.

  5. An Adaptive Observer-Based Algorithm for Solving Inverse Source Problem for the Wave Equation

    KAUST Repository

    Asiri, Sharefa M.; Zayane, Chadia; Laleg-Kirati, Taous-Meriem

    2015-01-01

    Observers are well known in control theory. Originally designed to estimate the hidden states of dynamical systems given some measurements, the observers scope has been recently extended to the estimation of some unknowns, for systems governed by partial differential equations. In this paper, observers are used to solve inverse source problem for a one-dimensional wave equation. An adaptive observer is designed to estimate the state and source components for a fully discretized system. The effectiveness of the algorithm is emphasized in noise-free and noisy cases and an insight on the impact of measurements’ size and location is provided.

  6. An Adaptive Observer-Based Algorithm for Solving Inverse Source Problem for the Wave Equation

    KAUST Repository

    Asiri, Sharefa M.

    2015-08-31

    Observers are well known in control theory. Originally designed to estimate the hidden states of dynamical systems given some measurements, the observers scope has been recently extended to the estimation of some unknowns, for systems governed by partial differential equations. In this paper, observers are used to solve inverse source problem for a one-dimensional wave equation. An adaptive observer is designed to estimate the state and source components for a fully discretized system. The effectiveness of the algorithm is emphasized in noise-free and noisy cases and an insight on the impact of measurements’ size and location is provided.

  7. Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

    Science.gov (United States)

    Soheili, Mahmoud; (Tom) Rientjes, T. H. M.; (Christiaan) van der Tol, C.

    2017-04-01

    Groundwater movement is influenced by several factors and processes in the hydrological cycle, from which, recharge is of high relevance. Since the amount of aquifer extractable water directly relates to the recharge amount, estimation of recharge is a perquisite of groundwater resources management. Recharge is highly affected by water loss mechanisms the major of which is actual evapotranspiration (ETa). It is, therefore, essential to have detailed assessment of ETa impact on groundwater recharge. The objective of this study was to evaluate how recharge was affected when satellite-based evapotranspiration was used instead of in-situ based ETa in the Salland area, the Netherlands. The Methodology for Interactive Planning for Water Management (MIPWA) model setup which includes a groundwater model for the northern part of the Netherlands was used for recharge estimation. The Surface Energy Balance Algorithm for Land (SEBAL) based actual evapotranspiration maps from Waterschap Groot Salland were also used. Comparison of SEBAL based ETa estimates with in-situ abased estimates in the Netherlands showed that these SEBAL estimates were not reliable. As such results could not serve for calibrating root zone parameters in the CAPSIM model. The annual cumulative ETa map produced by the model showed that the maximum amount of evapotranspiration occurs in mixed forest areas in the northeast and a portion of central parts. Estimates ranged from 579 mm to a minimum of 0 mm in the highest elevated areas with woody vegetation in the southeast of the region. Variations in mean seasonal hydraulic head and groundwater level for each layer showed that the hydraulic gradient follows elevation in the Salland area from southeast (maximum) to northwest (minimum) of the region which depicts the groundwater flow direction. The mean seasonal water balance in CAPSIM part was evaluated to represent recharge estimation in the first layer. The highest recharge estimated flux was for autumn

  8. Estimating Allee dynamics before they can be observed: polar bears as a case study.

    Directory of Open Access Journals (Sweden)

    Péter K Molnár

    Full Text Available Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus, and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori

  9. Optimal estimation retrieval of aerosol microphysical properties from SAGE II satellite observations in the volcanically unperturbed lower stratosphere

    Directory of Open Access Journals (Sweden)

    T. Deshler

    2010-05-01

    Full Text Available Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003. An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities, even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal size

  10. Optimal estimation retrieval of aerosol microphysical properties from SAGE~II satellite observations in the volcanically unperturbed lower stratosphere

    Science.gov (United States)

    Wurl, D.; Grainger, R. G.; McDonald, A. J.; Deshler, T.

    2010-05-01

    Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003). An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE) method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths) with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities), even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal) size distributions naturally

  11. Template-Based Estimation of Time-Varying Tempo

    Directory of Open Access Journals (Sweden)

    Peeters Geoffroy

    2007-01-01

    Full Text Available We present a novel approach to automatic estimation of tempo over time. This method aims at detecting tempo at the tactus level for percussive and nonpercussive audio. The front-end of our system is based on a proposed reassigned spectral energy flux for the detection of musical events. The dominant periodicities of this flux are estimated by a proposed combination of discrete Fourier transform and frequency-mapped autocorrelation function. The most likely meter, beat, and tatum over time are then estimated jointly using proposed meter/beat subdivision templates and a Viterbi decoding algorithm. The performances of our system have been evaluated on four different test sets among which three were used during the ISMIR 2004 tempo induction contest. The performances obtained are close to the best results of this contest.

  12. Robust observer based control for axial offset in pressurized-water nuclear reactors based on the multipoint reactor model using Lyapunov approach

    Energy Technology Data Exchange (ETDEWEB)

    Zaidabadinejad, Majid; Ansarifar, Gholam Reza [Isfahan Univ. (Iran, Islamic Republic of). Dept. of Nuclear Engineering

    2017-11-15

    In nuclear reactor imbalance of axial power distribution induces xenon oscillations. These fluctuations must be maintained bounded within allowable limits. Otherwise, the nuclear power plant could become unstable. Therefore, bounded these oscillations is considered to be a restriction for the load following operation. Also, in order to design the nuclear reactor control systems, poisons concentrations, especially xenon must be accessible. But, physical measurement of these parameters is impossible. In this paper, for the first time, in order to estimate the axial xenon oscillations and ensures these oscillations are kept bounded within allowable limits during load-following operation, a robust observer based nonlinear control based on multipoint kinetics reactor model for pressurized-water nuclear reactors is presented. The reactor core is simulated based on the multi-point nuclear reactor model (neutronic and thermal-hydraulic). Simulation results are presented to demonstrate the effectiveness of the proposed observer based controller for the load-following operation.

  13. Robust observer based control for axial offset in pressurized-water nuclear reactors based on the multipoint reactor model using Lyapunov approach

    International Nuclear Information System (INIS)

    Zaidabadinejad, Majid; Ansarifar, Gholam Reza

    2017-01-01

    In nuclear reactor imbalance of axial power distribution induces xenon oscillations. These fluctuations must be maintained bounded within allowable limits. Otherwise, the nuclear power plant could become unstable. Therefore, bounded these oscillations is considered to be a restriction for the load following operation. Also, in order to design the nuclear reactor control systems, poisons concentrations, especially xenon must be accessible. But, physical measurement of these parameters is impossible. In this paper, for the first time, in order to estimate the axial xenon oscillations and ensures these oscillations are kept bounded within allowable limits during load-following operation, a robust observer based nonlinear control based on multipoint kinetics reactor model for pressurized-water nuclear reactors is presented. The reactor core is simulated based on the multi-point nuclear reactor model (neutronic and thermal-hydraulic). Simulation results are presented to demonstrate the effectiveness of the proposed observer based controller for the load-following operation.

  14. Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach.

    Science.gov (United States)

    Alexakis, Dimitrios D; Mexis, Filippos-Dimitrios K; Vozinaki, Anthi-Eirini K; Daliakopoulos, Ioannis N; Tsanis, Ioannis K

    2017-06-21

    A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R² values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.

  15. Dynamic variability of the heading-flowering stages of single rice in China based on field observations and NDVI estimations.

    Science.gov (United States)

    Zhang, Zhao; Song, Xiao; Chen, Yi; Wang, Pin; Wei, Xing; Tao, Fulu

    2015-05-01

    Although many studies have indicated the consistent impact of warming on the natural ecosystem (e.g., an early flowering and prolonged growing period), our knowledge of the impacts on agricultural systems is still poorly understood. In this study, spatiotemporal variability of the heading-flowering stages of single rice was detected and compared at three different scales using field-based methods (FBMs) and satellite-based methods (SBMs). The heading-flowering stages from 2000 to 2009 with a spatial resolution of 1 km were extracted from the SPOT/VGT NDVI time series data using the Savizky-Golay filtering method in the areas in China dominated by single rice of Northeast China (NE), the middle-lower Yangtze River Valley (YZ), the Sichuan Basin (SC), and the Yunnan-Guizhou Plateau (YG). We found that approximately 52.6 and 76.3 % of the estimated heading-flowering stages by a SBM were within ±5 and ±10 days estimation error (a root mean square error (RMSE) of 8.76 days) when compared with those determined by a FBM. Both the FBM data and the SBM data had indicated a similar spatial pattern, with the earliest annual average heading-flowering stages in SC, followed by YG, NE, and YZ, which were inconsistent with the patterns reported in natural ecosystems. Moreover, diverse temporal trends were also detected in the four regions due to different climate conditions and agronomic factors such as cultivar shifts. Nevertheless, there were no significant differences (p > 0.05) between the FBM and the SBM in both the regional average value of the phenological stages and the trends, implying the consistency and rationality of the SBM at three scales.

  16. Artificial Neural Network Based State Estimators Integrated into Kalmtool

    DEFF Research Database (Denmark)

    Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad

    2012-01-01

    In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation as...

  17. Capacitance Estimation for DC-link Capacitors in a Back-to-Back Converter Based on Artificial Neural Network Algorithm

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Wang, Huai; Blaabjerg, Frede

    2016-01-01

    of the aforementioned challenges and shortcomings. In this paper, a pure software condition monitoring method based on Artificial Neural Network (ANN) algorithm is proposed. The implemented ANN estimates the capacitance of the dc-link capacitor in a back-to-back converter. The error analysis of the estimated results......The reliability of dc-link capacitors in power electronic converters is one of the critical aspects to be considered in modern power converter design. The observation of their ageing process and the estimation of their health status have been an attractive subject for the industrial field and hence...

  18. Estimating particle number size distributions from multi-instrument observations with Kalman Filtering

    Energy Technology Data Exchange (ETDEWEB)

    Viskari, T.

