Estimation of an Examinee's Ability in the Web-Based Computerized Adaptive Testing Program IRT-CAT

Directory of Open Access Journals (Sweden)

Yoon-Hwan Lee

2006-11-01

Full Text Available We developed a program to estimate an examinee's ability in order to provide freely available access to a web-based computerized adaptive testing (CAT program. We used PHP and Java Script as the program languages, PostgresSQL as the database management system on an Apache web server and Linux as the operating system. A system which allows for user input and searching within inputted items and creates tests was constructed. We performed an ability estimation on each test based on a Rasch model and 2- or 3-parametric logistic models. Our system provides an algorithm for a web-based CAT, replacing previous personal computer-based ones, and makes it possible to estimate an examinee?占퐏 ability immediately at the end of test.

FPSoC-Based Architecture for a Fast Motion Estimation Algorithm in H.264/AVC

Directory of Open Access Journals (Sweden)

Obianuju Ndili

2009-01-01

Full Text Available There is an increasing need for high quality video on low power, portable devices. Possible target applications range from entertainment and personal communications to security and health care. While H.264/AVC answers the need for high quality video at lower bit rates, it is significantly more complex than previous coding standards and thus results in greater power consumption in practical implementations. In particular, motion estimation (ME, in H.264/AVC consumes the largest power in an H.264/AVC encoder. It is therefore critical to speed-up integer ME in H.264/AVC via fast motion estimation (FME algorithms and hardware acceleration. In this paper, we present our hardware oriented modifications to a hybrid FME algorithm, our architecture based on the modified algorithm, and our implementation and prototype on a PowerPC-based Field Programmable System on Chip (FPSoC. Our results show that the modified hybrid FME algorithm on average, outperforms previous state-of-the-art FME algorithms, while its losses when compared with FSME, in terms of PSNR performance and computation time, are insignificant. We show that although our implementation platform is FPGA-based, our implementation results compare favourably with previous architectures implemented on ASICs. Finally we also show an improvement over some existing architectures implemented on FPGAs.

Model-based estimation with boundary side information or boundary regularization

International Nuclear Information System (INIS)

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

1994-01-01

The authors have previously developed a model-based strategy for joint estimation of myocardial perfusion and boundaries using ECT (Emission Computed Tomography). The authors have also reported difficulties with boundary estimation in low contrast and low count rate situations. In this paper, the authors propose using boundary side information (obtainable from high resolution MRI and CT images) or boundary regularization to improve both perfusion and boundary estimation in these situations. To fuse boundary side information into the emission measurements, the authors formulate a joint log-likelihood function to include auxiliary boundary measurements as well as ECT projection measurements. In addition, the authors introduce registration parameters to align auxiliary boundary measurements with ECT measurements and jointly estimate these parameters with other parameters of interest from the composite measurements. In simulated PET O-15 water myocardial perfusion studies using a simplified model, the authors show that the joint estimation improves perfusion estimation performance and gives boundary alignment accuracy of <0.5 mm even at 0.2 million counts. The authors implement boundary regularization through formulating a penalized log-likelihood function. The authors also demonstrate in simulations that simultaneous regularization of the epicardial boundary and myocardial thickness gives comparable perfusion estimation accuracy with the use of boundary side information

Statistical Discriminability Estimation for Pattern Classification Based on Neural Incremental Attribute Learning

DEFF Research Database (Denmark)

Wang, Ting; Guan, Sheng-Uei; Puthusserypady, Sadasivan

2014-01-01

Feature ordering is a significant data preprocessing method in Incremental Attribute Learning (IAL), a novel machine learning approach which gradually trains features according to a given order. Previous research has shown that, similar to feature selection, feature ordering is also important based...... estimation. Moreover, a criterion that summarizes all the produced values of AD is employed with a GA (Genetic Algorithm)-based approach to obtain the optimum feature ordering for classification problems based on neural networks by means of IAL. Compared with the feature ordering obtained by other approaches...

Dictionary-based fiber orientation estimation with improved spatial consistency.

Science.gov (United States)

Ye, Chuyang; Prince, Jerry L

2018-02-01

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

Learning Motion Features for Example-Based Finger Motion Estimation for Virtual Characters

Science.gov (United States)

Mousas, Christos; Anagnostopoulos, Christos-Nikolaos

2017-09-01

This paper presents a methodology for estimating the motion of a character's fingers based on the use of motion features provided by a virtual character's hand. In the presented methodology, firstly, the motion data is segmented into discrete phases. Then, a number of motion features are computed for each motion segment of a character's hand. The motion features are pre-processed using restricted Boltzmann machines, and by using the different variations of semantically similar finger gestures in a support vector machine learning mechanism, the optimal weights for each feature assigned to a metric are computed. The advantages of the presented methodology in comparison to previous solutions are the following: First, we automate the computation of optimal weights that are assigned to each motion feature counted in our metric. Second, the presented methodology achieves an increase (about 17%) in correctly estimated finger gestures in comparison to a previous method.

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

Science.gov (United States)

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

2003-01-01

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

GIS-based maps and area estimates of Northern Hemisphere permafrost extent during the Last Glacial Maximum

NARCIS (Netherlands)

Lindgren, A.; Hugelius, G.; Kuhry, P.; Christensen, T.R.; Vandenberghe, J.F.

2016-01-01

This study presents GIS-based estimates of permafrost extent in the northern circumpolar region during the Last Glacial Maximum (LGM), based on a review of previously published maps and compilations of field evidence in the form of ice-wedge pseudomorphs and relict sand wedges. We focus on field

Satellite telemetry reveals higher fishing mortality rates than previously estimated, suggesting overfishing of an apex marine predator.

Science.gov (United States)

Byrne, Michael E; Cortés, Enric; Vaudo, Jeremy J; Harvey, Guy C McN; Sampson, Mark; Wetherbee, Bradley M; Shivji, Mahmood

2017-08-16

Overfishing is a primary cause of population declines for many shark species of conservation concern. However, means of obtaining information on fishery interactions and mortality, necessary for the development of successful conservation strategies, are often fisheries-dependent and of questionable quality for many species of commercially exploited pelagic sharks. We used satellite telemetry as a fisheries-independent tool to document fisheries interactions, and quantify fishing mortality of the highly migratory shortfin mako shark ( Isurus oxyrinchus ) in the western North Atlantic Ocean. Forty satellite-tagged shortfin mako sharks tracked over 3 years entered the Exclusive Economic Zones of 19 countries and were harvested in fisheries of five countries, with 30% of tagged sharks harvested. Our tagging-derived estimates of instantaneous fishing mortality rates ( F = 0.19-0.56) were 10-fold higher than previous estimates from fisheries-dependent data (approx. 0.015-0.024), suggesting data used in stock assessments may considerably underestimate fishing mortality. Additionally, our estimates of F were greater than those associated with maximum sustainable yield, suggesting a state of overfishing. This information has direct application to evaluations of stock status and for effective management of populations, and thus satellite tagging studies have potential to provide more accurate estimates of fishing mortality and survival than traditional fisheries-dependent methodology. © 2017 The Author(s).

View Estimation Based on Value System

Science.gov (United States)

Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru

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

Observer-Based Human Knee Stiffness Estimation.

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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.

Robust linear discriminant analysis with distance based estimators

Science.gov (United States)

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

2017-11-01

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

Attribute and topology based change detection in a constellation of previously detected objects

Science.gov (United States)

Paglieroni, David W.; Beer, Reginald N.

2016-01-19

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

A methodology for modeling photocatalytic reactors for indoor pollution control using previously estimated kinetic parameters

Energy Technology Data Exchange (ETDEWEB)

Passalia, Claudio; Alfano, Orlando M. [INTEC - Instituto de Desarrollo Tecnologico para la Industria Quimica, CONICET - UNL, Gueemes 3450, 3000 Santa Fe (Argentina); FICH - Departamento de Medio Ambiente, Facultad de Ingenieria y Ciencias Hidricas, Universidad Nacional del Litoral, Ciudad Universitaria, 3000 Santa Fe (Argentina); Brandi, Rodolfo J., E-mail: rbrandi@santafe-conicet.gov.ar [INTEC - Instituto de Desarrollo Tecnologico para la Industria Quimica, CONICET - UNL, Gueemes 3450, 3000 Santa Fe (Argentina); FICH - Departamento de Medio Ambiente, Facultad de Ingenieria y Ciencias Hidricas, Universidad Nacional del Litoral, Ciudad Universitaria, 3000 Santa Fe (Argentina)

2012-04-15

Highlights: Black-Right-Pointing-Pointer Indoor pollution control via photocatalytic reactors. Black-Right-Pointing-Pointer Scaling-up methodology based on previously determined mechanistic kinetics. Black-Right-Pointing-Pointer Radiation interchange model between catalytic walls using configuration factors. Black-Right-Pointing-Pointer Modeling and experimental validation of a complex geometry photocatalytic reactor. - Abstract: A methodology for modeling photocatalytic reactors for their application in indoor air pollution control is carried out. The methodology implies, firstly, the determination of intrinsic reaction kinetics for the removal of formaldehyde. This is achieved by means of a simple geometry, continuous reactor operating under kinetic control regime and steady state. The kinetic parameters were estimated from experimental data by means of a nonlinear optimization algorithm. The second step was the application of the obtained kinetic parameters to a very different photoreactor configuration. In this case, the reactor is a corrugated wall type using nanosize TiO{sub 2} as catalyst irradiated by UV lamps that provided a spatially uniform radiation field. The radiative transfer within the reactor was modeled through a superficial emission model for the lamps, the ray tracing method and the computation of view factors. The velocity and concentration fields were evaluated by means of a commercial CFD tool (Fluent 12) where the radiation model was introduced externally. The results of the model were compared experimentally in a corrugated wall, bench scale reactor constructed in the laboratory. The overall pollutant conversion showed good agreement between model predictions and experiments, with a root mean square error less than 4%.

Optimization-based scatter estimation using primary modulation for computed tomography

Energy Technology Data Exchange (ETDEWEB)

Chen, Yi; Ma, Jingchen; Zhao, Jun, E-mail: junzhao@sjtu.edu.cn [School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Song, Ying [Department of Radiation Oncology, West China Hospital, Sichuan University, Chengdu 610041 (China)

2016-08-15

Purpose: Scatter reduces the image quality in computed tomography (CT), but scatter correction remains a challenge. A previously proposed primary modulation method simultaneously obtains the primary and scatter in a single scan. However, separating the scatter and primary in primary modulation is challenging because it is an underdetermined problem. In this study, an optimization-based scatter estimation (OSE) algorithm is proposed to estimate and correct scatter. Methods: In the concept of primary modulation, the primary is modulated, but the scatter remains smooth by inserting a modulator between the x-ray source and the object. In the proposed algorithm, an objective function is designed for separating the scatter and primary. Prior knowledge is incorporated in the optimization-based framework to improve the accuracy of the estimation: (1) the primary is always positive; (2) the primary is locally smooth and the scatter is smooth; (3) the location of penumbra can be determined; and (4) the scatter-contaminated data provide knowledge about which part is smooth. Results: The simulation study shows that the edge-preserving weighting in OSE improves the estimation accuracy near the object boundary. Simulation study also demonstrates that OSE outperforms the two existing primary modulation algorithms for most regions of interest in terms of the CT number accuracy and noise. The proposed method was tested on a clinical cone beam CT, demonstrating that OSE corrects the scatter even when the modulator is not accurately registered. Conclusions: The proposed OSE algorithm improves the robustness and accuracy in scatter estimation and correction. This method is promising for scatter correction of various kinds of x-ray imaging modalities, such as x-ray radiography, cone beam CT, and the fourth-generation CT.

Air Space Proportion in Pterosaur Limb Bones Using Computed Tomography and Its Implications for Previous Estimates of Pneumaticity

Science.gov (United States)

Martin, Elizabeth G.; Palmer, Colin

2014-01-01

Air Space Proportion (ASP) is a measure of how much air is present within a bone, which allows for a quantifiable comparison of pneumaticity between specimens and species. Measured from zero to one, higher ASP means more air and less bone. Conventionally, it is estimated from measurements of the internal and external bone diameter, or by analyzing cross-sections. To date, the only pterosaur ASP study has been carried out by visual inspection of sectioned bones within matrix. Here, computed tomography (CT) scans are used to calculate ASP in a small sample of pterosaur wing bones (mainly phalanges) and to assess how the values change throughout the bone. These results show higher ASPs than previous pterosaur pneumaticity studies, and more significantly, higher ASP values in the heads of wing bones than the shaft. This suggests that pneumaticity has been underestimated previously in pterosaurs, birds, and other archosaurs when shaft cross-sections are used to estimate ASP. Furthermore, ASP in pterosaurs is higher than those found in birds and most sauropod dinosaurs, giving them among the highest ASP values of animals studied so far, supporting the view that pterosaurs were some of the most pneumatized animals to have lived. The high degree of pneumaticity found in pterosaurs is proposed to be a response to the wing bone bending stiffness requirements of flight rather than a means to reduce mass, as is often suggested. Mass reduction may be a secondary result of pneumaticity that subsequently aids flight. PMID:24817312

Kidnapping Detection and Recognition in Previous Unknown Environment

Directory of Open Access Journals (Sweden)

Yang Tian

2017-01-01

Full Text Available An unaware event referred to as kidnapping makes the estimation result of localization incorrect. In a previous unknown environment, incorrect localization result causes incorrect mapping result in Simultaneous Localization and Mapping (SLAM by kidnapping. In this situation, the explored area and unexplored area are divided to make the kidnapping recovery difficult. To provide sufficient information on kidnapping, a framework to judge whether kidnapping has occurred and to identify the type of kidnapping with filter-based SLAM is proposed. The framework is called double kidnapping detection and recognition (DKDR by performing two checks before and after the “update” process with different metrics in real time. To explain one of the principles of DKDR, we describe a property of filter-based SLAM that corrects the mapping result of the environment using the current observations after the “update” process. Two classical filter-based SLAM algorithms, Extend Kalman Filter (EKF SLAM and Particle Filter (PF SLAM, are modified to show that DKDR can be simply and widely applied in existing filter-based SLAM algorithms. Furthermore, a technique to determine the adapted thresholds of metrics in real time without previous data is presented. Both simulated and experimental results demonstrate the validity and accuracy of the proposed method.

Convolution-based estimation of organ dose in tube current modulated CT

Science.gov (United States)

Tian, Xiaoyu; Segars, W. Paul; Dixon, Robert L.; Samei, Ehsan

2016-05-01

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ({{h}\\text{Organ}} ) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} with the organ dose coefficients ({{h}\\text{Organ}} ). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The

A Modelling Framework for estimating Road Segment Based On-Board Vehicle Emissions

International Nuclear Information System (INIS)

Lin-Jun, Yu; Ya-Lan, Liu; Yu-Huan, Ren; Zhong-Ren, Peng; Meng, Liu Meng

2014-01-01

Traditional traffic emission inventory models aim to provide overall emissions at regional level which cannot meet planners' demand for detailed and accurate traffic emissions information at the road segment level. Therefore, a road segment-based emission model for estimating light duty vehicle emissions is proposed, where floating car technology is used to collect information of traffic condition of roads. The employed analysis framework consists of three major modules: the Average Speed and the Average Acceleration Module (ASAAM), the Traffic Flow Estimation Module (TFEM) and the Traffic Emission Module (TEM). The ASAAM is used to obtain the average speed and the average acceleration of the fleet on each road segment using FCD. The TFEM is designed to estimate the traffic flow of each road segment in a given period, based on the speed-flow relationship and traffic flow spatial distribution. Finally, the TEM estimates emissions from each road segment, based on the results of previous two modules. Hourly on-road light-duty vehicle emissions for each road segment in Shenzhen's traffic network are obtained using this analysis framework. The temporal-spatial distribution patterns of the pollutant emissions of road segments are also summarized. The results show high emission road segments cluster in several important regions in Shenzhen. Also, road segments emit more emissions during rush hours than other periods. The presented case study demonstrates that the proposed approach is feasible and easy-to-use to help planners make informed decisions by providing detailed road segment-based emission information

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

Science.gov (United States)

Poon, P.; Kinoshita, A. M.

2017-12-01

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

Response to health insurance by previously uninsured rural children.

Science.gov (United States)

Tilford, J M; Robbins, J M; Shema, S J; Farmer, F L

1999-08-01

To examine the healthcare utilization and costs of previously uninsured rural children. Four years of claims data from a school-based health insurance program located in the Mississippi Delta. All children who were not Medicaid-eligible or were uninsured, were eligible for limited benefits under the program. The 1987 National Medical Expenditure Survey (NMES) was used to compare utilization of services. The study represents a natural experiment in the provision of insurance benefits to a previously uninsured population. Premiums for the claims cost were set with little or no information on expected use of services. Claims from the insurer were used to form a panel data set. Mixed model logistic and linear regressions were estimated to determine the response to insurance for several categories of health services. The use of services increased over time and approached the level of utilization in the NMES. Conditional medical expenditures also increased over time. Actuarial estimates of claims cost greatly exceeded actual claims cost. The provision of a limited medical, dental, and optical benefit package cost approximately $20-$24 per member per month in claims paid. An important uncertainty in providing health insurance to previously uninsured populations is whether a pent-up demand exists for health services. Evidence of a pent-up demand for medical services was not supported in this study of rural school-age children. States considering partnerships with private insurers to implement the State Children's Health Insurance Program could lower premium costs by assembling basic data on previously uninsured children.

Model-based estimation with boundary side information or boundary regularization [cardiac emission CT].

Science.gov (United States)

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

1994-01-01

The authors have previously developed a model-based strategy for joint estimation of myocardial perfusion and boundaries using ECT (emission computed tomography). They have also reported difficulties with boundary estimation in low contrast and low count rate situations. Here they propose using boundary side information (obtainable from high resolution MRI and CT images) or boundary regularization to improve both perfusion and boundary estimation in these situations. To fuse boundary side information into the emission measurements, the authors formulate a joint log-likelihood function to include auxiliary boundary measurements as well as ECT projection measurements. In addition, they introduce registration parameters to align auxiliary boundary measurements with ECT measurements and jointly estimate these parameters with other parameters of interest from the composite measurements. In simulated PET O-15 water myocardial perfusion studies using a simplified model, the authors show that the joint estimation improves perfusion estimation performance and gives boundary alignment accuracy of <0.5 mm even at 0.2 million counts. They implement boundary regularization through formulating a penalized log-likelihood function. They also demonstrate in simulations that simultaneous regularization of the epicardial boundary and myocardial thickness gives comparable perfusion estimation accuracy with the use of boundary side information.

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

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

2011-01-01

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

Estimation of Alcohol Concentration of Red Wine Based on Cole-Cole Plot

Science.gov (United States)

Watanabe, Kota; Taka, Yoshinori; Fujiwara, Osamu

To evaluate the quality of wine, we previously measured the complex relative permittivity of wine in the frequency range from 10 MHz to 6 GHz with a network analyzer, and suggested a possibility that the maturity and alcohol concentration of wine can simultaneously be estimated from the Cole-Cole plot. Although the absolute accuracy has not been examined yet, this method will enable one to estimate the alcohol concentration of alcoholic beverages without any distillation equipment simply. In this study, to investigate the estimation accuracy of the alcohol concentration of wine by its Cole-Cole plots, we measured the complex relative permittivity of pure water and diluted ethanol solution from 100 MHz to 40 GHz, and obtained the dependence of the Cole-Cole plot parameters on alcohol concentration and temperature. By using these results as calibration data, we estimated the alcohol concentration of red wine from the Cole-Cole plots, which was compared with the measured one based on a distillation method. As a result, we have confirmed that the estimated alcohol concentration of red wine agrees with the measured results in an absolute error by less than 1 %.

