Observer-Based Human Knee Stiffness Estimation.
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.
Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis
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
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.)
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.
Estimating Evapotranspiration Using an Observation Based Terrestrial Water Budget
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.
Distributed estimation based on observations prediction in wireless sensor networks
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
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...
Distributed estimation based on observations prediction in wireless sensor networks
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.
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.
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
Observer-Based Fault Estimation and Accomodation for Dynamic Systems
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...
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...
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
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.
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.
Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations
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.
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.
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.
Estimation of the neuronal activation using fMRI data: An observer-based approach
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.
An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations
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.
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.
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.
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.
Estimating atmospheric visibility using synergy of MODIS data and ground-based observations
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.
Estimation of soft sediment thickness in Kuala Lumpur based on microtremor observation data
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.
Observation-based estimation of aerosol-induced reduction of planetary boundary layer height
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.
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
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.
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....
Estimating Global Impervious Surface based on Social-economic Data and Satellite Observations
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.
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....
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
Estimating the Grain Size Distribution of Mars based on Fragmentation Theory and Observations
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
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.
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.
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.
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.
Directory of Open Access Journals (Sweden)
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.
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...
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.
Observation-based estimate of the Fukushima radionuclide in the North Pacific
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.
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.
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.
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
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.
Estimation of the neuronal activation using fMRI data: An observer-based approach
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
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.
Estimates of Lightning NOx Production Based on OMI NO2 Observations Over the Gulf of Mexico
Pickering, Kenneth E.; Bucsela, Eric; Allen, Dale; Ring, Allison; Holzworth, Robert; Krotkov, Nickolay
2016-01-01
We evaluate nitrogen oxide (NO(sub x) NO + NO2) production from lightning over the Gulf of Mexico region using data from the Ozone Monitoring Instrument (OMI) aboard NASAs Aura satellite along with detection efficiency-adjusted lightning data from the World Wide Lightning Location Network (WWLLN). A special algorithm was developed to retrieve the lightning NOx [(LNO(sub x)] signal from OMI. The algorithm in its general form takes the total slant column NO2 from OMI and removes the stratospheric contribution and tropospheric background and includes an air mass factor appropriate for the profile of lightning NO(sub x) to convert the slant column LNO2 to a vertical column of LNO(sub x). WWLLN flashes are totaled over a period of 3 h prior to OMI overpass, which is the time an air parcel is expected to remain in a 1 deg. x 1 deg. grid box. The analysis is conducted for grid cells containing flash counts greater than a threshold value of 3000 flashes that yields an expected LNO(sub x) signal greater than the background. Pixels with cloud radiance fraction greater than a criterion value (0.9) indicative of highly reflective clouds are used. Results for the summer seasons during 2007-2011 yield mean LNO(sub x) production of approximately 80 +/- 45 mol per flash over the region for the two analysis methods after accounting for biases and uncertainties in the estimation method. These results are consistent with literature estimates and more robust than many prior estimates due to the large number of storms considered but are sensitive to several substantial sources of uncertainty.
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...
Choudhury, Bhaskar J.
An approach is presented for calculating interannual variation of net primary production (C) of terrestrial plant communities at regional scale using satellite and ground measurements. C has been calculated as the difference of gross photosynthesis (A g) and respiration (R), recognizing that different biophysical factors exert major control on these two processes. A g has been expressed as the product of radiation use efficiency for gross photosynthesis by an unstressed canopy and intercepted photosynthetically active radiation, which is then adjusted for stresses due to soil water shortage and temperature away from optimum. R has been calculated as the sum of growth and maintenance components (respectively, R g and R m. The R m has been determined from nitrogen content of plant tissue per unit ground area, while R g has been obtained as a fraction of the difference of A g and R m. Model parameters have not been determined by matching the calculated fluxes against observations at any location. Results are presented for cultivated and temperate deciduous forest areas over North America for five consecutive years (1986-1990) and compared with observations.
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.
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.
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
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
LOD estimation from DORIS observations
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.
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...
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...
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...
Observer variability in estimating numbers: An experiment
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.
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.
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.
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.
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
Redemann, J.; Livingston, J.; Shinozuka, Y.; Kacenelenbogen, M.; Russell, P.; LeBlanc, S.; Vaughan, M.; Ferrare, R.; Hostetler, C.; Rogers, R.;
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.
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.
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
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.
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.
CSIR Research Space (South Africa)
Symes, CT
2011-04-01
Full Text Available , observations (93.8%) and stable isotopes (92.6%), no significant differ- ence was recognized (t-test dependent samples, t = 0.84, P = 0.46). Discussion Observations A widely used method of studying feeding habits in termites is by assessing the choice.... Canadian Journal of Zoology, 78, 1?27. LaFage, J.P. and Nutting, W.L. (1978) Food and feeding habits of termites. Nutrient Dynamics of Termites (ed. M.V. Brian), pp. 165?232. Cambridge University Press, Cambridge. McKechnie, A.E. (2004) Stable isotopes...
Kalman filter data assimilation: targeting observations and parameter estimation.
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.
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
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.
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%.
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.
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....
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
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
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
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.
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...
Observers for vehicle tyre/road forces estimation: experimental validation
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.
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
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.
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.)
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.)
Evidence Estimation for Bayesian Partially Observed MRFs
Chen, Y.; Welling, M.
2013-01-01
Bayesian estimation in Markov random fields is very hard due to the intractability of the partition function. The introduction of hidden units makes the situation even worse due to the presence of potentially very many modes in the posterior distribution. For the first time we propose a
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)
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...
Estimating the Geocenter from GNSS Observations
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
Meteor trajectory estimation from radio meteor observations
Kákona, J.
2016-01-01
Radio meteor observation techniques are generally accepted as meteor counting methods useful mainly for meteor flux detection. Due to the technical progress in radio engineering and electronics a construction of a radio meteor detection network with software defined receivers has become possible. These receivers could be precisely time synchronized and could obtain data which provide us with more information than just the meteor count. We present a technique which is able to compute a meteor trajectory from the data recorded by multiple radio stations.
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.
Observationally constrained estimates of carbonaceous aerosol radiative forcing.
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.
Directory of Open Access Journals (Sweden)
Y. Chetouani
2008-12-01
Full Text Available This study presents a FDI strategy for nonlinear dynamic systems. It shows a methodology of tackling the fault detection and isolation issue by combining a technique based on the residuals signal and a technique using the multiple Kalman filters. The usefulness of this combination is the on-line implementation of the set of models, which represents the normal mode and all dynamics of faults, if the statistical decision threshold on the residuals exceeds a fixed value. In other cases, one Extended Kalman Filter (EKF is enough to estimate the process state. After describing the system architecture and the proposed FDI methodology, we present a realistic application in order to show the technique's potential. An algorithm is described and applied to a chemical process like a perfectly stirred chemical reactor functioning in a semi-batch mode. The chemical reaction used is an oxido reduction one, the oxidation of sodium thiosulfate by hydrogen peroxide.
Directory of Open Access Journals (Sweden)
Straand Jørund
2011-03-01
Full Text Available Abstract Background It is desirable that those at highest risk of cardiovascular disease should have priority for preventive measures, eg. treatment with prescription drugs to modify their risk. We wanted to investigate to what extent present use of cardiovascular medication (CVM correlates with cardiovascular risk estimated by three different risk scores (Framingham, SCORE and NORRISK ten years ago. Methods Prospective logitudinal observational study of 20 252 participants in The Hordaland Health Study born 1950-57, not using CVM in 1997-99. Prescription data obtained from The Norwegian Prescription Database in 2008. Results 26% of men and 22% of women aged 51-58 years had started to use some CVM during the previous decade. As a group, persons using CVM scored significantly higher on the risk algorithms Framingham, SCORE and NORRISK compared to those not treated. 16-20% of men and 20-22% of women with risk scores below the high-risk thresholds for the three risk scores were treated with CVM, while 60-65% of men and 25-45% of women with scores above the high-risk thresholds received no treatment. Among women using CVM, only 2.2% (NORRISK, 4.4% (SCORE and 14.5% (Framingham had risk scores above the high-risk values. Low education, poor self-reported general health, muscular pains, mental distress (in females only and a family history of premature cardiovascular disease correlated with use of CVM. Elevated blood pressure was the single factor most strongly predictive of CVM treatment. Conclusion Prescription of CVM to middle-aged individuals by large seems to occur independently of estimated total cardiovascular risk, and this applies especially to females.
US Air Force Base Observations
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...
Tong, X. X.; Hu, B.; Xu, W. S.; Liu, J. G.; Zhang, P. C.
2017-12-01
In this paper, Three Gorges Reservoir Area (TGRA) was chosen to be the study area, the export coefficients of different land-use type were calculated through the observation experiments and literature consultation, and then the load of non-point source (NPS) nitrogen and phosphorus of different pollution sources such as farmland pollution sources, decentralized livestock and poultry breeding pollution sources and domestic pollution sources were estimated. The results show as follows: the pollution load of dry land is the main source of farmland pollution. The order of total nitrogen load of different pollution sources from high to low is livestock breeding pollution, domestic pollution, land use pollution, while the order of phosphorus load of different pollution sources from high to low is land use pollution, livestock breeding pollution, domestic pollution, Therefore, reasonable farmland management, effective control methods of dry land fertilization and sewage discharge of livestock breeding are the keys to the prevention and control of NPS nitrogen and phosphorus in TGRA.
Estimating Coastal Turbidity using MODIS 250 m Band Observations
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.
Lindaas, J.; Commane, R.; Luus, K. A.; Chang, R. Y. W.; Miller, C. E.; Dinardo, S. J.; Henderson, J.; Mountain, M. E.; Karion, A.; Sweeney, C.; Miller, J. B.; Lin, J. C.; Daube, B. C.; Pittman, J. V.; Wofsy, S. C.
2014-12-01
The Alaskan region has historically been a sink of atmospheric CO2, but permafrost currently stores large amounts of carbon that are vulnerable to release to the atmosphere as northern high-latitudes continue to warm faster than the global average. We use aircraft CO2 data with a remote-sensing based model driven by MODIS satellite products and validated by CO2 flux tower data to calculate average daily CO2 fluxes for the region of Alaska during the growing seasons of 2012 and 2013. Atmospheric trace gases were measured during CARVE (Carbon in Arctic Reservoirs Vulnerability Experiment) aboard the NASA Sherpa C-23 aircraft. For profiles along the flight track, we couple the Weather Research and Forecasting (WRF) model with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, and convolve these footprints of surface influence with our remote-sensing based model, the Polar Vegetation Photosynthesis Respiration Model (PolarVPRM). We are able to calculate average regional fluxes for each month by minimizing the difference between the data and model column integrals. Our results provide a snapshot of the current state of regional Alaskan growing season net ecosystem exchange (NEE). We are able to begin characterizing the interannual variation in Alaskan NEE and to inform future refinements in process-based modeling that will produce better estimates of past, present, and future pan-Arctic NEE. Understanding if/when/how the Alaskan region transitions from a sink to a source of CO2 is crucial to predicting the trajectory of future climate change.
View Estimation Based on Value System
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.
Directory of Open Access Journals (Sweden)
Bizhong Xia
2017-08-01
Full Text Available Accurate state of charge (SOC estimation can prolong lithium-ion battery life and improve its performance in practice. This paper proposes a new method for SOC estimation. The second-order resistor-capacitor (2RC equivalent circuit model (ECM is applied to describe the dynamic behavior of lithium-ion battery on deriving state space equations. A novel method for SOC estimation is then presented. This method does not require any matrix calculation, so the computation cost can be very low, making it more suitable for hardware implementation. The Federal Urban Driving Schedule (FUDS, The New European Driving Cycle (NEDC, and the West Virginia Suburban Driving Schedule (WVUSUB experiments are carried to evaluate the performance of the proposed method. Experimental results show that the SOC estimation error can converge to 3% error boundary within 30 seconds when the initial SOC estimation error is 20%, and the proposed method can maintain an estimation error less than 3% with 1% voltage noise and 5% current noise. Further, the proposed method has excellent robustness against parameter disturbance. Also, it has higher estimation accuracy than the extended Kalman filter (EKF, but with decreased hardware requirements and faster convergence rate.
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...
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...
Estimating tropical vertical motion profile shapes from satellite observations
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.
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.
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...
Tuomi, Jari Michael; Voorbraak, Frans; Jones, Douglas L.; Ruijter, Jan M.
2010-01-01
For real-time monitoring of PCR amplification of DNA, quantitative PCR (qPCR) assays use various fluorescent reporters. DNA binding molecules and hybridization reporters (primers and probes) only fluoresce when bound to DNA and result in the non-cumulative increase in observed fluorescence.
Lee, Chulkyu; Martin Randall V.; vanDonkelaar, Aaron; Lee, Hanlim; Dickerson, RUssell R.; Hains, Jennifer C.; Krotkov, Nickolay; Richter, Andreas; Vinnikov, Konstantine; Schwab, James J.
2011-01-01
Top-down constraints on global sulfur dioxide (SO2) emissions are inferred through inverse modeling using SO2 column observations from two satellite instruments (SCIAMACHY and OMI). We first evaluated the S02 column observations with surface SO2 measurements by applying local scaling factors from a global chemical transport model (GEOS-Chem) to SO2 columns retrieved from the satellite instruments. The resulting annual mean surface SO2 mixing ratios for 2006 exhibit a significant spatial correlation (r=0.86, slope=0.91 for SCIAMACHY and r=0.80, slope = 0.79 for OMI) with coincident in situ measurements from monitoring networks throughout the United States and Canada. We evaluate the GEOS-Chem simulation of the SO2 lifetime with that inferred from in situ measurements to verity the applicability of GEOS-Chem for inversion of SO2 columns to emissions. The seasonal mean SO2 lifetime calculated with the GEOS-Chem model over the eastern United States is 13 h in summer and 48 h in winter, compared to lifetimes inferred from in situ measurements of 19 +/- 7 h in summer and 58 +/- 20 h in winter. We apply SO2 columns from SCIAMACHY and OMI to derive a top-down anthropogenic SO2 emission inventory over land by using the local GEOS-Chem relationship between SO2 columns and emissions. There is little seasonal variation in the top-down emissions (SO2 emissions (52.4 Tg S/yr from SCIAMACHY and 49.9 Tg S / yr from OMI) closely agrees with the bottom-up emissions (54.6 Tg S/yr) in the GEOS-Chem model and exhibits consistency in global distributions with the bottom-up emissions (r = 0.78 for SCIAMACHY, and r = 0.77 for OMI). However, there are significant regional differences.
Surface Soil Moisture Memory Estimated from Models and SMAP Observations
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
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.
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
Directory of Open Access Journals (Sweden)
K. Mizutani
2007-07-01
Full Text Available It is important to obtain the year-to-year trend of stratospheric minor species in the context of global changes. An important example is the trend in global ozone depletion. The purpose of this paper is to report the accuracy and precision of measurements of stratospheric chemical species that are made at our Poker Flat site in Alaska (65° N, 147° W. Since 1999, minor atmospheric molecules have been observed using a Fourier-Transform solar-absorption infrared Spectrometer (FTS at Poker Flat. Vertical profiles of the abundances of ozone, HNO3, HCl, and HF for the period from 2001 to 2003 were retrieved from FTS spectra using Rodgers' formulation of the Optimal Estimation Method (OEM. The accuracy and precision of the retrievals were estimated by formal error analysis. Errors for the total column were estimated to be 5.3%, 3.4%, 5.9%, and 5.3% for ozone, HNO3, HCl, and HF, respectively. The ozone vertical profiles were in good agreement with profiles derived from collocated ozonesonde measurements that were smoothed with averaging kernel functions that had been obtained with the retrieval procedure used in the analysis of spectra from the ground-based FTS (gb-FTS. The O3, HCl, and HF columns that were retrieved from the FTS measurements were consistent with Earth Probe/Total Ozone Mapping Spectrometer (TOMS and HALogen Occultation Experiment (HALOE data over Alaska within the error limits of all the respective datasets. This is the first report from the Poker Flat FTS observation site on a number of stratospheric gas profiles including a comprehensive error analysis.
NASA Software Cost Estimation Model: An Analogy Based Estimation Model
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.
Fast Emission Estimates in China Constrained by Satellite Observations (Invited)
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
Estimating North Dakota's Economic Base
Coon, Randal C.; Leistritz, F. Larry
2009-01-01
North Dakota’s economic base is comprised of those activities producing a product paid for by nonresidents, or products exported from the state. North Dakota’s economic base activities include agriculture, mining, manufacturing, tourism, and federal government payments for construction and to individuals. Development of the North Dakota economic base data is important because it provides the information to quantify the state’s economic growth, and it creates the final demand sectors for the N...
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)
Estimation of human core temperature from sequential heart rate observations.
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.
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.
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.
Consistent estimate of ocean warming, land ice melt and sea level rise from Observations
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.
Estimates of lightning NOx production from GOME satellite observations
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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
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.
A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data
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.
Estimation of Regional Carbon Balance from Atmospheric Observations
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
Biogenic nonmethane hydrocarbon emissions estimated from tethered balloon observations
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.
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.
Monte Carlo-based tail exponent estimator
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.
Channel Estimation in DCT-Based OFDM
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
Statistical inference based on latent ability estimates
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
Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance
Nag, Sreeja; Gatebe, Charles K.; de Weck, Olivier
2015-01-01
The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.
Observing system simulations for small satellite formations estimating bidirectional reflectance
Nag, Sreeja; Gatebe, Charles K.; Weck, Olivier de
2015-12-01
The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.
An adaptive observer for on-line tool wear estimation in turning, Part I: Theory
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).
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.
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
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.
Fine-tuning satellite-based rainfall estimates
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.
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.
Estimating the intrinsic properties of miras from observational data
International Nuclear Information System (INIS)
Cahn, J.H.; Wyatt, S.P.