    2012-07-01

    Atmospheric aerosol particles have several important effects on the environment and human society. The exact impact of aerosol particles is largely determined by their particle size distributions. However, no single instrument is able to measure the whole range of the particle size distribution. Estimating a particle size distribution from multiple simultaneous measurements remains a challenge in aerosol physical research. Current methods to combine different measurements require assumptions concerning the overlapping measurement ranges and have difficulties in accounting for measurement uncertainties. In this thesis, Extended Kalman Filter (EKF) is presented as a promising method to estimate particle number size distributions from multiple simultaneous measurements. The particle number size distribution estimated by EKF includes information from prior particle number size distributions as propagated by a dynamical model and is based on the reliabilities of the applied information sources. Known physical processes and dynamically evolving error covariances constrain the estimate both over time and particle size. The method was tested with measurements from Differential Mobility Particle Sizer (DMPS), Aerodynamic Particle Sizer (APS) and nephelometer. The particle number concentration was chosen as the state of interest. The initial EKF implementation presented here includes simplifications, yet the results are positive and the estimate successfully incorporated information from the chosen instruments. For particle sizes smaller than 4 micrometers, the estimate fits the available measurements and smooths the particle number size distribution over both time and particle diameter. The estimate has difficulties with particles larger than 4 micrometers due to issues with both measurements and the dynamical model in that particle size range. The EKF implementation appears to reduce the impact of measurement noise on the estimate, but has a delayed reaction to sudden

  19. Population estimates and geographical distributions of swans and geese in East Asia based on counts during the non-breeding season

    DEFF Research Database (Denmark)

    Jia, Qiang; Koyama, Kazuo; Choi, Chang-Yong

    2016-01-01

    For the first time, we estimated the population sizes of two swan species and four goose species from observations during the non-breeding period in East Asia. Based on combined counts from South Korea, Japan and China, we estimated the total abundance of these species as follows: 42,000–47,000 W......For the first time, we estimated the population sizes of two swan species and four goose species from observations during the non-breeding period in East Asia. Based on combined counts from South Korea, Japan and China, we estimated the total abundance of these species as follows: 42......,000–47,000 Whooper Swans Cygnus cygnus ; 99,000–141,000 Tundra Swans C. columbianus bewickii ; 56,000–98,000 Swan Geese Anser cygnoides ; 157,000–194,000 Bean Geese A. fabalis ; 231,000–283,000 Greater White-fronted Geese A. albifrons ; and 14,000–19,000 Lesser White-fronted Geese A. erythropus. While the count data...... from Korea and Japan provide a good reflection of numbers present, there remain gaps in the coverage in China, which particularly affect the precision of the estimates for Bean, Greater and Lesser White-fronted Geese as well as Tundra Swans. Lack of subspecies distinction of Bean Geese in China until...

  20. Accuracy of visual wave observation from merchant ships and estimated wave loads; Accuracy of visual wave observation from merchant ships and estimated wave loads

    Energy Technology Data Exchange (ETDEWEB)

    Kawabe, H. [National Defense Academy, Kanagawa (Japan); Masaoka, K. [University of Osaka Prefecture, Osaka (Japan). Faculty of Engineering

    1998-06-01

    There is a large number of studies on discussions concerning accuracy of visual observation of waves and the correction method thereon. This paper give considerations on observation accuracy placing a viewpoint on that by merchant ships. Based on ship meteorological observation tables reported to the Meteorological Agency of Japan on meteorology in North Pacific during 14 years from 1976 to1989, wave observation values taken by merchant ships and observation ships were compared statistically to investigate the accuracy of visual wave observations carried out by merchant ships. With regard to wave heights, the observation values taken by the observation ships and the merchant ships have strong correlation, where the merchant ships evaluate them somewhat higher than the observation ships. Regarding wave cycles of wind waves, the merchant ships tend to have the observation values on longer cycle side. Correlation between the observations values by the merchant ships and the observation ships is weak both in wind waves and swells. There is not much of variation in accuracy of observations during daytime and at night performed by the merchant ships. It will be necessary in the future to give considerations on a method to correct the observation values on wave cycles taken by the merchant ship, and on a correction method in which both of the wave cycles and the wave heights are corrected simultaneously to make the observation values of the merchant ship equal to those of the observation ships. Thus, the observation values reported by general merchant ships in a large number every year will have to be utilized more effectively. 11 refs., 21 figs., 2 tabs.

  1. Application of Cherenkov light observation to reactor measurements (1). Estimation of reactor power from Cherenkov light intensity

    International Nuclear Information System (INIS)

    Yamamoto, Keiichi; Takeuchi, Tomoaki; Kimura, Nobuaki; Ohtsuka, Noriaki; Tsuchiya, Kunihiko; Sano, Tadafumi; Nakajima, Ken; Homma, Ryohei; Kosuge, Fumiaki

    2015-01-01

    Development of the reactor measurement system was started to obtain the real-time in-core nuclear and thermal information, where the quantitative measurement of brightness of Cherenkov light was investigated. The system would be applied as a monitoring system in severe accidents and for the advanced operation management technology in existing LWRs. The calculation and the observation were performed to obtain the quantity of the Cherenkov light caused by the gamma and beta rays emitted from the fuels in the core of Kyoto University Research Reactor. The results indicate that the real-time reactor power can be estimated from the brightness of the Cherenkov light observed by a CCD camera. This method can also work for the estimation of the burn-up of spent fuels at commercial reactors. Since the observed brightness value of the Cherenkov light was influenced by the camera position, the optical observation method should be improved to achieve high accuracy observation. (author)

  2. Automated mode shape estimation in agent-based wireless sensor networks

    Science.gov (United States)

    Zimmerman, Andrew T.; Lynch, Jerome P.

    2010-04-01

    Recent advances in wireless sensing technology have made it possible to deploy dense networks of sensing transducers within large structural systems. Because these networks leverage the embedded computing power and agent-based abilities integral to many wireless sensing devices, it is possible to analyze sensor data autonomously and in-network. In this study, market-based techniques are used to autonomously estimate mode shapes within a network of agent-based wireless sensors. Specifically, recent work in both decentralized Frequency Domain Decomposition and market-based resource allocation is leveraged to create a mode shape estimation algorithm derived from free-market principles. This algorithm allows an agent-based wireless sensor network to autonomously shift emphasis between improving mode shape accuracy and limiting the consumption of certain scarce network resources: processing time, storage capacity, and power consumption. The developed algorithm is validated by successfully estimating mode shapes using a network of wireless sensor prototypes deployed on the mezzanine balcony of Hill Auditorium, located on the University of Michigan campus.

  3. Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

    Directory of Open Access Journals (Sweden)

    Yun Li

    2013-01-01

    Full Text Available A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.

  4. DOA and Pitch Estimation of Audio Sources using IAA-based Filtering

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll

    2014-01-01

    For decades, it has been investigated how to separately solve the problems of both direction-of-arrival (DOA) and pitch estimation. Recently, it was found that estimating these parameters jointly from multichannel recordings of audio can be extremely beneficial. Many joint estimators are based...... on knowledge of the inverse sample covariance matrix. Typically, this covariance is estimated using the sample covariance matrix, but for this estimate to be full rank, many temporal samples are needed. In cases with non-stationary signals, this is a serious limitation. We therefore investigate how a recent...... joint DOA and pitch filtering-based estimator can be combined with the iterative adaptive approach to circumvent this limitation in joint DOA and pitch estimation of audio sources. Simulations show a clear improvement compared to when using the sample covariance matrix and the considered approach also...

  5. Tropical cyclones-Pacific Asian Research Campaign for Improvement of Intensity estimations/forecasts (T-PARCII): A research plan of typhoon aircraft observations in Japan

    Science.gov (United States)

    Tsuboki, Kazuhisa

    2017-04-01

    Typhoons are the most devastating weather system occurring in the western North Pacific and the South China Sea. Violent wind and heavy rainfall associated with a typhoon cause huge disaster in East Asia including Japan. In 2013, Supertyphoon Haiyan struck the Philippines caused a very high storm surge and more than 7000 people were killed. In 2015, two typhoons approached the main islands of Japan and severe flood occurred in the northern Kanto region. Typhoons are still the largest cause of natural disaster in East Asia. Moreover, many researches have projected increase of typhoon intensity with the climate change. This suggests that a typhoon risk is increasing in East Asia. However, the historical data of typhoon include large uncertainty. In particular, intensity data of the most intense typhoon category have larger error after the US aircraft reconnaissance of typhoon was terminated in 1987.The main objective of the present study is improvements of typhoon intensity estimations and of forecasts of intensity and track. We will perform aircraft observation of typhoon and the observed data are assimilated to numerical models to improve intensity estimation. Using radars and balloons, observations of thermodynamical and cloud-microphysical processes of typhoons will be also performed to improve physical processes of numerical model. In typhoon seasons (mostly in August and September), we will perform aircraft observations of typhoons. Using dropsondes from the aircraft, temperature, humidity, pressure, and wind are measured in surroundings of the typhoon inner core region. The dropsonde data are assimilated to a cloud-resolving model which has been developed in Nagoya University and named the Cloud Resolving Storm Simulator (CReSS). Then, more accurate estimations and forecasts of the typhoon intensity will be made as well as typhoon tracks. Furthermore, we will utilize a ground-based balloon with microscope camera, X-band precipitation radar, Ka-band cloud radar

  6. Intra-Urban Movement Flow Estimation Using Location Based Social Networking Data

    Science.gov (United States)

    Kheiri, A.; Karimipour, F.; Forghani, M.

    2015-12-01

    In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience. Location-based social network data, as a new travel demand data source, seems to be an alternative or complement to survey data in the study of mobility behavior and activity analysis because of its relatively high access and low cost. In this paper, three OD estimation models have been utilized in order to investigate their relative performance when using Location-Based Social Networking (LBSN) data. For this, the Foursquare LBSN data was used to analyze the intra-urban movement behavioral patterns for the study area, Manhattan, the most densely populated of the five boroughs of New York city. The outputs of models are evaluated using real observations based on different criterions including distance distribution, destination travel constraints. The results demonstrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.

  7. INTRA-URBAN MOVEMENT FLOW ESTIMATION USING LOCATION BASED SOCIAL NETWORKING DATA

    Directory of Open Access Journals (Sweden)

    A. Kheiri

    2015-12-01

    Full Text Available In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience. Location-based social network data, as a new travel demand data source, seems to be an alternative or complement to survey data in the study of mobility behavior and activity analysis because of its relatively high access and low cost. In this paper, three OD estimation models have been utilized in order to investigate their relative performance when using Location-Based Social Networking (LBSN data. For this, the Foursquare LBSN data was used to analyze the intra-urban movement behavioral patterns for the study area, Manhattan, the most densely populated of the five boroughs of New York city. The outputs of models are evaluated using real observations based on different criterions including distance distribution, destination travel constraints. The results demonstrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.