Optimal difference-based estimation for partially linear models

KAUST Repository

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

2017-01-01

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

Optimal difference-based estimation for partially linear models

KAUST Repository

Zhou, Yuejin

2017-12-16

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

DOA Estimation of Multiple LFM Sources Using a STFT-based and FBSS-based MUSIC Algorithm

Directory of Open Access Journals (Sweden)

K. B. Cui

2017-12-01

Full Text Available Direction of arrival (DOA estimation is an important problem in array signal processing. An effective multiple signal classification (MUSIC method based on the short-time Fourier transform (STFT and forward/ backward spatial smoothing (FBSS techniques for the DOA estimation problem of multiple time-frequency (t-f joint LFM sources is addressed. Previous work in the area e. g. STFT-MUSIC algorithm cannot resolve the t-f completely or largely joint sources because they can only select the single-source t-f points. The proposed method con¬structs the spatial t-f distributions (STFDs by selecting the multiple-source t-f points and uses the FBSS techniques to solve the problem of rank loss. In this way, the STFT-FBSS-MUSIC algorithm can resolve the t-f largely joint or completely joint LFM sources. In addition, the proposed algorithm also owns pretty low computational complexity when resolving multiple LFM sources because it can reduce the times of the feature decomposition and spectrum search. The performance of the proposed method is compared with that of the existing t-f based MUSIC algorithms through computer simulations and the results show its good performance.

Process-based Cost Estimation for Ramjet/Scramjet Engines

Science.gov (United States)

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

2003-01-01

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

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

International Nuclear Information System (INIS)

Barut, Murat

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-10-15

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

New population-based exome data question the pathogenicity of some genetic variants previously associated with Marfan syndrome

DEFF Research Database (Denmark)

Yang, Ren-Qiang; Jabbari, Javad; Cheng, Xiao-Shu

2014-01-01

BACKGROUND: Marfan syndrome (MFS) is a rare autosomal dominantly inherited connective tissue disorder with an estimated prevalence of 1:5,000. More than 1000 variants have been previously reported to be associated with MFS. However, the disease-causing effect of these variants may be questionable...

Vineyard Yield Estimation Based on the Analysis of High Resolution Images Obtained with Artificial Illumination at Night

Directory of Open Access Journals (Sweden)

Davinia Font

2015-04-01

Full Text Available This paper presents a method for vineyard yield estimation based on the analysis of high-resolution images obtained with artificial illumination at night. First, this paper assesses different pixel-based segmentation methods in order to detect reddish grapes: threshold based, Mahalanobis distance, Bayesian classifier, linear color model segmentation and histogram segmentation, in order to obtain the best estimation of the area of the clusters of grapes in this illumination conditions. The color spaces tested were the original RGB and the Hue-Saturation-Value (HSV. The best segmentation method in the case of a non-occluded reddish table-grape variety was the threshold segmentation applied to the H layer, with an estimation error in the area of 13.55%, improved up to 10.01% by morphological filtering. Secondly, after segmentation, two procedures for yield estimation based on a previous calibration procedure have been proposed: (1 the number of pixels corresponding to a cluster of grapes is computed and converted directly into a yield estimate; and (2 the area of a cluster of grapes is converted into a volume by means of a solid of revolution, and this volume is converted into a yield estimate; the yield errors obtained were 16% and −17%, respectively.

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

Monte Carlo-based tail exponent estimator

Science.gov (United States)

Barunik, Jozef; Vacha, Lukas

2010-11-01

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

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

DEFF Research Database (Denmark)

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

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

Further Rehabilitating CIV-based Black Hole Mass Estimates in Quasars

Science.gov (United States)

Brotherton, Michael S.; Runnoe, Jessie C.; Shang, Zhaohui; Varju, Melinda

2016-06-01

Virial black hole masses are routinely estimated for high-redshift quasars using the C IV lambda 1549 emission line using single-epoch spectra that provide a gas velocity and a continuum luminosity. Such masses are very uncertain, however, especially because C IV likely possesses a non-virial component that varies with the Eddington ratio. We have previously used the 1400 feature, a blend of S i IV and O IV] emission that does not suffer the problems of C IV, to rehabilitate C IV-based mases by providing a correction term. The C IV profile itself, however, provides enough information to correct the black hole masses and remove the effects of the non-virial component. We use Mg II-based black hole masses to calibrate and test a new C IV-based black hole mass formula using only C IV and continuum measurements superior to existing formulations, as well as to test for additional dependencies on luminosity.

Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

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Danping Wang

2017-01-01

Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

Estimating leptospirosis incidence using hospital-based surveillance and a population-based health care utilization survey in Tanzania.

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Holly M Biggs

Full Text Available The incidence of leptospirosis, a neglected zoonotic disease, is uncertain in Tanzania and much of sub-Saharan Africa, resulting in scarce data on which to prioritize resources for public health interventions and disease control. In this study, we estimate the incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania.We conducted a population-based household health care utilization survey in two districts in the Kilimanjaro Region of Tanzania and identified leptospirosis cases at two hospital-based fever sentinel surveillance sites in the Kilimanjaro Region. We used multipliers derived from the health care utilization survey and case numbers from hospital-based surveillance to calculate the incidence of leptospirosis. A total of 810 households were enrolled in the health care utilization survey and multipliers were derived based on responses to questions about health care seeking in the event of febrile illness. Of patients enrolled in fever surveillance over a 1 year period and residing in the 2 districts, 42 (7.14% of 588 met the case definition for confirmed or probable leptospirosis. After applying multipliers to account for hospital selection, test sensitivity, and study enrollment, we estimated the overall incidence of leptospirosis ranges from 75-102 cases per 100,000 persons annually.We calculated a high incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania, where leptospirosis incidence was previously unknown. Multiplier methods, such as used in this study, may be a feasible method of improving availability of incidence estimates for neglected diseases, such as leptospirosis, in resource constrained settings.

Estimating Leptospirosis Incidence Using Hospital-Based Surveillance and a Population-Based Health Care Utilization Survey in Tanzania

Science.gov (United States)

Biggs, Holly M.; Hertz, Julian T.; Munishi, O. Michael; Galloway, Renee L.; Marks, Florian; Saganda, Wilbrod; Maro, Venance P.; Crump, John A.

2013-01-01

Background The incidence of leptospirosis, a neglected zoonotic disease, is uncertain in Tanzania and much of sub-Saharan Africa, resulting in scarce data on which to prioritize resources for public health interventions and disease control. In this study, we estimate the incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania. Methodology/Principal Findings We conducted a population-based household health care utilization survey in two districts in the Kilimanjaro Region of Tanzania and identified leptospirosis cases at two hospital-based fever sentinel surveillance sites in the Kilimanjaro Region. We used multipliers derived from the health care utilization survey and case numbers from hospital-based surveillance to calculate the incidence of leptospirosis. A total of 810 households were enrolled in the health care utilization survey and multipliers were derived based on responses to questions about health care seeking in the event of febrile illness. Of patients enrolled in fever surveillance over a 1 year period and residing in the 2 districts, 42 (7.14%) of 588 met the case definition for confirmed or probable leptospirosis. After applying multipliers to account for hospital selection, test sensitivity, and study enrollment, we estimated the overall incidence of leptospirosis ranges from 75–102 cases per 100,000 persons annually. Conclusions/Significance We calculated a high incidence of leptospirosis in two districts in the Kilimanjaro Region of Tanzania, where leptospirosis incidence was previously unknown. Multiplier methods, such as used in this study, may be a feasible method of improving availability of incidence estimates for neglected diseases, such as leptospirosis, in resource constrained settings. PMID:24340122

Comparability of estimating energy rebound effect should be based on uniform mechanism and benchmark: A reply to Du and Lin

International Nuclear Information System (INIS)

Li, Chengyu; Shao, Shuai; Yang, Lili; Yu, Mingliang

2016-01-01

Du and Lin (2015) argued that the estimation model of the economy-wide energy rebound effect proposed by Shao et al. (2014) should be revised and provided an alternative approach, which they considered to be more consistent with the definition of the rebound effect. However, in this comment, we do not find a valid correction or modification to our original model, because their criticism logic does not originate from the corresponding mechanism in Shao et al. (2014), and their estimation formula has a different benchmark with ours. Moreover, their data samples were also different from ours, generating the incomparable results, and there are some irrational results in the comment. Even based on different estimation formulas in the two studies and using the same estimation method and data sample, the comparison results show that the problem of the estimation formula in our previous study which they claimed does not really exist. We argue that this comment is not consistent with the principle of the rebound effect. Actually, their work can be only regarded as proposing an alternative approach for the estimate of the rebound effect. Therefore, their argument is not enough to overturn our previous study. - Highlights: • A reply to Du and Lin (2015), who questioned our previous study, is provided. • Their criticism logic does not originate from our corresponding mechanism. • Their estimation formula has a different benchmark with ours. • Different data samples in the two papers make their results incomparable. • Their argument is not enough to overturn our previous study.

CONTROL BASED ON NUMERICAL METHODS AND RECURSIVE BAYESIAN ESTIMATION IN A CONTINUOUS ALCOHOLIC FERMENTATION PROCESS

Directory of Open Access Journals (Sweden)

Olga L. Quintero

Full Text Available Biotechnological processes represent a challenge in the control field, due to their high nonlinearity. In particular, continuous alcoholic fermentation from Zymomonas mobilis (Z.m presents a significant challenge. This bioprocess has high ethanol performance, but it exhibits an oscillatory behavior in process variables due to the influence of inhibition dynamics (rate of ethanol concentration over biomass, substrate, and product concentrations. In this work a new solution for control of biotechnological variables in the fermentation process is proposed, based on numerical methods and linear algebra. In addition, an improvement to a previously reported state estimator, based on particle filtering techniques, is used in the control loop. The feasibility estimator and its performance are demonstrated in the proposed control loop. This methodology makes it possible to develop a controller design through the use of dynamic analysis with a tested biomass estimator in Z.m and without the use of complex calculations.

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...

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

Science.gov (United States)

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

2014-01-21

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

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

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Ounpraseuth Songthip

2012-11-01

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

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

vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

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Demeter Lisa

2010-05-01

Full Text Available Abstract Background The replication rate (or fitness between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV. HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Results Based on a mathematical model and several statistical methods (least-squares approach and measurement error models, a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1. Conclusions Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at http://bis.urmc.rochester.edu/vFitness/.

Estimating SPT-N Value Based on Soil Resistivity using Hybrid ANN-PSO Algorithm

Science.gov (United States)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Standard Penetration Resistance (N value) is used in many empirical geotechnical engineering formulas. Meanwhile, soil resistivity is a measure of soil’s resistance to electrical flow. For a particular site, usually, only a limited N value data are available. In contrast, resistivity data can be obtained extensively. Moreover, previous studies showed evidence of a correlation between N value and resistivity value. Yet, no existing method is able to interpret resistivity data for estimation of N value. Thus, the aim is to develop a method for estimating N-value using resistivity data. This study proposes a hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) method to estimate N value using resistivity data. Five different ANN-PSO models based on five boreholes were developed and analyzed. The performance metrics used were the coefficient of determination, R2 and mean absolute error, MAE. Analysis of result found that this method can estimate N value (R2 best=0.85 and MAEbest=0.54) given that the constraint, Δ {\\bar{l}}ref, is satisfied. The results suggest that ANN-PSO method can be used to estimate N value with good accuracy.

Design-based stereological estimation of the total number of cardiac myocytes in histological sections

DEFF Research Database (Denmark)

Brüel, Annemarie; Nyengaard, Jens Randel

2005-01-01

in LM sections using design-based stereology. MATERIALS AND METHODS: From formalin-fixed left rat ventricles (LV) isotropic uniformly random sections were cut. The total number of myocyte nuclei per LV was estimated using the optical disector. Two-microm-thick serial paraffin sections were stained......BACKGROUND: Counting the total number of cardiac myocytes has not previously been possible in ordinary histological sections using light microscopy (LM) due to difficulties in defining the myocyte borders properly. AIM: To describe a method by which the total number of cardiac myocytes is estimated...... with antibodies against cadherin and type IV collagen to visualise the intercalated discs and the myocyte membranes, respectively. Using the physical disector in "local vertical windows" of the serial sections, the average number of nuclei per myocyte was estimated.RESULTS: The total number of myocyte nuclei...

Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation

Directory of Open Access Journals (Sweden)

Sekhar S Chandra

2004-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

Science.gov (United States)

Guo, T. H.; Musgrave, J.

1992-11-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using

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...

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....

Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

Science.gov (United States)

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

Dynamic estimator for determining operating conditions in an internal combustion engine

Science.gov (United States)

Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

2016-01-05

Methods and systems are provided for estimating engine performance information for a combustion cycle of an internal combustion engine. Estimated performance information for a previous combustion cycle is retrieved from memory. The estimated performance information includes an estimated value of at least one engine performance variable. Actuator settings applied to engine actuators are also received. The performance information for the current combustion cycle is then estimated based, at least in part, on the estimated performance information for the previous combustion cycle and the actuator settings applied during the previous combustion cycle. The estimated performance information for the current combustion cycle is then stored to the memory to be used in estimating performance information for a subsequent combustion cycle.

Multiframe Superresolution of Vehicle License Plates Based on Distribution Estimation Approach

Directory of Open Access Journals (Sweden)

Renchao Jin

2016-01-01

Full Text Available Low-resolution (LR license plate images or videos are often captured in the practical applications. In this paper, a distribution estimation based superresolution (SR algorithm is proposed to reconstruct the license plate image. Different from the previous work, here, the high-resolution (HR image is estimated via the obtained posterior probability distribution by using the variational Bayesian framework. To regularize the estimated HR image, a feature-specific prior model is proposed by considering the most significant characteristic of license plate images; that is, the target has high contrast with the background. In order to assure the success of the SR reconstruction, the models representing smoothness constraints on images are also used to regularize the estimated HR image with the proposed feature-specific prior model. We show by way of experiments, under challenging blur with size 7 × 7 and zero-mean Gaussian white noise with variances 0.2 and 0.5, respectively, that the proposed method could achieve the peak signal-to-noise ratio (PSNR of 22.69 dB and the structural similarity (SSIM of 0.9022 under the noise with variance 0.2 and the PSNR of 19.89 dB and the SSIM of 0.8582 even under the noise with variance 0.5, which are 1.84 dB and 0.04 improvements in comparison with other methods.

Statistical inference based on latent ability estimates

NARCIS (Netherlands)

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

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

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

Science.gov (United States)

Qian, Xuewen; Deng, Honggui; He, Hailang

2017-10-01

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

Wildlife Loss Estimates and Summary of Previous Mitigation Related to Hydroelectric Projects in Montana, Volume Three, Hungry Horse Project.

Energy Technology Data Exchange (ETDEWEB)

Casey, Daniel

1984-10-01

This assessment addresses the impacts to the wildlife populations and wildlife habitats due to the Hungry Horse Dam project on the South Fork of the Flathead River and previous mitigation of theses losses. In order to develop and focus mitigation efforts, it was first necessary to estimate wildlife and wildlife hatitat losses attributable to the construction and operation of the project. The purpose of this report was to document the best available information concerning the degree of impacts to target wildlife species. Indirect benefits to wildlife species not listed will be identified during the development of alternative mitigation measures. Wildlife species incurring positive impacts attributable to the project were identified.

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...

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...

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.

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...

Forest height estimation from mountain forest areas using general model-based decomposition for polarimetric interferometric synthetic aperture radar images

Science.gov (United States)

Minh, Nghia Pham; Zou, Bin; Cai, Hongjun; Wang, Chengyi

2014-01-01

The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model-based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.

Directional Canopy Emissivity Estimation Based on Spectral Invariants

Science.gov (United States)

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.

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

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.

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

Science.gov (United States)

Wang, Yingbin; Jiao, Yan

2015-05-01

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

Estimations of climate sensitivity based on top-of-atmosphere radiation imbalance

Directory of Open Access Journals (Sweden)

B. Lin

2010-02-01

Full Text Available Large climate feedback uncertainties limit the accuracy in predicting the response of the Earth's climate to the increase of CO₂ concentration within the atmosphere. This study explores a potential to reduce uncertainties in climate sensitivity estimations using energy balance analysis, especially top-of-atmosphere (TOA radiation imbalance. The time-scales studied generally cover from decade to century, that is, middle-range climate sensitivity is considered, which is directly related to the climate issue caused by atmospheric CO₂ change. The significant difference between current analysis and previous energy balance models is that the current study targets at the boundary condition problem instead of solving the initial condition problem. Additionally, climate system memory and deep ocean heat transport are considered. The climate feedbacks are obtained based on the constraints of the TOA radiation imbalance and surface temperature measurements of the present climate. In this study, the TOA imbalance value of 0.85 W/m² is used. Note that this imbalance value has large uncertainties. Based on this value, a positive climate feedback with a feedback coefficient ranging from −1.3 to −1.0 W/m²/K is found. The range of feedback coefficient is determined by climate system memory. The longer the memory, the stronger the positive feedback. The estimated time constant of the climate is large (70~120 years mainly owing to the deep ocean heat transport, implying that the system may be not in an equilibrium state under the external forcing during the industrial era. For the doubled-CO₂ climate (or 3.7 W/m² forcing, the estimated global warming would be 3.1 K if the current estimate of 0.85 W/m² TOA net radiative heating could be confirmed. With accurate long-term measurements of TOA radiation, the analysis method suggested by this study provides a great potential in the

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

DEFF Research Database (Denmark)

Jacobsen, Martin; Martinussen, Torben

2016-01-01

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

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

NARCIS (Netherlands)

Moddemeijer, R

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

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

NARCIS (Netherlands)

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

2014-01-01

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

A novel SURE-based criterion for parametric PSF estimation.

Science.gov (United States)

Xue, Feng; Blu, Thierry

2015-02-01

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

Model-based estimation of finite population total in stratified sampling

African Journals Online (AJOL)

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

Model-based estimation for dynamic cardiac studies using ECT.

Science.gov (United States)

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

1994-01-01

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

Estimation of measurement variances

International Nuclear Information System (INIS)

Anon.

1981-01-01

In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

Prediction of RNA secondary structure using generalized centroid estimators.

Science.gov (United States)

Hamada, Michiaki; Kiryu, Hisanori; Sato, Kengo; Mituyama, Toutai; Asai, Kiyoshi

2009-02-15

Recent studies have shown that the methods for predicting secondary structures of RNAs on the basis of posterior decoding of the base-pairing probabilities has an advantage with respect to prediction accuracy over the conventionally utilized minimum free energy methods. However, there is room for improvement in the objective functions presented in previous studies, which are maximized in the posterior decoding with respect to the accuracy measures for secondary structures. We propose novel estimators which improve the accuracy of secondary structure prediction of RNAs. The proposed estimators maximize an objective function which is the weighted sum of the expected number of the true positives and that of the true negatives of the base pairs. The proposed estimators are also improved versions of the ones used in previous works, namely CONTRAfold for secondary structure prediction from a single RNA sequence and McCaskill-MEA for common secondary structure prediction from multiple alignments of RNA sequences. We clarify the relations between the proposed estimators and the estimators presented in previous works, and theoretically show that the previous estimators include additional unnecessary terms in the evaluation measures with respect to the accuracy. Furthermore, computational experiments confirm the theoretical analysis by indicating improvement in the empirical accuracy. The proposed estimators represent extensions of the centroid estimators proposed in Ding et al. and Carvalho and Lawrence, and are applicable to a wide variety of problems in bioinformatics. Supporting information and the CentroidFold software are available online at: http://www.ncrna.org/software/centroidfold/.

Estimating monthly temperature using point based interpolation techniques

Science.gov (United States)

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

2013-04-01

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

Design of Artificial Neural Network-Based pH Estimator

Directory of Open Access Journals (Sweden)

Shebel A. Alsabbah

2010-10-01

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

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

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...

Accuracy of the Estimated Core Temperature (ECTemp) Algorithm in Estimating Circadian Rhythm Indicators

Science.gov (United States)

2017-04-12

measurement of CT outside of stringent laboratory environments. This study evaluated ECTempTM, a heart rate- based extended Kalman Filter CT...were lower than heart-rate based models analyzed in previous studies. As such, ECTempTM demonstrates strong potential for estimating circadian CT...control of heat transfer from the core to the extremities [11]. As such, heart rate plays a pivotal role in thermoregulation as a primary

A Channelization-Based DOA Estimation Method for Wideband Signals

Directory of Open Access Journals (Sweden)

Rui Guo

2016-07-01

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

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%.