1978-01-01
We explore several of the consequences of the model of late stellar evolution recently investigated by Wood and Cahn. As stars ascend the asymptotic giant branch in the H-R plane, they evolve from left to right in the (M, log L) -plane, and also sink downward as they suffer a steady stellar-wind mass loss of the Reimers type. Stars in the approximate range of 1--2 M/sub sun/ eventually evolve to the point where they apparently begin first-overtone oscillation; during this phase they are Mira variables for a few hundred thousand years. At the end of their Mira stage, many of these stars evolve directly to white dwarfs; the rest of them eject one or more planetary nebulae before entering white-dwarf territory. Higher-mass stars evolve across the (M, log L) -plane without ever penetrating the Mira region and go on directly to give rise to planetary nebulae and eventually become white dwarfs. Stars of even greater mass presumably end their migration across the (M, logL) -domain by becoming supernovae. We adopt this broad picture and go on first to the Mira variables, seeking to establish an empirical diagram of period of light variation against mean spectral type at maximum light. Curves of constant period and constant spectral type are superposed on the (M, logL) -plane, along with evolutionary tracks and time scales. Thus a knowlege of the observed mean spectral type at maximum light and the period of a star permits approximate estimates to be made of its mean bolometric luminosity and present mass and gives a bird's-eve view of its past and future evolutionary track
Estimation of Skin to Subarachnoid Space Depth: An Observational Study.
Hazarika, Rajib; Choudhury, Dipika; Nath, Sangeeta; Parua, Samit
2016-10-01
In a patient, the skin to Subarachnoid Space Depth (SSD) varies considerably at different levels of the spinal cord. It also varies from patient to patient at the same vertebral level as per age, sex and Body Mass Index (BMI). Estimation of the skin to SSD reduces complications related to spinal anaesthesia. To measure the skin to SSD in the Indian population and to find a formula for predicting this depth. Three hundred adult patients belonging to American Society of Anaesthesiologist class I and II, undergoing surgery using spinal anaesthesia in various surgical specialities of Gauhati Medical College were selected by systemic sampling for this prospective, observational study. Patients were divided into three groups: Group M containing male patients, Group F containing non-pregnant female patients, and Group PF containing pregnant female's patients. SSD was measured after performing lumbar puncture. The relationship between SSD and patient characteristics were studied, correlated and statistical analysis was used to find a formula for predicting the skin to SSD. Statistical analysis was done using Statistical Package for Social Sciences (SPSS 21.0, Chicago, IL, USA). One-way ANOVA with post-hoc(Bonferroni correction factor) analysis was applied to compare the three groups. Multivariate analysis was done for the covariates followed by a multivariate regression analysis to evaluate the covariates influencing SSD for each group separately. Mean SSD was 4.37±0.31cm in the overall population. SSD in adult males was 4.49±0.19cm which was significantly longer than that observed in female's 4.18±0.39cm which was comparable with SSD in parturient 4.43±0.19 cm. The formula for predicting the skin to SSD in the male population was 1.718+0.077×BMI+0.632×Height, in nonpregnant female population was 1.828+0.077×BMI+0.018×Height+0.007×Age and 0.748+0.209×BMI+4.703×Height-0.054×weight in parturient females, respectively. Skin to SSD correlated with the BMI in all
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...
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.
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.
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...
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
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.
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
Model-based estimation for dynamic cardiac studies using ECT.
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.
Observation of the pulse oximeter trace to estimate systolic blood ...
African Journals Online (AJOL)
Background: The estimation of systolic blood pressure by disappearance and reappearance of the pulse oximeter trace during cuff inflation and deflation was compared with non-invasive blood pressure (NIBP) measurement, across the range of body mass index (BMI), during spinal anaesthesia for Caesarean section.
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...
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.
Atmospheric evaporative demand observations, estimates and driving factors in Spain (1961-2011)
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.
Atmospheric evaporative demand observations, estimates and driving factors in Spain (1961-2011)
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.
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
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
... prediction, offshore energy, power generation, and commercial fishing. Our findings suggest that annual benefits to users from the deployment of ocean observing systems are likely to run in the multiple...
Ab initio estimates of the size of the observable universe
International Nuclear Information System (INIS)
Page, Don N.
2011-01-01
When one combines multiverse predictions by Bousso, Hall, and Nomura for the observed age and size of the universe in terms of the proton and electron charge and masses with anthropic predictions of Carter, Carr, and Rees for these masses in terms of the charge, one gets that the age of the universe should be roughly the inverse 64th power, and the cosmological constant should be around the 128th power, of the proton charge. Combining these with a further renormalization group argument gives a single approximate equation for the proton charge, with no continuous adjustable or observed parameters, and with a solution that is within 8% of the observed value. Using this solution gives large logarithms for the age and size of the universe and for the cosmological constant that agree with the observed values within 17%
Ab initio estimates of the size of the observable universe
Energy Technology Data Exchange (ETDEWEB)
Page, Don N., E-mail: profdonpage@gmail.com [Department of Physics, 4-183 CCIS, University of Alberta, Edmonton, Alberta T6G 2E1 Canada (Canada)
2011-09-01
When one combines multiverse predictions by Bousso, Hall, and Nomura for the observed age and size of the universe in terms of the proton and electron charge and masses with anthropic predictions of Carter, Carr, and Rees for these masses in terms of the charge, one gets that the age of the universe should be roughly the inverse 64th power, and the cosmological constant should be around the 128th power, of the proton charge. Combining these with a further renormalization group argument gives a single approximate equation for the proton charge, with no continuous adjustable or observed parameters, and with a solution that is within 8% of the observed value. Using this solution gives large logarithms for the age and size of the universe and for the cosmological constant that agree with the observed values within 17%.
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)
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...
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
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.
Estimates of lightning NOx production from GOME satellite observations
Boersma, K.F.; Eskes, H.J.; Meijer, E.W.; Kelder, H.M.
2005-01-01
Tropospheric NO2 column retreivals from the Global Ozone Monitoring Expeiment (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
Cosmological Parameter Estimation with Large Scale Structure Observations
Di Dio, Enea; Durrer, Ruth; Lesgourgues, Julien
2014-01-01
We estimate the sensitivity of future galaxy surveys to cosmological parameters, using the redshift dependent angular power spectra of galaxy number counts, $C_\\ell(z_1,z_2)$, calculated with all relativistic corrections at first order in perturbation theory. We pay special attention to the redshift dependence of the non-linearity scale and present Fisher matrix forecasts for Euclid-like and DES-like galaxy surveys. We compare the standard $P(k)$ analysis with the new $C_\\ell(z_1,z_2)$ method. We show that for surveys with photometric redshifts the new analysis performs significantly better than the $P(k)$ analysis. For spectroscopic redshifts, however, the large number of redshift bins which would be needed to fully profit from the redshift information, is severely limited by shot noise. We also identify surveys which can measure the lensing contribution and we study the monopole, $C_0(z_1,z_2)$.
Estimation of dynamic properties of attractors observed in hollow ...
Indian Academy of Sciences (India)
Laser and Plasma Technology Division, Bhabha Atomic Research Centre, Trombay, ... online control have been reported based on time series, power spectrum, .... nals are different due to their different intrinsic dependence in terms of micro– ...
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.
SCIAMACHY formaldehyde observations: constraint for isoprene emission estimates over Europe?
Directory of Open Access Journals (Sweden)
G. Dufour
2009-03-01
Full Text Available Formaldehyde (HCHO is an important intermediate compound in the degradation of volatile organic compounds (VOCs in the troposphere. Sources of HCHO are largely dominated by its secondary production from VOC oxidation, methane and isoprene being the main precursors in unpolluted areas. As a result of the moderate lifetime of HCHO, its spatial distribution is determined by reactive hydrocarbon emissions. We focus here on Europe and investigate the influence of the different emissions on HCHO tropospheric columns with the CHIMERE chemical transport model in order to interpret the comparisons between SCIAMACHY and simulated HCHO columns. Europe was never specifically studied before for these purposes using satellite observations. The bias between measurements and model is less than 20% on average. The differences are discussed according to the errors on the model and the observations and remaining discrepancies are attributed to a misrepresentation of biogenic emissions. This study requires the characterisation of: (1 the model errors and performances concerning formaldehyde. The errors on the HCHO columns, mainly related to chemistry and mixed emission types, are evaluated to 2×10^{15} molecule/cm^{2} and the model performances evaluated using surface measurements are satisfactory (~13%; (2 the observation errors that define the needs in spatial and temporal averaging for meaningful comparisons. Using SCIAMACHY observations as constraint for biogenic isoprene emissions in an inverse modelling scheme reduces their uncertainties by about a factor of two in region of intense emissions. The retrieved correction factors for the isoprene emissions range from a factor of 0.15 (North Africa to a factor of 2 (Poland, the United Kingdom depending on the regions.
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...
Estimating daily climatologies for climate indices derived from climate model data and observations
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
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.
Ground-based observations of exoplanet atmospheres
Mooij, Ernst Johan Walter de
2011-01-01
This thesis focuses on the properties of exoplanet atmospheres. The results for ground-based near-infrared secondary eclipse observations of three different exoplanets, TrES-3b, HAT-P-1b and WASP-33b, are presented which have been obtained with ground-based telescopes as part of the GROUSE project.
Learning Theory Estimates with Observations from General Stationary Stochastic Processes.
Hang, Hanyuan; Feng, Yunlong; Steinwart, Ingo; Suykens, Johan A K
2016-12-01
This letter investigates the supervised learning problem with observations drawn from certain general stationary stochastic processes. Here by general, we mean that many stationary stochastic processes can be included. We show that when the stochastic processes satisfy a generalized Bernstein-type inequality, a unified treatment on analyzing the learning schemes with various mixing processes can be conducted and a sharp oracle inequality for generic regularized empirical risk minimization schemes can be established. The obtained oracle inequality is then applied to derive convergence rates for several learning schemes such as empirical risk minimization (ERM), least squares support vector machines (LS-SVMs) using given generic kernels, and SVMs using gaussian kernels for both least squares and quantile regression. It turns out that for independent and identically distributed (i.i.d.) processes, our learning rates for ERM recover the optimal rates. For non-i.i.d. processes, including geometrically [Formula: see text]-mixing Markov processes, geometrically [Formula: see text]-mixing processes with restricted decay, [Formula: see text]-mixing processes, and (time-reversed) geometrically [Formula: see text]-mixing processes, our learning rates for SVMs with gaussian kernels match, up to some arbitrarily small extra term in the exponent, the optimal rates. For the remaining cases, our rates are at least close to the optimal rates. As a by-product, the assumed generalized Bernstein-type inequality also provides an interpretation of the so-called effective number of observations for various mixing processes.
Postprocessing MPEG based on estimated quantization parameters
DEFF Research Database (Denmark)
Forchhammer, Søren
2009-01-01
the case where the coded stream is not accessible, or from an architectural point of view not desirable to use, and instead estimate some of the MPEG stream parameters based on the decoded sequence. The I-frames are detected and the quantization parameters are estimated from the coded stream and used...... in the postprocessing. We focus on deringing and present a scheme which aims at suppressing ringing artifacts, while maintaining the sharpness of the texture. The goal is to improve the visual quality, so perceptual blur and ringing metrics are used in addition to PSNR evaluation. The performance of the new `pure......' postprocessing compares favorable to a reference postprocessing filter which has access to the quantization parameters not only for I-frames but also on P and B-frames....
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...
Observations and estimates of wave-driven water level extremes at the Marshall Islands
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.
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
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.
ESTIMATION OF STATURE BASED ON FOOT LENGTH
Directory of Open Access Journals (Sweden)
Vidyullatha Shetty
2015-01-01
Full Text Available BACKGROUND : Stature is the height of the person in the upright posture. It is an important measure of physical identity. Estimation of body height from its segments or dismember parts has important considerations for identifications of living or dead human body or remains recovered from disasters or other similar conditions. OBJECTIVE : Stature is an important indicator for identification. There are numerous means to establish stature and their significance lies in the simplicity of measurement, applicability and accuracy in prediction. Our aim of the study was to review the relationship between foot length and body height. METHODS : The present study reviews various prospective studies which were done to estimate the stature. All the measurements were taken by using standard measuring devices and standard anthropometric techniques. RESULTS : This review shows there is a correlation between stature and foot dimensions it is found to be positive and statistically highly significant. Prediction of stature was found to be most accurate by multiple regression analysis. CONCLUSIONS : Stature and gender estimation can be done by using foot measurements and stud y will help in medico - legal cases in establishing identity of an individual and this would be useful for Anatomists and Anthropologists to calculate stature based on foot length
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.
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.
On the estimation of ice thickness from scattering observations
Williams, T. D.; Squire, V. A.
2010-04-01
This paper is inspired by the proposition that it may be possible to extract descriptive physical parameters - in particular the ice thickness, of a sea-ice field from ocean wave information. The motivation is that mathematical theory describing wave propagation in such media has reached a point where the inherent heterogeneity, expressed as pressure ridge keels and sails, leads, thickness variations and changes of material property and draught, can be fully assimilated exactly or through approximations whose limitations are understood. On the basis that leads have the major wave scattering effect for most sea-ice [Williams, T.D., Squire, V.A., 2004. Oblique scattering of plane flexural-gravity waves by heterogeneities in sea ice. Proc. R. Soc. Lon. Ser.-A 460 (2052), 3469-3497], a model two dimensional sea-ice sheet composed of a large number of such features, randomly dispersed, is constructed. The wide spacing approximation is used to predict how wave trains of different period will be affected, after first establishing that this produces results that are very close to the exact solution. Like Kohout and Meylan [Kohout, A.L., Meylan, M.H., 2008. An elastic plate model for wave attenuation and ice floe breaking in the marginal ice zone. J. Geophys. Res. 113, C09016, doi:10.1029/2007JC004434], we find that on average the magnitude of a wave transmitted by a field of leads decays exponentially with the number of leads. Then, by fitting a curve based on this assumption to the data, the thickness of the ice sheet is obtained. The attenuation coefficient can always be calculated numerically by ensemble averaging but in some cases more rapidly computed approximations work extremely well. Moreover, it is found that the underlying thickness can be determined to good accuracy by the method as long as Archimedean draught is correctly provided for, suggesting that waves can indeed be effective as a remote sensing agent to measure ice thickness in areas where pressure ridges
Lévy matters IV estimation for discretely observed Lévy processes
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...
Quantifying Surface Energy Flux Estimation Uncertainty Using Land Surface Temperature Observations
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.
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.
Estimating Soil Hydraulic Parameters using Gradient Based Approach
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.
The effect of correlated observations on the performance of distributed estimation
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
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)
Estimating Terrestrial Wood Biomass from Observed Concentrations of Atmospheric Carbon Dioxide
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
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...
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.
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.
Observability-Based Guidance and Sensor Placement
Hinson, Brian T.
Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.
ESTIMATION OF GRASPING TORQUE USING ROBUST REACTION TORQUE OBSERVER FOR ROBOTIC FORCEPS
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...
Access Based Cost Estimation for Beddown Analysis
National Research Council Canada - National Science Library
Pennington, Jasper E
2006-01-01
The purpose of this research is to develop an automated web-enabled beddown estimation application for Air Mobility Command in order to increase the effectiveness and enhance the robustness of beddown estimates...
An optimal pole-matching observer design for estimating tyre-road friction force
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.
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
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
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...
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...
Observing Tsunamis in the Ionosphere Using Ground Based GPS Measurements
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.
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.
Estimating surface soil moisture from SMAP observations using a Neural Network technique.
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.
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.
Estimating Field Scale Crop Evapotranspiration using Landsat and MODIS Satellite Observations
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.
Observation, Sherlock Holmes, and Evidence Based Medicine.
Osborn, John
2002-01-01
Sir Arthur Conan Doyle, the creator of the fictional detective Sherlock Holmes, studied medicine at the University of Edinburgh between 1876 and 1881 under Doctor Joseph Bell who emphasised in his teaching the importance of observation, deduction and evidence. Sherlock Holmes was modelled on Joseph Bell. The modern notions of Evidence Based Medicine (EBM) are not new. A very brief indication of some of the history of EBM is presented including a discussion of the important and usually overlooked contribution of statisticians to the Popperian philosophy of EBM.
FPGA-Based Embedded Motion Estimation Sensor
Directory of Open Access Journals (Sweden)
Zhaoyi Wei
2008-01-01
Full Text Available Accurate real-time motion estimation is very critical to many computer vision tasks. However, because of its computational power and processing speed requirements, it is rarely used for real-time applications, especially for micro unmanned vehicles. In our previous work, a FPGA system was built to process optical flow vectors of 64 frames of 640×480 image per second. Compared to software-based algorithms, this system achieved much higher frame rate but marginal accuracy. In this paper, a more accurate optical flow algorithm is proposed. Temporal smoothing is incorporated in the hardware structure which significantly improves the algorithm accuracy. To accommodate temporal smoothing, the hardware structure is composed of two parts: the derivative (DER module produces intermediate results and the optical flow computation (OFC module calculates the final optical flow vectors. Software running on a built-in processor on the FPGA chip is used in the design to direct the data flow and manage hardware components. This new design has been implemented on a compact, low power, high performance hardware platform for micro UV applications. It is able to process 15 frames of 640×480 image per second and with much improved accuracy. Higher frame rate can be achieved with further optimization and additional memory space.
Dictionary-based fiber orientation estimation with improved spatial consistency.
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
Small-mammal density estimation: A field comparison of grid-based vs. web-based density estimators
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
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...
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.
MODIS Based Estimation of Forest Aboveground Biomass in China
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
MODIS Based Estimation of Forest Aboveground Biomass in China.
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.
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.
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)
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.
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.
Reliability Estimation Based Upon Test Plan Results
National Research Council Canada - National Science Library
Read, Robert
1997-01-01
The report contains a brief summary of aspects of the Maximus reliability point and interval estimation technique as it has been applied to the reliability of a device whose surveillance tests contain...