  8. Adaptive Spectral Doppler Estimation

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jakobsson, Andreas; Jensen, Jørgen Arendt

    2009-01-01

    . The methods can also provide better quality of the estimated power spectral density (PSD) of the blood signal. Adaptive spectral estimation techniques are known to pro- vide good spectral resolution and contrast even when the ob- servation window is very short. The 2 adaptive techniques are tested......In this paper, 2 adaptive spectral estimation techniques are analyzed for spectral Doppler ultrasound. The purpose is to minimize the observation window needed to estimate the spectrogram to provide a better temporal resolution and gain more flexibility when designing the data acquisition sequence...... and compared with the averaged periodogram (Welch’s method). The blood power spectral capon (BPC) method is based on a standard minimum variance technique adapted to account for both averaging over slow-time and depth. The blood amplitude and phase estimation technique (BAPES) is based on finding a set...

  9. Dynamic surface tracking controller design for a constrained hypersonic vehicle based on disturbance observer

    Directory of Open Access Journals (Sweden)

    Fang Wang

    2017-05-01

    Full Text Available The tracking control problem of a flexible air-breathing hypersonic vehicle subjects to aerodynamic parameter uncertainty and input constraint is investigated by combining nonlinear disturbance observer and dynamic surface control. To design controller simply, a control-oriented model is firstly derived and divided into two subsystems, velocity subsystem and altitude subsystem based on the engineering backgrounds of flexible air-breathing hypersonic vehicle. In every subsystem, compounded disturbances are included to consider aerodynamic uncertainty and the effect of the flexible modes. Then, disturbance observer is not only used to handle the compounded disturbance but also to handle the input constraint, where the estimation error converges to a random small region through appropriately choosing the observer parameters. To sequel, the disturbance observer–based robust control scheme and the disturbance observer-based dynamic surface control scheme are developed for the velocity subsystem and altitude subsystem, respectively. Besides, novel filters are designed to alleviate the problem of “explosion of terms” induced by backstepping method. On the basis of Lyapunov stability theory, the presented control scheme can assure that tracking error converges to an arbitrarily small neighborhood around zero by rigorous theoretical analysis. At last, simulation result shows the effectiveness of the presented control method.

  10. Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity

    Science.gov (United States)

    Xu, Li; Shan, Lin; Adachi, Fumiyuki

    2014-01-01

    In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting intersymbol interference (ISI) over data transmission. Broadband channel model is often described by very few dominant channel taps and they can be probed by compressive sensing based sparse channel estimation (SCE) methods, for example, orthogonal matching pursuit algorithm, which can take the advantage of sparse structure effectively in the channel as for prior information. However, these developed methods are vulnerable to both noise interference and column coherence of training signal matrix. In other words, the primary objective of these conventional methods is to catch the dominant channel taps without a report of posterior channel uncertainty. To improve the estimation performance, we proposed a compressive sensing based Bayesian sparse channel estimation (BSCE) method which cannot only exploit the channel sparsity but also mitigate the unexpected channel uncertainty without scarifying any computational complexity. The proposed method can reveal potential ambiguity among multiple channel estimators that are ambiguous due to observation noise or correlation interference among columns in the training matrix. Computer simulations show that proposed method can improve the estimation performance when comparing with conventional SCE methods. PMID:24983012

  11. Estimate-Merge-Technique-based algorithms to track an underwater ...

    Indian Academy of Sciences (India)

    D V A N Ravi Kumar

    2017-07-04

    Jul 4, 2017 ... In this paper, two novel methods based on the Estimate Merge Technique ... mentioned advantages of the proposed novel methods is shown by carrying out Monte Carlo simulation in .... equations are converted to sequential equations to make ... estimation error and low convergence time) at feasibly high.

  12. Observer-Based Load Frequency Control for Island Microgrid with Photovoltaic Power

    Directory of Open Access Journals (Sweden)

    Chaoxu Mu

    2017-01-01

    Full Text Available As renewable energy is widely integrated into the power system, the stochastic and intermittent power generation from renewable energy may cause system frequency deviating from the prescribed level, especially for a microgrid. In this paper, the load frequency control (LFC of an island microgrid with photovoltaic (PV power and electric vehicles (EVs is investigated, where the EVs can be treated as distributed energy storages. Considering the disturbances from load change and PV power, an observer-based integral sliding mode (OISM controller is designed to regulate the frequency back to the prescribed value, where the neural network observer is used to online estimate the PV power. Simulation studies on a benchmark microgrid system are presented to illustrate the effectiveness of OISM controller, and comparative results also demonstrate that the proposed method has a superior performance for stabilizing the frequency over the PID control.

  13. Increasing precision of turbidity-based suspended sediment concentration and load estimates.

    Science.gov (United States)

    Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

    2010-01-01

    Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.

  14. On sliding mode observer for a hybrid three-cell converter

    KAUST Repository

    Khelouat, Samir

    2013-10-01

    In this paper, we propose a sliding mode observer to estimate the capacitor voltages of the 3-cell converter. New concept recently introduced, based on geometrical condition for observability analysis is used. The convergence of estimation error based on the solution of an LMI system is shown. Finally, illustrative results are given in order to show the efficiency of the designed observer. © 2013 IEEE.

  15. Observer-Based Perturbation Extremum Seeking Control with Input Constraints for Direct-Contact Membrane Distillation Process

    KAUST Repository

    Eleiwi, Fadi

    2017-05-08

    An Observer-based Perturbation Extremum Seeking Control (PESC) is proposed for a Direct-Contact Membrane Distillation (DCMD) process. The process is described with a dynamic model that is based on a 2D Advection-Diffusion Equation (ADE) model which has pump flow rates as process inputs. The objective of the controller is to optimize the trade-off between the permeate mass flux and the energy consumption by the pumps inside the process. Cases of single and multiple control inputs are considered through the use of only the feed pump flow rate or both the feed and the permeate pump flow rates. A nonlinear Lyapunov-based observer is designed to provide an estimation for the temperature distribution all over the designated domain of the DCMD process. Moreover, control inputs are constrained with an anti-windup technique to be within feasible and physical ranges. Performance of the proposed structure is analyzed, and simulations based on real DCMD process parameters for each control input are provided.

  16. Observer-based perturbation extremum seeking control with input constraints for direct-contact membrane distillation process

    Science.gov (United States)

    Eleiwi, Fadi; Laleg-Kirati, Taous Meriem

    2018-06-01

    An observer-based perturbation extremum seeking control is proposed for a direct-contact membrane distillation (DCMD) process. The process is described with a dynamic model that is based on a 2D advection-diffusion equation model which has pump flow rates as process inputs. The objective of the controller is to optimise the trade-off between the permeate mass flux and the energy consumption by the pumps inside the process. Cases of single and multiple control inputs are considered through the use of only the feed pump flow rate or both the feed and the permeate pump flow rates. A nonlinear Lyapunov-based observer is designed to provide an estimation for the temperature distribution all over the designated domain of the DCMD process. Moreover, control inputs are constrained with an anti-windup technique to be within feasible and physical ranges. Performance of the proposed structure is analysed, and simulations based on real DCMD process parameters for each control input are provided.

  17. Prospects for Observing Ultracompact Binaries with Space-Based Gravitational Wave Interferometers and Optical Telescopes

    Science.gov (United States)

    Littenberg, T. B.; Larson, S. L.; Nelemans, G.; Cornish, N. J.

    2012-01-01

    Space-based gravitational wave interferometers are sensitive to the galactic population of ultracompact binaries. An important subset of the ultracompact binary population are those stars that can be individually resolved by both gravitational wave interferometers and electromagnetic telescopes. The aim of this paper is to quantify the multimessenger potential of space-based interferometers with arm-lengths between 1 and 5 Gm. The Fisher information matrix is used to estimate the number of binaries from a model of the Milky Way which are localized on the sky by the gravitational wave detector to within 1 and 10 deg(exp 2) and bright enough to be detected by a magnitude-limited survey.We find, depending on the choice ofGW detector characteristics, limiting magnitude and observing strategy, that up to several hundred gravitational wave sources could be detected in electromagnetic follow-up observations.

  18. An Inverse Source Problem for a One-dimensional Wave Equation: An Observer-Based Approach

    KAUST Repository

    Asiri, Sharefa M.

    2013-01-01

    Observers are well known in the theory of dynamical systems. They are used to estimate the states of a system from some measurements. However, recently observers have also been developed to estimate some unknowns for systems governed by Partial

  19. A Probabilistic and Observation Based Methodology to Estimate Small Craft Harbor Vulnerability to Tsunami Events

    Science.gov (United States)

    Keen, A. S.; Lynett, P. J.; Ayca, A.

    2016-12-01

    Because of the damage resulting from the 2010 Chile and 2011 Japanese tele-tsunamis, the tsunami risk to the small craft marinas in California has become an important concern. The talk will outline an assessment tool which can be used to assess the tsunami hazard to small craft harbors. The methodology is based on the demand and structural capacity of the floating dock system, composed of floating docks/fingers and moored vessels. The structural demand is determined using a Monte Carlo methodology. Monte Carlo methodology is a probabilistic computational tool where the governing might be well known, but the independent variables of the input (demand) as well as the resisting structural components (capacity) may not be completely known. The Monte Carlo approach uses a distribution of each variable, and then uses that random variable within the described parameters, to generate a single computation. The process then repeats hundreds or thousands of times. The numerical model "Method of Splitting Tsunamis" (MOST) has been used to determine the inputs for the small craft harbors within California. Hydrodynamic model results of current speed, direction and surface elevation were incorporated via the drag equations to provide the bases of the demand term. To determine the capacities, an inspection program was developed to identify common features of structural components. A total of six harbors have been inspected ranging from Crescent City in Northern California to Oceanside Harbor in Southern California. Results from the inspection program were used to develop component capacity tables which incorporated the basic specifications of each component (e.g. bolt size and configuration) and a reduction factor (which accounts for the component reduction in capacity with age) to estimate in situ capacities. Like the demand term, these capacities are added probabilistically into the model. To date the model has been applied to Santa Cruz Harbor as well as Noyo River. Once

  20. Affordance estimation for vision-based object replacement on a humanoid robot

    DEFF Research Database (Denmark)

    Mustafa, Wail; Wächter, Mirko; Szedmak, Sandor

    2016-01-01

    In this paper, we address the problem of finding replacements of missing objects, involved in the execution of manipulation tasks. Our approach is based on estimating functional affordances for the unknown objects in order to propose replacements. We use a vision-based affordance estimation syste...