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....

Accurate position estimation methods based on electrical impedance tomography measurements

Science.gov (United States)

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

2017-08-01

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

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

Science.gov (United States)

Brás, Lígia P; Menezes, José C

2007-06-01

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

Parallel Factor-Based Model for Two-Dimensional Direction Estimation

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Nizar Tayem

2017-01-01

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

Estimation of Thermal Sensation Based on Wrist Skin Temperatures

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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

Estimating Driving Performance Based on EEG Spectrum Analysis

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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.

Estimation model for evaporative emissions from gasoline vehicles based on thermodynamics.

Science.gov (United States)

Hata, Hiroo; Yamada, Hiroyuki; Kokuryo, Kazuo; Okada, Megumi; Funakubo, Chikage; Tonokura, Kenichi

2018-03-15

In this study, we conducted seven-day diurnal breathing loss (DBL) tests on gasoline vehicles. We propose a model based on the theory of thermodynamics that can represent the experimental results of the current and previous studies. The experiments were performed using 14 physical parameters to determine the dependence of total emissions on temperature, fuel tank fill, and fuel vapor pressure. In most cases, total emissions after an apparent breakthrough were proportional to the difference between minimum and maximum environmental temperatures during the day, fuel tank empty space, and fuel vapor pressure. Volatile organic compounds (VOCs) were measured using a Gas Chromatography Mass Spectrometer and Flame Ionization Detector (GC-MS/FID) to determine the Ozone Formation Potential (OFP) of after-breakthrough gas emitted to the atmosphere. Using the experimental results, we constructed a thermodynamic model for estimating the amount of evaporative emissions after a fully saturated canister breakthrough occurred, and a comparison between the thermodynamic model and previous models was made. Finally, the total annual evaporative emissions and OFP in Japan were determined and compared by each model. Copyright © 2017 Elsevier B.V. All rights reserved.

Particle filter based MAP state estimation: A comparison

NARCIS (Netherlands)

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

2009-01-01

MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis

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Aandahl, R. Zachariah; Reyes, Josephine F.; Sisson, Scott A.; Tanaka, Mark M.

2012-01-01

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around to per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is (95% CI: ,)and under the linear model, the mean mutation rate per locus per repeat unit is (95% CI: ,). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future. PMID:22761563

Estimation of Compaction Parameters Based on Soil Classification

Science.gov (United States)

Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.

2018-02-01

Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.

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

Science.gov (United States)

Otsuka, J; Kawai, Y; Sugaya, N

2001-11-21

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

Estimating a WTP-based value of a QALY: the 'chained' approach.

Science.gov (United States)

Robinson, Angela; Gyrd-Hansen, Dorte; Bacon, Philomena; Baker, Rachel; Pennington, Mark; Donaldson, Cam

2013-09-01

A major issue in health economic evaluation is that of the value to place on a quality adjusted life year (QALY), commonly used as a measure of health care effectiveness across Europe. This critical policy issue is reflected in the growing interest across Europe in development of more sound methods to elicit such a value. EuroVaQ was a collaboration of researchers from 9 European countries, the main aim being to develop more robust methods to determine the monetary value of a QALY based on surveys of the general public. The 'chained' approach of deriving a societal willingness-to-pay (WTP) based monetary value of a QALY used the following basic procedure. First, utility values were elicited for health states using the standard gamble (SG) and time trade off (TTO) methods. Second, a monetary value to avoid some risk/duration of that health state was elicited and the implied WTP per QALY estimated. We developed within EuroVaQ an adaptation to the 'chained approach' that attempts to overcome problems documented previously (in particular the tendency to arrive at exceedingly high WTP per QALY values). The survey was administered via Internet panels in each participating country and almost 22,000 responses achieved. Estimates of the value of a QALY varied across question and were, if anything, on the low side with the (trimmed) 'all country' mean WTP per QALY ranging from $18,247 to $34,097. Untrimmed means were considerably higher and medians considerably lower in each case. We conclude that the adaptation to the chained approach described here is a potentially useful technique for estimating WTP per QALY. A number of methodological challenges do still exist, however, and there is scope for further refinement. Copyright © 2013 Elsevier Ltd. All rights reserved.

A survey on OFDM channel estimation techniques based on denoising strategies

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Pallaviram Sure

2017-04-01

Full Text Available Channel estimation forms the heart of any orthogonal frequency division multiplexing (OFDM based wireless communication receiver. Frequency domain pilot aided channel estimation techniques are either least squares (LS based or minimum mean square error (MMSE based. LS based techniques are computationally less complex. Unlike MMSE ones, they do not require a priori knowledge of channel statistics (KCS. However, the mean square error (MSE performance of the channel estimator incorporating MMSE based techniques is better compared to that obtained with the incorporation of LS based techniques. To enhance the MSE performance using LS based techniques, a variety of denoising strategies have been developed in the literature, which are applied on the LS estimated channel impulse response (CIR. The advantage of denoising threshold based LS techniques is that, they do not require KCS but still render near optimal MMSE performance similar to MMSE based techniques. In this paper, a detailed survey on various existing denoising strategies, with a comparative discussion of these strategies is presented.

Towards Remote Estimation of Radiation Use Efficiency in Maize Using UAV-Based Low-Cost Camera Imagery

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Andreas Tewes

2018-02-01

Full Text Available Radiation Use Efficiency (RUE defines the productivity with which absorbed photosynthetically active radiation (APAR is converted to plant biomass. Readily used in crop growth models to predict dry matter accumulation, RUE is commonly determined by elaborate static sensor measurements in the field. Different definitions are used, based on total absorbed PAR (RUEtotal or PAR absorbed by the photosynthetically active leaf tissue only (RUEgreen. Previous studies have shown that the fraction of PAR absorbed (fAPAR, which supports the assessment of RUE, can be reliably estimated via remote sensing (RS, but unfortunately at spatial resolutions too coarse for experimental agriculture. UAV-based RS offers the possibility to cover plant reflectance at very high spatial and temporal resolution, possibly covering several experimental plots in little time. We investigated if (a UAV-based low-cost camera imagery allowed estimating RUEs in different experimental plots where maize was cultivated in the growing season of 2016, (b those values were different from the ones previously reported in literature and (c there was a difference between RUEtotal and RUEgreen. We determined fractional cover and canopy reflectance based on the RS imagery. Our study found that RUEtotal ranges between 4.05 and 4.59, and RUEgreen between 4.11 and 4.65. These values are higher than those published in other research articles, but not outside the range of plausibility. The difference between RUEtotal and RUEgreen was minimal, possibly due to prolonged canopy greenness induced by the stay-green trait of the cultivar grown. The procedure presented here makes time-consuming APAR measurements for determining RUE especially in large experiments superfluous.

MODIS-based global terrestrial estimates of gross primary productivity and evapotranspiration

Science.gov (United States)

Ryu, Y.; Baldocchi, D. D.; Kobayashi, H.; Li, J.; van Ingen, C.; Agarwal, D.; Jackson, K.; Humphrey, M.

2010-12-01

We propose a novel approach to quantify gross primary productivity (GPP) and evapotranspiration (ET) at global scale (5 km resolution with 8-day interval). The MODIS-based, process-oriented approach couples photosynthesis, evaporation, two-leaf energy balance and nitrogen, which are different from the previous satellite-based approaches. We couple information from MODIS with flux towers to assess the drivers and parameters of GPP and ET. Incoming shortwave radiation components (direct and diffuse PAR, NIR) under all sky condition are modeled using a Monte-Carlo based atmospheric radiative transfer model. The MODIS Level 2 Atmospheric products are gridded and overlaid with MODIS Land products to produce spatially compatible forcing variables. GPP is modeled using a two-leaf model (sunlit and shaded leaf) and the maximum carboxylation rate is estimated using albedo-Nitrogen-leaf trait relations. The GPP is used to calculate canopy conductance via Ball-Berry model. Then, we apply Penman-Monteith equation to calculate evapotranspiration. The process-oriented approach allows us to investigate the main drivers of GPP and ET at global scale. Finally we explore the spatial and temporal variability of GPP and ET at global scale.

A new preprocessing parameter estimation based on geodesic active contour model for automatic vestibular neuritis diagnosis.

Science.gov (United States)

Ben Slama, Amine; Mouelhi, Aymen; Sahli, Hanene; Manoubi, Sondes; Mbarek, Chiraz; Trabelsi, Hedi; Fnaiech, Farhat; Sayadi, Mounir

2017-07-01

The diagnostic of the vestibular neuritis (VN) presents many difficulties to traditional assessment methods This paper deals with a fully automatic VN diagnostic system based on nystagmus parameter estimation using a pupil detection algorithm. A geodesic active contour model is implemented to find an accurate segmentation region of the pupil. Hence, the novelty of the proposed algorithm is to speed up the standard segmentation by using a specific mask located on the region of interest. This allows a drastically computing time reduction and a great performance and accuracy of the obtained results. After using this fast segmentation algorithm, the obtained estimated parameters are represented in temporal and frequency settings. A useful principal component analysis (PCA) selection procedure is then applied to obtain a reduced number of estimated parameters which are used to train a multi neural network (MNN). Experimental results on 90 eye movement videos show the effectiveness and the accuracy of the proposed estimation algorithm versus previous work. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of Above Ground Biomass Estimation Accuracy for Alpine Meadow Based on MODIS Vegetation Indices

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Meng Bao-Ping

2017-01-01

Full Text Available Animal husbandry is the main agricultural type over the Tibetan Plateau, above ground biomass (AGB is very important to monitor the productivity for administration of grassland resources and grazing balance. The MODIS vegetation indices have been successfully used in numerous studies on grassland AGB estimation in the Tibetan Plateau area. However, there are considerable differences of AGB estimation models both in the form of the models and the accuracy of estimation. In this study, field measurements of AGB data at Sangke Town, Gansu Province, China in four years (2013-2016 and MODIS indices (NDVI and EVI are combined to construct AGB estimation models of alpine meadow grassland. The field measured AGB are also used to evaluate feasibility of models developed for large scale in applying to small area. The results show that (1 the differences in biomass were relatively large among the 5 sample areas of alpine meadow grassland in the study area during 2013-2016, with the maximum and minimum biomass values of 3,963 kg DW/ha and 745.5 kg DW/ha, respectively, and mean value of 1,907.7 kg DW/ha; the mean of EVI value range (0.42-0.60 are slightly smaller than the NDVI’s (0.59-0.75; (2 the optimum estimation model of grassland AGB in the study area is the exponential model based on MODIS EVI, with root mean square error of 656.6 kg DW/ha and relative estimation errors (REE of 36.3%; (3 the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, the Gannan Prefecture, and Xiahe County are higher than those directly constructed based on the small area of this study by 9.5%–31.7%, with the increase of the modeling study area scales, the REE increasing as well. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing

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

Variable disparity-motion estimation based fast three-view video coding

Science.gov (United States)

Bae, Kyung-Hoon; Kim, Seung-Cheol; Hwang, Yong Seok; Kim, Eun-Soo

2009-02-01

In this paper, variable disparity-motion estimation (VDME) based 3-view video coding is proposed. In the encoding, key-frame coding (KFC) based motion estimation and variable disparity estimation (VDE) for effectively fast three-view video encoding are processed. These proposed algorithms enhance the performance of 3-D video encoding/decoding system in terms of accuracy of disparity estimation and computational overhead. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm's PSNRs is 37.66 and 40.55 dB, and the processing time is 0.139 and 0.124 sec/frame, respectively.

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

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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.

Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

Science.gov (United States)

Schur, Nadine; Hürlimann, Eveline; Garba, Amadou; Traoré, Mamadou S.; Ndir, Omar; Ratard, Raoult C.; Tchuem Tchuenté, Louis-Albert; Kristensen, Thomas K.; Utzinger, Jürg; Vounatsou, Penelope

2011-01-01

Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We

Estimation of Dynamic Friction Process of the Akatani Landslide Based on the Waveform Inversion and Numerical Simulation

Science.gov (United States)

Yamada, M.; Mangeney, A.; Moretti, L.; Matsushi, Y.

2014-12-01

Understanding physical parameters, such as frictional coefficients, velocity change, and dynamic history, is important issue for assessing and managing the risks posed by deep-seated catastrophic landslides. Previously, landslide motion has been inferred qualitatively from topographic changes caused by the event, and occasionally from eyewitness reports. However, these conventional approaches are unable to evaluate source processes and dynamic parameters. In this study, we use broadband seismic recordings to trace the dynamic process of the deep-seated Akatani landslide that occurred on the Kii Peninsula, Japan, which is one of the best recorded large slope failures. Based on the previous results of waveform inversions and precise topographic surveys done before and after the event, we applied numerical simulations using the SHALTOP numerical model (Mangeney et al., 2007). This model describes homogeneous continuous granular flows on a 3D topography based on a depth averaged thin layer approximation. We assume a Coulomb's friction law with a constant friction coefficient, i. e. the friction is independent of the sliding velocity. We varied the friction coefficients in the simulation so that the resulting force acting on the surface agrees with the single force estimated from the seismic waveform inversion. Figure shows the force history of the east-west components after the band-pass filtering between 10-100 seconds. The force history of the simulation with frictional coefficient 0.27 (thin red line) the best agrees with the result of seismic waveform inversion (thick gray line). Although the amplitude is slightly different, phases are coherent for the main three pulses. This is an evidence that the point-source approximation works reasonably well for this particular event. The friction coefficient during the sliding was estimated to be 0.38 based on the seismic waveform inversion performed by the previous study and on the sliding block model (Yamada et al., 2013

A comprehensive estimation of the economic effects of meteorological services based on the input-output method.

Science.gov (United States)

Wu, Xianhua; Wei, Guo; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

Science.gov (United States)

Wu, Xianhua; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian

2014-01-01

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries. PMID:24578666

Statistical inference for remote sensing-based estimates of net deforestation

Science.gov (United States)

Ronald E. McRoberts; Brian F. Walters

2012-01-01

Statistical inference requires expression of an estimate in probabilistic terms, usually in the form of a confidence interval. An approach to constructing confidence intervals for remote sensing-based estimates of net deforestation is illustrated. The approach is based on post-classification methods using two independent forest/non-forest classifications because...

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...

A fuel-based approach to estimating motor vehicle exhaust emissions

Science.gov (United States)

Singer, Brett Craig

Motor vehicles contribute significantly to air pollution problems; accurate motor vehicle emission inventories are therefore essential to air quality planning. Current travel-based inventory models use emission factors measured from potentially biased vehicle samples and predict fleet-average emissions which are often inconsistent with on-road measurements. This thesis presents a fuel-based inventory approach which uses emission factors derived from remote sensing or tunnel-based measurements of on-road vehicles. Vehicle activity is quantified by statewide monthly fuel sales data resolved to the air basin level. Development of the fuel-based approach includes (1) a method for estimating cold start emission factors, (2) an analysis showing that fuel-normalized emission factors are consistent over a range of positive vehicle loads and that most fuel use occurs during loaded-mode driving, (3) scaling factors relating infrared hydrocarbon measurements to total exhaust volatile organic compound (VOC) concentrations, and (4) an analysis showing that economic factors should be considered when selecting on-road sampling sites. The fuel-based approach was applied to estimate carbon monoxide (CO) emissions from warmed-up vehicles in the Los Angeles area in 1991, and CO and VOC exhaust emissions for Los Angeles in 1997. The fuel-based CO estimate for 1991 was higher by a factor of 2.3 +/- 0.5 than emissions predicted by California's MVEI 7F model. Fuel-based inventory estimates for 1997 were higher than those of California's updated MVEI 7G model by factors of 2.4 +/- 0.2 for CO and 3.5 +/- 0.6 for VOC. Fuel-based estimates indicate a 20% decrease in the mass of CO emitted, despite an 8% increase in fuel use between 1991 and 1997; official inventory models predict a 50% decrease in CO mass emissions during the same period. Cold start CO and VOC emission factors derived from parking garage measurements were lower than those predicted by the MVEI 7G model. Current inventories

48 CFR 2452.216-70 - Estimated cost, base fee and award fee.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Estimated cost, base fee... Provisions and Clauses 2452.216-70 Estimated cost, base fee and award fee. As prescribed in 2416.406(e)(1), insert the following clause in all cost-plus-award-fee contracts: Estimated Cost, Base Fee and Award Fee...

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)

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...

Head pose estimation algorithm based on deep learning

Science.gov (United States)

Cao, Yuanming; Liu, Yijun

2017-05-01

Head pose estimation has been widely used in the field of artificial intelligence, pattern recognition and intelligent human-computer interaction and so on. Good head pose estimation algorithm should deal with light, noise, identity, shelter and other factors robustly, but so far how to improve the accuracy and robustness of attitude estimation remains a major challenge in the field of computer vision. A method based on deep learning for pose estimation is presented. Deep learning with a strong learning ability, it can extract high-level image features of the input image by through a series of non-linear operation, then classifying the input image using the extracted feature. Such characteristics have greater differences in pose, while they are robust of light, identity, occlusion and other factors. The proposed head pose estimation is evaluated on the CAS-PEAL data set. Experimental results show that this method is effective to improve the accuracy of pose estimation.

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

Science.gov (United States)

Ahmed, Ammar; Tufail, Muhammad

2017-05-01

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

Numerosity estimation in visual stimuli in the absence of luminance-based cues.

Directory of Open Access Journals (Sweden)

Peter Kramer

2011-02-01

Full Text Available Numerosity estimation is a basic preverbal ability that humans share with many animal species and that is believed to be foundational of numeracy skills. It is notoriously difficult, however, to establish whether numerosity estimation is based on numerosity itself, or on one or more non-numerical cues like-in visual stimuli-spatial extent and density. Frequently, different non-numerical cues are held constant on different trials. This strategy, however, still allows numerosity estimation to be based on a combination of non-numerical cues rather than on any particular one by itself.Here we introduce a novel method, based on second-order (contrast-based visual motion, to create stimuli that exclude all first-order (luminance-based cues to numerosity. We show that numerosities can be estimated almost as well in second-order motion as in first-order motion.The results show that numerosity estimation need not be based on first-order spatial filtering, first-order density perception, or any other processing of luminance-based cues to numerosity. Our method can be used as an effective tool to control non-numerical variables in studies of numerosity estimation.

Efficacy of peg-interferon based treatment in patients with hepatitis C refractory to previous conventional interferon-based treatment

International Nuclear Information System (INIS)

Shaikh, S.; Devrajani, B.R.; Kalhoro, M.

2012-01-01

Objective: To determine the efficacy of peg-interferon-based therapy in patients refractory to previous conventional interferon-based treatment and factors predicting sustained viral response (SVR). Study Design: Analytical study. Place and Duration of Study: Medical Unit IV, Liaquat University Hospital, Jamshoro, from July 2009 to June 2011. Methodology: This study included consecutive patients of hepatitis C who were previously treated with conventional interferon-based treatment for 6 months but were either non-responders, relapsed or had virologic breakthrough and stage = 2 with fibrosis on liver biopsy. All eligible patients were provided peg-interferon at the dosage of 180 mu g weekly with ribavirin thrice a day for 6 months. Sustained Viral Response (SVR) was defined as absence of HCV RNA at twenty four week after treatment. All data was processed on SPSS version 16. Results: Out of 450 patients enrolled in the study, 192 were excluded from the study on the basis of minimal fibrosis (stage 0 and 1). Two hundred and fifty eight patients fulfilled the inclusion criteria and 247 completed the course of peg-interferon treatment. One hundred and sixty one (62.4%) were males and 97 (37.6%) were females. The mean age was 39.9 +- 6.1 years, haemoglobin was 11.49 +- 2.45 g/dl, platelet count was 127.2 +- 50.6 10/sup 3/ /mm/sup 3/, ALT was 99 +- 65 IU/L. SVR was achieved in 84 (32.6%). The strong association was found between SVR and the pattern of response (p = 0. 001), degree of fibrosis and early viral response (p = 0.001). Conclusion: Peg-interferon based treatment is an effective and safe treatment option for patients refractory to conventional interferon-based treatment. (author)

Parametric cost estimation for space science missions

Science.gov (United States)

Lillie, Charles F.; Thompson, Bruce E.