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
Estimating Allee dynamics before they can be observed: polar bears as a case study.
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
Monte Carlo-Based Tail Exponent Estimator
Czech Academy of Sciences Publication Activity Database
Baruník, Jozef; Vácha, Lukáš
2010-01-01
Roč. 2010, č. 6 (2010), s. 1-26 R&D Projects: GA ČR GA402/09/0965; GA ČR GD402/09/H045; GA ČR GP402/08/P207 Institutional research plan: CEZ:AV0Z10750506 Keywords : Hill estimator * α-stable distributions * tail exponent estimation Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2010/E/barunik-0342493.pdf
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....
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....
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....
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....
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
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.
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
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.
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.
Plouff, Donald
2000-01-01
Gravity observations are directly made or are obtained from other sources by the U.S. Geological Survey in order to prepare maps of the anomalous gravity field and consequently to interpret the subsurface distribution of rock densities and associated lithologic or geologic units. Observations are made in the field with gravity meters at new locations and at reoccupations of previously established gravity "stations." This report illustrates an interactively-prompted series of steps needed to convert gravity "readings" to values that are tied to established gravity datums and includes computer programs to implement those steps. Inasmuch as individual gravity readings have small variations, gravity-meter (instrument) drift may not be smoothly variable, and acommodations may be needed for ties to previously established stations, the reduction process is iterative. Decision-making by the program user is prompted by lists of best values and graphical displays. Notes about irregularities of topography, which affect the value of observed gravity but are not shown in sufficient detail on topographic maps, must be recorded in the field. This report illustrates ways to record field notes (distances, heights, and slope angles) and includes computer programs to convert field notes to gravity terrain corrections. This report includes approaches that may serve as models for other applications, for example: portrayal of system flow; style of quality control to document and validate computer applications; lack of dependence on proprietary software except source code compilation; method of file-searching with a dwindling list; interactive prompting; computer code to write directly in the PostScript (Adobe Systems Incorporated) printer language; and high-lighting the four-digit year on the first line of time-dependent data sets for assured Y2K compatibility. Computer source codes provided are written in the Fortran scientific language. In order for the programs to operate, they first
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.
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
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.
Web-based Interspecies Correlation Estimation
Web-ICE estimates acute toxicity (LC50/LD50) of a chemical to a species, genus, or family from the known toxicity of the chemical to a surrogate species. Web-ICE has modules to predict acute toxicity to aquatic (fish and invertebrates) and wildlife (birds and mammals) taxa for us...
Empirically Driven Variable Selection for the Estimation of Causal Effects with Observational Data
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…
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
A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations
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
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.
Clutch pressure estimation for a power-split hybrid transmission using nonlinear robust observer
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.
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
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.
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.
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.
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
Adaptive nonparametric estimation for L\\'evy processes observed at low frequency
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, ...
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
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
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...
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.
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.
The observer-based synchronization and parameter estimation of a ...
Indian Academy of Sciences (India)
Haipeng Su
2017-10-31
Oct 31, 2017 ... of a class of chaotic system via a single output. HAIPENG SU, RUNZI LUO ... considerable attention due to its potential applications in many areas, such ... by using the chaotic- search artificial bee colony algorithm (CSABC) is.
Irving, J. D.; Singha, K.
2010-12-01
Traditionally, hydrological measurements have been used to estimate subsurface properties controlling groundwater flow and contaminant transport. However, such measurements are limited by their support volume and expense. A considerable benefit of geophysical measurements is that they provide a degree of spatial coverage and resolution that are unattainable with other methods, and the data can be acquired in a cost-effective manner. In particular, dynamic geophysical data allow us to indirectly observe changes in hydrological state variables as flow and transport processes occur, and can thus provide a link to hydrological properties when coupled with a process-based model. Stochastic fusion of these two data types offers the potential to provide not only estimates of subsurface hydrological properties, but also a quantification of their uncertainty. This information is critical when considering the end use of the data, which may be for groundwater remediation and management decision making. Here, we examine a number of key issues in the stochastic fusion of dynamic hydrogeophysical data. We focus our attention on the specific problem of integrating time-lapse crosshole electrical resistivity measurements and saline tracer-test concentration data in order to estimate the spatial distribution of hydraulic conductivity (K). To assimilate the geophysical and hydrological measurements in a stochastic manner, we use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology. This provides multiple realizations of the subsurface K field that are consistent with the measured data and assumptions regarding model structure and data errors. To account for incomplete petrophysical knowledge, the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration following the general form of Archie’s law. To make the spatially distributed, fully stochastic inverse problem computationally tractable, we take
Estimating the size of non-observed economy in Croatia using the MIMIC approach
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 ...
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.
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...
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.
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.
Mesospheric temperatures estimated from the meteor radar observations at Mohe, China
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
Estimating a Global Hydrological Carrying Capacity Using GRACE Observed Water Stress
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)
Normal estimation for pointcloud using GPU based sparse tensor voting
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...
The effect of correlated observations on the performance of distributed estimation
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.
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.
Uniform stable observer for the disturbance estimation in two renewable energy systems.
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.
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.
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
Sample Based Unit Liter Dose Estimates
International Nuclear Information System (INIS)
JENSEN, L.
2000-01-01
The Tank Waste Characterization Program has taken many core samples, grab samples, and auger samples from the single-shell and double-shell tanks during the past 10 years. Consequently, the amount of sample data available has increased, both in terms of quantity of sample results and the number of tanks characterized. More and better data is available than when the current radiological and toxicological source terms used in the Basis for Interim Operation (BIO) (FDH 1999a) and the Final Safety Analysis Report (FSAR) (FDH 1999b) were developed. The Nuclear Safety and Licensing (NS and L) organization wants to use the new data to upgrade the radiological and toxicological source terms used in the BIO and FSAR. The NS and L organization requested assistance in producing a statistically based process for developing the source terms. This report describes the statistical techniques used and the assumptions made to support the development of a new radiological source term for liquid and solid wastes stored in single-shell and double-shell tanks. The results given in this report are a revision to similar results given in an earlier version of the document (Jensen and Wilmarth 1999). The main difference between the results in this document and the earlier version is that the dose conversion factors (DCF) for converting μCi/g or μCi/L to Sv/L (sieverts per liter) have changed. There are now two DCFs, one based on ICRP-68 and one based on ICW-71 (Brevick 2000)
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.
Optimal difference-based estimation for partially linear models
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.
Optimal difference-based estimation for partially linear models
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.
A novel method for state of charge estimation of lithium-ion batteries using a nonlinear observer
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.
Chaos synchronization based on intermittent state observer
Institute of Scientific and Technical Information of China (English)
Li Guo-Hui; Zhou Shi-Ping; Xu De-Ming
2004-01-01
This paper describes the method of synchronizing slave to the master trajectory using an intermittent state observer by constructing a synchronizer which drives the response system globally tracing the driving system asymptotically. It has been shown from the theory of synchronization error-analysis that a satisfactory result of chaos synchronization is expected under an appropriate intermittent period and state observer. Compared with continuous control method,the proposed intermittent method can target the desired orbit more efficiently. The application of the method is demonstrated on the hyperchaotic Rossler systems. Numerical simulations show that the length of the synchronization interval rs is of crucial importance for our scheme, and the method is robust with respect to parameter mismatch.
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.
Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Kim, Kyu-Myong
2004-01-01
Over the tropical land regions observations of the 85 GHz brightness temperature (T(sub 85v)) made by the TRMM Microwave Imager (TMI) radiometer when analyzed with the help of rain rate (R(sub pR)) deduced from the TRMM Precipitation Radar (PR) indicate that there are two maxima in rain rate. One strong maximum occurs when T(sub 85) has a value of about 220 K and the other weaker one when T(sub 85v) is much colder approx. 150 K. Together with the help of earlier studies based on airborne Doppler Radar observations and radiative transfer theoretical simulations, we infer the maximum near 220 K is a result of relatively weak scattering due to super cooled rain drops and water coated ice hydrometeors associated with a developing thunderstorm (Cb) that has a strong updraft. The other maximum is associated with strong scattering due to ice particles that are formed when the updraft collapses and the rain from the Cb is transit2oning from convective type to stratiform type. Incorporating these ideas and with a view to improve the estimation of rain rate from existing operational method applicable to the tropical land areas, we have developed a rain retrieval model. This model utilizes two parameters, that have a horizontal scale of approx. 20km, deduced from the TMI measurements at 19, 21 and 37 GHz (T(sub 19v), T(sub 21v), T(sub 37v). The third parameter in the model, namely the horizontal gradient of brightness temperature within the 20 km scale, is deduced from TMI measurements at 85 GHz. Utilizing these parameters our retrieval model is formulated to yield instantaneous rain rate on a scale of 20 km and seasonal average on a mesoscale that agree well with that of the PR.
Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks
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
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
Data base to compare calculations and observations
International Nuclear Information System (INIS)
Tichler, J.L.
1985-01-01
Meteorological and climatological data bases were compared with known tritium release points and diffusion calculations to determine if calculated concentrations could replace measure concentrations at the monitoring stations. Daily tritium concentrations were monitored at 8 stations and 16 possible receptors. Automated data retrieval strategies are listed
Sample Based Unit Liter Dose Estimates
International Nuclear Information System (INIS)
JENSEN, L.
1999-01-01
The Tank Waste Characterization Program has taken many core samples, grab samples, and auger samples from the single-shell and double-shell tanks during the past 10 years. Consequently, the amount of sample data available has increased, both in terms of quantity of sample results and the number of tanks characterized. More and better data is available than when the current radiological and toxicological source terms used in the Basis for Interim Operation (BIO) (FDH 1999) and the Final Safety Analysis Report (FSAR) (FDH 1999) were developed. The Nuclear Safety and Licensing (NS and L) organization wants to use the new data to upgrade the radiological and toxicological source terms used in the BIO and FSAR. The NS and L organization requested assistance in developing a statistically based process for developing the source terms. This report describes the statistical techniques used and the assumptions made to support the development of a new radiological source term for liquid and solid wastes stored in single-shell and double-shell tanks
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.
Cloud Based Earth Observation Data Exploitation Platforms
Romeo, A.; Pinto, S.; Loekken, S.; Marin, A.
2017-12-01
In the last few years data produced daily by several private and public Earth Observation (EO) satellites reached the order of tens of Terabytes, representing for scientists and commercial application developers both a big opportunity for their exploitation and a challenge for their management. New IT technologies, such as Big Data and cloud computing, enable the creation of web-accessible data exploitation platforms, which offer to scientists and application developers the means to access and use EO data in a quick and cost effective way. RHEA Group is particularly active in this sector, supporting the European Space Agency (ESA) in the Exploitation Platforms (EP) initiative, developing technology to build multi cloud platforms for the processing and analysis of Earth Observation data, and collaborating with larger European initiatives such as the European Plate Observing System (EPOS) and the European Open Science Cloud (EOSC). An EP is a virtual workspace, providing a user community with access to (i) large volume of data, (ii) algorithm development and integration environment, (iii) processing software and services (e.g. toolboxes, visualization routines), (iv) computing resources, (v) collaboration tools (e.g. forums, wiki, etc.). When an EP is dedicated to a specific Theme, it becomes a Thematic Exploitation Platform (TEP). Currently, ESA has seven TEPs in a pre-operational phase dedicated to geo-hazards monitoring and prevention, costal zones, forestry areas, hydrology, polar regions, urban areas and food security. On the technology development side, solutions like the multi cloud EO data processing platform provides the technology to integrate ICT resources and EO data from different vendors in a single platform. In particular it offers (i) Multi-cloud data discovery, (ii) Multi-cloud data management and access and (iii) Multi-cloud application deployment. This platform has been demonstrated with the EGI Federated Cloud, Innovation Platform Testbed Poland
Estimating Soil and Vegetation Parameters using Synergies between Optical and Microwave Observations
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.
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...
Number of discernible colors for color-deficient observers estimated from the MacAdam limits.
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.
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.
Disease prevalence estimations based on contact registrations in general practice
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
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.
Watanabe, T.; Nohara, D.
2017-12-01
The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.
Robust linear discriminant analysis with distance based estimators
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.
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.
Discrete-time state estimation for stochastic polynomial systems over polynomial observations
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.
Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model
Directory of Open Access Journals (Sweden)
Xue Feng Hu
2017-01-01
Full Text Available Abstract Background Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence. Methods We proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD, with prevalence data from successive surveys and mortality data from empirical studies. Hallett’s method designed for estimating HIV infections in Africa was modified to estimate the incidence of myocardial infarction (MI in the U.S. population and incidence of heart disease in the Canadian population. Results Model-derived estimates were in close agreement with observed incidence from cohort studies and population surveillance systems. This method correctly captured the trend in incidence given sufficient waves of cross-sectional surveys. The estimated MI declining rate in the U.S. population was in accordance with the literature. This method was superior to closed cohort, in terms of the estimating trend of population cardiovascular disease incidence. Conclusion It is possible to estimate CVD incidence accurately at the population level from cross-sectional prevalence data. This method has the potential to be used for age- and sex- specific incidence estimates, or to be expanded to other chronic conditions.
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...
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.
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...
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...
Estimating security betas using prior information based on firm fundamentals
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
Particle filter based MAP state estimation: A comparison
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
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...
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.
Fast emission estimates in China and South Africa constrained by satellite observations
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
Rate estimation in partially observed Markov jump processes with measurement errors
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...
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.
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
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
Frequency Estimator Performance for a Software-Based Beacon Receiver
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.
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...
An RSS based location estimation technique for cognitive relay networks
Qaraqe, Khalid A.; Hussain, Syed Imtiaz; Ç elebi, Hasari Burak; Abdallah, Mohamed M.; Alouini, Mohamed-Slim
2010-01-01
In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine
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)
Luo, Xiaodong; Hoteit, Ibrahim
2014-01-01
-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
Head pose estimation algorithm based on deep learning
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.
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...
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....
Iterative observer based method for source localization problem for Poisson equation in 3D
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.
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.
Estimating monthly temperature using point based interpolation techniques
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.
Directory of Open Access Journals (Sweden)
Xujun Han
Full Text Available The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL; the other is observation localization (OL. Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.
Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano
2015-01-01
The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.
Process-based Cost Estimation for Ramjet/Scramjet Engines
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.
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.
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.
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...
Directory of Open Access Journals (Sweden)
Sarah Ehlers
2018-04-01
Full Text Available Today, non-expensive remote sensing (RS data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as composite estimation and data assimilation can be used for combining the different sources of information to obtain up-to-date and precise estimates of the characteristics of interest. In composite estimation a standard procedure is to assign weights to the different individual estimates inversely proportional to their variance. However, in case the estimates are correlated, the correlations must be considered in assigning weights or otherwise a composite estimator may be inefficient and its variance be underestimated. In this study we assessed the correlation of plot level estimates of forest characteristics from different RS datasets, between assessments using the same type of sensor as well as across different sensors. The RS data evaluated were SPOT-5 multispectral data, 3D airborne laser scanning data, and TanDEM-X interferometric radar data. Studies were made for plot level mean diameter, mean height, and growing stock volume. All data were acquired from a test site dominated by coniferous forest in southern Sweden. We found that the correlation between plot level estimates based on the same type of RS data were positive and strong, whereas the correlations between estimates using different sources of RS data were not as strong, and weaker for mean height than for mean diameter and volume. The implications of such correlations in composite estimation are demonstrated and it is discussed how correlations may affect results from data assimilation procedures.
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.
Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations
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.
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
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.
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.
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.
Stability basin estimates fall risk from observed kinematics, demonstrated on the Sit-to-Stand task.
Shia, Victor; Moore, Talia Yuki; Holmes, Patrick; Bajcsy, Ruzena; Vasudevan, Ram
2018-04-27
The ability to quantitatively measure stability is essential to ensuring the safety of locomoting systems. While the response to perturbation directly reflects the stability of a motion, this experimental method puts human subjects at risk. Unfortunately, existing indirect methods for estimating stability from unperturbed motion have been shown to have limited predictive power. This paper leverages recent advances in dynamical systems theory to accurately estimate the stability of human motion without requiring perturbation. This approach relies on kinematic observations of a nominal Sit-to-Stand motion to construct an individual-specific dynamic model, input bounds, and feedback control that are then used to compute the set of perturbations from which the model can recover. This set, referred to as the stability basin, was computed for 14 individuals, and was able to successfully differentiate between less and more stable Sit-to-Stand strategies for each individual with greater accuracy than existing methods. Copyright © 2018 Elsevier Ltd. All rights reserved.
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)
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...
Accurate position estimation methods based on electrical impedance tomography measurements
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
A Gossip-based Churn Estimator for Large Dynamic Networks
Giuffrida, C.; Ortolani, S.
2010-01-01
Gossip-based aggregation is an emerging paradigm to perform distributed computations and measurements in a large-scale setting. In this paper we explore the possibility of using gossip-based aggregation to estimate churn in arbitrarily large networks. To this end, we introduce a new model to compute
Parameter extraction and estimation based on the PV panel outdoor ...
African Journals Online (AJOL)
The experimental data obtained are validated and compared with the estimated results obtained through simulation based on the manufacture's data sheet. The simulation is based on the Newton-Raphson iterative method in MATLAB environment. This approach aids the computation of the PV module's parameters at any ...
Temporal validation for landsat-based volume estimation model
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...
Randerson, J. T.; Chen, Y.; Giglio, L.; Rogers, B. M.; van der Werf, G.