  1. Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

    Science.gov (United States)

    Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

    2018-06-01

    Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

  2. Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

    Science.gov (United States)

    Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

    2018-03-01

    Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

  3. Correction of Misclassifications Using a Proximity-Based Estimation Method

    Directory of Open Access Journals (Sweden)

    Shmulevich Ilya

    2004-01-01

    Full Text Available An estimation method for correcting misclassifications in signal and image processing is presented. The method is based on the use of context-based (temporal or spatial information in a sliding-window fashion. The classes can be purely nominal, that is, an ordering of the classes is not required. The method employs nonlinear operations based on class proximities defined by a proximity matrix. Two case studies are presented. In the first, the proposed method is applied to one-dimensional signals for processing data that are obtained by a musical key-finding algorithm. In the second, the estimation method is applied to two-dimensional signals for correction of misclassifications in images. In the first case study, the proximity matrix employed by the estimation method follows directly from music perception studies, whereas in the second case study, the optimal proximity matrix is obtained with genetic algorithms as the learning rule in a training-based optimization framework. Simulation results are presented in both case studies and the degree of improvement in classification accuracy that is obtained by the proposed method is assessed statistically using Kappa analysis.

  4. An integrated approach to estimate storage reliability with initial failures based on E-Bayesian estimates

    International Nuclear Information System (INIS)

    Zhang, Yongjin; Zhao, Ming; Zhang, Shitao; Wang, Jiamei; Zhang, Yanjun

    2017-01-01

    Storage reliability that measures the ability of products in a dormant state to keep their required functions is studied in this paper. For certain types of products, Storage reliability may not always be 100% at the beginning of storage, unlike the operational reliability, which exist possible initial failures that are normally neglected in the models of storage reliability. In this paper, a new integrated technique, the non-parametric measure based on the E-Bayesian estimates of current failure probabilities is combined with the parametric measure based on the exponential reliability function, is proposed to estimate and predict the storage reliability of products with possible initial failures, where the non-parametric method is used to estimate the number of failed products and the reliability at each testing time, and the parameter method is used to estimate the initial reliability and the failure rate of storage product. The proposed method has taken into consideration that, the reliability test data of storage products containing the unexamined before and during the storage process, is available for providing more accurate estimates of both the initial failure probability and the storage failure probability. When storage reliability prediction that is the main concern in this field should be made, the non-parametric estimates of failure numbers can be used into the parametric models for the failure process in storage. In the case of exponential models, the assessment and prediction method for storage reliability is presented in this paper. Finally, a numerical example is given to illustrate the method. Furthermore, a detailed comparison between the proposed and traditional method, for examining the rationality of assessment and prediction on the storage reliability, is investigated. The results should be useful for planning a storage environment, decision-making concerning the maximum length of storage, and identifying the production quality. - Highlights:

  5. Long-Term Geomagnetically Induced Current Observations From New Zealand: Peak Current Estimates for Extreme Geomagnetic Storms

    Science.gov (United States)

    Rodger, Craig J.; Mac Manus, Daniel H.; Dalzell, Michael; Thomson, Alan W. P.; Clarke, Ellen; Petersen, Tanja; Clilverd, Mark A.; Divett, Tim

    2017-11-01

    Geomagnetically induced current (GIC) observations made in New Zealand over 14 years show induction effects associated with a rapidly varying horizontal magnetic field (dBH/dt) during geomagnetic storms. This study analyzes the GIC observations in order to estimate the impact of extreme storms as a hazard to the power system in New Zealand. Analysis is undertaken of GIC in transformer number six in Islington, Christchurch (ISL M6), which had the highest observed currents during the 6 November 2001 storm. Using previously published values of 3,000 nT/min as a representation of an extreme storm with 100 year return period, induced currents of 455 A were estimated for Islington (with the 95% confidence interval range being 155-605 A). For 200 year return periods using 5,000 nT/min, current estimates reach 755 A (confidence interval range 155-910 A). GIC measurements from the much shorter data set collected at transformer number 4 in Halfway Bush, Dunedin, (HWB T4), found induced currents to be consistently a factor of 3 higher than at Islington, suggesting equivalent extreme storm effects of 460-1,815 A (100 year return) and 460-2,720 A (200 year return). An estimate was undertaken of likely failure levels for single-phase transformers, such as HWB T4 when it failed during the 6 November 2001 geomagnetic storm, identifying that induced currents of 100 A can put such transformer types at risk of damage. Detailed modeling of the New Zealand power system is therefore required to put this regional analysis into a global context.

  6. On-Orbit Camera Misalignment Estimation Framework and Its Application to Earth Observation Satellite

    Directory of Open Access Journals (Sweden)

    Seungwoo Lee

    2015-03-01

    Full Text Available Despite the efforts for precise alignment of imaging sensors and attitude sensors before launch, the accuracy of pre-launch alignment is limited. The misalignment between attitude frame and camera frame is especially important as it is related to the localization error of the spacecraft, which is one of the essential factors of satellite image quality. In this paper, a framework for camera misalignment estimation is presented with its application to a high-resolution earth-observation satellite—Deimos-2. The framework intends to provide a solution for estimation and correction of the camera misalignment of a spacecraft, covering image acquisition planning to mathematical solution of camera misalignment. Considerations for effective image acquisition planning to obtain reliable results are discussed, followed by a detailed description on a practical method for extracting many GCPs automatically using reference ortho-photos. Patterns of localization errors that commonly occur due to the camera misalignment are also investigated. A mathematical model for camera misalignment estimation is described comprehensively. The results of simulation experiments showing the validity and accuracy of the misalignment estimation model are provided. The proposed framework was applied to Deimos-2. The real-world data and results from Deimos-2 are presented.

  7. Frequency domain based LS channel estimation in OFDM based Power line communications

    OpenAIRE

    Bogdanović, Mario

    2015-01-01

    This paper is focused on low voltage power line communication (PLC) realization with an emphasis on channel estimation techniques. The Orthogonal Frequency Division Multiplexing (OFDM) scheme is preferred technology in PLC systems because of its effective combat with frequency selective fading properties of PLC channel. As the channel estimation is one of the crucial problems in OFDM based PLC system because of a problematic area of PLC signal attenuation and interference, the improved LS est...

  8. A novel flux estimator based on SOGI with FLL for induction machine drives

    DEFF Research Database (Denmark)

    Zhao, Rende; Xin, Zhen; Loh, Poh Chiang

    2016-01-01

    by the initial conditions with no need for the magnitude and phase compensation. Because the dc and harmonic components are inversely proportional to the speed in the estimated flux, the performance of the single SOGI-based estimator become worse at low speed. A multiple SOGI-based flux estimator is the proposed......It is very important to estimate flux accurately in implementing high-performance control of AC motors. Theoretical analysis has been made to illustrate the performance of the pure-integration-based and the Low-Pass Filter (LPF) based flux estimators. A novel flux estimator based on Second......-Order General Integrator (SOGI) with Frequency Locked-Loop (FLL) is investigated in this paper for induction machine drives. A single SOGI instead of pure integrator or LPF is used to integrate the back electromotive force (EMF). It can solve the problems of the integration saturation and the dc drift caused...

  9. CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

    Science.gov (United States)

    Thorsen, Tyler; Fu, Qiang

    2016-01-01

    Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at midlatitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30-50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

  10. Volume estimation of extensor muscles of the lower leg based on MR imaging

    International Nuclear Information System (INIS)

    Lund, Hans; Christensen, Line; Savnik, Anette; Danneskiold-Samsoee, Bente; Bliddal, Henning; Boesen, Jens

    2002-01-01

    Magnetic resonance imaging can be used to measure the muscle volume of a given muscle or muscle group. The purpose of this study was to determine both the intra- and inter-observer variation of the manually outlined volume of the extensor muscles (tibialis anterior, extensor digitorum longus and extensor hallucis longus), to estimate the minimum number of slices needed for these calculations and to compare estimates of volume based on an assumed conic shape of the muscles with that of an assumed cylindrical shape, the calculation in both cases based on the Cavalieri principle. Eleven young and healthy subjects (4 women and 7 men, age range 24-40 years) participated. Magnetic resonance imaging of the left leg was obtained on a 1.5-T MR system using a knee coil (receive only). A total of 50 consecutive slices were obtained beginning 10 cm below the caput fibula sin. and proceeding distally with a slice thickness of 1.5 mm without gap. The intra-class correlation coefficient (ICC) was used to calculate the relative reliability (interval from 0 to 1.0). A high reliability for both intra- and inter-reliability was observed (ICC 0.98 and 1.0). The difference was only 0.004% between calculations based on measurement of all 50 slices with respect to 8 slices equally distributed along the muscle group. No difference was found between the two different volumetric assumptions in the Cavalieri principle. The manually outlining of extensor muscles volumes was reliable and only 8 slices of the calf were needed. No difference was seen between the two used mathematical calculations. (orig.)

  11. Double-Capon and double-MUSICAL for arrival separation and observable estimation in an acoustic waveguide

    Science.gov (United States)

    Touzé, Grégoire Le; Nicolas, Barbara; Mars, Jérôme I.; Roux, Philippe; Oudompheng, Benoit

    2012-12-01

    Recent developments in shallow water ocean acoustic tomography propose the use of an original configuration composed of two source-receiver vertical arrays and wideband sources. The recording space thus has three dimensions, with two spatial dimensions and the frequency dimension. Using this recording space, it is possible to build a three-dimensional (3D) estimation space that gives access to the three observables associated with the acoustic arrivals: the direction of departure, the direction of arrivals, and the time of arrival. The main interest of this 3D estimation space is its capability for the separation of acoustic arrivals that usually interfere in the recording space, due to multipath propagation. A 3D estimator called double beamforming has already been developed, although it has limited resolution. In this study, the new 3D high-resolution estimators of double Capon and double MUSICAL are proposed to achieve this task. The ocean acoustic tomography configuration allows a single recording realization to estimate the cross-spectral data matrix, which is necessary to build high-resolution estimators. 3D smoothing techniques are thus proposed to increase the rank of the matrix. The estimators developed are validated on real data recorded in an ultrasonic tank, and their detection performances are compared to existing 2D and 3D methods.

  12. Observation of lens aberrations for high resolution electron microscopy II: Simple expressions for optimal estimates

    Energy Technology Data Exchange (ETDEWEB)

    Saxton, W. Owen, E-mail: wos1@cam.ac.uk

    2015-04-15

    This paper lists simple closed-form expressions estimating aberration coefficients (defocus, astigmatism, three-fold astigmatism, coma / misalignment, spherical aberration) on the basis of image shift or diffractogram shape measurements as a function of injected beam tilt. Simple estimators are given for a large number of injected tilt configurations, optimal in the sense of least-squares fitting of all the measurements, and so better than most reported previously. Standard errors are given for most, allowing different approaches to be compared. Special attention is given to the measurement of the spherical aberration, for which several simple procedures are given, and the effect of foreknowledge of this on other aberration estimates is noted. Details and optimal expressions are also given for a new and simple method of analysis, requiring measurements of the diffractogram mirror axis direction only, which are simpler to make than the focus and astigmatism measurements otherwise required. - Highlights: • Optimal estimators for CTEM lens aberrations are more accurate and/or use fewer observations. • Estimators have been found for defocus, astigmatism, three-fold astigmatism, coma and spherical aberration. • Estimators have been found relying on diffractogram shape, image shift and diffractogram orientation only, for a variety of beam tilts. • The standard error for each estimator has been found.