2008-07-01

Cost estimation for space science missions is critically important in budgeting for successful missions. The process requires consideration of a number of parameters, where many of the values are only known to a limited accuracy. The results of cost estimation are not perfect, but must be calculated and compared with the estimates that the government uses for budgeting purposes. Uncertainties in the input parameters result from evolving requirements for missions that are typically the "first of a kind" with "state-of-the-art" instruments and new spacecraft and payload technologies that make it difficult to base estimates on the cost histories of previous missions. Even the cost of heritage avionics is uncertain due to parts obsolescence and the resulting redesign work. Through experience and use of industry best practices developed in participation with the Aerospace Industries Association (AIA), Northrop Grumman has developed a parametric modeling approach that can provide a reasonably accurate cost range and most probable cost for future space missions. During the initial mission phases, the approach uses mass- and powerbased cost estimating relationships (CER)'s developed with historical data from previous missions. In later mission phases, when the mission requirements are better defined, these estimates are updated with vendor's bids and "bottoms- up", "grass-roots" material and labor cost estimates based on detailed schedules and assigned tasks. In this paper we describe how we develop our CER's for parametric cost estimation and how they can be applied to estimate the costs for future space science missions like those presented to the Astronomy & Astrophysics Decadal Survey Study Committees.

An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking

Directory of Open Access Journals (Sweden)

Sujay Saha

2016-01-01

Full Text Available Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382, Breast Cancer dataset (GSE349-350, Prostate Cancer dataset, and DLBCL-FL (Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.

Decay in blood loss estimation skills after web-based didactic training.

Science.gov (United States)

Toledo, Paloma; Eosakul, Stanley T; Goetz, Kristopher; Wong, Cynthia A; Grobman, William A

2012-02-01

Accuracy in blood loss estimation has been shown to improve immediately after didactic training. The objective of this study was to evaluate retention of blood loss estimation skills 9 months after a didactic web-based training. Forty-four participants were recruited from a cohort that had undergone web-based training and testing in blood loss estimation. The web-based posttraining test, consisting of pictures of simulated blood loss, was repeated 9 months after the initial training and testing. The primary outcome was the difference in accuracy of estimated blood loss (percent error) at 9 months compared with immediately posttraining. At the 9-month follow-up, the median error in estimation worsened to -34.6%. Although better than the pretraining error of -47.8% (P = 0.003), the 9-month error was significantly less accurate than the immediate posttraining error of -13.5% (P = 0.01). Decay in blood loss estimation skills occurs by 9 months after didactic training.

A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model

International Nuclear Information System (INIS)

Wei, Zhongbao; Zhao, Jiyun; Ji, Dongxu; Tseng, King Jet

2017-01-01

Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.

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

Science.gov (United States)

Shrivastava, Akash; Mohanty, A. R.

2018-03-01

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

Frequency Estimator Performance for a Software-Based Beacon Receiver

Science.gov (United States)

Zemba, Michael J.; Morse, Jacquelynne Rose; Nessel, James A.; Miranda, Felix

2014-01-01

As propagation terminals have evolved, their design has trended more toward a software-based approach that facilitates convenient adjustment and customization of the receiver algorithms. One potential improvement is the implementation of a frequency estimation algorithm, through which the primary frequency component of the received signal can be estimated with a much greater resolution than with a simple peak search of the FFT spectrum. To select an estimator for usage in a QV-band beacon receiver, analysis of six frequency estimators was conducted to characterize their effectiveness as they relate to beacon receiver design.

Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

Science.gov (United States)

Soheili, Mahmoud; (Tom) Rientjes, T. H. M.; (Christiaan) van der Tol, C.

2017-04-01

Groundwater movement is influenced by several factors and processes in the hydrological cycle, from which, recharge is of high relevance. Since the amount of aquifer extractable water directly relates to the recharge amount, estimation of recharge is a perquisite of groundwater resources management. Recharge is highly affected by water loss mechanisms the major of which is actual evapotranspiration (ETa). It is, therefore, essential to have detailed assessment of ETa impact on groundwater recharge. The objective of this study was to evaluate how recharge was affected when satellite-based evapotranspiration was used instead of in-situ based ETa in the Salland area, the Netherlands. The Methodology for Interactive Planning for Water Management (MIPWA) model setup which includes a groundwater model for the northern part of the Netherlands was used for recharge estimation. The Surface Energy Balance Algorithm for Land (SEBAL) based actual evapotranspiration maps from Waterschap Groot Salland were also used. Comparison of SEBAL based ETa estimates with in-situ abased estimates in the Netherlands showed that these SEBAL estimates were not reliable. As such results could not serve for calibrating root zone parameters in the CAPSIM model. The annual cumulative ETa map produced by the model showed that the maximum amount of evapotranspiration occurs in mixed forest areas in the northeast and a portion of central parts. Estimates ranged from 579 mm to a minimum of 0 mm in the highest elevated areas with woody vegetation in the southeast of the region. Variations in mean seasonal hydraulic head and groundwater level for each layer showed that the hydraulic gradient follows elevation in the Salland area from southeast (maximum) to northwest (minimum) of the region which depicts the groundwater flow direction. The mean seasonal water balance in CAPSIM part was evaluated to represent recharge estimation in the first layer. The highest recharge estimated flux was for autumn

State of charge estimation of lithium-ion batteries based on an improved parameter identification method

International Nuclear Information System (INIS)

Xia, Bizhong; Chen, Chaoren; Tian, Yong; Wang, Mingwang; Sun, Wei; Xu, Zhihui

2015-01-01

The SOC (state of charge) is the most important index of the battery management systems. However, it cannot be measured directly with sensors and must be estimated with mathematical techniques. An accurate battery model is crucial to exactly estimate the SOC. In order to improve the model accuracy, this paper presents an improved parameter identification method. Firstly, the concept of polarization depth is proposed based on the analysis of polarization characteristics of the lithium-ion batteries. Then, the nonlinear least square technique is applied to determine the model parameters according to data collected from pulsed discharge experiments. The results show that the proposed method can reduce the model error as compared with the conventional approach. Furthermore, a nonlinear observer presented in the previous work is utilized to verify the validity of the proposed parameter identification method in SOC estimation. Finally, experiments with different levels of discharge current are carried out to investigate the influence of polarization depth on SOC estimation. Experimental results show that the proposed method can improve the SOC estimation accuracy as compared with the conventional approach, especially under the conditions of large discharge current. - Highlights: • The polarization characteristics of lithium-ion batteries are analyzed. • The concept of polarization depth is proposed to improve model accuracy. • A nonlinear least square technique is applied to determine the model parameters. • A nonlinear observer is used as the SOC estimation algorithm. • The validity of the proposed method is verified by experimental results.

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.

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling

Science.gov (United States)

Gagnon, Pieter; Margolis, Robert; Melius, Jennifer; Phillips, Caleb; Elmore, Ryan

2018-02-01

We provide a detailed estimate of the technical potential of rooftop solar photovoltaic (PV) electricity generation throughout the contiguous United States. This national estimate is based on an analysis of select US cities that combines light detection and ranging (lidar) data with a validated analytical method for determining rooftop PV suitability employing geographic information systems. We use statistical models to extend this analysis to estimate the quantity and characteristics of roofs in areas not covered by lidar data. Finally, we model PV generation for all rooftops to yield technical potential estimates. At the national level, 8.13 billion m2 of suitable roof area could host 1118 GW of PV capacity, generating 1432 TWh of electricity per year. This would equate to 38.6% of the electricity that was sold in the contiguous United States in 2013. This estimate is substantially higher than a previous estimate made by the National Renewable Energy Laboratory. The difference can be attributed to increases in PV module power density, improved estimation of building suitability, higher estimates of total number of buildings, and improvements in PV performance simulation tools that previously tended to underestimate productivity. Also notable, the nationwide percentage of buildings suitable for at least some PV deployment is high—82% for buildings smaller than 5000 ft2 and over 99% for buildings larger than that. In most states, rooftop PV could enable small, mostly residential buildings to offset the majority of average household electricity consumption. Even in some states with a relatively poor solar resource, such as those in the Northeast, the residential sector has the potential to offset around 100% of its total electricity consumption with rooftop PV.

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...

Estimating Risks and Relative Risks in Case-Base Studies under the Assumptions of Gene-Environment Independence and Hardy-Weinberg Equilibrium

Science.gov (United States)

Chui, Tina Tsz-Ting; Lee, Wen-Chung

2014-01-01

Many diseases result from the interactions between genes and the environment. An efficient method has been proposed for a case-control study to estimate the genetic and environmental main effects and their interactions, which exploits the assumptions of gene-environment independence and Hardy-Weinberg equilibrium. To estimate the absolute and relative risks, one needs to resort to an alternative design: the case-base study. In this paper, the authors show how to analyze a case-base study under the above dual assumptions. This approach is based on a conditional logistic regression of case-counterfactual controls matched data. It can be easily fitted with readily available statistical packages. When the dual assumptions are met, the method is approximately unbiased and has adequate coverage probabilities for confidence intervals. It also results in smaller variances and shorter confidence intervals as compared with a previous method for a case-base study which imposes neither assumption. PMID:25137392

Estimating risks and relative risks in case-base studies under the assumptions of gene-environment independence and Hardy-Weinberg equilibrium.

Directory of Open Access Journals (Sweden)

Tina Tsz-Ting Chui

Full Text Available Many diseases result from the interactions between genes and the environment. An efficient method has been proposed for a case-control study to estimate the genetic and environmental main effects and their interactions, which exploits the assumptions of gene-environment independence and Hardy-Weinberg equilibrium. To estimate the absolute and relative risks, one needs to resort to an alternative design: the case-base study. In this paper, the authors show how to analyze a case-base study under the above dual assumptions. This approach is based on a conditional logistic regression of case-counterfactual controls matched data. It can be easily fitted with readily available statistical packages. When the dual assumptions are met, the method is approximately unbiased and has adequate coverage probabilities for confidence intervals. It also results in smaller variances and shorter confidence intervals as compared with a previous method for a case-base study which imposes neither assumption.

Automated mode shape estimation in agent-based wireless sensor networks

Science.gov (United States)

Zimmerman, Andrew T.; Lynch, Jerome P.

2010-04-01

Recent advances in wireless sensing technology have made it possible to deploy dense networks of sensing transducers within large structural systems. Because these networks leverage the embedded computing power and agent-based abilities integral to many wireless sensing devices, it is possible to analyze sensor data autonomously and in-network. In this study, market-based techniques are used to autonomously estimate mode shapes within a network of agent-based wireless sensors. Specifically, recent work in both decentralized Frequency Domain Decomposition and market-based resource allocation is leveraged to create a mode shape estimation algorithm derived from free-market principles. This algorithm allows an agent-based wireless sensor network to autonomously shift emphasis between improving mode shape accuracy and limiting the consumption of certain scarce network resources: processing time, storage capacity, and power consumption. The developed algorithm is validated by successfully estimating mode shapes using a network of wireless sensor prototypes deployed on the mezzanine balcony of Hill Auditorium, located on the University of Michigan campus.

DOA and Pitch Estimation of Audio Sources using IAA-based Filtering

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll

2014-01-01

For decades, it has been investigated how to separately solve the problems of both direction-of-arrival (DOA) and pitch estimation. Recently, it was found that estimating these parameters jointly from multichannel recordings of audio can be extremely beneficial. Many joint estimators are based...... on knowledge of the inverse sample covariance matrix. Typically, this covariance is estimated using the sample covariance matrix, but for this estimate to be full rank, many temporal samples are needed. In cases with non-stationary signals, this is a serious limitation. We therefore investigate how a recent...... joint DOA and pitch filtering-based estimator can be combined with the iterative adaptive approach to circumvent this limitation in joint DOA and pitch estimation of audio sources. Simulations show a clear improvement compared to when using the sample covariance matrix and the considered approach also...

Robust Diagnosis Method Based on Parameter Estimation for an Interturn Short-Circuit Fault in Multipole PMSM under High-Speed Operation.

Science.gov (United States)

Lee, Jewon; Moon, Seokbae; Jeong, Hyeyun; Kim, Sang Woo

2015-11-20

This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates the q-axis inductance (Lq) of the faulty PMSM to solve this problem. The proposed method also estimates the faulty phase and the value of G, which serves as an index of the severity of the fault. The q-axis current is used to estimate the faulty phase, the values of G and Lq. For this reason, two open-loop observers and an optimization method based on a particle-swarm are implemented. The q-axis current of a healthy PMSM is estimated by the open-loop observer with the parameters of a healthy PMSM. The Lq estimation significantly compensates for the estimation errors in high-speed operation. The experimental results demonstrate that the proposed method can estimate the faulty phase, G, and Lq besides exhibiting robustness against parameter uncertainties.

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.

Increasing precision of turbidity-based suspended sediment concentration and load estimates.

Science.gov (United States)

Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

2010-01-01

Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.

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

Directory of Open Access Journals (Sweden)

Elizabeth Thomson

2013-12-01

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

Experimental Verification of a Vehicle Localization based on Moving Horizon Estimation Integrating LRS and Odometry

International Nuclear Information System (INIS)

Sakaeta, Kuniyuki; Nonaka, Kenichiro; Sekiguchi, Kazuma

2016-01-01

Localization is an important function for the robots to complete various tasks. For localization, both internal and external sensors are used generally. The odometry is widely used as the method based on the internal sensors, but it suffers from cumulative errors. In the method using the laser range sensor (LRS) which is a kind of external sensor, the estimation accuracy is affected by the number of available measurement data. In our previous study, we applied moving horizon estimation (MHE) to the vehicle localization for integrating the LRS measurement data and the odometry information where the weightings of them are balanced relatively adapting to the number of the available LRS measurement data. In this paper, the effectiveness of the proposed localization method is verified through both numerical simulations and experiments using a 1/10 scale vehicle. The verification is conducted in the situations where the vehicle position cannot be localized uniquely on a certain direction using the LRS measurement data only. We achieve accurate localization even in such a situation by integrating the odometry and LRS based on MHE. We also show the superiority of the method through comparisons with a method using extended Kalman filter (EKF). (paper)

Affordance estimation for vision-based object replacement on a humanoid robot

DEFF Research Database (Denmark)

Mustafa, Wail; Wächter, Mirko; Szedmak, Sandor

2016-01-01

In this paper, we address the problem of finding replacements of missing objects, involved in the execution of manipulation tasks. Our approach is based on estimating functional affordances for the unknown objects in order to propose replacements. We use a vision-based affordance estimation syste...

Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

Science.gov (United States)

Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

2018-06-01

Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

Science.gov (United States)

Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

2018-03-01

Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

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.

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...

A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

Directory of Open Access Journals (Sweden)

Xianhua Wu

2014-01-01

Full Text Available Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51. Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.

An integrated approach to estimate storage reliability with initial failures based on E-Bayesian estimates

International Nuclear Information System (INIS)

Zhang, Yongjin; Zhao, Ming; Zhang, Shitao; Wang, Jiamei; Zhang, Yanjun

2017-01-01

Storage reliability that measures the ability of products in a dormant state to keep their required functions is studied in this paper. For certain types of products, Storage reliability may not always be 100% at the beginning of storage, unlike the operational reliability, which exist possible initial failures that are normally neglected in the models of storage reliability. In this paper, a new integrated technique, the non-parametric measure based on the E-Bayesian estimates of current failure probabilities is combined with the parametric measure based on the exponential reliability function, is proposed to estimate and predict the storage reliability of products with possible initial failures, where the non-parametric method is used to estimate the number of failed products and the reliability at each testing time, and the parameter method is used to estimate the initial reliability and the failure rate of storage product. The proposed method has taken into consideration that, the reliability test data of storage products containing the unexamined before and during the storage process, is available for providing more accurate estimates of both the initial failure probability and the storage failure probability. When storage reliability prediction that is the main concern in this field should be made, the non-parametric estimates of failure numbers can be used into the parametric models for the failure process in storage. In the case of exponential models, the assessment and prediction method for storage reliability is presented in this paper. Finally, a numerical example is given to illustrate the method. Furthermore, a detailed comparison between the proposed and traditional method, for examining the rationality of assessment and prediction on the storage reliability, is investigated. The results should be useful for planning a storage environment, decision-making concerning the maximum length of storage, and identifying the production quality. - Highlights: �

Frequency domain based LS channel estimation in OFDM based Power line communications

OpenAIRE

Bogdanović, Mario

2015-01-01

This paper is focused on low voltage power line communication (PLC) realization with an emphasis on channel estimation techniques. The Orthogonal Frequency Division Multiplexing (OFDM) scheme is preferred technology in PLC systems because of its effective combat with frequency selective fading properties of PLC channel. As the channel estimation is one of the crucial problems in OFDM based PLC system because of a problematic area of PLC signal attenuation and interference, the improved LS est...

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

Science.gov (United States)

Lubey, D.; Scheeres, D.

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

A novel flux estimator based on SOGI with FLL for induction machine drives

DEFF Research Database (Denmark)

Zhao, Rende; Xin, Zhen; Loh, Poh Chiang

2016-01-01

by the initial conditions with no need for the magnitude and phase compensation. Because the dc and harmonic components are inversely proportional to the speed in the estimated flux, the performance of the single SOGI-based estimator become worse at low speed. A multiple SOGI-based flux estimator is the proposed......It is very important to estimate flux accurately in implementing high-performance control of AC motors. Theoretical analysis has been made to illustrate the performance of the pure-integration-based and the Low-Pass Filter (LPF) based flux estimators. A novel flux estimator based on Second......-Order General Integrator (SOGI) with Frequency Locked-Loop (FLL) is investigated in this paper for induction machine drives. A single SOGI instead of pure integrator or LPF is used to integrate the back electromotive force (EMF). It can solve the problems of the integration saturation and the dc drift caused...

Predicting the required number of training samples. [for remotely sensed image data based on covariance matrix estimate quality criterion of normal distribution

Science.gov (United States)

Kalayeh, H. M.; Landgrebe, D. A.

1983-01-01

A criterion which measures the quality of the estimate of the covariance matrix of a multivariate normal distribution is developed. Based on this criterion, the necessary number of training samples is predicted. Experimental results which are used as a guide for determining the number of training samples are included. Previously announced in STAR as N82-28109

Phase difference estimation method based on data extension and Hilbert transform

International Nuclear Information System (INIS)

Shen, Yan-lin; Tu, Ya-qing; Chen, Lin-jun; Shen, Ting-ao

2015-01-01

To improve the precision and anti-interference performance of phase difference estimation for non-integer periods of sampling signals, a phase difference estimation method based on data extension and Hilbert transform is proposed. Estimated phase difference is obtained by means of data extension, Hilbert transform, cross-correlation, auto-correlation, and weighted phase average. Theoretical analysis shows that the proposed method suppresses the end effects of Hilbert transform effectively. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of phase difference estimation and has better performance of phase difference estimation than the correlation, Hilbert transform, and data extension-based correlation methods, which contribute to improving the measurement precision of the Coriolis mass flowmeter. (paper)

Prevalence of pain in the head, back and feet in refugees previously exposed to torture: a ten-year follow-up study

DEFF Research Database (Denmark)

Olsen, Dorthe Reff; Montgomery, Edith; Bøjholm, Søren

2007-01-01

AIM: To estimate change over 10 years concerning the prevalence of pain in the head, back and feet, among previously tortured refugees settled in Denmark, and to compare associations between methods of torture and prevalent pain at baseline and at 10-year follow-up. METHODS: 139 refugees previous...... associated with the type and bodily focus of the torture. This presents a considerable challenge to future evidence-based development of effective treatment programs....

A Simulation-Based Soft Error Estimation Methodology for Computer Systems

OpenAIRE

Sugihara, Makoto; Ishihara, Tohru; Hashimoto, Koji; Muroyama, Masanori

2006-01-01

This paper proposes a simulation-based soft error estimation methodology for computer systems. Accumulating soft error rates (SERs) of all memories in a computer system results in pessimistic soft error estimation. This is because memory cells are used spatially and temporally and not all soft errors in them make the computer system faulty. Our soft-error estimation methodology considers the locations and the timings of soft errors occurring at every level of memory hierarchy and estimates th...