2011-12-01
In several important biomes, including croplands and tropical forests, many small fires exist that have sizes that are well below the detection limit for the current generation of burned area products derived from moderate resolution spectroradiometers. These fires likely have important effects on greenhouse gas and aerosol emissions and regional air quality. Here we developed an approach for combining 1km thermal anomalies (active fires; MOD14A2) and 500m burned area observations (MCD64A1) to estimate the prevalence of these fires and their likely contribution to burned area and carbon emissions. We first estimated active fires within and outside of 500m burn scars in 0.5 degree grid cells during 2001-2010 for which MCD64A1 burned area observations were available. For these two sets of active fires we then examined mean fire radiative power (FRP) and changes in enhanced vegetation index (EVI) derived from 16-day intervals immediately before and after each active fire observation. To estimate the burned area associated with sub-500m fires, we first applied burned area to active fire ratios derived solely from within burned area perimeters to active fires outside of burn perimeters. In a second step, we further modified our sub-500m burned area estimates using EVI changes from active fires outside and within of burned areas (after subtracting EVI changes derived from control regions). We found that in northern and southern Africa savanna regions and in Central and South America dry forest regions, the number of active fires outside of MCD64A1 burned areas increased considerably towards the end of the fire season. EVI changes for active fires outside of burn perimeters were, on average, considerably smaller than EVI changes associated with active fires inside burn scars, providing evidence for burn scars that were substantially smaller than the 25 ha area of a single 500m pixel. FRP estimates also were lower for active fires outside of burn perimeters. In our
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.
Directory of Open Access Journals (Sweden)
Comfort CM
2017-07-01
Full Text Available The Hawaiian mesopelagic boundary community is a slope-associated assemblage of micronekton that undergoes diel migrations along the slopes of the islands, residing at greater depths during the day and moving upslope to forage in shallower water at night. The timing of these migrations may be influenced by environmental factors such as moon phase or ambient light. To investigate the movements of this community, we examined echo intensity data from acoustic Doppler current profilers (ADCPs deployed at shallow and deep sites on the southern slope of Oahu, Hawaii. Diel changes in echo intensity (and therefore in estimated backscatter were observed and determined to be caused, at least in part, by the horizontal migration of the mesopelagic boundary community. Generalized additive modeling (GAM was used to assess the impact of environmental factors on the migration timing. Sunset time and lunar illumination were found to be significant factors. Movement speeds of the mesopelagic boundary community were estimated at 1.25–1.99 km h-1 (35–55 cm s-1. The location at which the migrations were observed is the future site of a seawater air conditioning system, which will cause artificial upwelling at our shallow observation site and may cause animal entrainment at the seawater intake near our deep water observation site. This study is the first to observe the diel migration of the mesopelagic boundary community on southern Oahu in both deep and shallow parts of the habitat, and it is also the first to examine migration trends over long time scales, which allows a better assessment of the effects of seasons and lunar illumination on micronekton migrations. Understanding the driving mechanisms of mesopelagic boundary community behavior will increase our ability to assess and manage coastal ecosystems in the face of increasing anthropogenic impacts.
Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves?
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Steve Kelling
Full Text Available Volunteers are increasingly being recruited into citizen science projects to collect observations for scientific studies. An additional goal of these projects is to engage and educate these volunteers. Thus, there are few barriers to participation resulting in volunteer observers with varying ability to complete the project's tasks. To improve the quality of a citizen science project's outcomes it would be useful to account for inter-observer variation, and to assess the rarely tested presumption that participating in a citizen science projects results in volunteers becoming better observers. Here we present a method for indexing observer variability based on the data routinely submitted by observers participating in the citizen science project eBird, a broad-scale monitoring project in which observers collect and submit lists of the bird species observed while birding. Our method for indexing observer variability uses species accumulation curves, lines that describe how the total number of species reported increase with increasing time spent in collecting observations. We find that differences in species accumulation curves among observers equates to higher rates of species accumulation, particularly for harder-to-identify species, and reveals increased species accumulation rates with continued participation. We suggest that these properties of our analysis provide a measure of observer skill, and that the potential to derive post-hoc data-derived measurements of participant ability should be more widely explored by analysts of data from citizen science projects. We see the potential for inferential results from analyses of citizen science data to be improved by accounting for observer skill.
Estimation of Compaction Parameters Based on Soil Classification
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.
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...
State Estimation-based Transmission line parameter identification
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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%.
Time of arrival based location estimation for cooperative relay networks
Çelebi, Hasari Burak
2010-09-01
In this paper, we investigate the performance of a cooperative relay network performing location estimation through time of arrival (TOA). We derive Cramer-Rao lower bound (CRLB) for the location estimates using the relay network. The analysis is extended to obtain average CRLB considering the signal fluctuations in both relay and direct links. The effects of the channel fading of both relay and direct links and amplification factor and location of the relay node on average CRLB are investigated. Simulation results show that the channel fading of both relay and direct links and amplification factor and location of relay node affect the accuracy of TOA based location estimation. ©2010 IEEE.
Time of arrival based location estimation for cooperative relay networks
Ç elebi, Hasari Burak; Abdallah, Mohamed M.; Hussain, Syed Imtiaz; Qaraqe, Khalid A.; Alouini, Mohamed-Slim
2010-01-01
In this paper, we investigate the performance of a cooperative relay network performing location estimation through time of arrival (TOA). We derive Cramer-Rao lower bound (CRLB) for the location estimates using the relay network. The analysis is extended to obtain average CRLB considering the signal fluctuations in both relay and direct links. The effects of the channel fading of both relay and direct links and amplification factor and location of the relay node on average CRLB are investigated. Simulation results show that the channel fading of both relay and direct links and amplification factor and location of relay node affect the accuracy of TOA based location estimation. ©2010 IEEE.
A Dynamic Travel Time Estimation Model Based on Connected Vehicles
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Daxin Tian
2015-01-01
Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.
An Inverse Source Problem for a One-dimensional Wave Equation: An Observer-Based Approach
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.
Fragnelli, Genni
2016-01-01
The authors consider a parabolic problem with degeneracy in the interior of the spatial domain, and they focus on observability results through Carleman estimates for the associated adjoint problem. The novelties of the present paper are two. First, the coefficient of the leading operator only belongs to a Sobolev space. Second, the degeneracy point is allowed to lie even in the interior of the control region, so that no previous result can be adapted to this situation; however, different cases can be handled, and new controllability results are established as a consequence.
Observation-Driven Estimation of the Spatial Variability of 20th Century Sea Level Rise
Hamlington, B. D.; Burgos, A.; Thompson, P. R.; Landerer, F. W.; Piecuch, C. G.; Adhikari, S.; Caron, L.; Reager, J. T.; Ivins, E. R.
2018-03-01
Over the past two decades, sea level measurements made by satellites have given clear indications of both global and regional sea level rise. Numerous studies have sought to leverage the modern satellite record and available historic sea level data provided by tide gauges to estimate past sea level rise, leading to several estimates for the 20th century trend in global mean sea level in the range between 1 and 2 mm/yr. On regional scales, few attempts have been made to estimate trends over the same time period. This is due largely to the inhomogeneity and quality of the tide gauge network through the 20th century, which render commonly used reconstruction techniques inadequate. Here, a new approach is adopted, integrating data from a select set of tide gauges with prior estimates of spatial structure based on historical sea level forcing information from the major contributing processes over the past century. The resulting map of 20th century regional sea level rise is optimized to agree with the tide gauge-measured trends, and provides an indication of the likely contributions of different sources to regional patterns. Of equal importance, this study demonstrates the sensitivities of this regional trend map to current knowledge and uncertainty of the contributing processes.
Optical Enhancement of Exoskeleton-Based Estimation of Glenohumeral Angles
Cortés, Camilo; Unzueta, Luis; de los Reyes-Guzmán, Ana; Ruiz, Oscar E.; Flórez, Julián
2016-01-01
In Robot-Assisted Rehabilitation (RAR) the accurate estimation of the patient limb joint angles is critical for assessing therapy efficacy. In RAR, the use of classic motion capture systems (MOCAPs) (e.g., optical and electromagnetic) to estimate the Glenohumeral (GH) joint angles is hindered by the exoskeleton body, which causes occlusions and magnetic disturbances. Moreover, the exoskeleton posture does not accurately reflect limb posture, as their kinematic models differ. To address the said limitations in posture estimation, we propose installing the cameras of an optical marker-based MOCAP in the rehabilitation exoskeleton. Then, the GH joint angles are estimated by combining the estimated marker poses and exoskeleton Forward Kinematics. Such hybrid system prevents problems related to marker occlusions, reduced camera detection volume, and imprecise joint angle estimation due to the kinematic mismatch of the patient and exoskeleton models. This paper presents the formulation, simulation, and accuracy quantification of the proposed method with simulated human movements. In addition, a sensitivity analysis of the method accuracy to marker position estimation errors, due to system calibration errors and marker drifts, has been carried out. The results show that, even with significant errors in the marker position estimation, method accuracy is adequate for RAR. PMID:27403044
Lester L. Yuan,; Amina I. Pollard,; Carlisle, Daren M.
2009-01-01
Analyses of observational data can provide insights into relationships between environmental conditions and biological responses across a broader range of natural conditions than experimental studies, potentially complementing insights gained from experiments. However, observational data must be analyzed carefully to minimize the likelihood that confounding variables bias observed relationships. Propensity scores provide a robust approach for controlling for the effects of measured confounding variables when analyzing observational data. Here, we use propensity scores to estimate changes in mean invertebrate taxon richness in streams that have experienced insecticide concentrations that exceed aquatic life use benchmark concentrations. A simple comparison of richness in sites exposed to elevated insecticides with those that were not exposed suggests that exposed sites had on average 6.8 fewer taxa compared to unexposed sites. The presence of potential confounding variables makes it difficult to assert a causal relationship from this simple comparison. After controlling for confounding factors using propensity scores, the difference in richness between exposed and unexposed sites was reduced to 4.1 taxa, a difference that was still statistically significant. Because the propensity score analysis controlled for the effects of a wide variety of possible confounding variables, we infer that the change in richness observed in the propensity score analysis was likely caused by insecticide exposure.
Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation
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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.
A novel SURE-based criterion for parametric PSF estimation.
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.
Estimation of Thermal Sensation Based on Wrist Skin Temperatures
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
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
de Beurs, K. M.; Ioffe, G.
2011-12-01
Agricultural reform has been one of the most important anthropogenic change processes in European Russia that has been unfolding since the formal collapse of the Soviet Union at the end of 1991. Widespread land abandonment is perhaps the most vivid side effect of the reform, even visible in synoptic imagery. Currently, Russia is transitioning into a country with an internal "archipelago" of islands of productive agriculture around cities embedded in a matrix of unproductive, abandoned lands. This heterogeneous spatial pattern is mainly driven by depopulation of the least favorable parts of the countryside, where "least favorable" is a function of fertility, remoteness, and their interaction. In this work we provide a satellite, GIS and field based overview of the current agricultural developments in Russia and look beyond the unstable period immediately following the collapse of the Soviet Union. We apply Landsat images in one of Russia's oblasts to create a detailed land cover map. We then use a logistic model to link the Landsat land cover map with the inter-annual variability in key phenological parameters calculated from MODIS to derive the percent of cropland per 500m MODIS pixel. By evaluating the phenological characteristics of the MODIS curves for each year we determine whether a pixel was actually cropped or left fallow. A comparison of satellite-estimated cropped areas with regional statistics (by rayon) revealed that the satellite estimates are highly correlated with the regional statistics for both arable lands and successfully cropped areas. We use the crop maps to determine the number of times a particular area was cropped between 2002 and 2009 by summing all the years with crops per pixel. This variable provides a good indication about the intensification and de-intensification of the Russian croplands over the last decade. We have visited several rural areas in Russia and we link the satellite data with information acquired through field interviews
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:
Cherukuru, Nagur; Ford, Phillip W.; Matear, Richard J.; Oubelkheir, Kadija; Clementson, Lesley A.; Suber, Ken; Steven, Andrew D. L.
2016-10-01
Dissolved Organic Carbon (DOC) is an important component in the global carbon cycle. It also plays an important role in influencing the coastal ocean biogeochemical (BGC) cycles and light environment. Studies focussing on DOC dynamics in coastal waters are data constrained due to the high costs associated with in situ water sampling campaigns. Satellite optical remote sensing has the potential to provide continuous, cost-effective DOC estimates. In this study we used a bio-optics dataset collected in turbid coastal waters of Moreton Bay (MB), Australia, during 2011 to develop a remote sensing algorithm to estimate DOC. This dataset includes data from flood and non-flood conditions. In MB, DOC concentration varied over a wide range (20-520 μM C) and had a good correlation (R2 = 0.78) with absorption due to coloured dissolved organic matter (CDOM) and remote sensing reflectance. Using this data set we developed an empirical algorithm to derive DOC concentrations from the ratio of Rrs(412)/Rrs(488) and tested it with independent datasets. In this study, we demonstrate the ability to estimate DOC using remotely sensed optical observations in turbid coastal waters.
Estimation of Physical Layer Performance inWSNs Exploiting the Method of Indirect Observations
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Luigi Atzori
2012-11-01
Full Text Available Wireless Sensor Networks (WSNs are used in many industrial and consumer applications that are increasingly gaining impact in our day to day lives. Still great efforts are needed towards the definition of methodologies for their effective management. One big issue is themonitoring of the network status, which requires the definition of the performance indicators and methodologies and should be accurate and not intrusive at the same time. In this paper, we present a new process for the monitoring of the physical layer in WSNs making use of a completely passive methodology. From data sniffed by external nodes, we first estimate the position of the nodes by applying the Weighted Least Squares (WLS to the method of indirect observations. The resulting node positions are then used to estimate the status of the communication links using the most appropriate propagation model. We performed a significant number of measurements on the field in both indoor and outdoor environments. From the experiments, we were able to achieve an accurate estimation of the channel links status with an average error lower than 1 dB, which is around 5 dB lower than the error introduced without the application of the proposed method.
Abdelgadir, Jihad; Tran, Tu; Muhindo, Alex; Obiga, Doomwin; Mukasa, John; Ssenyonjo, Hussein; Muhumza, Michael; Kiryabwire, Joel; Haglund, Michael M; Sloan, Frank A
2017-05-01
There are no data on cost of neurosurgery in low-income and middle-income countries. The objective of this study was to estimate the cost of neurosurgical procedures in a low-resource setting to better inform resource allocation and health sector planning. In this observational economic analysis, microcosting was used to estimate the direct and indirect costs of neurosurgical procedures at Mulago National Referral Hospital (Kampala, Uganda). During the study period, October 2014 to September 2015, 1440 charts were reviewed. Of these patients, 434 had surgery, whereas the other 1006 were treated nonsurgically. Thirteen types of procedures were performed at the hospital. The estimated mean cost of a neurosurgical procedure was $542.14 (standard deviation [SD], $253.62). The mean cost of different procedures ranged from $291 (SD, $101) for burr hole evacuations to $1,221 (SD, $473) for excision of brain tumors. For most surgeries, overhead costs represented the largest proportion of the total cost (29%-41%). This is the first study using primary data to determine the cost of neurosurgery in a low-resource setting. Operating theater capacity is likely the binding constraint on operative volume, and thus, investing in operating theaters should achieve a higher level of efficiency. Findings from this study could be used by stakeholders and policy makers for resource allocation and to perform economic analyses to establish the value of neurosurgery in achieving global health goals. Copyright © 2017 Elsevier Inc. All rights reserved.
Estimation of daily solar radiation from routinely observed meteorological data in Chongqing, China
International Nuclear Information System (INIS)
Li Maofen; Liu Hongbin; Guo Pengtao; Wu Wei
2010-01-01
Solar radiation is a very important and major variable in crop simulation models. However, it is measured at a very limited number of meteorological stations worldwide. Models were developed to estimate daily solar radiation in Chongqing, one of the most important agricultural areas in China. Several routinely observed meteorological variables including daily maximum and minimum temperatures, daily mean dew point temperature, fog and rainfall had been obtained, investigated and analyzed from 1986 to 2000 for Chongqing. The monthly mean daily solar radiation at this location ranged from a maximum of 15.082 MJ m -2 day -1 in August and a minimum of 3.042 MJ m -2 day -1 in December. A newly developed model that included all selected variables proved the best method with a RMSE value of 2.522 MJ m -2 day -1 . The best performed models for different seasons were further evaluated according to divide-and-conquer principle. The model using all selected variables provided the best estimates of daily solar radiation in winter and autumn with RMSE values of 1.491 and 2.037 MJ m -2 day -1 , respectively. The method involving temperatures and rainfall information could be used to estimate daily solar radiation in summer with a RMSE value of 3.163 MJ m -2 day -1 . The model using temperature, rainfall and dew point data performed better than other models in spring with a RMSE value of 2.910 MJ m -2 day -1 .
International Nuclear Information System (INIS)
Murata, Takeshi; Matsumoto, Hiroshi; Kojima, Hirotsugu
1995-01-01
We estimate the location of the reconnection line and plasmoid size in the geomagnetic tail using data from the Plasma Wave Instrument onboard the GEOTAIL spacecraft. We first compare AKR onset events with high energy particle observations at geosynchronous orbit. We determine the plasmoid ejection (re-connection) time by the AKR enhancement only when it corrresponds to energetic particle enhancement within five minutes. The traveling time of the plasmoid from the X-line to the spacecraft is calculated by the difference in time of the AKR onset and that of the plasmoid encounter with GEOTAIL. Assuming the plasmoid propagates with the Alfven velocity in the tail lobe as MHD simulations predict, we estimate the location of the reconnection line in 11 events. The results show that the most probable location of the plasmoid edge is distributed around Χ = -60 R E in the GSE coordinates. The estimated size of the plasmoids ranges from 10 to 50 R E in the χ direction. If we apply this result to the alternative plasmoid model in which the evolution of the tearing instability causes the generation of plasmoids, the X-line should be approximately at χ = -35 R E . 15 refs., 3 figs., 1 tab
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.
A Channelization-Based DOA Estimation Method for Wideband Signals
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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.