  13. Phase difference estimation method based on data extension and Hilbert transform

    International Nuclear Information System (INIS)

    Shen, Yan-lin; Tu, Ya-qing; Chen, Lin-jun; Shen, Ting-ao

    2015-01-01

    To improve the precision and anti-interference performance of phase difference estimation for non-integer periods of sampling signals, a phase difference estimation method based on data extension and Hilbert transform is proposed. Estimated phase difference is obtained by means of data extension, Hilbert transform, cross-correlation, auto-correlation, and weighted phase average. Theoretical analysis shows that the proposed method suppresses the end effects of Hilbert transform effectively. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of phase difference estimation and has better performance of phase difference estimation than the correlation, Hilbert transform, and data extension-based correlation methods, which contribute to improving the measurement precision of the Coriolis mass flowmeter. (paper)

  14. Delineation of Rain Areas with TRMM Microwave Observations Based on PNN

    Directory of Open Access Journals (Sweden)

    Shiguang Xu

    2014-12-01

    Full Text Available False alarm and misdetected precipitation are prominent drawbacks of high-resolution satellite precipitation datasets, and they usually lead to serious uncertainty in hydrological and meteorological applications. In order to provide accurate rain area delineation for retrieving high-resolution precipitation datasets using satellite microwave observations, a probabilistic neural network (PNN-based rain area delineation method was developed with rain gauge observations over the Yangtze River Basin and three parameters, including polarization corrected temperature at 85 GHz, difference of brightness temperature at vertically polarized 37 and 19 GHz channels (termed as TB37V and TB19V, respectively and the sum of TB37V and TB19V derived from the observations of the Tropical Rainfall Measuring Mission (TRMM Microwave Imager (TMI. The PNN method was validated with independent samples, and the performance of this method was compared with dynamic cluster K-means method, TRMM Microwave Imager (TMI Level 2 Hydrometeor Profile Product and the threshold method used in the Scatter Index (SI, a widely used microwave-based precipitation retrieval algorithm. Independent validation indicated that the PNN method can provide more reasonable rain areas than the other three methods. Furthermore, the precipitation volumes estimated by the SI algorithm were significantly improved by substituting the PNN method for the threshold method in the traditional SI algorithm. This study suggests that PNN is a promising way to obtain reasonable rain areas with satellite observations, and the development of an accurate rain area delineation method deserves more attention for improving the accuracy of satellite precipitation datasets.

  15. A Simulation-Based Soft Error Estimation Methodology for Computer Systems

    OpenAIRE

    Sugihara, Makoto; Ishihara, Tohru; Hashimoto, Koji; Muroyama, Masanori

    2006-01-01

    This paper proposes a simulation-based soft error estimation methodology for computer systems. Accumulating soft error rates (SERs) of all memories in a computer system results in pessimistic soft error estimation. This is because memory cells are used spatially and temporally and not all soft errors in them make the computer system faulty. Our soft-error estimation methodology considers the locations and the timings of soft errors occurring at every level of memory hierarchy and estimates th...

  16. Population-based absolute risk estimation with survey data

    Science.gov (United States)

    Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

    2013-01-01

    Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614

  17. Fault Severity Estimation of Rotating Machinery Based on Residual Signals

    Directory of Open Access Journals (Sweden)

    Fan Jiang

    2012-01-01

    Full Text Available Fault severity estimation is an important part of a condition-based maintenance system, which can monitor the performance of an operation machine and enhance its level of safety. In this paper, a novel method based on statistical property and residual signals is developed for estimating the fault severity of rotating machinery. The fast Fourier transformation (FFT is applied to extract the so-called multifrequency-band energy (MFBE from the vibration signals of rotating machinery with different fault severity levels in the first stage. Usually these features of the working conditions with different fault sensitivities are different. Therefore a sensitive features-selecting algorithm is defined to construct the feature matrix and calculate the statistic parameter (mean in the second stage. In the last stage, the residual signals computed by the zero space vector are used to estimate the fault severity. Simulation and experimental results reveal that the proposed method based on statistics and residual signals is effective and feasible for estimating the severity of a rotating machine fault.

  18. Realized range-based estimation of integrated variance

    DEFF Research Database (Denmark)

    Christensen, Kim; Podolskij, Mark

    2007-01-01

    We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...

  19. Channel estimation in DFT-based offset-QAM OFDM systems.

    Science.gov (United States)

    Zhao, Jian

    2014-10-20

    Offset quadrature amplitude modulation (offset-QAM) orthogonal frequency division multiplexing (OFDM) exhibits enhanced net data rates compared to conventional OFDM, and reduced complexity compared to Nyquist FDM (N-FDM). However, channel estimation in discrete-Fourier-transform (DFT) based offset-QAM OFDM is different from that in conventional OFDM and requires particular study. In this paper, we derive a closed-form expression for the demultiplexed signal in DFT-based offset-QAM systems and show that although the residual crosstalk is orthogonal to the decoded signal, its existence degrades the channel estimation performance when the conventional least-square method is applied. We propose and investigate four channel estimation algorithms for offset-QAM OFDM that vary in terms of performance, complexity, and tolerance to system parameters. It is theoretically and experimentally shown that simple channel estimation can be realized in offset-QAM OFDM with the achieved performance close to the theoretical limit. This, together with the existing advantages over conventional OFDM and N-FDM, makes this technology very promising for optical communication systems.

  20. The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

    Science.gov (United States)

    Ronald E. McRoberts

    2010-01-01

    Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

  1. Sliding mode observers for automotive alternator

    Science.gov (United States)

    Chen, De-Shiou

    Estimator development for synchronous rectification of the automotive alternator is a desirable approach for estimating alternator's back electromotive forces (EMFs) without a direct mechanical sensor of the rotor position. Recent theoretical studies show that estimation of the back EMF may be observed based on system's phase current model by sensing electrical variables (AC phase currents and DC bus voltage) of the synchronous rectifier. Observer design of the back EMF estimation has been developed for constant engine speed. In this work, we are interested in nonlinear observer design of the back EMF estimation for the real case of variable engine speed. Initial back EMF estimate can be obtained from a first-order sliding mode observer (SMO) based on the phase current model. A fourth-order nonlinear asymptotic observer (NAO), complemented by the dynamics of the back EMF with time-varying frequency and amplitude, is then incorporated into the observer design for chattering reduction. Since the cost of required phase current sensors may be prohibitive, the most applicable approach in real implementation by measuring DC current of the synchronous rectifier is carried out in the dissertation. It is shown that the DC link current consists of sequential "windows" with partial information of the phase currents, hence, the cascaded NAO is responsible not only for the purpose of chattering reduction but also for necessarily accomplishing the process of estimation. Stability analyses of the proposed estimators are considered for most linear and time-varying cases. The stability of the NAO without speed information is substantiated by both numerical and experimental results. Prospective estimation algorithms for the case of battery current measurements are investigated. Theoretical study indicates that the convergence of the proposed LAO may be provided by high gain inputs. Since the order of the LAO/NAO for the battery current case is one order higher than that of the link

  2. Event-based state estimation a stochastic perspective

    CERN Document Server

    Shi, Dawei; Chen, Tongwen

    2016-01-01

    This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs ...

  3. An Adaptive Gain Nonlinear Observer for State of Charge Estimation of Lithium-Ion Batteries in Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Yong Tian

    2014-09-01

    Full Text Available The state of charge (SOC is important for the safety and reliability of battery operation since it indicates the remaining capacity of a battery. However, it is difficult to get an accurate value of SOC, because the SOC cannot be directly measured by a sensor. In this paper, an adaptive gain nonlinear observer (AGNO for SOC estimation of lithium-ion batteries (LIBs in electric vehicles (EVs is proposed. The second-order resistor–capacitor (2RC equivalent circuit model is used to simulate the dynamic behaviors of a LIB, based on which the state equations are derived to design the AGNO for SOC estimation. The model parameters are identified using the exponential-function fitting method. The sixth-order polynomial function is used to describe the highly nonlinear relationship between the open circuit voltage (OCV and the SOC. The convergence of the proposed AGNO is proved using the Lyapunov stability theory. Two typical driving cycles, including the New European Driving Cycle (NEDC and Federal Urban Driving Schedule (FUDS are adopted to evaluate the performance of the AGNO by comparing with the unscented Kalman filter (UKF algorithm. The experimental results show that the AGNO has better performance than the UKF algorithm in terms of reducing the computation cost, improving the estimation accuracy and enhancing the convergence ability.

  4. Correlation between the model accuracy and model-based SOC estimation

    International Nuclear Information System (INIS)

    Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

    2017-01-01

    State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

  5. Accurate torque-sensorless control approach for interior permanent-magnet synchronous machine based on cascaded sliding mode observer

    Directory of Open Access Journals (Sweden)

    Kai-Hui Zhao

    2017-06-01

    Full Text Available To improve the accuracy of torque control for vector control of interior permanent-magnet synchronous machine (IPMSM, this study proposes a torque-sensorless control method based on cascaded sliding mode observer (SMO. First, the active flux model is discussed, which converts the model of IPMSM into the equivalent model of surface-mounted permanent-magnet synchronous machine. Second, to reduce chattering caused by system parameters variations and external disturbances, the cascaded observer is designed, which is composed of a variable gain adaptive SMO and an active flux SMO. The variable gain adaptive SMO is designed to estimate the speed, rotor position and stator resistance in the d–q reference frame. The active flux SMO is designed to estimate the active flux and torque in the α–β reference frame. Global asymptotic stability of the observers is guaranteed by the Lyapunov stability analysis. Finally, simulations and experiments are carried out to verify the effectiveness of the proposed control scheme.

  6. Fatigue Damage Estimation and Data-based Control for Wind Turbines

    DEFF Research Database (Denmark)

    Barradas Berglind, Jose de Jesus; Wisniewski, Rafal; Soltani, Mohsen

    2015-01-01

    based on hysteresis operators, which can be used in control loops. The authors propose a data-based model predictive control (MPC) strategy that incorporates an online fatigue estimation method through the objective function, where the ultimate goal in mind is to reduce the fatigue damage of the wind......The focus of this work is on fatigue estimation and data-based controller design for wind turbines. The main purpose is to include a model of the fatigue damage of the wind turbine components in the controller design and synthesis process. This study addresses an online fatigue estimation method...... turbine components. The outcome is an adaptive or self-tuning MPC strategy for wind turbine fatigue damage reduction, which relies on parameter identification on previous measurement data. The results of the proposed strategy are compared with a baseline model predictive controller....