Population-based absolute risk estimation with survey data

Science.gov (United States)

Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

2013-01-01

Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614

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.

Estimating Soil Hydraulic Parameters using Gradient Based Approach

Science.gov (United States)

Rai, P. K.; Tripathi, S.

2017-12-01

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

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...

Channel estimation in DFT-based offset-QAM OFDM systems.

Science.gov (United States)

Zhao, Jian

2014-10-20

Offset quadrature amplitude modulation (offset-QAM) orthogonal frequency division multiplexing (OFDM) exhibits enhanced net data rates compared to conventional OFDM, and reduced complexity compared to Nyquist FDM (N-FDM). However, channel estimation in discrete-Fourier-transform (DFT) based offset-QAM OFDM is different from that in conventional OFDM and requires particular study. In this paper, we derive a closed-form expression for the demultiplexed signal in DFT-based offset-QAM systems and show that although the residual crosstalk is orthogonal to the decoded signal, its existence degrades the channel estimation performance when the conventional least-square method is applied. We propose and investigate four channel estimation algorithms for offset-QAM OFDM that vary in terms of performance, complexity, and tolerance to system parameters. It is theoretically and experimentally shown that simple channel estimation can be realized in offset-QAM OFDM with the achieved performance close to the theoretical limit. This, together with the existing advantages over conventional OFDM and N-FDM, makes this technology very promising for optical communication systems.

Event-based state estimation a stochastic perspective

CERN Document Server

Shi, Dawei; Chen, Tongwen

2016-01-01

This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs ...

Improving The Accuracy Of Bluetooth Based Travel Time Estimation Using Low-Level Sensor Data

DEFF Research Database (Denmark)

Araghi, Bahar Namaki; Tørholm Christensen, Lars; Krishnan, Rajesh

2013-01-01

triggered by a single device. This could lead to location ambiguity and reduced accuracy of travel time estimation. Therefore, the accuracy of travel time estimations by Bluetooth Technology (BT) depends upon how location ambiguity is handled by the estimation method. The issue of multiple detection events...... in the context of travel time estimation by BT has been considered by various researchers. However, treatment of this issue has remained simplistic so far. Most previous studies simply used the first detection event (Enter-Enter) as the best estimate. No systematic analysis for exploring the most accurate method...... of estimating travel time using multiple detection events has been conducted. In this study different aspects of BT detection zone, including size and its impact on the accuracy of travel time estimation, are discussed. Moreover, four alternative methods are applied; namely, Enter-Enter, Leave-Leave, Peak...

Correlation between the model accuracy and model-based SOC estimation

International Nuclear Information System (INIS)

Wang, Qianqian; Wang, Jiao; Zhao, Pengju; Kang, Jianqiang; Yan, Few; Du, Changqing

2017-01-01

State-of-charge (SOC) estimation is a core technology for battery management systems. Considerable progress has been achieved in the study of SOC estimation algorithms, especially the algorithm on the basis of Kalman filter to meet the increasing demand of model-based battery management systems. The Kalman filter weakens the influence of white noise and initial error during SOC estimation but cannot eliminate the existing error of the battery model itself. As such, the accuracy of SOC estimation is directly related to the accuracy of the battery model. Thus far, the quantitative relationship between model accuracy and model-based SOC estimation remains unknown. This study summarizes three equivalent circuit lithium-ion battery models, namely, Thevenin, PNGV, and DP models. The model parameters are identified through hybrid pulse power characterization test. The three models are evaluated, and SOC estimation conducted by EKF-Ah method under three operating conditions are quantitatively studied. The regression and correlation of the standard deviation and normalized RMSE are studied and compared between the model error and the SOC estimation error. These parameters exhibit a strong linear relationship. Results indicate that the model accuracy affects the SOC estimation accuracy mainly in two ways: dispersion of the frequency distribution of the error and the overall level of the error. On the basis of the relationship between model error and SOC estimation error, our study provides a strategy for selecting a suitable cell model to meet the requirements of SOC precision using Kalman filter.

Temporal validation for landsat-based volume estimation model

Science.gov (United States)

Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan

2015-01-01

Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

Real-time estimation of FLE for point-based registration

Science.gov (United States)

Wiles, Andrew D.; Peters, Terry M.

2009-02-01

In image-guide surgery, optimizing the accuracy in localizing the surgical tools within the virtual reality environment or 3D image is vitally important, significant effort has been spent reducing the measurement errors at the point of interest or target. This target registration error (TRE) is often defined by a root-mean-square statistic which reduces the vector data to a single term that can be minimized. However, lost in the data reduction is the directionality of the error which, can be modelled using a 3D covariance matrix. Recently, we developed a set of expressions that modeled the TRE statistics for point-based registrations as a function of the fiducial marker geometry, target location and the fiducial localizer error (FLE). Unfortunately, these expressions are only as good as the definition of the FLE. In order to close the gap, we have subsequently developed a closed form expression that estimates the FLE as a function of the estimated fiducial registration error (FRE, the error between the measured fiducials and the best fit locations of those fiducials). The FRE covariance matrix is estimated using a sliding window technique and used as input into the closed form expression to estimate the FLE. The estimated FLE can then used to estimate the TRE which, can be given to the surgeon to permit the procedure to be designed such that the errors associated with the point-based registrations are minimized.

Effectiveness of Ritonavir-Boosted Protease Inhibitor Monotherapy in Clinical Practice Even with Previous Virological Failures to Protease Inhibitor-Based Regimens.

Directory of Open Access Journals (Sweden)

Luis F López-Cortés

Full Text Available Significant controversy still exists about ritonavir-boosted protease inhibitor monotherapy (mtPI/rtv as a simplification strategy that is used up to now to treat patients that have not experienced previous virological failure (VF while on protease inhibitor (PI -based regimens. We have evaluated the effectiveness of two mtPI/rtv regimens in an actual clinical practice setting, including patients that had experienced previous VF with PI-based regimens.This retrospective study analyzed 1060 HIV-infected patients with undetectable viremia that were switched to lopinavir/ritonavir or darunavir/ritonavir monotherapy. In cases in which the patient had previously experienced VF while on a PI-based regimen, the lack of major HIV protease resistance mutations to lopinavir or darunavir, respectively, was mandatory. The primary endpoint of this study was the percentage of participants with virological suppression after 96 weeks according to intention-to-treat analysis (non-complete/missing = failure.A total of 1060 patients were analyzed, including 205 with previous VF while on PI-based regimens, 90 of whom were on complex therapies due to extensive resistance. The rates of treatment effectiveness (intention-to-treat analysis and virological efficacy (on-treatment analysis at week 96 were 79.3% (CI95, 76.8-81.8 and 91.5% (CI95, 89.6-93.4, respectively. No relationships were found between VF and earlier VF while on PI-based regimens, the presence of major or minor protease resistance mutations, the previous time on viral suppression, CD4+ T-cell nadir, and HCV-coinfection. Genotypic resistance tests were available in 49 out of the 74 patients with VFs and only four patients presented new major protease resistance mutations.Switching to mtPI/rtv achieves sustained virological control in most patients, even in those with previous VF on PI-based regimens as long as no major resistance mutations are present for the administered drug.

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...

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.

M-Arctan estimator based on the trust-region method

Energy Technology Data Exchange (ETDEWEB)

Hassaine, Yacine; Delourme, Benoit; Panciatici, Patrick [Gestionnaire du Reseau de Transport d Electricite Departement Methodes et appui Immeuble Le Colbert 9, Versailles Cedex (France); Walter, Eric [Laboratoire des signaux et systemes (L2S) Supelec, Gif-sur-Yvette (France)

2006-11-15

In this paper a new approach is proposed to increase the robustness of the classical L{sub 2}-norm state estimation. To achieve this task a new formulation of the Levemberg-Marquardt algorithm based on the trust-region method is applied to a new M-estimator, which we called M-Arctan. Results obtained on IEEE networks up to 300 buses are presented. (author)

Bayesian and maximum likelihood estimation of genetic maps

DEFF Research Database (Denmark)

York, Thomas L.; Durrett, Richard T.; Tanksley, Steven

2005-01-01

There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods...... of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances....

Estimation of potential uranium resources

International Nuclear Information System (INIS)

Curry, D.L.

1977-09-01

Potential estimates, like reserves, are limited by the information on hand at the time and are not intended to indicate the ultimate resources. Potential estimates are based on geologic judgement, so their reliability is dependent on the quality and extent of geologic knowledge. Reliability differs for each of the three potential resource classes. It is greatest for probable potential resources because of the greater knowledge base resulting from the advanced stage of exploration and development in established producing districts where most of the resources in this class are located. Reliability is least for speculative potential resources because no significant deposits are known, and favorability is inferred from limited geologic data. Estimates of potential resources are revised as new geologic concepts are postulated, as new types of uranium ore bodies are discovered, and as improved geophysical and geochemical techniques are developed and applied. Advances in technology that permit the exploitation of deep or low-grade deposits, or the processing of ores of previously uneconomic metallurgical types, also will affect the estimates

Estimation of Muscle Force Based on Neural Drive in a Hemispheric Stroke Survivor.

Science.gov (United States)

Dai, Chenyun; Zheng, Yang; Hu, Xiaogang

2018-01-01

Robotic assistant-based therapy holds great promise to improve the functional recovery of stroke survivors. Numerous neural-machine interface techniques have been used to decode the intended movement to control robotic systems for rehabilitation therapies. In this case report, we tested the feasibility of estimating finger extensor muscle forces of a stroke survivor, based on the decoded descending neural drive through population motoneuron discharge timings. Motoneuron discharge events were obtained by decomposing high-density surface electromyogram (sEMG) signals of the finger extensor muscle. The neural drive was extracted from the normalized frequency of the composite discharge of the motoneuron pool. The neural-drive-based estimation was also compared with the classic myoelectric-based estimation. Our results showed that the neural-drive-based approach can better predict the force output, quantified by lower estimation errors and higher correlations with the muscle force, compared with the myoelectric-based estimation. Our findings suggest that the neural-drive-based approach can potentially be used as a more robust interface signal for robotic therapies during the stroke rehabilitation.

Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Science.gov (United States)

These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

A numerical integration-based yield estimation method for integrated circuits

International Nuclear Information System (INIS)

Liang Tao; Jia Xinzhang

2011-01-01

A novel integration-based yield estimation method is developed for yield optimization of integrated circuits. This method tries to integrate the joint probability density function on the acceptability region directly. To achieve this goal, the simulated performance data of unknown distribution should be converted to follow a multivariate normal distribution by using Box-Cox transformation (BCT). In order to reduce the estimation variances of the model parameters of the density function, orthogonal array-based modified Latin hypercube sampling (OA-MLHS) is presented to generate samples in the disturbance space during simulations. The principle of variance reduction of model parameters estimation through OA-MLHS together with BCT is also discussed. Two yield estimation examples, a fourth-order OTA-C filter and a three-dimensional (3D) quadratic function are used for comparison of our method with Monte Carlo based methods including Latin hypercube sampling and importance sampling under several combinations of sample sizes and yield values. Extensive simulations show that our method is superior to other methods with respect to accuracy and efficiency under all of the given cases. Therefore, our method is more suitable for parametric yield optimization. (semiconductor integrated circuits)

A numerical integration-based yield estimation method for integrated circuits

Energy Technology Data Exchange (ETDEWEB)

Liang Tao; Jia Xinzhang, E-mail: tliang@yahoo.cn [Key Laboratory of Ministry of Education for Wide Bandgap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi' an 710071 (China)

2011-04-15

A novel integration-based yield estimation method is developed for yield optimization of integrated circuits. This method tries to integrate the joint probability density function on the acceptability region directly. To achieve this goal, the simulated performance data of unknown distribution should be converted to follow a multivariate normal distribution by using Box-Cox transformation (BCT). In order to reduce the estimation variances of the model parameters of the density function, orthogonal array-based modified Latin hypercube sampling (OA-MLHS) is presented to generate samples in the disturbance space during simulations. The principle of variance reduction of model parameters estimation through OA-MLHS together with BCT is also discussed. Two yield estimation examples, a fourth-order OTA-C filter and a three-dimensional (3D) quadratic function are used for comparison of our method with Monte Carlo based methods including Latin hypercube sampling and importance sampling under several combinations of sample sizes and yield values. Extensive simulations show that our method is superior to other methods with respect to accuracy and efficiency under all of the given cases. Therefore, our method is more suitable for parametric yield optimization. (semiconductor integrated circuits)

Estimating security betas using prior information based on firm fundamentals

NARCIS (Netherlands)

Cosemans, M.; Frehen, R.; Schotman, P.C.; Bauer, R.

2010-01-01

This paper proposes a novel approach for estimating time-varying betas of individual stocks that incorporates prior information based on fundamentals. We shrink the rolling window estimate of beta towards a firm-specific prior that is motivated by asset pricing theory. The prior captures structural

Response-based estimation of sea state parameters - Influence of filtering

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam

2007-01-01

Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The wave spectrum can be estimated from procedures based on measured ship responses. The paper deals with two procedures—Bayesian Modelling and Parametric Modelling...

Bayesian estimation of the discrete coefficient of determination.

Science.gov (United States)

Chen, Ting; Braga-Neto, Ulisses M

2016-12-01

The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.

Object Detection and Tracking-Based Camera Calibration for Normalized Human Height Estimation

Directory of Open Access Journals (Sweden)

Jaehoon Jung

2016-01-01

Full Text Available This paper presents a normalized human height estimation algorithm using an uncalibrated camera. To estimate the normalized human height, the proposed algorithm detects a moving object and performs tracking-based automatic camera calibration. The proposed method consists of three steps: (i moving human detection and tracking, (ii automatic camera calibration, and (iii human height estimation and error correction. The proposed method automatically calibrates camera by detecting moving humans and estimates the human height using error correction. The proposed method can be applied to object-based video surveillance systems and digital forensic.

Non-Destructive, Laser-Based Individual Tree Aboveground Biomass Estimation in a Tropical Rainforest

Directory of Open Access Journals (Sweden)

Muhammad Zulkarnain Abd Rahman

2017-03-01

Full Text Available Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been driven by advances in remote sensing technology. The conventional approach to biomass estimation heavily relies on the tree species and site-specific allometric equations, which are based on destructive methods. This paper introduces a non-destructive, laser-based approach (terrestrial laser scanner for individual tree aboveground biomass estimation in the Royal Belum forest reserve, Perak, Malaysia. The study area is in the state park, and it is believed to be one of the oldest rainforests in the world. The point clouds generated for 35 forest plots, using the terrestrial laser scanner, were geo-rectified and cleaned to produce separate point clouds for individual trees. The volumes of tree trunks were estimated based on a cylinder model fitted to the point clouds. The biomasses of tree trunks were calculated by multiplying the volume and the species wood density. The biomasses of branches and leaves were also estimated based on the estimated volume and density values. Branch and leaf volumes were estimated based on the fitted point clouds using an alpha-shape approach. The estimated individual biomass and the total above ground biomass were compared with the aboveground biomass (AGB value estimated using existing allometric equations and individual tree census data collected in the field. The results show that the combination of a simple single-tree stem reconstruction and wood density can be used to estimate stem biomass comparable to the results usually obtained through existing allometric equations. However, there are several issues associated with the data and method used for branch and leaf biomass estimations, which need further improvement.

A Novel Rules Based Approach for Estimating Software Birthmark

Science.gov (United States)

Binti Alias, Norma; Anwar, Sajid

2015-01-01

Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363

Magma viscosity estimation based on analysis of erupted products. Potential assessment for large-scale pyroclastic eruptions

International Nuclear Information System (INIS)

Takeuchi, Shingo

2010-01-01

After the formulation of guidelines for volcanic hazards in site evaluation for nuclear installations (e.g. JEAG4625-2009), it is required to establish appropriate methods to assess potential of large-scale pyroclastic eruptions at long-dormant volcanoes, which is one of the most hazardous volcanic phenomena on the safety of the installations. In considering the volcanic dormancy, magma eruptability is an important concept. The magma eruptability is dominantly controlled by magma viscosity, which can be estimated from petrological analysis of erupted materials. Therefore, viscosity estimation of magmas erupted in past eruptions should provide important information to assess future activities at hazardous volcanoes. In order to show the importance of magma viscosity in the concept of magma eruptability, this report overviews dike propagation processes from a magma chamber and nature of magma viscosity. Magma viscosity at pre-eruptive conditions of magma chambers were compiled based on previous petrological studies on past eruptions in Japan. There are only 16 examples of eruptions at 9 volcanoes satisfying data requirement for magma viscosity estimation. Estimated magma viscosities range from 10 2 to 10 7 Pa·s for basaltic to rhyolitic magmas. Most of examples fall below dike propagation limit of magma viscosity (ca. 10 6 Pa·s) estimated based on a dike propagation model. Highly viscous magmas (ca. 10 7 Pa·s) than the dike propagation limit are considered to lose eruptability which is the ability to form dikes and initiate eruptions. However, in some cases, small precursory eruptions of less viscous magmas commonly occurred just before climactic eruptions of the highly viscous magmas, suggesting that the precursory dike propagation by the less viscous magmas induced the following eruptions of highly viscous magmas (ca. 10 7 Pa·s). (author)

The application of mean field theory to image motion estimation.

Science.gov (United States)

Zhang, J; Hanauer, G G

1995-01-01

Previously, Markov random field (MRF) model-based techniques have been proposed for image motion estimation. Since motion estimation is usually an ill-posed problem, various constraints are needed to obtain a unique and stable solution. The main advantage of the MRF approach is its capacity to incorporate such constraints, for instance, motion continuity within an object and motion discontinuity at the boundaries between objects. In the MRF approach, motion estimation is often formulated as an optimization problem, and two frequently used optimization methods are simulated annealing (SA) and iterative-conditional mode (ICM). Although the SA is theoretically optimal in the sense of finding the global optimum, it usually takes many iterations to converge. The ICM, on the other hand, converges quickly, but its results are often unsatisfactory due to its "hard decision" nature. Previously, the authors have applied the mean field theory to image segmentation and image restoration problems. It provides results nearly as good as SA but with much faster convergence. The present paper shows how the mean field theory can be applied to MRF model-based motion estimation. This approach is demonstrated on both synthetic and real-world images, where it produced good motion estimates.

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

Science.gov (United States)

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.

Age estimation based on aspartic acid racemization in human sclera.

Science.gov (United States)

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.

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...

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

Science.gov (United States)

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

2018-04-01

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

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

International Nuclear Information System (INIS)

Ruan, Dan

2010-01-01

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

A model-based approach to estimating forest area

Science.gov (United States)

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...

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.

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

Science.gov (United States)

Simon, Donald L.; Garg, Sanjay

2011-01-01

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation

An empirical comparison of isolate-based and sample-based definitions of antimicrobial resistance and their effect on estimates of prevalence.

Science.gov (United States)

Humphry, R W; Evans, J; Webster, C; Tongue, S C; Innocent, G T; Gunn, G J

2018-02-01

Antimicrobial resistance is primarily a problem in human medicine but there are unquantified links of transmission in both directions between animal and human populations. Quantitative assessment of the costs and benefits of reduced antimicrobial usage in livestock requires robust quantification of transmission of resistance between animals, the environment and the human population. This in turn requires appropriate measurement of resistance. To tackle this we selected two different methods for determining whether a sample is resistant - one based on screening a sample, the other on testing individual isolates. Our overall objective was to explore the differences arising from choice of measurement. A literature search demonstrated the widespread use of testing of individual isolates. The first aim of this study was to compare, quantitatively, sample level and isolate level screening. Cattle or sheep faecal samples (n=41) submitted for routine parasitology were tested for antimicrobial resistance in two ways: (1) "streak" direct culture onto plates containing the antimicrobial of interest; (2) determination of minimum inhibitory concentration (MIC) of 8-10 isolates per sample compared to published MIC thresholds. Two antibiotics (ampicillin and nalidixic acid) were tested. With ampicillin, direct culture resulted in more than double the number of resistant samples than the MIC method based on eight individual isolates. The second aim of this study was to demonstrate the utility of the observed relationship between these two measures of antimicrobial resistance to re-estimate the prevalence of antimicrobial resistance from a previous study, in which we had used "streak" cultures. Boot-strap methods were used to estimate the proportion of samples that would have tested resistant in the historic study, had we used the isolate-based MIC method instead. Our boot-strap results indicate that our estimates of prevalence of antimicrobial resistance would have been

A Gossip-based Churn Estimator for Large Dynamic Networks

NARCIS (Netherlands)

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

Assessing Error Correlations in Remote Sensing-Based Estimates of Forest Attributes for Improved Composite Estimation

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.