On Compressed Sensing and the Estimation of Continuous Parameters From Noisy Observations
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt
2012-01-01
Compressed sensing (CS) has in recent years become a very popular way of sampling sparse signals. This sparsity is measured with respect to some known dictionary consisting of a finite number of atoms. Most models for real world signals, however, are parametrised by continuous parameters correspo......Compressed sensing (CS) has in recent years become a very popular way of sampling sparse signals. This sparsity is measured with respect to some known dictionary consisting of a finite number of atoms. Most models for real world signals, however, are parametrised by continuous parameters...... corresponding to a dictionary with an infinite number of atoms. Examples of such parameters are the temporal and spatial frequency. In this paper, we analyse how CS affects the estimation performance of any unbiased estimator when we assume such infinite dictionaries. We base our analysis on the Cramer...
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
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.)
Estimating wind-turbine-caused bird and bat fatality when zero carcasses are observed
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
Estimating wind-turbine-caused bird and bat fatality when zero carcasses are observed.
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.
Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM
Sheng, Hanlin; Zhang, Tianhong
2017-08-01
In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.
Design of Virtual Crank Angle Sensor based on Torque Estimation
Roswall, Tobias
2016-01-01
The topic of thesis is estimation of the crank angle based on pulse signals from an induction sensor placed on the ﬂywheel. The engine management system performs many calculations in the crank angle domain which means that a good accuracy is needed for this measurement. To estimate the crank angle degree the torque balance on the crankshaft based on Newtons 2nd law is used. The resulting acceleration is integrated to give engine speed and crank angle. This approach is made for two crankshaft ...
Age estimation based on aspartic acid racemization in human sclera.
Klumb, Karolin; Matzenauer, Christian; Reckert, Alexandra; Lehmann, Klaus; Ritz-Timme, Stefanie
2016-01-01
Age estimation based on racemization of aspartic acid residues (AAR) in permanent proteins has been established in forensic medicine for years. While dentine is the tissue of choice for this molecular method of age estimation, teeth are not always available which leads to the need to identify other suitable tissues. We examined the suitability of total tissue samples of human sclera for the estimation of age at death. Sixty-five samples of scleral tissue were analyzed. The samples were hydrolyzed and after derivatization, the extent of aspartic acid racemization was determined by gas chromatography. The degree of AAR increased with age. In samples from younger individuals, the correlation of age and D-aspartic acid content was closer than in samples from older individuals. The age-dependent racemization in total tissue samples proves that permanent or at least long-living proteins are present in scleral tissue. The correlation of AAR in human sclera and age at death is close enough to serve as basis for age estimation. However, the precision of age estimation by this method is lower than that of age estimation based on the analysis of dentine which is due to molecular inhomogeneities of total tissue samples of sclera. Nevertheless, the approach may serve as a valuable alternative or addition in exceptional cases.
Power system dynamic state estimation using prediction based evolutionary technique
International Nuclear Information System (INIS)
Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan
2016-01-01
In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.
Verkhoglyadova, O. P.; Meng, X.; Mannucci, A. J.; Mlynczak, M. G.; Hunt, L. A.; Lu, G.
2017-09-01
The ionosphere-thermosphere (IT) energy partitioning for the interplanetary coronal mass ejection (ICME) storms of 16-19 March 2013 and 2015 is estimated with the Global Ionosphere-Thermosphere Model (GITM), empirical models and proxies derived from in situ measurements. We focus on auroral heating, Joule heating, and thermospheric cooling. Solar wind data, F10.7, OVATION Prime model and the Weimer 2005 model are used to drive GITM from above. Thermospheric nitric oxide and carbon dioxide cooling emission powers and fluxes are estimated from TIMED/SABER measurements. Assimilative mapping of ionospheric electrodynamics (AMIE) estimations of hemispheric power and Joule heating are presented, based on data from global magnetometers, the AMPERE magnetic field data, SSUSI auroral images, and the SuperDARN radar network. Modeled Joule heating and auroral heating of the IT system are mostly controlled by external driving in the March 2013 and 2015 storms, while NO cooling persists into the storm recovery phase. The total heating in the model is about 1000 GW to 3000 GW. Additionally, we intercompare contributions in selected energy channels for five coronal mass ejection-type storms modeled with GITM. Modeled auroral heating shows reasonable agreement with AMIE hemispheric power and is higher than other observational proxies. Joule heating and infrared cooling are likely underestimated in GITM. We discuss challenges and discrepancies in estimating and global modeling of the IT energy partitioning, especially Joule heating, during geomagnetic storms.
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.
Directory of Open Access Journals (Sweden)
V. Shutyaev
2018-06-01
Full Text Available The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters of the model. The observation data, and hence the optimal solution, may contain uncertainties. A response function is considered as a functional of the optimal solution after assimilation. Based on the second-order adjoint techniques, the sensitivity of the response function to the observation data is studied. The gradient of the response function is related to the solution of a nonstandard problem involving the coupled system of direct and adjoint equations. The nonstandard problem is studied, based on the Hessian of the original cost function. An algorithm to compute the gradient of the response function with respect to observations is presented. A numerical example is given for the variational data assimilation problem related to sea surface temperature for the Baltic Sea thermodynamics model.
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.
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
Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration
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
A comparison of resampling schemes for estimating model observer performance with small ensembles
Elshahaby, Fatma E. A.; Jha, Abhinav K.; Ghaly, Michael; Frey, Eric C.
2017-09-01
In objective assessment of image quality, an ensemble of images is used to compute the 1st and 2nd order statistics of the data. Often, only a finite number of images is available, leading to the issue of statistical variability in numerical observer performance. Resampling-based strategies can help overcome this issue. In this paper, we compared different combinations of resampling schemes (the leave-one-out (LOO) and the half-train/half-test (HT/HT)) and model observers (the conventional channelized Hotelling observer (CHO), channelized linear discriminant (CLD) and channelized quadratic discriminant). Observer performance was quantified by the area under the ROC curve (AUC). For a binary classification task and for each observer, the AUC value for an ensemble size of 2000 samples per class served as a gold standard for that observer. Results indicated that each observer yielded a different performance depending on the ensemble size and the resampling scheme. For a small ensemble size, the combination [CHO, HT/HT] had more accurate rankings than the combination [CHO, LOO]. Using the LOO scheme, the CLD and CHO had similar performance for large ensembles. However, the CLD outperformed the CHO and gave more accurate rankings for smaller ensembles. As the ensemble size decreased, the performance of the [CHO, LOO] combination seriously deteriorated as opposed to the [CLD, LOO] combination. Thus, it might be desirable to use the CLD with the LOO scheme when smaller ensemble size is available.
Lievens, H.; Martens, B.; Verhoest, N. E. C.; Hahn, S.; Reichle, R. H.; Miralles, D. G.
2017-01-01
Active radar backscatter (s?) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s? and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s? or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s? and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.
Bumpless Transfer between Observer-based Gain Scheduled Controllers
DEFF Research Database (Denmark)
Bendtsen, Jan Dimon; Stoustrup, Jakob; Trangbæk, Klaus
2005-01-01
This paper deals with bumpless transfer between a number of observer-based controllers in a gain scheduling architecture. Linear observer-based controllers are designed for a number of linear approximations of a nonlinear system in a set of operating points, and gain scheduling control can...
A Web-Based System for Bayesian Benchmark Dose Estimation.
Shao, Kan; Shapiro, Andrew J
2018-01-11
Benchmark dose (BMD) modeling is an important step in human health risk assessment and is used as the default approach to identify the point of departure for risk assessment. A probabilistic framework for dose-response assessment has been proposed and advocated by various institutions and organizations; therefore, a reliable tool is needed to provide distributional estimates for BMD and other important quantities in dose-response assessment. We developed an online system for Bayesian BMD (BBMD) estimation and compared results from this software with U.S. Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). The system is built on a Bayesian framework featuring the application of Markov chain Monte Carlo (MCMC) sampling for model parameter estimation and BMD calculation, which makes the BBMD system fundamentally different from the currently prevailing BMD software packages. In addition to estimating the traditional BMDs for dichotomous and continuous data, the developed system is also capable of computing model-averaged BMD estimates. A total of 518 dichotomous and 108 continuous data sets extracted from the U.S. EPA's Integrated Risk Information System (IRIS) database (and similar databases) were used as testing data to compare the estimates from the BBMD and BMDS programs. The results suggest that the BBMD system may outperform the BMDS program in a number of aspects, including fewer failed BMD and BMDL calculations and estimates. The BBMD system is a useful alternative tool for estimating BMD with additional functionalities for BMD analysis based on most recent research. Most importantly, the BBMD has the potential to incorporate prior information to make dose-response modeling more reliable and can provide distributional estimates for important quantities in dose-response assessment, which greatly facilitates the current trend for probabilistic risk assessment. https://doi.org/10.1289/EHP1289.
A non-stationary cost-benefit based bivariate extreme flood estimation approach
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.
Single event upset threshold estimation based on local laser irradiation
International Nuclear Information System (INIS)
Chumakov, A.I.; Egorov, A.N.; Mavritsky, O.B.; Yanenko, A.V.
1999-01-01
An approach for estimation of ion-induced SEU threshold based on local laser irradiation is presented. Comparative experiment and software simulation research were performed at various pulse duration and spot size. Correlation of single event threshold LET to upset threshold laser energy under local irradiation was found. The computer analysis of local laser irradiation of IC structures was developed for SEU threshold LET estimation. The correlation of local laser threshold energy with SEU threshold LET was shown. Two estimation techniques were suggested. The first one is based on the determination of local laser threshold dose taking into account the relation of sensitive area to local irradiated area. The second technique uses the photocurrent peak value instead of this relation. The agreement between the predicted and experimental results demonstrates the applicability of this approach. (authors)
Improved air ventilation rate estimation based on a statistical model
International Nuclear Information System (INIS)
Brabec, M.; Jilek, K.
2004-01-01
A new approach to air ventilation rate estimation from CO measurement data is presented. The approach is based on a state-space dynamic statistical model, allowing for quick and efficient estimation. Underlying computations are based on Kalman filtering, whose practical software implementation is rather easy. The key property is the flexibility of the model, allowing various artificial regimens of CO level manipulation to be treated. The model is semi-parametric in nature and can efficiently handle time-varying ventilation rate. This is a major advantage, compared to some of the methods which are currently in practical use. After a formal introduction of the statistical model, its performance is demonstrated on real data from routine measurements. It is shown how the approach can be utilized in a more complex situation of major practical relevance, when time-varying air ventilation rate and radon entry rate are to be estimated simultaneously from concurrent radon and CO measurements
Lightning stroke distance estimation from single station observation and validation with WWLLN data
Directory of Open Access Journals (Sweden)
V. Ramachandran
2007-07-01
Full Text Available A simple technique to estimate the distance of the lightning strikes d with a single VLF electromagnetic wave receiver at a single station is described. The technique is based on the recording of oscillatory waveforms of the electric fields of sferics. Even though the process of estimating d using the waveform is a rather classical one, a novel and simple procedure for finding d is proposed in this paper. The procedure adopted provides two independent estimates of the distance of the stroke. The accuracy of measurements has been improved by employing high speed (333 ns sampling rate signal processing techniques. GPS time is used as the reference time, which enables us to compare the calculated distances of the lightning strikes, by both methods, with those calculated from the data obtained by the World-Wide Lightning Location Network (WWLLN, which uses a multi-station technique. The estimated distances of the lightning strikes (77, whose times correlated, ranged from ~3000–16 250 km. When dd compared with those calculated with the multi-station lightning location system is ~4.7%, while for all the strokes it was ~8.8%. One of the lightnings which was recorded by WWLLN, whose field pattern was recorded and the spectrogram of the sferic was also recorded at the site, is analyzed in detail. The deviations in d calculated from the field pattern and from the arrival time of the sferic were 3.2% and 1.5%, respectively, compared to d calculated from the WWLLN location. FFT analysis of the waveform showed that only a narrow band of frequencies is received at the site, which is confirmed by the intensity of the corresponding sferic in the spectrogram.
Automated Detection of Small Bodies by Space Based Observation
Bidstrup, P. R.; Grillmayer, G.; Andersen, A. C.; Haack, H.; Jorgensen, J. L.
The number of known comets and asteroids is increasing every year. Up till now this number is including approximately 250,000 of the largest minor planets, as they are usually referred. These discoveries are due to the Earth-based observation which has intensified over the previous decades. Additionally larger telescopes and arrays of telescopes are being used for exploring our Solar System. It is believed that all near- Earth and Main-Belt asteroids of diameters above 10 to 30 km have been discovered, leaving these groups of objects as observationally complete. However, the cataloguing of smaller bodies is incomplete as only a very small fraction of the expected number has been discovered. It is estimated that approximately 1010 main belt asteroids in the size range 1 m to 1 km are too faint to be observed using Earth-based telescopes. In order to observe these small bodies, space-based search must be initiated to remove atmospheric disturbances and to minimize the distance to the asteroids and thereby minimising the requirement for long camera integration times. A new method of space-based detection of moving non-stellar objects is currently being developed utilising the Advanced Stellar Compass (ASC) built for spacecraft attitude determination by Ørsted, Danish Technical University. The ASC serves as a backbone technology in the project as it is capable of fully automated distinction of known and unknown celestial objects. By only processing objects of particular interest, i.e. moving objects, it will be possible to discover small bodies with a minimum of ground control, with the ultimate ambition of a fully automated space search probe. Currently, the ASC is being mounted on the Flying Laptop satellite of the Institute of Space Systems, Universität Stuttgart. It will, after a launch into a low Earth polar orbit in 2008, test the detection method with the ASC equipment that already had significant in-flight experience. A future use of the ASC based automated
Fuzzy model-based observers for fault detection in CSTR.
Ballesteros-Moncada, Hazael; Herrera-López, Enrique J; Anzurez-Marín, Juan
2015-11-01
Under the vast variety of fuzzy model-based observers reported in the literature, what would be the properone to be used for fault detection in a class of chemical reactor? In this study four fuzzy model-based observers for sensor fault detection of a Continuous Stirred Tank Reactor were designed and compared. The designs include (i) a Luenberger fuzzy observer, (ii) a Luenberger fuzzy observer with sliding modes, (iii) a Walcott-Zak fuzzy observer, and (iv) an Utkin fuzzy observer. A negative, an oscillating fault signal, and a bounded random noise signal with a maximum value of ±0.4 were used to evaluate and compare the performance of the fuzzy observers. The Utkin fuzzy observer showed the best performance under the tested conditions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
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.
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....
International Nuclear Information System (INIS)
Hung, Ching Pui; Jouve, Laurène; Brun, Allan Sacha; Fournier, Alexandre; Talagrand, Olivier
2015-01-01
We show how magnetic observations of the Sun can be used in conjunction with an axisymmetric flux-transport solar dynamo model in order to estimate the large-scale meridional circulation throughout the convection zone. Our innovative approach rests on variational data assimilation, whereby the distance between predictions and observations (measured by an objective function) is iteratively minimized by means of an optimization algorithm seeking the meridional flow that best accounts for the data. The minimization is performed using a quasi-Newton technique, which requires knowledge of the sensitivity of the objective function to the meridional flow. That sensitivity is efficiently computed via the integration of the adjoint flux-transport dynamo model. Closed-loop (also known as twin) experiments using synthetic data demonstrate the validity and accuracy of this technique for a variety of meridional flow configurations, ranging from unicellular and equatorially symmetric to multicellular and equatorially asymmetric. In this well-controlled synthetic context, we perform a systematic study of the behavior of our variational approach under different observational configurations by varying their spatial density, temporal density, and noise level, as well as the width of the assimilation window. We find that the method is remarkably robust, leading in most cases to a recovery of the true meridional flow to within better than 1%. These encouraging results are a first step toward using this technique to (i) better constrain the physical processes occurring inside the Sun and (ii) better predict solar activity on decadal timescales
Energy Technology Data Exchange (ETDEWEB)
Hung, Ching Pui; Jouve, Laurène; Brun, Allan Sacha [Laboratoire AIM Paris-Saclay, CEA/IRFU Université Paris-Diderot CNRS/INSU, F-91191 Gif-Sur-Yvette (France); Fournier, Alexandre [Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot UMR 7154 CNRS, F-75005 Paris (France); Talagrand, Olivier [Laboratoire de météorologie dynamique, UMR 8539, Ecole Normale Supérieure, Paris Cedex 05 (France)
2015-12-01
We show how magnetic observations of the Sun can be used in conjunction with an axisymmetric flux-transport solar dynamo model in order to estimate the large-scale meridional circulation throughout the convection zone. Our innovative approach rests on variational data assimilation, whereby the distance between predictions and observations (measured by an objective function) is iteratively minimized by means of an optimization algorithm seeking the meridional flow that best accounts for the data. The minimization is performed using a quasi-Newton technique, which requires knowledge of the sensitivity of the objective function to the meridional flow. That sensitivity is efficiently computed via the integration of the adjoint flux-transport dynamo model. Closed-loop (also known as twin) experiments using synthetic data demonstrate the validity and accuracy of this technique for a variety of meridional flow configurations, ranging from unicellular and equatorially symmetric to multicellular and equatorially asymmetric. In this well-controlled synthetic context, we perform a systematic study of the behavior of our variational approach under different observational configurations by varying their spatial density, temporal density, and noise level, as well as the width of the assimilation window. We find that the method is remarkably robust, leading in most cases to a recovery of the true meridional flow to within better than 1%. These encouraging results are a first step toward using this technique to (i) better constrain the physical processes occurring inside the Sun and (ii) better predict solar activity on decadal timescales.
Girotto, Manuela
2018-01-01
Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).
Estimating interevent time distributions from finite observation periods in communication networks
Kivelä, Mikko; Porter, Mason A.
2015-11-01
A diverse variety of processes—including recurrent disease episodes, neuron firing, and communication patterns among humans—can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions.
Ekman estimates of upwelling at cape columbine based on ...
African Journals Online (AJOL)
Ekman estimates of upwelling at cape columbine based on measurements of longshore wind from a 35-year time-series. AS Johnson, G Nelson. Abstract. Cape Columbine is a prominent headland on the south-west coast of Africa at approximately 32°50´S, where there is a substantial upwelling tongue, enhancing the ...