  7. Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE

    Science.gov (United States)

    Sreelash, K.; Sekhar, M.; Ruiz, L.; Tomer, S. K.; Guérif, M.; Buis, S.; Durand, P.; Gascuel-Odoux, C.

    2012-08-01

    SummaryEstimation of soil parameters by inverse modeling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise when heterogeneous layered soils are considered. The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables - leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS. This was performed using GLUE method on a synthetic data set on varying soil types and on a data set from a field experiment carried out in two maize plots in South India. The main results were (i) combination of surface soil moisture and above-ground biomass provided consistently good estimates with small uncertainity of soil properties for the two soil layers, for a wide range of soil paramater values, both in the synthetic and the field experiment, (ii) above-ground biomass was found to give relatively better estimates and lower uncertainty than LAI when combined with surface soil moisture, especially for estimation of soil depth, (iii) surface soil moisture data, either alone or combined with crop variables, provided a very good estimate of the water holding capacity of the upper soil layer with very small uncertainty whereas using the surface soil moisture alone gave very poor estimates of the soil properties of the deeper layer, and (iv) using crop variables alone (else above-ground biomass or LAI) provided reasonable estimates of the deeper layer properties depending on the soil type but provided poor estimates of the first layer properties. The robustness of combining observations of the surface soil moisture and the above-ground biomass for estimating two layer soil properties, which was demonstrated using both synthetic and field experiments in this study, needs now to

  8. Temporal validation for landsat-based volume estimation model

    Science.gov (United States)

    Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan

    2015-01-01

    Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

  9. Observer-based design of set-point tracking adaptive controllers for nonlinear chaotic systems

    International Nuclear Information System (INIS)

    Khaki-Sedigh, A.; Yazdanpanah-Goharrizi, A.

    2006-01-01

    A gradient based approach for the design of set-point tracking adaptive controllers for nonlinear chaotic systems is presented. In this approach, Lyapunov exponents are used to select the controller gain. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, an effective adaptive strategy is used for online identification of Lyapunov exponents and adaptive control of nonlinear chaotic plants. Also, a nonlinear observer for estimation of the states is proposed. Simulation results are provided to show the effectiveness of the proposed methodology

  10. Observer-based design of set-point tracking adaptive controllers for nonlinear chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Khaki-Sedigh, A. [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran 16314 (Iran, Islamic Republic of)]. E-mail: sedigh@kntu.ac.ir; Yazdanpanah-Goharrizi, A. [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran 16314 (Iran, Islamic Republic of)]. E-mail: yazdanpanah@ee.kntu.ac.ir

    2006-09-15

    A gradient based approach for the design of set-point tracking adaptive controllers for nonlinear chaotic systems is presented. In this approach, Lyapunov exponents are used to select the controller gain. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, an effective adaptive strategy is used for online identification of Lyapunov exponents and adaptive control of nonlinear chaotic plants. Also, a nonlinear observer for estimation of the states is proposed. Simulation results are provided to show the effectiveness of the proposed methodology.

  11. Estimating seasonal variations in cloud droplet number concentration over the boreal forest from satellite observations

    NARCIS (Netherlands)

    Janssen, R.; Ganzeveld, L.N.; Kabat, P.; Kulmala, M.; Nieminen, T.; Roebeling, R.A.

    2011-01-01

    Seasonal variations in cloud droplet number concentration (NCD) in low-level stratiform clouds over the boreal forest are estimated from MODIS observations of cloud optical and microphysical properties, using a sub-adiabatic cloud model to interpret vertical profiles of cloud properties. An

  12. Real-time estimation of FLE for point-based registration

    Science.gov (United States)

    Wiles, Andrew D.; Peters, Terry M.

    2009-02-01

    In image-guide surgery, optimizing the accuracy in localizing the surgical tools within the virtual reality environment or 3D image is vitally important, significant effort has been spent reducing the measurement errors at the point of interest or target. This target registration error (TRE) is often defined by a root-mean-square statistic which reduces the vector data to a single term that can be minimized. However, lost in the data reduction is the directionality of the error which, can be modelled using a 3D covariance matrix. Recently, we developed a set of expressions that modeled the TRE statistics for point-based registrations as a function of the fiducial marker geometry, target location and the fiducial localizer error (FLE). Unfortunately, these expressions are only as good as the definition of the FLE. In order to close the gap, we have subsequently developed a closed form expression that estimates the FLE as a function of the estimated fiducial registration error (FRE, the error between the measured fiducials and the best fit locations of those fiducials). The FRE covariance matrix is estimated using a sliding window technique and used as input into the closed form expression to estimate the FLE. The estimated FLE can then used to estimate the TRE which, can be given to the surgeon to permit the procedure to be designed such that the errors associated with the point-based registrations are minimized.

  13. Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

    Directory of Open Access Journals (Sweden)

    K. Andrea Scott

    2015-09-01

    Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

  14. Improving incidence estimation in practice-based sentinel surveillance networks using spatial variation in general practitioner density

    Directory of Open Access Journals (Sweden)

    Cécile Souty

    2016-11-01

    Full Text Available Abstract Background In surveillance networks based on voluntary participation of health-care professionals, there is little choice regarding the selection of participants’ characteristics. External information about participants, for example local physician density, can help reduce bias in incidence estimates reported by the surveillance network. Methods There is an inverse association between the number of reported influenza-like illness (ILI cases and local general practitioners (GP density. We formulated and compared estimates of ILI incidence using this relationship. To compare estimates, we simulated epidemics using a spatially explicit disease model and their observation by surveillance networks with different characteristics: random, maximum coverage, largest cities, etc. Results In the French practice-based surveillance network – the “Sentinelles” network – GPs reported 3.6% (95% CI [3;4] less ILI cases as local GP density increased by 1 GP per 10,000 inhabitants. Incidence estimates varied markedly depending on scenarios for participant selection in surveillance. Yet accounting for change in GP density for participants allowed reducing bias. Applied on data from the Sentinelles network, changes in overall incidence ranged between 1.6 and 9.9%. Conclusions Local GP density is a simple measure that provides a way to reduce bias in estimating disease incidence in general practice. It can contribute to improving disease monitoring when it is not possible to choose the characteristics of participants.

  15. A Modified Gash Model for Estimating Rainfall Interception Loss of Forest Using Remote Sensing Observations at Regional Scale

    Directory of Open Access Journals (Sweden)

    Yaokui Cui

    2014-04-01

    Full Text Available Rainfall interception loss of forest is an important component of water balance in a forested ecosystem. The Gash analytical model has been widely used to estimate the forest interception loss at field scale. In this study, we proposed a simple model to estimate rainfall interception loss of heterogeneous forest at regional scale with several reasonable assumptions using remote sensing observations. The model is a modified Gash analytical model using easily measured parameters of forest structure from satellite data and extends the original Gash model from point-scale to the regional scale. Preliminary results, using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS products, field measured rainfall data, and meteorological data of the Automatic Weather Station (AWS over a picea crassifolia forest in the upper reaches of the Heihe River Basin in northwestern China, showed reasonable accuracy in estimating rainfall interception loss at both the Dayekou experimental site (R2 = 0.91, RMSE = 0.34 mm∙d −1 and the Pailugou experimental site (R2 = 0.82, RMSE = 0.6 mm∙d −1, compared with ground measurements based on per unit area of forest. The interception loss map of the study area was shown to be strongly heterogeneous. The modified model has robust physics and is insensitive to the input parameters, according to the sensitivity analysis using numerical simulations. The modified model appears to be stable and easy to be applied for operational estimation of interception loss over large areas.

  16. Age estimation of living Indian individuals based on aspartic acid racemization from tooth biopsy specimen

    Science.gov (United States)

    Rastogi, Manu; Logani, Ajay; Shah, Naseem; Kumar, Abhishek; Arora, Saurabh

    2017-01-01

    Background: Age estimation in living individuals is imperative to amicably settle civil and criminal disputes. A biochemical method based on amino acid racemization was evaluated for age estimation of living Indian individuals. Design: Caries-free maxillary/mandibular premolar teeth (n = 90) were collected from participants with age proof documents and divided into predefined nine age groups. Materials and Methods: Dentine biopsy from the labial aspect of the tooth crown was taken with an indigenously developed microtrephine. The samples were processed and subjected to gas chromatography. Dextrorotatory:levorotatory ratios were calculated, and a regression equation was formulated. Results: Across all age groups, an error of 0 ± 4 years between protein racemization age and chronological age was observed. Conclusion: Aspartic acid racemization from dentine biopsy samples could be a viable and accurate technique for age estimation of living individuals who have attained a state of skeletal maturity. PMID:29263613

  17. Estimating the operator's performance time of emergency procedural tasks based on a task complexity measure

    International Nuclear Information System (INIS)

    Jung, Won Dae; Park, Jink Yun

    2012-01-01

    It is important to understand the amount of time required to execute an emergency procedural task in a high-stress situation for managing human performance under emergencies in a nuclear power plant. However, the time to execute an emergency procedural task is highly dependent upon expert judgment due to the lack of actual data. This paper proposes an analytical method to estimate the operator's performance time (OPT) of a procedural task, which is based on a measure of the task complexity (TACOM). The proposed method for estimating an OPT is an equation that uses the TACOM as a variable, and the OPT of a procedural task can be calculated if its relevant TACOM score is available. The validity of the proposed equation is demonstrated by comparing the estimated OPTs with the observed OPTs for emergency procedural tasks in a steam generator tube rupture scenario.

  18. Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold

    Directory of Open Access Journals (Sweden)

    Xiaoqiang Hua

    2018-03-01

    Full Text Available This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD matrices. The means associated with information divergences are derived and used as the estimators. Without resorting to the complete knowledge of the probability distribution of the sample data, the geometry of the Riemannian manifold of HPD matrices is considered in mean estimators. Moreover, the robustness of mean estimators is analyzed using the influence function. Simulation results indicate the robustness and superiority of an adaptive normalized matched filter with our proposed estimators compared with the existing alternatives.