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

Science.gov (United States)

Bolen, Steve; Chandrasekar, V.

2002-01-01

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

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

Science.gov (United States)

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

2008-01-01

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

Design of Virtual Crank Angle Sensor based on Torque Estimation

OpenAIRE

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 ...

Optical Enhancement of Exoskeleton-Based Estimation of Glenohumeral Angles

Science.gov (United States)

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

Estimating correlation and covariance matrices by weighting of market similarity

OpenAIRE

Michael C. M\\"unnix; Rudi Sch\\"afer; Oliver Grothe

2010-01-01

We discuss a weighted estimation of correlation and covariance matrices from historical financial data. To this end, we introduce a weighting scheme that accounts for similarity of previous market conditions to the present one. The resulting estimators are less biased and show lower variance than either unweighted or exponentially weighted estimators. The weighting scheme is based on a similarity measure which compares the current correlation structure of the market to the structures at past ...

Compressive Parameter Estimation for Sparse Translation-Invariant Signals Using Polar Interpolation

DEFF Research Database (Denmark)

Fyhn, Karsten; Duarte, Marco F.; Jensen, Søren Holdt

2015-01-01

We propose new compressive parameter estimation algorithms that make use of polar interpolation to improve the estimator precision. Our work extends previous approaches involving polar interpolation for compressive parameter estimation in two aspects: (i) we extend the formulation from real non...... to attain good estimation precision and keep the computational complexity low. Our numerical experiments show that the proposed algorithms outperform existing approaches that either leverage polynomial interpolation or are based on a conversion to a frequency-estimation problem followed by a super...... interpolation increases the estimation precision....

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.

Estimation of Radar Cross Section of a Target under Track

Directory of Open Access Journals (Sweden)

Hong Sun-Mog

2010-01-01

Full Text Available In allocating radar beam for tracking a target, it is attempted to maintain the signal-to-noise ratio (SNR of signal returning from the illuminated target close to an optimum value for efficient track updates. An estimate of the average radar cross section (RCS of the target is required in order to adjust transmitted power based on the estimate such that a desired SNR can be realized. In this paper, a maximum-likelihood (ML approach is presented for estimating the average RCS, and a numerical solution to the approach is proposed based on a generalized expectation maximization (GEM algorithm. Estimation accuracy of the approach is compared to that of a previously reported procedure.

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)

A service based estimation method for MPSoC performance modelling

DEFF Research Database (Denmark)

Tranberg-Hansen, Anders Sejer; Madsen, Jan; Jensen, Bjørn Sand

2008-01-01

This paper presents an abstract service based estimation method for MPSoC performance modelling which allows fast, cycle accurate design space exploration of complex architectures including multi processor configurations at a very early stage in the design phase. The modelling method uses a service...... oriented model of computation based on Hierarchical Colored Petri Nets and allows the modelling of both software and hardware in one unified model. To illustrate the potential of the method, a small MPSoC system, developed at Bang & Olufsen ICEpower a/s, is modelled and performance estimates are produced...

[Estimating non work-related sickness leave absences related to a previous occupational injury in Catalonia (Spain)].

Science.gov (United States)

Molinero-Ruiz, Emilia; Navarro, Albert; Moriña, David; Albertí-Casas, Constança; Jardí-Lliberia, Josefina; de Montserrat-Nonó, Jaume

2015-01-01

To estimate the frequency of non-work sickness absence (ITcc) related to previous occupational injuries with (ATB) or without (ATSB) sick leave. Prospective longitudinal study. Workers with ATB or ATSB notified to the Occupational Accident Registry of Catalonia were selected in the last term of 2009. They were followed-up for six months after returning to work (ATB) or after the accident (ATSB), by sex and occupation. Official labor and health authority registries were used as information sources. An "injury-associated ITcc" was defined when the sick leave occurred in the following six months and within the same diagnosis group. The absolute and relative frequency were calculated according to time elapsed and its duration (cumulated days, measures of central trend and dispersion), by diagnosis group or affected body area, as compared to all of Catalonia. 2,9%of ATB (n=627) had an injury-associated ITcc, with differences by diagnosis, sex and occupation; this was also the case for 2,1% of ATSB (n=496).With the same diagnosis, duration of ITcc was longer among those who had an associated injury, and with respect to all of Catalonia. Some of the under-reporting of occupational pathology corresponds to episodes initially recognized as being work-related. Duration of sickness absence depends not only on diagnosis and clinical course, but also on criteria established by the entities managing the case. This could imply that more complicated injuries are referred to the national health system, resulting in personal, legal, healthcare and economic cost consequences for all involved stakeholders. Copyright belongs to the Societat Catalana de Salut Laboral.

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

Science.gov (United States)

Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

2017-09-01

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

Networked Estimation for Event-Based Sampling Systems with Packet Dropouts

Directory of Open Access Journals (Sweden)

Young Soo Suh

2009-04-01

Full Text Available This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. Event-based sampling has been shown to be more efficient than the time-triggered one in some situations, especially in network bandwidth improvement. However, it cannot detect packet dropout situations because data transmission and reception do not use a periodical time-stamp mechanism as found in time-triggered sampling systems. Motivated by this issue, we propose a modified event-based sampling scheme called modified SOD in which sensor data are sent when either the change of sensor output exceeds a given threshold or the time elapses more than a given interval. Through simulation results, we show that the proposed modified SOD sampling significantly improves estimation performance when packet dropouts happen.

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.

Toward an enhanced Bayesian estimation framework for multiphase flow soft-sensing

International Nuclear Information System (INIS)

Luo, Xiaodong; Lorentzen, Rolf J; Stordal, Andreas S; Nævdal, Geir

2014-01-01

In this work the authors study the multiphase flow soft-sensing problem based on a previously established framework. There are three functional modules in this framework, namely, a transient well flow model that describes the response of certain physical variables in a well, for instance, temperature, velocity and pressure, to the flow rates entering and leaving the well zones; a Markov jump process that is designed to capture the potential abrupt changes in the flow rates; and an estimation method that is adopted to estimate the underlying flow rates based on the measurements from the physical sensors installed in the well. In the previous studies, the variances of the flow rates in the Markov jump process are chosen manually. To fill this gap, in the current work two automatic approaches are proposed in order to optimize the variance estimation. Through a numerical example, we show that, when the estimation framework is used in conjunction with these two proposed variance-estimation approaches, it can achieve reasonable performance in terms of matching both the measurements of the physical sensors and the true underlying flow rates. (paper)

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

Science.gov (United States)

Miles, Jeffrey Hilton

2015-01-01

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

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

Science.gov (United States)

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

2017-10-17

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

Estimating Evapotranspiration Using an Observation Based Terrestrial Water Budget

Science.gov (United States)

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

2011-01-01

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

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....

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...

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...

The influence of different PAST-based subspace trackers on DaPT parameter estimation

Science.gov (United States)

Lechtenberg, M.; Götze, J.

2012-09-01

In the context of parameter estimation, subspace-based methods like ESPRIT have become common. They require a subspace separation e.g. based on eigenvalue/-vector decomposition. In time-varying environments, this can be done by subspace trackers. One class of these is based on the PAST algorithm. Our non-linear parameter estimation algorithm DaPT builds on-top of the ESPRIT algorithm. Evaluation of the different variants of the PAST algorithm shows which variant of the PAST algorithm is worthwhile in the context of frequency estimation.

DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays.

Science.gov (United States)

Li, Jianfeng; Wang, Feng; Jiang, Defu

2017-03-20

A fast direction of arrival (DOA) estimation method using a real-valued cross-correlation matrix (CCM) of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS) method and estimation of signal parameter via rotational invariance (ESPRIT) based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach.

A History-based Estimation for LHCb job requirements

Science.gov (United States)

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.

Use of Low-Level Sensor Data to Improve the Accuracy of Bluetooth-Based Travel Time Estimation

DEFF Research Database (Denmark)

Araghi, Bahar Namaki; Christensen, Lars Tørholm; Krishnan, Rajesh

2013-01-01

by a single device. The latter situation could lead to location ambiguity and could reduce the accuracy of travel time estimation. Therefore, the accuracy of travel time estimation by Bluetooth technology depends on how location ambiguity is handled by the estimation method. The issue of multiple detection...... events in the context of travel time estimation by Bluetooth technology has been considered by various researchers. However, treatment of this issue has been simplistic. Most previous studies have used the first detection event (enter-enter) as the best estimate. No systematic analysis has been conducted...... to explore the most accurate method of travel time estimation with multiple detection events. In this study, different aspects of the Bluetooth detection zone, including size and impact on the accuracy of travel time estimation, were discussed. Four methods were applied to estimate travel time: enter...

Markov Jump Linear Systems-Based Position Estimation for Lower Limb Exoskeletons

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Samuel L. Nogueira

2014-01-01

Full Text Available In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF to improve the performance of inertial measurement units (IMUs based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank are not taken into account in other link position estimation (e.g., the foot. In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties.

Ant-Based Phylogenetic Reconstruction (ABPR: A new distance algorithm for phylogenetic estimation based on ant colony optimization

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Karla Vittori

2008-12-01

Full Text Available We propose a new distance algorithm for phylogenetic estimation based on Ant Colony Optimization (ACO, named Ant-Based Phylogenetic Reconstruction (ABPR. ABPR joins two taxa iteratively based on evolutionary distance among sequences, while also accounting for the quality of the phylogenetic tree built according to the total length of the tree. Similar to optimization algorithms for phylogenetic estimation, the algorithm allows exploration of a larger set of nearly optimal solutions. We applied the algorithm to four empirical data sets of mitochondrial DNA ranging from 12 to 186 sequences, and from 898 to 16,608 base pairs, and covering taxonomic levels from populations to orders. We show that ABPR performs better than the commonly used Neighbor-Joining algorithm, except when sequences are too closely related (e.g., population-level sequences. The phylogenetic relationships recovered at and above species level by ABPR agree with conventional views. However, like other algorithms of phylogenetic estimation, the proposed algorithm failed to recover expected relationships when distances are too similar or when rates of evolution are very variable, leading to the problem of long-branch attraction. ABPR, as well as other ACO-based algorithms, is emerging as a fast and accurate alternative method of phylogenetic estimation for large data sets.

Two-Step Time of Arrival Estimation for Pulse-Based Ultra-Wideband Systems

Directory of Open Access Journals (Sweden)

H. Vincent Poor

2008-05-01

Full Text Available In cooperative localization systems, wireless nodes need to exchange accurate position-related information such as time-of-arrival (TOA and angle-of-arrival (AOA, in order to obtain accurate location information. One alternative for providing accurate position-related information is to use ultra-wideband (UWB signals. The high time resolution of UWB signals presents a potential for very accurate positioning based on TOA estimation. However, it is challenging to realize very accurate positioning systems in practical scenarios, due to both complexity/cost constraints and adverse channel conditions such as multipath propagation. In this paper, a two-step TOA estimation algorithm is proposed for UWB systems in order to provide accurate TOA estimation under practical constraints. In order to speed up the estimation process, the first step estimates a coarse TOA of the received signal based on received signal energy. Then, in the second step, the arrival time of the first signal path is estimated by considering a hypothesis testing approach. The proposed scheme uses low-rate correlation outputs and is able to perform accurate TOA estimation in reasonable time intervals. The simulation results are presented to analyze the performance of the estimator.

Satellite Angular Velocity Estimation Based on Star Images and Optical Flow Techniques

Directory of Open Access Journals (Sweden)

Giancarmine Fasano

2013-09-01

Full Text Available An optical flow-based technique is proposed to estimate spacecraft angular velocity based on sequences of star-field images. It does not require star identification and can be thus used to also deliver angular rate information when attitude determination is not possible, as during platform de tumbling or slewing. Region-based optical flow calculation is carried out on successive star images preprocessed to remove background. Sensor calibration parameters, Poisson equation, and a least-squares method are then used to estimate the angular velocity vector components in the sensor rotating frame. A theoretical error budget is developed to estimate the expected angular rate accuracy as a function of camera parameters and star distribution in the field of view. The effectiveness of the proposed technique is tested by using star field scenes generated by a hardware-in-the-loop testing facility and acquired by a commercial-off-the shelf camera sensor. Simulated cases comprise rotations at different rates. Experimental results are presented which are consistent with theoretical estimates. In particular, very accurate angular velocity estimates are generated at lower slew rates, while in all cases the achievable accuracy in the estimation of the angular velocity component along boresight is about one order of magnitude worse than the other two components.

State of charge estimation for lithium-ion pouch batteries based on stress measurement

International Nuclear Information System (INIS)

Dai, Haifeng; Yu, Chenchen; Wei, Xuezhe; Sun, Zechang

2017-01-01

State of charge (SOC) estimation is one of the important tasks of battery management system (BMS). Being different from other researches, a novel method of SOC estimation for pouch lithium-ion battery cells based on stress measurement is proposed. With a comprehensive experimental study, we find that, the stress of the battery during charge/discharge is composed of the static stress and the dynamic stress. The static stress, which is the measured stress in equilibrium state, corresponds to SOC, this phenomenon facilitates the design of our stress-based SOC estimation. The dynamic stress, on the other hand, is influenced by multiple factors including charge accumulation or depletion, current and historical operation, thus a multiple regression model of the dynamic stress is established. Based on the relationship between static stress and SOC, as well as the dynamic stress modeling, the SOC estimation method is founded. Experimental results show that the stress-based method performs well with a good accuracy, and this method offers a novel perspective for SOC estimation. - Highlights: • A State of Charge estimator based on stress measurement is proposed. • The stress during charge and discharge is investigated with comprehensive experiments. • Effects of SOC, current, and operation history on battery stress are well studied. • A multiple regression model of the dynamic stress is established.

Data Sources for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

Science.gov (United States)

The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

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.

Adaptive Methods for Permeability Estimation and Smart Well Management

Energy Technology Data Exchange (ETDEWEB)

Lien, Martha Oekland

2005-04-01

indicators, are described in Chapter 3. In Chapter 4, we give an introduction to level set functions as a tool to solve geometric inverse problems. Permeability estimation is the topic of Chapter 5. This includes an introduction of different data sources and a discussion about error and identifiability of the estimated parameters. An introduction to the proposed combination of adaptive multiscale estimation and level set functions for absolute permeability estimation is also given. In Chapter 6, we present water flood optimization by means of smart wells in the framework of optimal control theory. Here, hierarchical regularization methods are introduced to this problem, i.e. multiscale estimation and refinement indicators. Based on the theory presented in the previous chapters, summaries of the Based on the theory presented in the previous chapters, summaries of the research papers are given in Chapter 7. Part II: In Part II, four research papers are presented.

Computerized cost estimation spreadsheet and cost data base for fusion devices

International Nuclear Information System (INIS)

Hamilton, W.R.; Rothe, K.E.

1985-01-01

An automated approach to performing and cataloging cost estimates has been developed at the Fusion Engineering Design Center (FEDC), wherein the cost estimate record is stored in the LOTUS 1-2-3 spreadsheet on an IBM personal computer. The cost estimation spreadsheet is based on the cost coefficient/cost algorithm approach and incorporates a detailed generic code of cost accounts for both tokamak and tandem mirror devices. Component design parameters (weight, surface area, etc.) and cost factors are input, and direct and indirect costs are calculated. The cost data base file derived from actual cost experience within the fusion community and refined to be compatible with the spreadsheet costing approach is a catalog of cost coefficients, algorithms, and component costs arranged into data modules corresponding to specific components and/or subsystems. Each data module contains engineering, equipment, and installation labor cost data for different configurations and types of the specific component or subsystem. This paper describes the assumptions, definitions, methodology, and architecture incorporated in the development of the cost estimation spreadsheet and cost data base, along with the type of input required and the output format

Sliding-MOMP Based Channel Estimation Scheme for ISDB-T Systems

Directory of Open Access Journals (Sweden)

Ziji Ma

2016-01-01

Full Text Available Compressive sensing based channel estimation has shown its advantage of accurate reconstruction for sparse signal with less pilots for OFDM systems. However, high computational cost requirement of CS method, due to linear programming, significantly restricts its implementation in practical applications. In this paper, we propose a reduced complexity channel estimation scheme of modified orthogonal matching pursuit with sliding windows for ISDB-T (Integrated Services Digital Broadcasting for Terrestrial system. The proposed scheme can reduce the computational cost by limiting the searching region as well as making effective use of the last estimation result. In addition, adaptive tracking strategy with sliding sampling window can improve the robustness of CS based methods to guarantee its accuracy of channel matrix reconstruction, even for fast time-variant channels. The computer simulation demonstrates its impact on improving bit error rate and computational complexity for ISDB-T system.

Testing and comparison of three frequency-based magnitude estimating parameters for earthquake early warning based events in the Yunnan region, China in 2014

Science.gov (United States)

Zhang, Jianjing; Li, Hongjie

2018-06-01

To mitigate potential seismic disasters in the Yunnan region, China, building up suitable magnitude estimation scaling laws for an earthquake early warning system (EEWS) is in high demand. In this paper, the records from the main and after-shocks of the Yingjiang earthquake (M W 5.9), the Ludian earthquake (M W 6.2) and the Jinggu earthquake (M W 6.1), which occurred in Yunnan in 2014, were used to develop three estimators, including the maximum of the predominant period ({{τ }{{p}}}\\max ), the characteristic period (τ c) and the log-average period (τ log), for estimating earthquake magnitude. The correlations between these three frequency-based parameters and catalog magnitudes were developed, compared and evaluated against previous studies. The amplitude and period of seismic waves might be amplified in the Ludian mountain-canyon area by multiple reflections and resonance, leading to excessive values of the calculated parameters, which are consistent with Sichuan’s scaling. As a result, τ log was best correlated with magnitude and τ c had the highest slope of regression equation, while {{τ }{{p}}}\\max performed worst with large scatter and less sensitivity for the change of magnitude. No evident saturation occurred in the case of M 6.1 and M 6.2 in this study. Even though both τ c and τ log performed similarly and can well reflect the size of the Earthquake, τ log has slightly fewer prediction errors for small scale earthquakes (M ≤ 4.5), which was also observed by previous research. Our work offers an insight into the feasibility of a EEWS in Yunnan, China, and this study shows that it is necessary to build up an appropriate scaling law suitable for the warning region.

Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries

Directory of Open Access Journals (Sweden)

Zhongyue Zou

2014-08-01

Full Text Available Four model-based State of Charge (SOC estimation methods for lithium-ion (Li-ion batteries are studied and evaluated in this paper. Different from existing literatures, this work evaluates different aspects of the SOC estimation, such as the estimation error distribution, the estimation rise time, the estimation time consumption, etc. The equivalent model of the battery is introduced and the state function of the model is deduced. The four model-based SOC estimation methods are analyzed first. Simulations and experiments are then established to evaluate the four methods. The urban dynamometer driving schedule (UDDS current profiles are applied to simulate the drive situations of an electrified vehicle, and a genetic algorithm is utilized to identify the model parameters to find the optimal parameters of the model of the Li-ion battery. The simulations with and without disturbance are carried out and the results are analyzed. A battery test workbench is established and a Li-ion battery is applied to test the hardware in a loop experiment. Experimental results are plotted and analyzed according to the four aspects to evaluate the four model-based SOC estimation methods.

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.