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...
An Approach to Quality Estimation in Model-Based Development
DEFF Research Database (Denmark)
Holmegaard, Jens Peter; Koch, Peter; Ravn, Anders Peter
2004-01-01
We present an approach to estimation of parameters for design space exploration in Model-Based Development, where synthesis of a system is done in two stages. Component qualities like space, execution time or power consumption are defined in a repository by platform dependent values. Connectors...
A model-based approach to estimating forest area
Ronald E. McRoberts
2006-01-01
A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and...
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...
Directory of Open Access Journals (Sweden)
Enrique Castillo
2015-01-01
Full Text Available A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.
Estimation of pump operational state with model-based methods
International Nuclear Information System (INIS)
Ahonen, Tero; Tamminen, Jussi; Ahola, Jero; Viholainen, Juha; Aranto, Niina; Kestilae, Juha
2010-01-01
Pumps are widely used in industry, and they account for 20% of the industrial electricity consumption. Since the speed variation is often the most energy-efficient method to control the head and flow rate of a centrifugal pump, frequency converters are used with induction motor-driven pumps. Although a frequency converter can estimate the operational state of an induction motor without external measurements, the state of a centrifugal pump or other load machine is not typically considered. The pump is, however, usually controlled on the basis of the required flow rate or output pressure. As the pump operational state can be estimated with a general model having adjustable parameters, external flow rate or pressure measurements are not necessary to determine the pump flow rate or output pressure. Hence, external measurements could be replaced with an adjustable model for the pump that uses estimates of the motor operational state. Besides control purposes, modelling the pump operation can provide useful information for energy auditing and optimization purposes. In this paper, two model-based methods for pump operation estimation are presented. Factors affecting the accuracy of the estimation methods are analyzed. The applicability of the methods is verified by laboratory measurements and tests in two pilot installations. Test results indicate that the estimation methods can be applied to the analysis and control of pump operation. The accuracy of the methods is sufficient for auditing purposes, and the methods can inform the user if the pump is driven inefficiently.
Wang, Yilong; Broquet, Grégoire; Ciais, Philippe; Chevallier, Frédéric; Vogel, Felix; Wu, Lin; Yin, Yi; Wang, Rong; Tao, Shu
2018-03-01
Combining measurements of atmospheric CO2 and its radiocarbon (14CO2) fraction and transport modeling in atmospheric inversions offers a way to derive improved estimates of CO2 emitted from fossil fuel (FFCO2). In this study, we solve for the monthly FFCO2 emission budgets at regional scale (i.e., the size of a medium-sized country in Europe) and investigate the performance of different observation networks and sampling strategies across Europe. The inversion system is built on the LMDZv4 global transport model at 3.75° × 2.5° resolution. We conduct Observing System Simulation Experiments (OSSEs) and use two types of diagnostics to assess the potential of the observation and inverse modeling frameworks. The first one relies on the theoretical computation of the uncertainty in the estimate of emissions from the inversion, known as posterior uncertainty, and on the uncertainty reduction compared to the uncertainty in the inventories of these emissions, which are used as a prior knowledge by the inversion (called prior uncertainty). The second one is based on comparisons of prior and posterior estimates of the emission to synthetic true emissions when these true emissions are used beforehand to generate the synthetic fossil fuel CO2 mixing ratio measurements that are assimilated in the inversion. With 17 stations currently measuring 14CO2 across Europe using 2-week integrated sampling, the uncertainty reduction for monthly FFCO2 emissions in a country where the network is rather dense like Germany, is larger than 30 %. With the 43 14CO2 measurement stations planned in Europe, the uncertainty reduction for monthly FFCO2 emissions is increased for the UK, France, Italy, eastern Europe and the Balkans, depending on the configuration of prior uncertainty. Further increasing the number of stations or the sampling frequency improves the uncertainty reduction (up to 40 to 70 %) in high emitting regions, but the performance of the inversion remains limited over low
Directory of Open Access Journals (Sweden)
Y. Wang
2018-03-01
Full Text Available Combining measurements of atmospheric CO2 and its radiocarbon (14CO2 fraction and transport modeling in atmospheric inversions offers a way to derive improved estimates of CO2 emitted from fossil fuel (FFCO2. In this study, we solve for the monthly FFCO2 emission budgets at regional scale (i.e., the size of a medium-sized country in Europe and investigate the performance of different observation networks and sampling strategies across Europe. The inversion system is built on the LMDZv4 global transport model at 3.75° × 2.5° resolution. We conduct Observing System Simulation Experiments (OSSEs and use two types of diagnostics to assess the potential of the observation and inverse modeling frameworks. The first one relies on the theoretical computation of the uncertainty in the estimate of emissions from the inversion, known as posterior uncertainty, and on the uncertainty reduction compared to the uncertainty in the inventories of these emissions, which are used as a prior knowledge by the inversion (called prior uncertainty. The second one is based on comparisons of prior and posterior estimates of the emission to synthetic true emissions when these true emissions are used beforehand to generate the synthetic fossil fuel CO2 mixing ratio measurements that are assimilated in the inversion. With 17 stations currently measuring 14CO2 across Europe using 2-week integrated sampling, the uncertainty reduction for monthly FFCO2 emissions in a country where the network is rather dense like Germany, is larger than 30 %. With the 43 14CO2 measurement stations planned in Europe, the uncertainty reduction for monthly FFCO2 emissions is increased for the UK, France, Italy, eastern Europe and the Balkans, depending on the configuration of prior uncertainty. Further increasing the number of stations or the sampling frequency improves the uncertainty reduction (up to 40 to 70 % in high emitting regions, but the performance of the inversion
Energy Technology Data Exchange (ETDEWEB)
Guetlein, Achim; Ciemniak, Christian; Feilitzsch, Franz von; Lanfranchi, Jean-Come; Oberauer, Lothar; Potzel, Walter; Roth, Sabine; Schoenert, Stefan; Sivers, Moritz von; Strauss, Raimund; Wawoczny, Stefan; Willers, Michael; Zoeller, Andreas [Technische Universitaet Muenchen, Physik-Department, E15 (Germany)
2012-07-01
The Coherent Neutrino Nucleus Scattering (CNNS) is a neutral current process of the weak interaction and is thus flavor independent. A low-energetic neutrino scatters off a target nucleus. For low transferred momenta the wavelength of the transferred Z{sup 0} boson is comparable to the diameter of the target nucleus. Thus, the neutrino interacts with all nucleons coherently and the cross section for the CNNS is enhanced. To observe CNNS for the first time we are developing cryogenic detectors with a target mass of about 10 g each and an energy threshold of less than 0.5 keV. The current status of this development is presented as well as the estimated background for an experiment in the vicinity of a nuclear power reactor as a strong neutrino source.
Estimation of sampling error uncertainties in observed surface air temperature change in China
Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun
2017-08-01
This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.
International Nuclear Information System (INIS)
Lihavainen, Heikki; Asmi, Eija; Aaltonen, Veijo; Makkonen, Ulla; Kerminen, Veli-Matti
2015-01-01
We used more than five years of continuous aerosol measurements to estimate the direct radiative feedback parameter associated with the formation of biogenic secondary organic aerosol (BSOA) at a remote continental site at the edge of the boreal forest zone in Northern Finland. Our upper-limit estimate for this feedback parameter during the summer period (ambient temperatures above 10 °C) was −97 ± 66 mW m −2 K −1 (mean ± STD) when using measurements of the aerosol optical depth (f AOD ) and −63 ± 40 mW m −2 K −1 when using measurements of the ‘dry’ aerosol scattering coefficient at the ground level (f σ ). Here STD represents the variability in f caused by the observed variability in the quantities used to derive the value of f. Compared with our measurement site, the magnitude of the direct radiative feedback associated with BSOA is expected to be larger in warmer continental regions with more abundant biogenic emissions, and even larger in regions where biogenic emissions are mixed with anthropogenic pollution. (letter)
de Moura, Yhasmin Mendes; Hilker, Thomas; Goncalves, Fabio Guimarães; Galvão, Lênio Soares; dos Santos, João Roberto; Lyapustin, Alexei; Maeda, Eduardo Eiji; de Jesus Silva, Camila Valéria
2018-01-01
Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2= 0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤ r2≤ 0.61; pMODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon. PMID:29618964
Directory of Open Access Journals (Sweden)
F. Liu
2016-04-01
Full Text Available We present a new method to quantify NOx emissions and corresponding atmospheric lifetimes from OMI NO2 observations together with ECMWF wind fields without further model input for sources located in a polluted background. NO2 patterns under calm wind conditions are used as proxy for the spatial patterns of NOx emissions, and the effective atmospheric NOx lifetime is determined from the change of spatial patterns measured at larger wind speeds. Emissions are subsequently derived from the NO2 mass above the background, integrated around the source of interest. Lifetimes and emissions are estimated for 17 power plants and 53 cities located in non-mountainous regions across China and the USA. The derived lifetimes for the ozone season (May–September are 3.8 ± 1.0 h (mean ± standard deviation with a range of 1.8 to 7.5 h. The derived NOx emissions show generally good agreement with bottom-up inventories for power plants and cities. Regional inventory shows better agreement with top-down estimates for Chinese cities compared to global inventory, most likely due to different downscaling approaches adopted in the two inventories.
SHORT GMC LIFETIMES: AN OBSERVATIONAL ESTIMATE WITH THE PdBI ARCSECOND WHIRLPOOL SURVEY (PAWS)
Energy Technology Data Exchange (ETDEWEB)
Meidt, Sharon E.; Hughes, Annie; Schinnerer, Eva; Colombo, Dario; Querejeta, Miguel [Max-Planck-Institut für Astronomie / Königstuhl 17 D-69117 Heidelberg (Germany); Dobbs, Clare L. [School of Physics and Astronomy, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); Pety, Jérôme [Institut de Radioastronomie Millimétrique, 300 Rue de la Piscine, F-38406 Saint Martin d’Hères (France); Thompson, Todd A. [Department of Astronomy, The Ohio State University, 140 W. 18th Ave., Columbus, OH 43210 (United States); García-Burillo, Santiago [Observatorio Astronómico Nacional—OAN, Observatorio de Madrid Alfonso XII, 3, E-28014 Madrid (Spain); Leroy, Adam K. [National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903 (United States); Kramer, Carsten [Instituto Radioastronomía Milimétrica, Av. Divina Pastora 7, Nucleo Central, E-18012 Granada (Spain); Schuster, Karl F.; Dumas, Gaëlle [Observatoire de Paris, 61 Avenue de l’Observatoire, F-75014 Paris (France)
2015-06-10
We describe and execute a novel approach to observationally estimate the lifetimes of giant molecular clouds (GMCs). We focus on the cloud population between the two main spiral arms in M51 (the inter-arm region) where cloud destruction via shear and star formation feedback dominates over formation processes. By monitoring the change in GMC number densities and properties across the inter-arm, we estimate the lifetime as a fraction of the inter-arm travel time. We find that GMC lifetimes in M51's inter-arm are finite and short, 20–30 Myr. Over most of the region under investigation shear appears to regulate the lifetime. As the shear timescale increases with galactocentric radius, we expect cloud destruction to switch primarily to feedback at larger radii. We identify a transition from shear- to feedback-dominated disruption, finding that shear is more efficient at dispersing clouds, whereas feedback transforms the population, e.g., by fragmenting high-mass clouds into lower mass pieces. Compared to the characteristic timescale for molecular hydrogen in M51, our short lifetimes suggest that gas can remain molecular while clouds disperse and reassemble. We propose that galaxy dynamics regulates the cycling of molecular material from diffuse to bound (and ultimately star-forming) objects, contributing to long observed molecular depletion times in normal disk galaxies. We also speculate that, in extreme environments like elliptical galaxies and concentrated galaxy centers, star formation can be suppressed when the shear timescale is short enough that some clouds will not survive to form stars.
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
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.
Estimation of Transpiration and Water Use Efficiency Using Satellite and Field Observations
Choudhury, Bhaskar J.; Quick, B. E.
2003-01-01
Structure and function of terrestrial plant communities bring about intimate relations between water, energy, and carbon exchange between land surface and atmosphere. Total evaporation, which is the sum of transpiration, soil evaporation and evaporation of intercepted water, couples water and energy balance equations. The rate of transpiration, which is the major fraction of total evaporation over most of the terrestrial land surface, is linked to the rate of carbon accumulation because functioning of stomata is optimized by both of these processes. Thus, quantifying the spatial and temporal variations of the transpiration efficiency (which is defined as the ratio of the rate of carbon accumulation and transpiration), and water use efficiency (defined as the ratio of the rate of carbon accumulation and total evaporation), and evaluation of modeling results against observations, are of significant importance in developing a better understanding of land surface processes. An approach has been developed for quantifying spatial and temporal variations of transpiration, and water-use efficiency based on biophysical process-based models, satellite and field observations. Calculations have been done using concurrent meteorological data derived from satellite observations and four dimensional data assimilation for four consecutive years (1987-1990) over an agricultural area in the Northern Great Plains of the US, and compared with field observations within and outside the study area. The paper provides substantive new information about interannual variation, particularly the effect of drought, on the efficiency values at a regional scale.
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.
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
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.
Event-based state estimation a stochastic perspective
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 ...
Estimation of Supercapacitor Energy Storage Based on Fractional Differential Equations.
Kopka, Ryszard
2017-12-22
In this paper, new results on using only voltage measurements on supercapacitor terminals for estimation of accumulated energy are presented. For this purpose, a study based on application of fractional-order models of supercapacitor charging/discharging circuits is undertaken. Parameter estimates of the models are then used to assess the amount of the energy accumulated in supercapacitor. The obtained results are compared with energy determined experimentally by measuring voltage and current on supercapacitor terminals. All the tests are repeated for various input signal shapes and parameters. Very high consistency between estimated and experimental results fully confirm suitability of the proposed approach and thus applicability of the fractional calculus to modelling of supercapacitor energy storage.
An RSS based location estimation technique for cognitive relay networks
Qaraqe, Khalid A.
2010-11-01
In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine the location of the source using the direct and the relayed signal at the destination. We derive the Cramer-Rao lower bound (CRLB) expressions separately for x and y coordinates of the location estimate. We analyze the effects of cognitive behaviour of the relay on the performance of the proposed method. We also discuss and quantify the reliability of the location estimate using the proposed technique if the source is not stationary. The overall performance of the proposed method is presented through simulations. ©2010 IEEE.
Estimating spacecraft attitude based on in-orbit sensor measurements
DEFF Research Database (Denmark)
Jakobsen, Britt; Lyn-Knudsen, Kevin; Mølgaard, Mathias
2014-01-01
of 2014/15. To better evaluate the performance of the payload, it is desirable to couple the payload data with the satellite's orientation. With AAUSAT3 already in orbit it is possible to collect data directly from space in order to evaluate the performance of the attitude estimation. An extended kalman...... filter (EKF) is used for quaternion-based attitude estimation. A Simulink simulation environment developed for AAUSAT3, containing a "truth model" of the satellite and the orbit environment, is used to test the performance The performance is tested using different sensor noise parameters obtained both...... from a controlled environment on Earth as well as in-orbit. By using sensor noise parameters obtained on Earth as the expected parameters in the attitude estimation, and simulating the environment using the sensor noise parameters from space, it is possible to assess whether the EKF can be designed...
Annual global tree cover estimated by fusing optical and SAR satellite observations
Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.
2017-12-01
Tree cover defined structurally as the proportional, vertically projected area of vegetation (including leaves, stems, branches, etc.) of woody plants above a given height affects terrestrial energy and water exchanges, photosynthesis and transpiration, net primary production, and carbon and nutrient fluxes. Tree cover provides a measurable attribute upon which forest cover may be defined. Changes in tree cover over time can be used to monitor and retrieve site-specific histories of forest disturbance, succession, and degradation. Measurements of Earth's tree cover have been produced at regional, national, and global extents. However, most representations are static, and those for which multiple time periods have been produced are neither intended nor adequate for consistent, long-term monitoring. Moreover, although a substantial proportion of change has been shown to occur at resolutions below 250 m, existing long-term, Landsat-resolution datasets are either produced as static layers or with annual, five- or ten-year temporal resolution. We have developed an algorithms to retrieve seamless and consistent, sub-hectare resolution estimates of tree-canopy from optical and radar satellite data sources (e.g., Landsat, Sentinel-2, and ALOS-PALSAR). Our approach to estimation enables assimilation of multiple data sources and produces estimates of both cover and its uncertainty at the scale of pixels. It has generated the world's first Landsat-based percent tree cover dataset in 2013. Our previous algorithms are being adapted to produce prototype percent-tree and water-cover layers globally in 2000, 2005, and 2010—as well as annually over North and South America from 2010 to 2015—from passive-optical (Landsat and Sentinel-2) and SAR measurements. Generating a global, annual dataset is beyond the scope of this support; however, North and South America represent all of the world's major biomes and so offer the complete global range of environmental sources of error and
Observation of aftershocks of the 2003 Tokachi-Oki earthquake for estimation of local site effects
Yamanaka, Hiroaki; Motoki, Kentaro; Etoh, Kiminobu; Murayama, Masanari; Komaba, Nobuhiko
2004-03-01
Observation of aftershocks of the 2003 Tokachi-Oki earthquake was conducted in the southern part of the Tokachi basin in Hokkaido, Japan for estimation of local site effects. We installed accelerographs at 12 sites in Chokubetsu, Toyokoro, and Taiki areas, where large strong motion records were obtained during the main shock at stations of the K-NET and KiK-net. The stations of the aftershock observation are situated with different geological conditions and some of the sites were installed on Pleistocene layers as reference sites. The site amplifications are investigated using spectral ratio of S-waves from the aftershocks. The S-wave amplification factor is dominant at a period of about 1 second at the site near the KiK-net site in Toyokoro. This amplification fits well with calculated 1D amplification of S-wave in alluvial layers with a thickness of 50 meters. In addition to the site effects, we detected nonlinear amplification of the soft soils only during the main shock. The site effects at the strong motion site of the K-NET at Chokubetsu have a dominate peak at a period of 0.4 seconds. This amplification is due to soft soils having a thickness of about 13 meters. Contrary to the results at the two areas, site effects are not significantly different at the stations in the Taiki area, because of similarity on surface geological conditions.