  19. Regional evapotranspiration estimation based on a two-layer remote-sensing scheme in Shahe River basin

    International Nuclear Information System (INIS)

    Yin, Jian; Wang, Huixiao

    2014-01-01

    Land surface evapotranspiration (ET) derived from remote sensing data has significant meaning for plant growth monitoring, crop yield assessment, disaster monitoring and understanding energy and water cycle in river basin area and surrounding regions. In the study, we developed a land surface ET remote sensing retrieval system to estimate the daily ET in Shahe river basin using the TM/ETM+ images. The system is based on the two-layer ET model and includes three parts: inversion of the evaporation ration using two-layer model, calculation of total daily net radiation, and estimation of daily ET based on evaporation fraction method. The results show that the average daily ET is about 2.28mm of the typical days in spring, and 2.97mm in summer, 1.59mm in autumn, and 0.5mm in winter. The ET in upstream areas covered by forest is higher than that in the downstream covered by settlement and farmland. In summer the difference of ET between the upper reaches and lower reaches is smaller compared to the other three seasons. The measurements by large aperture scintillometer and eddy correlation instrument were used for validation. By comparing the observed data with the estimated data, we found the estimation system had a high precision with the relative error between 0 and 16% (mean error of 11.1%), and the variance 0.77mm

  20. M-Arctan estimator based on the trust-region method

    Energy Technology Data Exchange (ETDEWEB)

    Hassaine, Yacine; Delourme, Benoit; Panciatici, Patrick [Gestionnaire du Reseau de Transport d Electricite Departement Methodes et appui Immeuble Le Colbert 9, Versailles Cedex (France); Walter, Eric [Laboratoire des signaux et systemes (L2S) Supelec, Gif-sur-Yvette (France)

    2006-11-15

    In this paper a new approach is proposed to increase the robustness of the classical L{sub 2}-norm state estimation. To achieve this task a new formulation of the Levemberg-Marquardt algorithm based on the trust-region method is applied to a new M-estimator, which we called M-Arctan. Results obtained on IEEE networks up to 300 buses are presented. (author)

  1. Performance Assessment of a Gnss-Based Troposphere Path Delay Estimation Software

    Science.gov (United States)

    Mariotti, Gilles; Avanzi, Alessandro; Graziani, Alberto; Tortora, Paolo

    2013-04-01

    Error budgets of Deep Space Radio Science experiments are heavily affected by interplanetary and Earth transmission media, that corrupt, due to their non-unitary refraction index, the radiometric information of signals coming from the spacecraft. An effective removal of these noise sources is crucial to achieve the accuracy and signal stability levels required by radio science applications. Depending on the nature of these refractions, transmission media are divided into dispersive (that consists of ionized particles, i.e. Solar Wind and Ionosphere) and non-dispersive ones (the refraction is caused by neutral particles: Earth Troposphere). While dispersive noises are successfully removed by multifrequency combinations (as for GPS with the well-known ionofree combination), the most accurate estimation of tropospheric noise is obtained using microwave radiometers (MWR). As the use of MWRs suffers from strong operational limitations (rain and heavy clouds conditions), the GNSS-based processing is still widely adopted to provide a cost-effective, all-weather condition estimation of the troposphere path delay. This work describes the development process and reports the results of a GNSS analysis code specifically aimed to the estimation of the path delays introduced by the troposphere above deep space complexes, to be used for the calibration of Range and Doppler radiometric data. The code has been developed by the Radio Science Laboratory of the University of Bologna in Forlì, and is currently in the testing phase. To this aim, the preliminary output is compared to MWR measurements and IGS TropoSINEX products in order to assess the reliability of the estimate. The software works using ionofree carrier-phase observables and is based upon a double-difference approach, in which the GNSS receiver placed nearby the Deep Space receiver acts as the rover station. Several baselines are then created with various IGS and EUREF stations (master or reference stations) in order to

  2. Estimation of Muscle Force Based on Neural Drive in a Hemispheric Stroke Survivor.

    Science.gov (United States)

    Dai, Chenyun; Zheng, Yang; Hu, Xiaogang

    2018-01-01

    Robotic assistant-based therapy holds great promise to improve the functional recovery of stroke survivors. Numerous neural-machine interface techniques have been used to decode the intended movement to control robotic systems for rehabilitation therapies. In this case report, we tested the feasibility of estimating finger extensor muscle forces of a stroke survivor, based on the decoded descending neural drive through population motoneuron discharge timings. Motoneuron discharge events were obtained by decomposing high-density surface electromyogram (sEMG) signals of the finger extensor muscle. The neural drive was extracted from the normalized frequency of the composite discharge of the motoneuron pool. The neural-drive-based estimation was also compared with the classic myoelectric-based estimation. Our results showed that the neural-drive-based approach can better predict the force output, quantified by lower estimation errors and higher correlations with the muscle force, compared with the myoelectric-based estimation. Our findings suggest that the neural-drive-based approach can potentially be used as a more robust interface signal for robotic therapies during the stroke rehabilitation.

  3. Geohydrological and environmental isotope observation of Sishen ground waters

    International Nuclear Information System (INIS)

    Verhagen, B.Th.; Dziembowski, Z.M.

    1985-01-01

    The dewatering of Sishen Mine in the northern Cape Province supplies good quality water for the mine and surrounding areas. Using various approaches, attempts are made to quantify the remaining storage of ground water. Geohydrological observations provide an estimate based on extrapolating the thickness of dewatered rock. Environmental isotope observations on various borehole outputs show contrasts between different ground-water bodies and their mixtures and allows for some extrapolations of observed trends. Indications are that previous estimates of storage, based on ground-water level changes, are conservative

  4. Estimating the Geocenter from GNSS Observations

    Science.gov (United States)

    Dach, Rolf; Michael, Meindl; Beutler, Gerhard; Schaer, Stefan; Lutz, Simon; Jäggi, Adrian

    2014-05-01

    The satellites of the Global Navigation Satellite Systems (GNSS) are orbiting the Earth according to the laws of celestial mechanics. As a consequence, the satellites are sensitive to the coordinates of the center of mass of the Earth. The coordinates of the (ground) tracking stations are referring to the center of figure as the conventional origin of the reference frame. The difference between the center of mass and center of figure is the instantaneous geocenter. Following this definition the global GNSS solutions are sensitive to the geocenter. Several studies demonstrated strong correlations of the GNSS-derived geocenter coordinates with parameters intended to absorb radiation pressure effects acting on the GNSS satellites, and with GNSS satellite clock parameters. One should thus pose the question to what extent these satellite-related parameters absorb (or hide) the geocenter information. A clean simulation study has been performed to answer this question. The simulation environment allows it in particular to introduce user-defined shifts of the geocenter (systematic inconsistencies between the satellite's and station's reference frames). These geocenter shifts may be recovered by the mentioned parameters - provided they were set up in the analysis. If the geocenter coordinates are not estimated, one may find out which other parameters absorb the user-defined shifts of the geocenter and to what extent. Furthermore, the simulation environment also allows it to extract the correlation matrix from the a posteriori covariance matrix to study the correlations between different parameter types of the GNSS analysis system. Our results show high degrees of correlations between geocenter coordinates, orbit-related parameters, and satellite clock parameters. These correlations are of the same order of magnitude as the correlations between station heights, troposphere, and receiver clock parameters in each regional or global GNSS network analysis. If such correlations

  5. Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Science.gov (United States)

    These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

  6. A numerical integration-based yield estimation method for integrated circuits

    International Nuclear Information System (INIS)

    Liang Tao; Jia Xinzhang

    2011-01-01

    A novel integration-based yield estimation method is developed for yield optimization of integrated circuits. This method tries to integrate the joint probability density function on the acceptability region directly. To achieve this goal, the simulated performance data of unknown distribution should be converted to follow a multivariate normal distribution by using Box-Cox transformation (BCT). In order to reduce the estimation variances of the model parameters of the density function, orthogonal array-based modified Latin hypercube sampling (OA-MLHS) is presented to generate samples in the disturbance space during simulations. The principle of variance reduction of model parameters estimation through OA-MLHS together with BCT is also discussed. Two yield estimation examples, a fourth-order OTA-C filter and a three-dimensional (3D) quadratic function are used for comparison of our method with Monte Carlo based methods including Latin hypercube sampling and importance sampling under several combinations of sample sizes and yield values. Extensive simulations show that our method is superior to other methods with respect to accuracy and efficiency under all of the given cases. Therefore, our method is more suitable for parametric yield optimization. (semiconductor integrated circuits)

  7. A numerical integration-based yield estimation method for integrated circuits

    Energy Technology Data Exchange (ETDEWEB)

    Liang Tao; Jia Xinzhang, E-mail: tliang@yahoo.cn [Key Laboratory of Ministry of Education for Wide Bandgap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi' an 710071 (China)

    2011-04-15

    A novel integration-based yield estimation method is developed for yield optimization of integrated circuits. This method tries to integrate the joint probability density function on the acceptability region directly. To achieve this goal, the simulated performance data of unknown distribution should be converted to follow a multivariate normal distribution by using Box-Cox transformation (BCT). In order to reduce the estimation variances of the model parameters of the density function, orthogonal array-based modified Latin hypercube sampling (OA-MLHS) is presented to generate samples in the disturbance space during simulations. The principle of variance reduction of model parameters estimation through OA-MLHS together with BCT is also discussed. Two yield estimation examples, a fourth-order OTA-C filter and a three-dimensional (3D) quadratic function are used for comparison of our method with Monte Carlo based methods including Latin hypercube sampling and importance sampling under several combinations of sample sizes and yield values. Extensive simulations show that our method is superior to other methods with respect to accuracy and efficiency under all of the given cases. Therefore, our method is more suitable for parametric yield optimization. (semiconductor integrated circuits)

  8. Observation-Based Estimates of Surface Cooling Inhibition by Heavy Rainfall under Tropical Cyclones

    Digital Repository Service at National Institute of Oceanography (India)

    Jourdain, N; Lengaigne, M.; Vialard, J.; Madec, G.; Menkes, C.E.; Vincent, E.M.; Jullien, E.; Barnier, B.

    Tropical cyclones drive intense ocean vertical mixing that explains most of the surface cooling observed in their wake (the "cold wake"). The influence of cyclonic rainfall on the cold wake at a global scale over the 2002-09 period is investigated...

  9. Efficient Estimating Functions for Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Jakobsen, Nina Munkholt

    The overall topic of this thesis is approximate martingale estimating function-based estimationfor solutions of stochastic differential equations, sampled at high frequency. Focuslies on the asymptotic properties of the estimators. The first part of the thesis deals with diffusions observed over...