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks

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Waqas Rehan

2016-09-01

Full Text Available Wireless sensor networks (WSNs have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM, that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI and the average of the link quality indicator (LQI of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC algorithm in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC algorithm, that can perform channel quality estimation on the basis of both current and past values of channel rank estimation

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

Science.gov (United States)

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-09-12

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end

DOA Estimation Based on Real-Valued Cross Correlation Matrix of Coprime Arrays

Directory of Open Access Journals (Sweden)

Jianfeng Li

2017-03-01

Full Text Available A fast direction of arrival (DOA estimation method using a real-valued cross-correlation matrix (CCM of coprime subarrays is proposed. Firstly, real-valued CCM with extended aperture is constructed to obtain the signal subspaces corresponding to the two subarrays. By analysing the relationship between the two subspaces, DOA estimations from the two subarrays are simultaneously obtained with automatic pairing. Finally, unique DOA is determined based on the common results from the two subarrays. Compared to partial spectral search (PSS method and estimation of signal parameter via rotational invariance (ESPRIT based method for coprime arrays, the proposed algorithm has lower complexity but achieves better DOA estimation performance and handles more sources. Simulation results verify the effectiveness of the approach.

An estimation of tourism dependence in French rural areas

OpenAIRE

Dissart, Jean-Christophe; Aubert, Francis; Truchet, Stéphanie; European Regional Science Association; Association de Science Régionale de Langue Française

2007-01-01

This paper intends to estimate the importance of tourism in the economy of rural areas. Considering previous analyses of rural dynamics, this paper 1) focuses on tourism activity, 2) analyzes the situation of Functional Economic Areas, and 3) takes into account socioeconomic indicators as well as landscape features. Based on secondary data, resource like regions are defined, the local share of tourism employment is estimated, stylized facts regarding tourism indicators by cluster are produced...

[Estimation of desert vegetation coverage based on multi-source remote sensing data].

Science.gov (United States)

Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

2012-12-01

Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

A Web-Based Tool to Estimate Pollutant Loading Using LOADEST

Directory of Open Access Journals (Sweden)

Youn Shik Park

2015-09-01

Full Text Available Collecting and analyzing water quality samples is costly and typically requires significant effort compared to streamflow data, thus water quality data are typically collected at a low frequency. Regression models, identifying a relationship between streamflow and water quality data, are often used to estimate pollutant loads. A web-based tool using LOAD ESTimator (LOADEST as a core engine with four modules was developed to provide user-friendly interfaces and input data collection via web access. The first module requests and receives streamflow and water quality data from the U.S. Geological Survey. The second module retrieves watershed area for computation of pollutant loads per unit area. The third module examines potential error of input datasets for LOADEST runs, and the last module computes estimated and allowable annual average pollutant loads and provides tabular and graphical LOADEST outputs. The web-based tool was applied to two watersheds in this study, one agriculturally-dominated and one urban-dominated. It was found that annual sediment load at the urban-dominant watershed exceeded the target load; therefore, the web-based tool identified correctly the watershed requiring best management practices to reduce pollutant loads.

Variance estimation for generalized Cavalieri estimators

OpenAIRE

Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

2011-01-01

The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Esteban Jiménez-Rodríguez

2016-12-01

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

Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in Montana StreamStats

Science.gov (United States)

Sando, Roy; Sando, Steven K.; McCarthy, Peter M.; Dutton, DeAnn M.

2016-04-05

this study were compared with results of previous studies. For most hydrologic regions, the regression equations reported for this study had lower mean standard errors of prediction (in percent) than the previously reported regression equations for Montana. The equations presented for this study are considered to be an improvement on the previously reported equations primarily because this study (1) included 13 more years of peak-flow data; (2) included 35 more streamflow-gaging stations than previous studies; (3) used a detailed geographic information system (GIS)-based definition of the regulation status of streamflow-gaging stations, which allowed better determination of the unregulated peak-flow records that are appropriate for use in the regional regression analysis; (4) included advancements in GIS and remote-sensing technologies, which allowed more convenient calculation of basin characteristics and investigation of many more candidate basin characteristics; and (5) included advancements in computational and analytical methods, which allowed more thorough and consistent data analysis.This report chapter also presents other methods for estimating peak-flow frequencies at ungaged sites. Two methods for estimating peak-flow frequencies at ungaged sites located on the same streams as streamflow-gaging stations are described. Additionally, envelope curves relating maximum recorded annual peak flows to contributing drainage area for each of the eight hydrologic regions in Montana are presented and compared to a national envelope curve. In addition to providing general information on characteristics of large peak flows, the regional envelope curves can be used to assess the reasonableness of peak-flow frequency estimates determined using the regression equations.

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

A feasibility study of mutual information based setup error estimation for radiotherapy

International Nuclear Information System (INIS)

Kim, Jeongtae; Fessler, Jeffrey A.; Lam, Kwok L.; Balter, James M.; Haken, Randall K. ten

2001-01-01

We have investigated a fully automatic setup error estimation method that aligns DRRs (digitally reconstructed radiographs) from a three-dimensional planning computed tomography image onto two-dimensional radiographs that are acquired in a treatment room. We have chosen a MI (mutual information)-based image registration method, hoping for robustness to intensity differences between the DRRs and the radiographs. The MI-based estimator is fully automatic since it is based on the image intensity values without segmentation. Using 10 repeated scans of an anthropomorphic chest phantom in one position and two single scans in two different positions, we evaluated the performance of the proposed method and a correlation-based method against the setup error determined by fiducial marker-based method. The mean differences between the proposed method and the fiducial marker-based method were smaller than 1 mm for translational parameters and 0.8 degree for rotational parameters. The standard deviations of estimates from the proposed method due to detector noise were smaller than 0.3 mm and 0.07 degree for the translational parameters and rotational parameters, respectively

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

Science.gov (United States)

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

2016-12-01

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

Sufficient Condition for Estimation in Designing H∞ Filter-Based SLAM

Directory of Open Access Journals (Sweden)

Nur Aqilah Othman

2015-01-01

Full Text Available Extended Kalman filter (EKF is often employed in determining the position of mobile robot and landmarks in simultaneous localization and mapping (SLAM. Nonetheless, there are some disadvantages of using EKF, namely, the requirement of Gaussian distribution for the state and noises, as well as the fact that it requires the smallest possible initial state covariance. This has led researchers to find alternative ways to mitigate the aforementioned shortcomings. Therefore, this study is conducted to propose an alternative technique by implementing H∞ filter in SLAM instead of EKF. In implementing H∞ filter in SLAM, the parameters of the filter especially γ need to be properly defined to prevent finite escape time problem. Hence, this study proposes a sufficient condition for the estimation purposes. Two distinct cases of initial state covariance are analysed considering an indoor environment to ensure the best solution for SLAM problem exists along with considerations of process and measurement noises statistical behaviour. If the prescribed conditions are not satisfied, then the estimation would exhibit unbounded uncertainties and consequently results in erroneous inference about the robot and landmarks estimation. The simulation results have shown the reliability and consistency as suggested by the theoretical analysis and our previous findings.

Left ventricular asynergy score as an indicator of previous myocardial infarction

International Nuclear Information System (INIS)

Backman, C.; Jacobsson, K.A.; Linderholm, H.; Osterman, G.

1986-01-01

Sixty-eight patients with coronary heart disease (CHD) i.e. a hisotry of angina of effort and/or previous 'possible infarction' were examined inter alia with ECG and cinecardioangiography. A system of scoring was designed which allowed a semiquantitative estimate of the left ventricular asynergy from cinecardioangiography - the left ventricular motion score (LVMS). The LVMS was associated with the presence of a previous myocardial infarction (MI), as indicated by the history and ECG findings. The ECG changes specific for a previous MI were associated with high LVMS values and unspecific or absent ECG changes with low LVMS values. Decision thresholds for ECG changes and asynergy in diagnosing a previous MI were evaluated by means of a ROC analysis. The accuracy of ECG in detecting a previous MI was slightly higher when asynergy indicated a 'true MI' than when autopsy result did so in a comparable group. Therefore the accuracy of asynergy (LVMS ≥ 1) in detecting a previous MI or myocardial fibrosis in patients with CHD should be at least comparable with that of autopsy (scar > 1 cm). (orig.)

Estimation of Multiple Pitches in Stereophonic Mixtures using a Codebook-based Approach

DEFF Research Database (Denmark)

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

2017-01-01

In this paper, a method for multi-pitch estimation of stereophonic mixtures of multiple harmonic signals is presented. The method is based on a signal model which takes the amplitude and delay panning parameters of the sources in a stereophonic mixture into account. Furthermore, the method is based...... on the extended invariance principle (EXIP), and a codebook of realistic amplitude vectors. For each fundamental frequency candidate in each of the sources, the amplitude estimates are mapped to entries in the codebook, and the pitch and model order are estimated jointly. The performance of the proposed method...

Vehicle Speed Estimation and Forecasting Methods Based on Cellular Floating Vehicle Data

Directory of Open Access Journals (Sweden)

Wei-Kuang Lai

2016-02-01

Full Text Available Traffic information estimation and forecasting methods based on cellular floating vehicle data (CFVD are proposed to analyze the signals (e.g., handovers (HOs, call arrivals (CAs, normal location updates (NLUs and periodic location updates (PLUs from cellular networks. For traffic information estimation, analytic models are proposed to estimate the traffic flow in accordance with the amounts of HOs and NLUs and to estimate the traffic density in accordance with the amounts of CAs and PLUs. Then, the vehicle speeds can be estimated in accordance with the estimated traffic flows and estimated traffic densities. For vehicle speed forecasting, a back-propagation neural network algorithm is considered to predict the future vehicle speed in accordance with the current traffic information (i.e., the estimated vehicle speeds from CFVD. In the experimental environment, this study adopted the practical traffic information (i.e., traffic flow and vehicle speed from Taiwan Area National Freeway Bureau as the input characteristics of the traffic simulation program and referred to the mobile station (MS communication behaviors from Chunghwa Telecom to simulate the traffic information and communication records. The experimental results illustrated that the average accuracy of the vehicle speed forecasting method is 95.72%. Therefore, the proposed methods based on CFVD are suitable for an intelligent transportation system.

A Novel Methodology for Estimating State-Of-Charge of Li-Ion Batteries Using Advanced Parameters Estimation

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Ibrahim M. Safwat

2017-11-01

Full Text Available State-of-charge (SOC estimations of Li-ion batteries have been the focus of many research studies in previous years. Many articles discussed the dynamic model’s parameters estimation of the Li-ion battery, where the fixed forgetting factor recursive least square estimation methodology is employed. However, the change rate of each parameter to reach the true value is not taken into consideration, which may tend to poor estimation. This article discusses this issue, and proposes two solutions to solve it. The first solution is the usage of a variable forgetting factor instead of a fixed one, while the second solution is defining a vector of forgetting factors, which means one factor for each parameter. After parameters estimation, a new idea is proposed to estimate state-of-charge (SOC of the Li-ion battery based on Newton’s method. Also, the error percentage and computational cost are discussed and compared with that of nonlinear Kalman filters. This methodology is applied on a 36 V 30 A Li-ion pack to validate this idea.

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

MODIS Based Estimation of Forest Aboveground Biomass in China.

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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.

MODIS Based Estimation of Forest Aboveground Biomass in China

Science.gov (United States)

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

2015-01-01

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

MODIS Based Estimation of Forest Aboveground Biomass in China.

Science.gov (United States)

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

2015-01-01

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

Plant Distribution Data Show Broader Climatic Limits than Expert-Based Climatic Tolerance Estimates.

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Caroline A Curtis

Full Text Available Although increasingly sophisticated environmental measures are being applied to species distributions models, the focus remains on using climatic data to provide estimates of habitat suitability. Climatic tolerance estimates based on expert knowledge are available for a wide range of plants via the USDA PLANTS database. We aim to test how climatic tolerance inferred from plant distribution records relates to tolerance estimated by experts. Further, we use this information to identify circumstances when species distributions are more likely to approximate climatic tolerance.We compiled expert knowledge estimates of minimum and maximum precipitation and minimum temperature tolerance for over 1800 conservation plant species from the 'plant characteristics' information in the USDA PLANTS database. We derived climatic tolerance from distribution data downloaded from the Global Biodiversity and Information Facility (GBIF and corresponding climate from WorldClim. We compared expert-derived climatic tolerance to empirical estimates to find the difference between their inferred climate niches (ΔCN, and tested whether ΔCN was influenced by growth form or range size.Climate niches calculated from distribution data were significantly broader than expert-based tolerance estimates (Mann-Whitney p values << 0.001. The average plant could tolerate 24 mm lower minimum precipitation, 14 mm higher maximum precipitation, and 7° C lower minimum temperatures based on distribution data relative to expert-based tolerance estimates. Species with larger ranges had greater ΔCN for minimum precipitation and minimum temperature. For maximum precipitation and minimum temperature, forbs and grasses tended to have larger ΔCN while grasses and trees had larger ΔCN for minimum precipitation.Our results show that distribution data are consistently broader than USDA PLANTS experts' knowledge and likely provide more robust estimates of climatic tolerance, especially for

Estimation of direction of arrival of a moving target using subspace based approaches

Science.gov (United States)

Ghosh, Ripul; Das, Utpal; Akula, Aparna; Kumar, Satish; Sardana, H. K.

2016-05-01

In this work, array processing techniques based on subspace decomposition of signal have been evaluated for estimation of direction of arrival of moving targets using acoustic signatures. Three subspace based approaches - Incoherent Wideband Multiple Signal Classification (IWM), Least Square-Estimation of Signal Parameters via Rotation Invariance Techniques (LS-ESPRIT) and Total Least Square- ESPIRIT (TLS-ESPRIT) are considered. Their performance is compared with conventional time delay estimation (TDE) approaches such as Generalized Cross Correlation (GCC) and Average Square Difference Function (ASDF). Performance evaluation has been conducted on experimentally generated data consisting of acoustic signatures of four different types of civilian vehicles moving in defined geometrical trajectories. Mean absolute error and standard deviation of the DOA estimates w.r.t. ground truth are used as performance evaluation metrics. Lower statistical values of mean error confirm the superiority of subspace based approaches over TDE based techniques. Amongst the compared methods, LS-ESPRIT indicated better performance.

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 ...

Improvement of Accuracy for Background Noise Estimation Method Based on TPE-AE

Science.gov (United States)

Itai, Akitoshi; Yasukawa, Hiroshi

This paper proposes a method of a background noise estimation based on the tensor product expansion with a median and a Monte carlo simulation. We have shown that a tensor product expansion with absolute error method is effective to estimate a background noise, however, a background noise might not be estimated by using conventional method properly. In this paper, it is shown that the estimate accuracy can be improved by using proposed methods.

ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES.

Science.gov (United States)

Fan, Jianqing; Rigollet, Philippe; Wang, Weichen

High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓ r norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics.

Satellite-based ET estimation using Landsat 8 images and SEBAL model

Directory of Open Access Journals (Sweden)

Bruno Bonemberger da Silva

Full Text Available ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

Joint Angle and Frequency Estimation Using Multiple-Delay Output Based on ESPRIT

Science.gov (United States)

Xudong, Wang

2010-12-01

This paper presents a novel ESPRIT algorithm-based joint angle and frequency estimation using multiple-delay output (MDJAFE). The algorithm can estimate the joint angles and frequencies, since the use of multiple output makes the estimation accuracy greatly improved when compared with a conventional algorithm. The useful behavior of the proposed algorithm is verified by simulations.

Vaccinia-based influenza vaccine overcomes previously induced immunodominance hierarchy for heterosubtypic protection.

Science.gov (United States)

Kwon, Ji-Sun; Yoon, Jungsoon; Kim, Yeon-Jung; Kang, Kyuho; Woo, Sunje; Jung, Dea-Im; Song, Man Ki; Kim, Eun-Ha; Kwon, Hyeok-Il; Choi, Young Ki; Kim, Jihye; Lee, Jeewon; Yoon, Yeup; Shin, Eui-Cheol; Youn, Jin-Won

2014-08-01

Growing concerns about unpredictable influenza pandemics require a broadly protective vaccine against diverse influenza strains. One of the promising approaches was a T cell-based vaccine, but the narrow breadth of T-cell immunity due to the immunodominance hierarchy established by previous influenza infection and efficacy against only mild challenge condition are important hurdles to overcome. To model T-cell immunodominance hierarchy in humans in an experimental setting, influenza-primed C57BL/6 mice were chosen and boosted with a mixture of vaccinia recombinants, individually expressing consensus sequences from avian, swine, and human isolates of influenza internal proteins. As determined by IFN-γ ELISPOT and polyfunctional cytokine secretion, the vaccinia recombinants of influenza expanded the breadth of T-cell responses to include subdominant and even minor epitopes. Vaccine groups were successfully protected against 100 LD50 challenges with PR/8/34 and highly pathogenic avian influenza H5N1, which contained the identical dominant NP366 epitope. Interestingly, in challenge with pandemic A/Cal/04/2009 containing mutations in the dominant epitope, only the group vaccinated with rVV-NP + PA showed improved protection. Taken together, a vaccinia-based influenza vaccine expressing conserved internal proteins improved the breadth of influenza-specific T-cell immunity and provided heterosubtypic protection against immunologically close as well as distant influenza strains. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Estimation of second primary cancers risk based on the treatment planning system

International Nuclear Information System (INIS)

Jin Chufeng; Sun Guangyao; Liu Hui; Zheng Huaqing; Cheng Mengyun; Li Gui; Wu Yican; FDS Team

2011-01-01

Estimates of second primary cancers risk after radiotherapy has become increasingly important for comparative treatment planning. A new method based on the treatment planning system to estimate the risk of second primary cancers was introduced in this paper. Using the Advanced/Accurate Radiotherapy Treatment System(ARTS), a treatment planning system developed by the FDS team,the risk of second primary cancer was estimated over two treatment plans for a patient with pancreatic cancer. Based on the second primary cancer risk, the two plans were compared. It was found that,kidney and gall-bladder had higher risk to develop second primary cancer. A better plan was chosen by the analysis of second primary cancer risk. The results showed that this risk estimation method we developed could be used to evaluate treatment plans. (authors)

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

Estimating and validating ground-based timber harvesting production through computer simulation

Science.gov (United States)

Jingxin Wang; Chris B. LeDoux

2003-01-01

Estimating ground-based timber harvesting systems production with an object oriented methodology was investigated. The estimation model developed generates stands of trees, simulates chain saw, drive-to-tree feller-buncher, swing-to-tree single-grip harvester felling, and grapple skidder and forwarder extraction activities, and analyzes costs and productivity. It also...

Soil profile property estimation with field and laboratory VNIR spectroscopy

Science.gov (United States)

Diffuse reflectance spectroscopy (DRS) soil sensors have the potential to provide rapid, high-resolution estimation of multiple soil properties. Although many studies have focused on laboratory-based visible and near-infrared (VNIR) spectroscopy of dried soil samples, previous work has demonstrated ...

Estimates of future climate based on SRES emission scenarios

Energy Technology Data Exchange (ETDEWEB)

Godal, Odd; Sygna, Linda; Fuglestvedt, Jan S.; Berntsen, Terje

2000-02-14

The preliminary emission scenarios in the Special Report on Emission Scenario (SRES) developed by the Intergovernmental Panel on Climate Change (IPCC), will eventually replace the old IS92 scenarios. By running these scenarios in a simple climate model (SCM) we estimate future temperature increase between 1.7 {sup o}C and 2.8 {sup o}C from 1990 to to 2100. The global sea level rise over the same period is between 0.33 m and 0.45 m. Compared to the previous IPCC scenarios (IS92) the SRES scenarios generally results in changes in both development over time and level of emissions, concentrations, radiative forcing, and finally temperature change and sea level rise. The most striking difference between the IS92 scenarios and the SRES scenarios is the lower level of SO{sub 2} emissions. The range in CO{sub 2} emissions is also expected to be narrower in the new scenarios. The SRES scenarios result in a narrower range both for temperature change and sea level rise from 1990 to 2100 compared to the range estimated for the IS92 scenarios. (author)

Cultivation-based multiplex phenotyping of human gut microbiota allows targeted recovery of previously uncultured bacteria

DEFF Research Database (Denmark)

Rettedal, Elizabeth; Gumpert, Heidi; Sommer, Morten

2014-01-01

The human gut microbiota is linked to a variety of human health issues and implicated in antibiotic resistance gene dissemination. Most of these associations rely on culture-independent methods, since it is commonly believed that gut microbiota cannot be easily or sufficiently cultured. Here, we...... microbiota. Based on the phenotypic mapping, we tailor antibiotic combinations to specifically select for previously uncultivated bacteria. Utilizing this method we cultivate and sequence the genomes of four isolates, one of which apparently belongs to the genus Oscillibacter; uncultivated Oscillibacter...