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
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
Energy Technology Data Exchange (ETDEWEB)
Guo, Y. [School of Astronomy and Space Science and Key Laboratory of Modern Astronomy and Astrophysics in Ministry of Education, Nanjing University, Nanjing 210023 (China); Pariat, E.; Moraitis, K. [LESIA, Observatoire de Paris, PSL Research University, CNRS, Sorbonne Université, UPMC Univ. Paris 06, Univ. Paris Diderot, Sorbonne Paris Cité, F-92190 Meudon (France); Valori, G. [University College London, Mullard Space Science Laboratory, Holmbury St. Mary, Dorking, Surrey, RH5 6NT (United Kingdom); Anfinogentov, S. [Institute of Solar-Terrestrial Physics SB RAS 664033, Irkutsk, P.O. box 291, Lermontov Street, 126a (Russian Federation); Chen, F. [Max-Plank-Institut für Sonnensystemforschung, D-37077 Göttingen (Germany); Georgoulis, M. K. [Research Center for Astronomy and Applied Mathematics of the Academy of Athens, 4 Soranou Efesiou Street, 11527 Athens (Greece); Liu, Y. [W. W. Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA 94305 (United States); Thalmann, J. K. [Institute of Physics, Univeristy of Graz, Universitätsplatz 5/II, A-8010 Graz (Austria); Yang, S., E-mail: guoyang@nju.edu.cn [Key Laboratory of Solar Activity, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China)
2017-05-01
We study the writhe, twist, and magnetic helicity of different magnetic flux ropes, based on models of the solar coronal magnetic field structure. These include an analytical force-free Titov–Démoulin equilibrium solution, non-force-free magnetohydrodynamic simulations, and nonlinear force-free magnetic field models. The geometrical boundary of the magnetic flux rope is determined by the quasi-separatrix layer and the bottom surface, and the axis curve of the flux rope is determined by its overall orientation. The twist is computed by the Berger–Prior formula, which is suitable for arbitrary geometry and both force-free and non-force-free models. The magnetic helicity is estimated by the twist multiplied by the square of the axial magnetic flux. We compare the obtained values with those derived by a finite volume helicity estimation method. We find that the magnetic helicity obtained with the twist method agrees with the helicity carried by the purely current-carrying part of the field within uncertainties for most test cases. It is also found that the current-carrying part of the model field is relatively significant at the very location of the magnetic flux rope. This qualitatively explains the agreement between the magnetic helicity computed by the twist method and the helicity contributed purely by the current-carrying magnetic field.
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.
Extrapolated HPGe efficiency estimates based on a single calibration measurement
International Nuclear Information System (INIS)
Winn, W.G.
1994-01-01
Gamma spectroscopists often must analyze samples with geometries for which their detectors are not calibrated. The effort to experimentally recalibrate a detector for a new geometry can be quite time consuming, causing delay in reporting useful results. Such concerns have motivated development of a method for extrapolating HPGe efficiency estimates from an existing single measured efficiency. Overall, the method provides useful preliminary results for analyses that do not require exceptional accuracy, while reliably bracketing the credible range. The estimated efficiency element-of for a uniform sample in a geometry with volume V is extrapolated from the measured element-of 0 of the base sample of volume V 0 . Assuming all samples are centered atop the detector for maximum efficiency, element-of decreases monotonically as V increases about V 0 , and vice versa. Extrapolation of high and low efficiency estimates element-of h and element-of L provides an average estimate of element-of = 1/2 [element-of h + element-of L ] ± 1/2 [element-of h - element-of L ] (general) where an uncertainty D element-of = 1/2 (element-of h - element-of L ] brackets limits for a maximum possible error. The element-of h and element-of L both diverge from element-of 0 as V deviates from V 0 , causing D element-of to increase accordingly. The above concepts guided development of both conservative and refined estimates for element-of
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.
Wang, Y. H.; Jan, S.; Wang, D. P.
2003-05-01
Tidal and mean flows in the Taiwan Strait are obtained from analysis of 2.5 years (1999-2001) of shipboard ADCP data using a spatial least-squares technique. The average tidal current amplitude is 0.46 ms -1, the maximum amplitude is 0.80 ms -1 at the northeast and southeast entrances and the minimum amplitude is 0.20 ms -1 in the middle of the Strait. The tidal current ellipses derived from the shipboard ADCP data compare well with the predictions of a high-resolution regional tidal model. For the mean currents, the average velocity is about 0.40 ms -1. The mean transport through the Strait is northward (into the East China Sea) at 1.8 Sv. The transport is related to the along Strait wind by a simple regression, transport (Sv)=2.42+0.12×wind (ms -1). Using this empirical formula, the maximum seasonal transport is in summer, about 2.7 Sv, the minimum transport is in winter, at 0.9 Sv, and the mean transport is 1.8 Sv. For comparison, this result indicates that the seasonal amplitude is almost identical to the classical estimate by Wyrtki (Physical oceanography of the southeast Asian waters, scientific results of marine investigations of the South China Sea and Gulf of Thailand, 1959-1961. Naga Report 2, Scripps Institute of Oceanography, 195 pp.) based on the mass balance in the South China Sea, while the mean is close to the recent estimate by Isobe [Continental Shelf Research 19 (1999) 195] based on the mass balance in the East China Sea.
Nonlinear observer based phase synchronization of chaotic systems
International Nuclear Information System (INIS)
Meng Juan; Wang Xingyuan
2007-01-01
This Letter analyzes the phase synchronization problem of autonomous chaotic systems. Based on the nonlinear state observer algorithm and the pole placement technique, a phase synchronization scheme is designed. The phase synchronization of a new chaotic system is achieved by using this observer controller. Numerical simulations further demonstrate the effectiveness of the proposed phase synchronization scheme
Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter
Directory of Open Access Journals (Sweden)
Jing Li
2016-01-01
Full Text Available Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF, which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF, which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation outputs of two filters are merged by interacting multiple model (IMM approach. Experimental results show the accuracy and robustness of the hybrid Kalman filter.
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.)
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.
A novel earth observation based ecological indicator for cyanobacterial blooms
Anttila, Saku; Fleming-Lehtinen, Vivi; Attila, Jenni; Junttila, Sofia; Alasalmi, Hanna; Hällfors, Heidi; Kervinen, Mikko; Koponen, Sampsa
2018-02-01
Cyanobacteria form spectacular mass occurrences almost annually in the Baltic Sea. These harmful algal blooms are the most visible consequences of marine eutrophication, driven by a surplus of nutrients from anthropogenic sources and internal processes of the ecosystem. We present a novel Cyanobacterial Bloom Indicator (CyaBI) targeted for the ecosystem assessment of eutrophication in marine areas. The method measures the current cyanobacterial bloom situation (an average condition of recent 5 years) and compares this to the estimated target level for 'good environmental status' (GES). The current status is derived with an index combining indicative bloom event variables. As such we used seasonal information from the duration, volume and severity of algal blooms derived from earth observation (EO) data. The target level for GES was set by using a remote sensing based data set named Fraction with Cyanobacterial Accumulations (FCA; Kahru & Elmgren, 2014) covering years 1979-2014. Here a shift-detection algorithm for time series was applied to detect time-periods in the FCA data where the level of blooms remained low several consecutive years. The average conditions from these time periods were transformed into respective CyaBI target values to represent target level for GES. The indicator is shown to pass the three critical factors set for marine indicator development, namely it measures the current status accurately, the target setting can be scientifically proven and it can be connected to the ecosystem management goal. An advantage of the CyaBI method is that it's not restricted to the data used in the development work, but can be complemented, or fully applied, by using different types of data sources providing information on cyanobacterial accumulations.
Adaptive algorithm for mobile user positioning based on environment estimation
Directory of Open Access Journals (Sweden)
Grujović Darko
2014-01-01
Full Text Available This paper analyzes the challenges to realize an infrastructure independent and a low-cost positioning method in cellular networks based on RSS (Received Signal Strength parameter, auxiliary timing parameter and environment estimation. The proposed algorithm has been evaluated using field measurements collected from GSM (Global System for Mobile Communications network, but it is technology independent and can be applied in UMTS (Universal Mobile Telecommunication Systems and LTE (Long-Term Evolution networks, also.
Comparison of physically based catchment models for estimating Phosphorus losses
Nasr, Ahmed Elssidig; Bruen, Michael
2003-01-01
As part of a large EPA-funded research project, coordinated by TEAGASC, the Centre for Water Resources Research at UCD reviewed the available distributed physically based catchment models with a potential for use in estimating phosphorous losses for use in implementing the Water Framework Directive. Three models, representative of different levels of approach and complexity, were chosen and were implemented for a number of Irish catchments. This paper reports on (i) the lessons and experience...
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.
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.
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.
A Novel Rules Based Approach for Estimating Software Birthmark
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
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...
DEFF Research Database (Denmark)
Ditlevsen, Susanne; Samson, Adeline
2014-01-01
Parameter estimation in multidimensional diffusion models with only one coordinate observed is highly relevant in many biological applications, but a statistically difficult problem. In neuroscience, the membrane potential evolution in single neurons can be measured at high frequency, but biophys...
Observation of top quark pair production and estimation of W+jets background with ATLAS at the LHC
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...
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
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
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.
Adámková, Věra; Hubáček, Jaroslav A; Zimmelová, Petra; Velemínský, Miloš
2011-01-01
Food intake is a commonly monitored issue in many studies. In contrast, almost no information has been published on beverage intake in adults. To evaluate beverage intake, we studied a population of 1, 200 adults (656 males and 544 females, aged 18-54 years). The volumes and types of beverages were obtained from self-reported questionnaires. The mean beverage intake was highly variable, with a minimum of 450 mL/day and a maximum of 5,330 mL/day. A mean of 1,575 mL/day was found in the entire population (2,300 mL in males and 840 mL in females). Different patterns in the consumption of beverage types were observed between the males and females. For both males and females, the most common beverage consumed was water followed by tea. The next preferable beverages were alcoholic beer, coffee, and non-alcoholic beer in males and coffee, milk, and alcoholic beer in females. The estimated caloric intake from beverages covers, in most individuals, 10-30% of the recommended daily caloric intake. There is substantial variation among individuals, both in beverage intake and in caloric intake through beverages. The caloric intake from beverages reaches, in some individuals, one-third of the recommended daily caloric rate. © 2011 Neuroendocrinology Letters
Ratio-based estimators for a change point in persistence.
Halunga, Andreea G; Osborn, Denise R
2012-11-01
We study estimation of the date of change in persistence, from [Formula: see text] to [Formula: see text] or vice versa. Contrary to statements in the original papers, our analytical results establish that the ratio-based break point estimators of Kim [Kim, J.Y., 2000. Detection of change in persistence of a linear time series. Journal of Econometrics 95, 97-116], Kim et al. [Kim, J.Y., Belaire-Franch, J., Badillo Amador, R., 2002. Corringendum to "Detection of change in persistence of a linear time series". Journal of Econometrics 109, 389-392] and Busetti and Taylor [Busetti, F., Taylor, A.M.R., 2004. Tests of stationarity against a change in persistence. Journal of Econometrics 123, 33-66] are inconsistent when a mean (or other deterministic component) is estimated for the process. In such cases, the estimators converge to random variables with upper bound given by the true break date when persistence changes from [Formula: see text] to [Formula: see text]. A Monte Carlo study confirms the large sample downward bias and also finds substantial biases in moderate sized samples, partly due to properties at the end points of the search interval.
Estimation of Sideslip Angle Based on Extended Kalman Filter
Directory of Open Access Journals (Sweden)
Yupeng Huang
2017-01-01
Full Text Available The sideslip angle plays an extremely important role in vehicle stability control, but the sideslip angle in production car cannot be obtained from sensor directly in consideration of the cost of the sensor; it is essential to estimate the sideslip angle indirectly by means of other vehicle motion parameters; therefore, an estimation algorithm with real-time performance and accuracy is critical. Traditional estimation method based on Kalman filter algorithm is correct in vehicle linear control area; however, on low adhesion road, vehicles have obvious nonlinear characteristics. In this paper, extended Kalman filtering algorithm had been put forward in consideration of the nonlinear characteristic of the tire and was verified by the Carsim and Simulink joint simulation, such as the simulation on the wet cement road and the ice and snow road with double lane change. To test and verify the effect of extended Kalman filtering estimation algorithm, the real vehicle test was carried out on the limit test field. The experimental results show that the accuracy of vehicle sideslip angle acquired by extended Kalman filtering algorithm is obviously higher than that acquired by Kalman filtering in the area of the nonlinearity.
A novel ULA-based geometry for improving AOA estimation
Directory of Open Access Journals (Sweden)
Akbari Farida
2011-01-01
Full Text Available Abstract Due to relatively simple implementation, Uniform Linear Array (ULA is a popular geometry for array signal processing. Despite this advantage, it does not have a uniform performance in all directions and Angle of Arrival (AOA estimation performance degrades considerably in the angles close to endfire. In this article, a new configuration is proposed which can solve this problem. Proposed Array (PA configuration adds two elements to the ULA in top and bottom of the array axis. By extending signal model of the ULA to the new proposed ULA-based array, AOA estimation performance has been compared in terms of angular accuracy and resolution threshold through two well-known AOA estimation algorithms, MUSIC and MVDR. In both algorithms, Root Mean Square Error (RMSE of the detected angles descends as the input Signal to Noise Ratio (SNR increases. Simulation results show that the proposed array geometry introduces uniform accurate performance and higher resolution in middle angles as well as border ones. The PA also presents less RMSE than the ULA in endfire directions. Therefore, the proposed array offers better performance for the border angles with almost the same array size and simplicity in both MUSIC and MVDR algorithms with respect to the conventional ULA. In addition, AOA estimation performance of the PA geometry is compared with two well-known 2D-array geometries: L-shape and V-shape, and acceptable results are obtained with equivalent or lower complexity.
A novel ULA-based geometry for improving AOA estimation
Shirvani-Moghaddam, Shahriar; Akbari, Farida
2011-12-01
Due to relatively simple implementation, Uniform Linear Array (ULA) is a popular geometry for array signal processing. Despite this advantage, it does not have a uniform performance in all directions and Angle of Arrival (AOA) estimation performance degrades considerably in the angles close to endfire. In this article, a new configuration is proposed which can solve this problem. Proposed Array (PA) configuration adds two elements to the ULA in top and bottom of the array axis. By extending signal model of the ULA to the new proposed ULA-based array, AOA estimation performance has been compared in terms of angular accuracy and resolution threshold through two well-known AOA estimation algorithms, MUSIC and MVDR. In both algorithms, Root Mean Square Error (RMSE) of the detected angles descends as the input Signal to Noise Ratio (SNR) increases. Simulation results show that the proposed array geometry introduces uniform accurate performance and higher resolution in middle angles as well as border ones. The PA also presents less RMSE than the ULA in endfire directions. Therefore, the proposed array offers better performance for the border angles with almost the same array size and simplicity in both MUSIC and MVDR algorithms with respect to the conventional ULA. In addition, AOA estimation performance of the PA geometry is compared with two well-known 2D-array geometries: L-shape and V-shape, and acceptable results are obtained with equivalent or lower complexity.
ANFIS-Based Modeling for Photovoltaic Characteristics Estimation
Directory of Open Access Journals (Sweden)
Ziqiang Bi
2016-09-01
Full Text Available Due to the high cost of photovoltaic (PV modules, an accurate performance estimation method is significantly valuable for studying the electrical characteristics of PV generation systems. Conventional analytical PV models are usually composed by nonlinear exponential functions and a good number of unknown parameters must be identified before using. In this paper, an adaptive-network-based fuzzy inference system (ANFIS based modeling method is proposed to predict the current-voltage characteristics of PV modules. The effectiveness of the proposed modeling method is evaluated through comparison with Villalva’s model, radial basis function neural networks (RBFNN based model and support vector regression (SVR based model. Simulation and experimental results confirm both the feasibility and the effectiveness of the proposed method.
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
Babaeian, E.; Tuller, M.; Sadeghi, M.; Franz, T.; Jones, S. B.
2017-12-01
Soil Moisture Active Passive (SMAP) soil moisture products are commonly validated based on point-scale reference measurements, despite the exorbitant spatial scale disparity. The difference between the measurement depth of point-scale sensors and the penetration depth of SMAP further complicates evaluation efforts. Cosmic-ray neutron probes (CRNP) with an approximately 500-m radius footprint provide an appealing alternative for SMAP validation. This study is focused on the validation of SMAP level-4 root zone soil moisture products with 9-km spatial resolution based on CRNP observations at twenty U.S. reference sites with climatic conditions ranging from semiarid to humid. The CRNP measurements are often biased by additional hydrogen sources such as surface water, atmospheric vapor, or mineral lattice water, which sometimes yield unrealistic moisture values in excess of the soil water storage capacity. These effects were removed during CRNP data analysis. Comparison of SMAP data with corrected CRNP observations revealed a very high correlation for most of the investigated sites, which opens new avenues for validation of current and future satellite soil moisture products.
Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications
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.
State and force observers based on multibody models and the indirect Kalman filter
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.