  10. An intercomparison and validation of satellite-based surface radiative energy flux estimates over the Arctic

    Science.gov (United States)

    Riihelä, Aku; Key, Jeffrey R.; Meirink, Jan Fokke; Kuipers Munneke, Peter; Palo, Timo; Karlsson, Karl-Göran

    2017-05-01

    Accurate determination of radiative energy fluxes over the Arctic is of crucial importance for understanding atmosphere-surface interactions, melt and refreezing cycles of the snow and ice cover, and the role of the Arctic in the global energy budget. Satellite-based estimates can provide comprehensive spatiotemporal coverage, but the accuracy and comparability of the existing data sets must be ascertained to facilitate their use. Here we compare radiative flux estimates from Clouds and the Earth's Radiant Energy System (CERES) Synoptic 1-degree (SYN1deg)/Energy Balanced and Filled, Global Energy and Water Cycle Experiment (GEWEX) surface energy budget, and our own experimental FluxNet / Satellite Application Facility on Climate Monitoring cLoud, Albedo and RAdiation (CLARA) data against in situ observations over Arctic sea ice and the Greenland Ice Sheet during summer of 2007. In general, CERES SYN1deg flux estimates agree best with in situ measurements, although with two particular limitations: (1) over sea ice the upwelling shortwave flux in CERES SYN1deg appears to be underestimated because of an underestimated surface albedo and (2) the CERES SYN1deg upwelling longwave flux over sea ice saturates during midsummer. The Advanced Very High Resolution Radiometer-based GEWEX and FluxNet-CLARA flux estimates generally show a larger range in retrieval errors relative to CERES, with contrasting tendencies relative to each other. The largest source of retrieval error in the FluxNet-CLARA downwelling shortwave flux is shown to be an overestimated cloud optical thickness. The results illustrate that satellite-based flux estimates over the Arctic are not yet homogeneous and that further efforts are necessary to investigate the differences in the surface and cloud properties which lead to disagreements in flux retrievals.

  11. Estimating security betas using prior information based on firm fundamentals

    NARCIS (Netherlands)

    Cosemans, M.; Frehen, R.; Schotman, P.C.; Bauer, R.

    2010-01-01

    This paper proposes a novel approach for estimating time-varying betas of individual stocks that incorporates prior information based on fundamentals. We shrink the rolling window estimate of beta towards a firm-specific prior that is motivated by asset pricing theory. The prior captures structural

  12. Response-based estimation of sea state parameters - Influence of filtering

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2007-01-01

    Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The wave spectrum can be estimated from procedures based on measured ship responses. The paper deals with two procedures—Bayesian Modelling and Parametric Modelling...

  13. A Comparison of Satellite Based, Modeled Derived Daily Solar Radiation Data with Observed Data for the Continental US

    Science.gov (United States)

    White, Jeffrey W.; Hoogenboom, Gerrit; Wilkens, Paul W.; Stackhouse, Paul W., Jr.; Hoell, James M.

    2010-01-01

    Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these tools. Daily solar radiation (SRAD) data are especially problematic because the instruments require electronic integrators, accurate sensors are expensive, and calibration standards are seldom available. The Prediction Of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov) project at the NASA Langley Research Center estimates daily solar radiation based on data that are derived from satellite observations of outgoing visible radiances and atmospheric parameters based upon satellite observations and assimilation models. The solar data are available for a global 1 degree x 1 degree coordinate grid. SRAD can also be estimated based on attenuation of extraterrestrial radiation (Q0) using daily temperature and rainfall data to estimate the optical thickness of the atmosphere. This study compares daily solar radiation data from NASA/POWER (SRADNP) with instrument readings from 295 stations (SRADOB), as well as with values that were estimated with the WGENR solar generator. WGENR was used both with daily temperature and precipitation records from the stations reporting solar data and records from the NOAA Cooperative Observer Program (COOP), thus providing two additional sources of solar data, SRADWG and SRADCO. Values of SRADNP for different grid cells consistently showed higher correlations (typically 0.85 to 0.95) with SRADOB data than did SRADWG or SRADCO for sites within the corresponding cells. Mean values of SRADOB, SRADWG and SRADNP for sites within a grid cell usually were within 1 MJm-2d-1 of each other, but NASA/POWER values averaged 1.1 MJm-2d-1 lower than SRADOB. The magnitude of this bias was greater at lower latitudes and during summer months and may be at

  14. Synergistic estimation of surface parameters from jointly using optical and microwave observations in EOLDAS

    Science.gov (United States)

    Timmermans, Joris; Gomez-Dans, Jose; Lewis, Philip; Loew, Alexander; Schlenz, Florian

    2017-04-01

    The large amount of remote sensing data nowadays available provides a huge potential for monitoring crop development, drought conditions and water efficiency. This potential however not been realized yet because algorithms for land surface parameter retrieval mostly use data from only a single sensor. Consequently products that combine different low-level observations from different sensors are hard to find. The lack of synergistic retrieval is caused because it is easier to focus on single sensor types/footprints and temporal observation times, than to find a way to compensate for differences. Different sensor types (microwave/optical) require different radiative transfer (RT) models and also require consistency between the models to have any impact on the retrieval of soil moisture by a microwave instrument. Varying spatial footprints require first proper collocation of the data before one can scale between different resolutions. Considering these problems, merging optical and microwave observations have not been performed yet. The goal of this research was to investigate the potential of integrating optical and microwave RT models within the Earth Observation Land Data Assimilation System (EOLDAS) synergistically to derive biophysical parameters. This system uses a Bayesian data assimilation approach together with observation operators such as the PROSAIL model to estimate land surface parameters. For the purpose of enabling the system to integrate passive microwave radiation (from an ELBARRA II passive microwave radiometer), the Community Microwave Emission Model (CMEM) RT-model, was integrated within the EOLDAS system. In order to quantify the potential, a variety of land surface parameters was chosen to be retrieved from the system, in particular variables that a) impact only optical RT (such as leaf water content and leaf dry matter), b) only impact the microwave RT (such as soil moisture and soil temperature), and c) Leaf Area Index (LAI) that impacts both

  15. Object Detection and Tracking-Based Camera Calibration for Normalized Human Height Estimation

    Directory of Open Access Journals (Sweden)

    Jaehoon Jung

    2016-01-01

    Full Text Available This paper presents a normalized human height estimation algorithm using an uncalibrated camera. To estimate the normalized human height, the proposed algorithm detects a moving object and performs tracking-based automatic camera calibration. The proposed method consists of three steps: (i moving human detection and tracking, (ii automatic camera calibration, and (iii human height estimation and error correction. The proposed method automatically calibrates camera by detecting moving humans and estimates the human height using error correction. The proposed method can be applied to object-based video surveillance systems and digital forensic.

  16. HOW GOOD ARE FUTURE LAWYERS IN JUDGING THE ACCURACY OF REMINISCENT DETAILS? THE ESTIMATION-OBSERVATION GAP IN REAL EYEWITNESS ACCOUNTS

    Directory of Open Access Journals (Sweden)

    Aileen Oeberst

    2015-07-01

    Full Text Available Research has shown a discrepancy between estimated and actually observed accuracy of reminiscent details in eyewitness accounts. This estimation-observation gap is of particular relevance with regard to the evaluation of eyewitnesses’ accounts in the legal context. To date it has only been demonstrated in non-naturalistic settings, however. In addition, it is not known whether this gap extends to other tasks routinely employed in real-world trials, for instance person-identification tasks. In this study, law students witnessed a staged event and were asked to either recall the event and perform a person identification task or estimate the accuracy of the others’ performance. Additionally, external estimations were obtained from students who had not witnessed the event, but received a written summary instead. The estimation-observation gap was replicated for reminiscent details under naturalistic encoding conditions. This gap was more pronounced when compared to forgotten details, but not significantly so when compared to consistent details. In contrast, accuracy on the person-identification task was not consistently underestimated. The results are discussed in light of their implications for real-world trials and future research.

  17. Non-Destructive, Laser-Based Individual Tree Aboveground Biomass Estimation in a Tropical Rainforest

    Directory of Open Access Journals (Sweden)

    Muhammad Zulkarnain Abd Rahman

    2017-03-01

    Full Text Available Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been driven by advances in remote sensing technology. The conventional approach to biomass estimation heavily relies on the tree species and site-specific allometric equations, which are based on destructive methods. This paper introduces a non-destructive, laser-based approach (terrestrial laser scanner for individual tree aboveground biomass estimation in the Royal Belum forest reserve, Perak, Malaysia. The study area is in the state park, and it is believed to be one of the oldest rainforests in the world. The point clouds generated for 35 forest plots, using the terrestrial laser scanner, were geo-rectified and cleaned to produce separate point clouds for individual trees. The volumes of tree trunks were estimated based on a cylinder model fitted to the point clouds. The biomasses of tree trunks were calculated by multiplying the volume and the species wood density. The biomasses of branches and leaves were also estimated based on the estimated volume and density values. Branch and leaf volumes were estimated based on the fitted point clouds using an alpha-shape approach. The estimated individual biomass and the total above ground biomass were compared with the aboveground biomass (AGB value estimated using existing allometric equations and individual tree census data collected in the field. The results show that the combination of a simple single-tree stem reconstruction and wood density can be used to estimate stem biomass comparable to the results usually obtained through existing allometric equations. However, there are several issues associated with the data and method used for branch and leaf biomass estimations, which need further improvement.

  18. Sea-ice monitoring by ship-based visual observation during JARE ―Simplification of observation method based on the ASPeCt protocol―

    OpenAIRE

    Kay I. Ohshima; Shuki Ushio; Akihisa S. Otsuki

    2006-01-01

    A protocol for ship-based visual observation of sea ice is proposed for the Japanese Antarctic Research Expedition (JARE). The protocol is a simplified version of the ASPeCt protocol, used for extracting quantitative information on sea ice. The ship-based visual observations started from JARE-46. In the pack ice region, ice thickness, ratio of deformed ice, and total ice volume increased toward the coast. Continuous monitoring of sea ice, particularly its thickness, by ship-based observation ...

  19. Control of variable speed variable pitch wind turbine based on a disturbance observer

    Science.gov (United States)

    Ren, Haijun; Lei, Xin

    2017-11-01

    In this paper, a novel sliding mode controller based on disturbance observer (DOB) to optimize the efficiency of variable speed variable pitch (VSVP) wind turbine is developed and analyzed. Due to the highly nonlinearity of the VSVP system, the model is linearly processed to obtain the state space model of the system. Then, a conventional sliding mode controller is designed and a DOB is added to estimate wind speed. The proposed control strategy can successfully deal with the random nature of wind speed, the nonlinearity of VSVP system, the uncertainty of parameters and external disturbance. Via adding the observer to the sliding mode controller, it can greatly reduce the chattering produced by the sliding mode switching gain. The simulation results show that the proposed control system has the effectiveness and robustness.

  20. A Novel Rules Based Approach for Estimating Software Birthmark

    Science.gov (United States)

    Binti Alias, Norma; Anwar, Sajid

    2015-01-01

    Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363