Small Area Model-Based Estimators Using Big Data Sources
Directory of Open Access Journals (Sweden)
Marchetti Stefano
2015-06-01
Full Text Available The timely, accurate monitoring of social indicators, such as poverty or inequality, on a finegrained spatial and temporal scale is a crucial tool for understanding social phenomena and policymaking, but poses a great challenge to official statistics. This article argues that an interdisciplinary approach, combining the body of statistical research in small area estimation with the body of research in social data mining based on Big Data, can provide novel means to tackle this problem successfully. Big Data derived from the digital crumbs that humans leave behind in their daily activities are in fact providing ever more accurate proxies of social life. Social data mining from these data, coupled with advanced model-based techniques for fine-grained estimates, have the potential to provide a novel microscope through which to view and understand social complexity. This article suggests three ways to use Big Data together with small area estimation techniques, and shows how Big Data has the potential to mirror aspects of well-being and other socioeconomic phenomena.
Marker-based estimation of genetic parameters in genomics.
Directory of Open Access Journals (Sweden)
Zhiqiu Hu
Full Text Available Linear mixed model (LMM analysis has been recently used extensively for estimating additive genetic variances and narrow-sense heritability in many genomic studies. While the LMM analysis is computationally less intensive than the Bayesian algorithms, it remains infeasible for large-scale genomic data sets. In this paper, we advocate the use of a statistical procedure known as symmetric differences squared (SDS as it may serve as a viable alternative when the LMM methods have difficulty or fail to work with large datasets. The SDS procedure is a general and computationally simple method based only on the least squares regression analysis. We carry out computer simulations and empirical analyses to compare the SDS procedure with two commonly used LMM-based procedures. Our results show that the SDS method is not as good as the LMM methods for small data sets, but it becomes progressively better and can match well with the precision of estimation by the LMM methods for data sets with large sample sizes. Its major advantage is that with larger and larger samples, it continues to work with the increasing precision of estimation while the commonly used LMM methods are no longer able to work under our current typical computing capacity. Thus, these results suggest that the SDS method can serve as a viable alternative particularly when analyzing 'big' genomic data sets.
Population-based absolute risk estimation with survey data
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
Simulation-based seismic loss estimation of seaport transportation system
International Nuclear Information System (INIS)
Ung Jin Na; Shinozuka, Masanobu
2009-01-01
Seaport transportation system is one of the major lifeline systems in modern society and its reliable operation is crucial for the well-being of the public. However, past experiences showed that earthquake damage to port components can severely disrupt terminal operation, and thus negatively impact on the regional economy. The main purpose of this study is to provide a methodology for estimating the effects of the earthquake on the performance of the operation system of a container terminal in seaports. To evaluate the economic loss of damaged system, an analytical framework is developed by integrating simulation models for terminal operation and fragility curves of port components in the context of seismic risk analysis. For this purpose, computerized simulation model is developed and verified with actual terminal operation records. Based on the analytical procedure to assess the seismic performance of the terminal, system fragility curves are also developed. This simulation-based loss estimation methodology can be used not only for estimating the seismically induced revenue loss but also serve as a decision-making tool to select specific seismic retrofit technique on the basis of benefit-cost analysis
External Force Estimation for Teleoperation Based on Proprioceptive Sensors
Directory of Open Access Journals (Sweden)
Enrique del Sol
2014-03-01
Full Text Available This paper establishes an approach to external force estimation for telerobotic control in radioactive environments by the use of an identified manipulator model and pressure sensors, without employing a force/torque sensor. The advantages of - and need for - force feedback have been well-established in the field of telerobotics, where electrical and back-drivable manipulators have traditionally been used. This research proposes a methodology employing hydraulic robots for telerobotics tasks based on a model identification scheme. Comparative results of a force sensor and the proposed approach using a hydraulic telemanipulator are presented under different conditions. This approach not only presents a cost effective solution but also a methodology for force estimation in radioactive environments, where the dose rates limit the use of electronic devices such as sensing equipment.
Optimization-based particle filter for state and parameter estimation
Institute of Scientific and Technical Information of China (English)
Li Fu; Qi Fei; Shi Guangming; Zhang Li
2009-01-01
In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.
Regularized Regression and Density Estimation based on Optimal Transport
Burger, M.
2012-03-11
The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).
Gradient-based stochastic estimation of the density matrix
Wang, Zhentao; Chern, Gia-Wei; Batista, Cristian D.; Barros, Kipton
2018-03-01
Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements f(H)ij decay rapidly with distance rij between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals, the stochastic error scales like S-(d+2)/2d, where d is the dimension and S is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.
METAPHOR: Probability density estimation for machine learning based photometric redshifts
Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-06-01
We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).
A History-based Estimation for LHCb job requirements
Rauschmayr, Nathalie
2015-12-01
The main goal of a Workload Management System (WMS) is to find and allocate resources for the given tasks. The more and better job information the WMS receives, the easier will be to accomplish its task, which directly translates into higher utilization of resources. Traditionally, the information associated with each job, like expected runtime, is defined beforehand by the Production Manager in best case and fixed arbitrary values by default. In the case of LHCb's Workload Management System no mechanisms are provided which automate the estimation of job requirements. As a result, much more CPU time is normally requested than actually needed. Particularly, in the context of multicore jobs this presents a major problem, since single- and multicore jobs shall share the same resources. Consequently, grid sites need to rely on estimations given by the VOs in order to not decrease the utilization of their worker nodes when making multicore job slots available. The main reason for going to multicore jobs is the reduction of the overall memory footprint. Therefore, it also needs to be studied how memory consumption of jobs can be estimated. A detailed workload analysis of past LHCb jobs is presented. It includes a study of job features and their correlation with runtime and memory consumption. Following the features, a supervised learning algorithm is developed based on a history based prediction. The aim is to learn over time how jobs’ runtime and memory evolve influenced due to changes in experiment conditions and software versions. It will be shown that estimation can be notably improved if experiment conditions are taken into account.
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.
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.
Estimation with Right-Censored Observations Under A Semi-Markov Model.
Zhao, Lihui; Hu, X Joan
2013-06-01
The semi-Markov process often provides a better framework than the classical Markov process for the analysis of events with multiple states. The purpose of this paper is twofold. First, we show that in the presence of right censoring, when the right end-point of the support of the censoring time is strictly less than the right end-point of the support of the semi-Markov kernel, the transition probability of the semi-Markov process is nonidentifiable, and the estimators proposed in the literature are inconsistent in general. We derive the set of all attainable values for the transition probability based on the censored data, and we propose a nonparametric inference procedure for the transition probability using this set. Second, the conventional approach to constructing confidence bands is not applicable for the semi-Markov kernel and the sojourn time distribution. We propose new perturbation resampling methods to construct these confidence bands. Different weights and transformations are explored in the construction. We use simulation to examine our proposals and illustrate them with hospitalization data from a recent cancer survivor study.
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.
Observer Based Sliding Mode Attitude Control: Theoretical and Experimental Results
Directory of Open Access Journals (Sweden)
U. Jørgensen
2011-07-01
Full Text Available In this paper we present the design of a sliding mode controller for attitude control of spacecraft actuated by three orthogonal reaction wheels. The equilibrium of the closed loop system is proved to be asymptotically stable in the sense of Lyapunov. Due to cases where spacecraft do not have angular velocity measurements, an estimator for the generalized velocity is derived and asymptotic stability is proven for the observer. The approach is tested on an experimental platform with a sphere shaped Autonomous Underwater Vehicle SATellite: AUVSAT, developed at the Norwegian University of Science and Technology.
Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.
2015-01-01
The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351
Novakovic, M.; Atkinson, G. M.
2015-12-01
We use a generalized inversion to solve for site response, regional source and attenuation parameters, in order to define a region-specific ground-motion prediction equation (GMPE) from ground motion observations in Alberta, following the method of Atkinson et al. (2015 BSSA). The database is compiled from over 200 small to moderate seismic events (M 1 to 4.2) recorded at ~50 regional stations (distances from 30 to 500 km), over the last few years; almost all of the events have been identified as being induced by oil and gas activity. We remove magnitude scaling and geometric spreading functions from observed ground motions and invert for stress parameter, regional attenuation and site amplification. Resolving these parameters allows for the derivation of a regionally-calibrated GMPE that can be used to accurately predict amplitudes across the region in real time, which is useful for ground-motion-based alerting systems and traffic light protocols. The derived GMPE has further applications for the evaluation of hazards from induced seismicity.
Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A
2015-04-21
The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.
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
Maximum-likelihood estimation of the hyperbolic parameters from grouped observations
DEFF Research Database (Denmark)
Jensen, Jens Ledet
1988-01-01
a least-squares problem. The second procedure Hypesti first approaches the maximum-likelihood estimate by iterating in the profile-log likelihood function for the scale parameter. Close to the maximum of the likelihood function, the estimation is brought to an end by iteration, using all four parameters...
Estimating time-based instantaneous total mortality rate based on the age-structured abundance index
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.
Directory of Open Access Journals (Sweden)
M. Wei
2012-09-01
Full Text Available Despite the tremendous progress that has been made in data assimilation (DA methodology, observing systems that reduce observation errors, and model improvements that reduce background errors, the analyses produced by the best available DA systems are still different from the truth. Analysis error and error covariance are important since they describe the accuracy of the analyses, and are directly related to the future forecast errors, i.e., the forecast quality. In addition, analysis error covariance is critically important in building an efficient ensemble forecast system (EFS.
Estimating analysis error covariance in an ensemble-based Kalman filter DA is straightforward, but it is challenging in variational DA systems, which have been in operation at most NWP (Numerical Weather Prediction centers. In this study, we use the Lanczos method in the NCEP (the National Centers for Environmental Prediction Gridpoint Statistical Interpolation (GSI DA system to look into other important aspects and properties of this method that were not exploited before. We apply this method to estimate the observation impact signals (OIS, which are directly related to the analysis error variances. It is found that the smallest eigenvalue of the transformed Hessian matrix converges to one as the number of minimization iterations increases. When more observations are assimilated, the convergence becomes slower and more eigenvectors are needed to retrieve the observation impacts. It is also found that the OIS over data-rich regions can be represented by the eigenvectors with dominant eigenvalues.
Since only a limited number of eigenvectors can be computed due to computational expense, the OIS is severely underestimated, and the analysis error variance is consequently overestimated. It is found that the mean OIS values for temperature and wind components at typical model levels are increased by about 1.5 times when the number of eigenvectors is doubled
An automatic iris occlusion estimation method based on high-dimensional density estimation.
Li, Yung-Hui; Savvides, Marios
2013-04-01
Iris masks play an important role in iris recognition. They indicate which part of the iris texture map is useful and which part is occluded or contaminated by noisy image artifacts such as eyelashes, eyelids, eyeglasses frames, and specular reflections. The accuracy of the iris mask is extremely important. The performance of the iris recognition system will decrease dramatically when the iris mask is inaccurate, even when the best recognition algorithm is used. Traditionally, people used the rule-based algorithms to estimate iris masks from iris images. However, the accuracy of the iris masks generated this way is questionable. In this work, we propose to use Figueiredo and Jain's Gaussian Mixture Models (FJ-GMMs) to model the underlying probabilistic distributions of both valid and invalid regions on iris images. We also explored possible features and found that Gabor Filter Bank (GFB) provides the most discriminative information for our goal. Finally, we applied Simulated Annealing (SA) technique to optimize the parameters of GFB in order to achieve the best recognition rate. Experimental results show that the masks generated by the proposed algorithm increase the iris recognition rate on both ICE2 and UBIRIS dataset, verifying the effectiveness and importance of our proposed method for iris occlusion estimation.
Precision phase estimation based on weak-value amplification
Qiu, Xiaodong; Xie, Linguo; Liu, Xiong; Luo, Lan; Li, Zhaoxue; Zhang, Zhiyou; Du, Jinglei
2017-02-01
In this letter, we propose a precision method for phase estimation based on the weak-value amplification (WVA) technique using a monochromatic light source. The anomalous WVA significantly suppresses the technical noise with respect to the intensity difference signal induced by the phase delay when the post-selection procedure comes into play. The phase measured precision of this method is proportional to the weak-value of a polarization operator in the experimental range. Our results compete well with the wide spectrum light phase weak measurements and outperform the standard homodyne phase detection technique.
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
Gaussian particle filter based pose and motion estimation
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.
The Event Detection and the Apparent Velocity Estimation Based on Computer Vision
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.
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
REDRAW-Based Evapotranspiration Estimation in Chongli, North China
Zhang, Z.; Wang, Z.
2017-12-01
Evapotranspiration (ET) is the key component of hydrological cycle and spatial estimates of ET are important elements of atmospheric circulation and hydrologic models. Quantifying the ET over large region is significant for water resources planning, hydrologic water balances, water rights management, and water division. In this study, Evapotranspiration (ET) was estimated using REDRAW model in the Chongli on 2014. REDRAW is a satellite-based balance algorithm with reference dry and wet limits model developed to estimate ET. Remote sensing data obtained from MODIS and meteorological data from China Meteorological Data Sharing Service System were used in ET model. In order to analyze the distribution and time variation of ET over the study region, daily, monthly and yearly ET were calculated for the study area, and ET of different land cover types were calculated. In terms of the monthly ET, the figure was low in winter and high in other seasons, and reaches the maximum value in August, showing a high monthly difference. The ET value of water body was the highest and that of barren or sparse vegetation were the lowest, which accorded with local actual condition. Evaluating spatial temporal distribution of actual ET could assist to understand the water consumption regularity in region and figure out the effect from different land cover, which helped to establish links between land use, water allocation, and water use planning in study region. Due to the groundwater recession in north China, the evaluation of regional total water resources become increasingly essential, and the result of this study can be used to plan the water use. As the Chongli will prepare the ski slopes for Winter Olympics on 2022, accuracy estimation of actual ET can efficiently resolve water conflict and relieve water scarcity.
Directional Canopy Emissivity Estimation Based on Spectral Invariants
Guo, M.; Cao, B.; Ren, H.; Yongming, D.; Peng, J.; Fan, W.
2017-12-01
Land surface emissivity is a crucial parameter for estimating land surface temperature from remote sensing data and also plays an important role in the physical process of surface energy and water balance from local to global scales. To our knowledge, the emissivity varies with surface type and cover. As for the vegetation, its canopy emissivity is dependent on vegetation types, viewing zenith angle and structure that changes in different growing stages. Lots of previous studies have focused on the emissivity model, but few of them are analytic and suited to different canopy structures. In this paper, a new physical analytic model is proposed to estimate the directional emissivity of homogenous vegetation canopy based on spectral invariants. The initial model counts the directional absorption in six parts: the direct absorption of the canopy and the soil, the absorption of the canopy and soil after a single scattering and after multiple scattering within the canopy-soil system. In order to analytically estimate the emissivity, the pathways of photons absorbed in the canopy-soil system are traced using the re-collision probability in Fig.1. After sensitive analysis on the above six absorptions, the initial complicated model was further simplified as a fixed mathematic expression to estimate the directional emissivity for vegetation canopy. The model was compared with the 4SAIL model, FRA97 model, FRA02 model and DART model in Fig.2, and the results showed that the FRA02 model is significantly underestimated while the FRA97 model is a little underestimated, on basis of the new model. On the contrary, the emissivity difference between the new model with the 4SAIL model and DART model was found to be less than 0.002. In general, since the new model has the advantages of mathematic expression with accurate results and clear physical meaning, the model is promising to be extended to simulate the directional emissivity for the discrete canopy in further study.
Guidelines for reporting evaluations based on observational methodology.
Portell, Mariona; Anguera, M Teresa; Chacón-Moscoso, Salvador; Sanduvete-Chaves, Susana
2015-01-01
Observational methodology is one of the most suitable research designs for evaluating fidelity of implementation, especially in complex interventions. However, the conduct and reporting of observational studies is hampered by the absence of specific guidelines, such as those that exist for other evaluation designs. This lack of specific guidance poses a threat to the quality and transparency of these studies and also constitutes a considerable publication hurdle. The aim of this study thus was to draw up a set of proposed guidelines for reporting evaluations based on observational methodology. The guidelines were developed by triangulating three sources of information: observational studies performed in different fields by experts in observational methodology, reporting guidelines for general studies and studies with similar designs to observational studies, and proposals from experts in observational methodology at scientific meetings. We produced a list of guidelines grouped into three domains: intervention and expected outcomes, methods, and results. The result is a useful, carefully crafted set of simple guidelines for conducting and reporting observational studies in the field of program evaluation.
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.
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.
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
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.
Order Tracking Based on Robust Peak Search Instantaneous Frequency Estimation
International Nuclear Information System (INIS)
Gao, Y; Guo, Y; Chi, Y L; Qin, S R
2006-01-01
Order tracking plays an important role in non-stationary vibration analysis of rotating machinery, especially to run-up or coast down. An instantaneous frequency estimation (IFE) based order tracking of rotating machinery is introduced. In which, a peak search algorithms of spectrogram of time-frequency analysis is employed to obtain IFE of vibrations. An improvement to peak search is proposed, which can avoid strong non-order components or noises disturbing to the peak search work. Compared with traditional methods of order tracking, IFE based order tracking is simplified in application and only software depended. Testing testify the validity of the method. This method is an effective supplement to traditional methods, and the application in condition monitoring and diagnosis of rotating machinery is imaginable
MVDR Algorithm Based on Estimated Diagonal Loading for Beamforming
Directory of Open Access Journals (Sweden)
Yuteng Xiao
2017-01-01
Full Text Available Beamforming algorithm is widely used in many signal processing fields. At present, the typical beamforming algorithm is MVDR (Minimum Variance Distortionless Response. However, the performance of MVDR algorithm relies on the accurate covariance matrix. The MVDR algorithm declines dramatically with the inaccurate covariance matrix. To solve the problem, studying the beamforming array signal model and beamforming MVDR algorithm, we improve MVDR algorithm based on estimated diagonal loading for beamforming. MVDR optimization model based on diagonal loading compensation is established and the interval of the diagonal loading compensation value is deduced on the basis of the matrix theory. The optimal diagonal loading value in the interval is also determined through the experimental method. The experimental results show that the algorithm compared with existing algorithms is practical and effective.
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