Estimation of the inverse Weibull distribution based on progressively censored data: Comparative study

International Nuclear Information System (INIS)

Musleh, Rola M.; Helu, Amal

2014-01-01

In this article we consider statistical inferences about the unknown parameters of the Inverse Weibull distribution based on progressively type-II censoring using classical and Bayesian procedures. For classical procedures we propose using the maximum likelihood; the least squares methods and the approximate maximum likelihood estimators. The Bayes estimators are obtained based on both the symmetric and asymmetric (Linex, General Entropy and Precautionary) loss functions. There are no explicit forms for the Bayes estimators, therefore, we propose Lindley's approximation method to compute the Bayes estimators. A comparison between these estimators is provided by using extensive simulation and three criteria, namely, Bias, mean squared error and Pitman nearness (PN) probability. It is concluded that the approximate Bayes estimators outperform the classical estimators most of the time. Real life data example is provided to illustrate our proposed estimators. - Highlights: • We consider progressively type-II censored data from the Inverse Weibull distribution (IW). • We derive MLEs, approximate MLEs, LS and Bayes estimate methods of scale and shape parameters of the IW. • Bayes estimator of shape parameter cannot be expressed in closed forms. • We suggest using Lindley's approximation. • We conclude that the Bayes estimates outperform the classical methods

Polynomial Phase Estimation Based on Adaptive Short-Time Fourier Transform.

Science.gov (United States)

Jing, Fulong; Zhang, Chunjie; Si, Weijian; Wang, Yu; Jiao, Shuhong

2018-02-13

Polynomial phase signals (PPSs) have numerous applications in many fields including radar, sonar, geophysics, and radio communication systems. Therefore, estimation of PPS coefficients is very important. In this paper, a novel approach for PPS parameters estimation based on adaptive short-time Fourier transform (ASTFT), called the PPS-ASTFT estimator, is proposed. Using the PPS-ASTFT estimator, both one-dimensional and multi-dimensional searches and error propagation problems, which widely exist in PPSs field, are avoided. In the proposed algorithm, the instantaneous frequency (IF) is estimated by S-transform (ST), which can preserve information on signal phase and provide a variable resolution similar to the wavelet transform (WT). The width of the ASTFT analysis window is equal to the local stationary length, which is measured by the instantaneous frequency gradient (IFG). The IFG is calculated by the principal component analysis (PCA), which is robust to the noise. Moreover, to improve estimation accuracy, a refinement strategy is presented to estimate signal parameters. Since the PPS-ASTFT avoids parameter search, the proposed algorithm can be computed in a reasonable amount of time. The estimation performance, computational cost, and implementation of the PPS-ASTFT are also analyzed. The conducted numerical simulations support our theoretical results and demonstrate an excellent statistical performance of the proposed algorithm.

Bootstrap-based confidence estimation in PCA and multivariate statistical process control

DEFF Research Database (Denmark)

Babamoradi, Hamid

be used to detect outliers in the data since the outliers can distort the bootstrap estimates. Bootstrap-based confidence limits were suggested as alternative to the asymptotic limits for control charts and contribution plots in MSPC (Paper II). The results showed that in case of the Q-statistic......Traditional/Asymptotic confidence estimation has limited applicability since it needs statistical theories to estimate the confidences, which are not available for all indicators/parameters. Furthermore, in case the theories are available for a specific indicator/parameter, the theories are based....... The goal was to improve process monitoring by improving the quality of MSPC charts and contribution plots. Bootstrapping algorithm to build confidence limits was illustrated in a case study format (Paper I). The main steps in the algorithm were discussed where a set of sensible choices (plus...

Population Estimation in Singapore Based on Remote Sensing and Open Data

Science.gov (United States)

Guo, H.; Cao, K.; Wang, P.

2017-09-01

Population estimation statistics are widely used in government, commercial and educational sectors for a variety of purposes. With growing emphases on real-time and detailed population information, data users nowadays have switched from traditional census data to more technology-based data source such as LiDAR point cloud and High-Resolution Satellite Imagery. Nevertheless, such data are costly and periodically unavailable. In this paper, the authors use West Coast District, Singapore as a case study to investigate the applicability and effectiveness of using satellite image from Google Earth for extraction of building footprint and population estimation. At the same time, volunteered geographic information (VGI) is also utilized as ancillary data for building footprint extraction. Open data such as Open Street Map OSM could be employed to enhance the extraction process. In view of challenges in building shadow extraction, this paper discusses several methods including buffer, mask and shape index to improve accuracy. It also illustrates population estimation methods based on building height and number of floor estimates. The results show that the accuracy level of housing unit method on population estimation can reach 92.5 %, which is remarkably accurate. This paper thus provides insights into techniques for building extraction and fine-scale population estimation, which will benefit users such as urban planners in terms of policymaking and urban planning of Singapore.

POPULATION ESTIMATION IN SINGAPORE BASED ON REMOTE SENSING AND OPEN DATA

Directory of Open Access Journals (Sweden)

H. Guo

2017-09-01

Full Text Available Population estimation statistics are widely used in government, commercial and educational sectors for a variety of purposes. With growing emphases on real-time and detailed population information, data users nowadays have switched from traditional census data to more technology-based data source such as LiDAR point cloud and High-Resolution Satellite Imagery. Nevertheless, such data are costly and periodically unavailable. In this paper, the authors use West Coast District, Singapore as a case study to investigate the applicability and effectiveness of using satellite image from Google Earth for extraction of building footprint and population estimation. At the same time, volunteered geographic information (VGI is also utilized as ancillary data for building footprint extraction. Open data such as Open Street Map（OSM）could be employed to enhance the extraction process. In view of challenges in building shadow extraction, this paper discusses several methods including buffer, mask and shape index to improve accuracy. It also illustrates population estimation methods based on building height and number of floor estimates. The results show that the accuracy level of housing unit method on population estimation can reach 92.5 %, which is remarkably accurate. This paper thus provides insights into techniques for building extraction and fine-scale population estimation, which will benefit users such as urban planners in terms of policymaking and urban planning of Singapore.

Online Kinematic and Dynamic-State Estimation for Constrained Multibody Systems Based on IMUs

Science.gov (United States)

Torres-Moreno, José Luis; Blanco-Claraco, José Luis; Giménez-Fernández, Antonio; Sanjurjo, Emilio; Naya, Miguel Ángel

2016-01-01

This article addresses the problems of online estimations of kinematic and dynamic states of a mechanism from a sequence of noisy measurements. In particular, we focus on a planar four-bar linkage equipped with inertial measurement units (IMUs). Firstly, we describe how the position, velocity, and acceleration of all parts of the mechanism can be derived from IMU signals by means of multibody kinematics. Next, we propose the novel idea of integrating the generic multibody dynamic equations into two variants of Kalman filtering, i.e., the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), in a way that enables us to handle closed-loop, constrained mechanisms, whose state space variables are not independent and would normally prevent the direct use of such estimators. The proposal in this work is to apply those estimators over the manifolds of allowed positions and velocities, by means of estimating a subset of independent coordinates only. The proposed techniques are experimentally validated on a testbed equipped with encoders as a means of establishing the ground-truth. Estimators are run online in real-time, a feature not matched by any previous procedure of those reported in the literature on multibody dynamics. PMID:26959027

PERFORMANCE ANALYSIS OF PILOT BASED CHANNEL ESTIMATION TECHNIQUES IN MB OFDM SYSTEMS

Directory of Open Access Journals (Sweden)

M. Madheswaran

2011-12-01

Full Text Available Ultra wideband (UWB communication is mainly used for short range of communication in wireless personal area networks. Orthogonal Frequency Division Multiplexing (OFDM is being used as a key physical layer technology for Fourth Generation (4G wireless communication. OFDM based communication gives high spectral efficiency and mitigates Inter-symbol Interference (ISI in a wireless medium. In this paper the IEEE 802.15.3a based Multiband OFDM (MB OFDM system is considered. The pilot based channel estimation techniques are considered to analyze the performance of MB OFDM systems over Liner Time Invariant (LTI Channel models. In this paper, pilot based Least Square (LS and Least Minimum Mean Square Error (LMMSE channel estimation technique has been considered for UWB OFDM system. In the proposed method, the estimated Channel Impulse Responses (CIRs are filtered in the time domain for the consideration of the channel delay spread. Also the performance of proposed system has been analyzed for different modulation techniques for various pilot density patterns.

Multi-objective mixture-based iterated density estimation evolutionary algorithms

NARCIS (Netherlands)

Thierens, D.; Bosman, P.A.N.

2001-01-01

We propose an algorithm for multi-objective optimization using a mixture-based iterated density estimation evolutionary algorithm (MIDEA). The MIDEA algorithm is a prob- abilistic model building evolutionary algo- rithm that constructs at each generation a mixture of factorized probability

Biometric estimation of chest wall thickness of females

International Nuclear Information System (INIS)

Berger, C.D.; Lane, B.H.

1985-01-01

Optimal use of whole-body counting data to estimate pulmonary deposition of many of the actinides is dependent upon accurate measurement of the thickness of the chest wall because of severe attenuation of low-energy x rays and photons associated with the decay of these radionuclides. An algorithm for estimation of female chest wall thicknesses, verified by real-time ultrasonic measurements, has been derived based on the correlation of measured chest wall thickness and other common biometric quantities. Use of this algorithm will reduce the error generally associated with estimation of internal actinide deposition previously resulting from assuming an average chest wall thickness for all female subjects

An EKF-based approach for estimating leg stiffness during walking.

Science.gov (United States)

Ochoa-Diaz, Claudia; Menegaz, Henrique M; Bó, Antônio P L; Borges, Geovany A

2013-01-01

The spring-like behavior is an inherent condition for human walking and running. Since leg stiffness k(leg) is a parameter that cannot be directly measured, many techniques has been proposed in order to estimate it, most of them using force data. This paper intends to address this problem using an Extended Kalman Filter (EKF) based on the Spring-Loaded Inverted Pendulum (SLIP) model. The formulation of the filter only uses as measurement information the Center of Mass (CoM) position and velocity, no a priori information about the stiffness value is known. From simulation results, it is shown that the EKF-based approach can generate a reliable stiffness estimation for walking.

On the Methods for Estimating the Corneoscleral Limbus.

Science.gov (United States)

Jesus, Danilo A; Iskander, D Robert

2017-08-01

The aim of this study was to develop computational methods for estimating limbus position based on the measurements of three-dimensional (3-D) corneoscleral topography and ascertain whether corneoscleral limbus routinely estimated from the frontal image corresponds to that derived from topographical information. Two new computational methods for estimating the limbus position are proposed: One based on approximating the raw anterior eye height data by series of Zernike polynomials and one that combines the 3-D corneoscleral topography with the frontal grayscale image acquired with the digital camera in-built in the profilometer. The proposed methods are contrasted against a previously described image-only-based procedure and to a technique of manual image annotation. The estimates of corneoscleral limbus radius were characterized with a high precision. The group average (mean ± standard deviation) of the maximum difference between estimates derived from all considered methods was 0.27 ± 0.14 mm and reached up to 0.55 mm. The four estimating methods lead to statistically significant differences (nonparametric ANOVA (the Analysis of Variance) test, p 0.05). Precise topographical limbus demarcation is possible either from the frontal digital images of the eye or from the 3-D topographical information of corneoscleral region. However, the results demonstrated that the corneoscleral limbus estimated from the anterior eye topography does not always correspond to that obtained through image-only based techniques. The experimental findings have shown that 3-D topography of anterior eye, in the absence of a gold standard, has the potential to become a new computational methodology for estimating the corneoscleral limbus.

Gross domestic product estimation based on electricity utilization by artificial neural network

Science.gov (United States)

Stevanović, Mirjana; Vujičić, Slađana; Gajić, Aleksandar M.

2018-01-01

The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization.

A Web-Based System for Bayesian Benchmark Dose Estimation.

Science.gov (United States)

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.

Time of arrival based location estimation for cooperative relay networks

KAUST Repository

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.

Time of arrival based location estimation for cooperative relay networks

KAUST Repository

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.

A Dynamic Travel Time Estimation Model Based on Connected Vehicles

Directory of Open Access Journals (Sweden)

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.

A review of global potentially available cropland estimates and their consequences for model-based assessments

NARCIS (Netherlands)

Eitelberg, D.A.; van Vliet, J.; Verburg, P.H.

2015-01-01

The world's population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to

[Dual process in large number estimation under uncertainty].

Science.gov (United States)

Matsumuro, Miki; Miwa, Kazuhisa; Terai, Hitoshi; Yamada, Kento

2016-08-01

According to dual process theory, there are two systems in the mind: an intuitive and automatic System 1 and a logical and effortful System 2. While many previous studies about number estimation have focused on simple heuristics and automatic processes, the deliberative System 2 process has not been sufficiently studied. This study focused on the System 2 process for large number estimation. First, we described an estimation process based on participants’ verbal reports. The task, corresponding to the problem-solving process, consisted of creating subgoals, retrieving values, and applying operations. Second, we investigated the influence of such deliberative process by System 2 on intuitive estimation by System 1, using anchoring effects. The results of the experiment showed that the System 2 process could mitigate anchoring effects.

Online Synchrophasor-Based Dynamic State Estimation using Real-Time Digital Simulator

DEFF Research Database (Denmark)

Khazraj, Hesam; Adewole, Adeyemi Charles; Udaya, Annakkage

2018-01-01

Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real-...... using the RTDS (real-time digital simulator). The dynamic state variables of multi-machine systems are monitored and measured for the study on the transient behavior of power systems.......Dynamic state estimation is a very important control center application used in the dynamic monitoring of state variables. This paper presents and validates a time-synchronized phasor measurement unit (PMU)-based for dynamic state estimation by unscented Kalman filter (UKF) method using the real......-time digital simulator (RTDS). The dynamic state variables of the system are the rotor angle and speed of the generators. The performance of the UKF method is tested with PMU measurements as inputs using the IEEE 14-bus test system. This test system was modeled in the RSCAD software and tested in real time...

A Temperature-Based Bioimpedance Correction for Water Loss Estimation During Sports.

Science.gov (United States)

Ring, Matthias; Lohmueller, Clemens; Rauh, Manfred; Mester, Joachim; Eskofier, Bjoern M

2016-11-01

The amount of total body water (TBW) can be estimated based on bioimpedance measurements of the human body. In sports, TBW estimations are of importance because mild water losses can impair muscular strength and aerobic endurance. Severe water losses can even be life threatening. TBW estimations based on bioimpedance, however, fail during sports because the increased body temperature corrupts bioimpedance measurements. Therefore, this paper proposes a machine learning method that eliminates the effects of increased temperature on bioimpedance and, consequently, reveals the changes in bioimpedance that are due to TBW loss. This is facilitated by utilizing changes in skin and core temperature. The method was evaluated in a study in which bioimpedance, temperature, and TBW loss were recorded every 15 min during a 2-h running workout. The evaluation demonstrated that the proposed method is able to reduce the error of TBW loss estimation by up to 71%, compared to the state of art. In the future, the proposed method in combination with portable bioimpedance devices might facilitate the development of wearable systems for continuous and noninvasive TBW loss monitoring during sports.

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

Directory of Open Access Journals (Sweden)

Andrew Haywood

2017-03-01

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

Sinusoidal Order Estimation Using Angles between Subspaces

Directory of Open Access Journals (Sweden)

Søren Holdt Jensen

2009-01-01

Full Text Available We consider the problem of determining the order of a parametric model from a noisy signal based on the geometry of the space. More specifically, we do this using the nontrivial angles between the candidate signal subspace model and the noise subspace. The proposed principle is closely related to the subspace orthogonality property known from the MUSIC algorithm, and we study its properties and compare it to other related measures. For the problem of estimating the number of complex sinusoids in white noise, a computationally efficient implementation exists, and this problem is therefore considered in detail. In computer simulations, we compare the proposed method to various well-known methods for order estimation. These show that the proposed method outperforms the other previously published subspace methods and that it is more robust to the noise being colored than the previously published methods.

Telemetry-based mortality estimates of juvenile spot in two North Carolina estuarine creeks

Science.gov (United States)

Friedl, Sarah E.; Buckel, Jeffery A.; Hightower, Joseph E.; Scharf, Frederick S.; Pollock, Kenneth H.

2013-01-01

We estimated natural mortality rates (M) of age-1 Spot Leiostomus xanthurus by using a sonic telemetry approach. Sonic transmitters were surgically implanted into a total of 123 age-1 Spot in two North Carolina estuarine creeks during spring 2009 and 2010, and the fish were monitored by using a stationary acoustic receiver array and manual tracking. Fates of telemetered Spot were inferred based on telemetry information from estimated locations and swimming speeds. Potential competitors of age-1 Spot were assessed through simultaneous otter trawl sampling, while potential predators of Spot were collected using gill nets and trammel nets. The number of inferred natural mortalities was zero in 2009 (based on 29 telemetered Spot at risk) and four in 2010 (based on 52 fish at risk), with fish being at risk for up to about 70 d each year. Catches of potential competitors or predators did not differ between years, and age-1 Spot were not found in analyzed stomach contents of potential predators. Our estimated 30-d M of 0.03 (95% credible interval = 0.01–0.07) was lower than that predicted from weight-based (M = 0.07) and life-history-based (M = 0.06–0.36) estimates. Our field-based estimate of M for age-1 Spot in this estuarine system can assist in the assessment and management of Spot by allowing a direct comparison with M-values predicted from fish size or life history characteristics. The field telemetry and statistical analysis techniques developed here provide guidance for future telemetry studies of relatively small fish in open, dynamic habitat systems, as they highlight strengths and weaknesses of using a telemetry approach to estimate M.

Photometry-based estimation of the total number of stars in the Universe.

Science.gov (United States)

Manojlović, Lazo M

2015-07-20

A novel photometry-based estimation of the total number of stars in the Universe is presented. The estimation method is based on the energy conservation law and actual measurements of the extragalactic background light levels. By assuming that every radiated photon is kept within the Universe volume, i.e., by approximating the Universe as an integrating cavity without losses, the total number of stars in the Universe of about 6×1022 has been obtained.

In vivo dentate nucleus MRI relaxometry correlates with previous administration of Gadolinium-based contrast agents

Energy Technology Data Exchange (ETDEWEB)

Tedeschi, Enrico; Canna, Antonietta; Cocozza, Sirio; Russo, Carmela; Angelini, Valentina; Brunetti, Arturo [University ' ' Federico II' ' , Neuroradiology, Department of Advanced Biomedical Sciences, Naples (Italy); Palma, Giuseppe; Quarantelli, Mario [National Research Council, Institute of Biostructure and Bioimaging, Naples (Italy); Borrelli, Pasquale; Salvatore, Marco [IRCCS SDN, Naples (Italy); Lanzillo, Roberta; Postiglione, Emanuela; Morra, Vincenzo Brescia [University ' ' Federico II' ' , Department of Neurosciences, Reproductive and Odontostomatological Sciences, Naples (Italy)

2016-12-15

To evaluate changes in T1 and T2* relaxometry of dentate nuclei (DN) with respect to the number of previous administrations of Gadolinium-based contrast agents (GBCA). In 74 relapsing-remitting multiple sclerosis (RR-MS) patients with variable disease duration (9.8±6.8 years) and severity (Expanded Disability Status Scale scores:3.1±0.9), the DN R1 (1/T1) and R2* (1/T2*) relaxation rates were measured using two unenhanced 3D Dual-Echo spoiled Gradient-Echo sequences with different flip angles. Correlations of the number of previous GBCA administrations with DN R1 and R2* relaxation rates were tested, including gender and age effect, in a multivariate regression analysis. The DN R1 (normalized by brainstem) significantly correlated with the number of GBCA administrations (p<0.001), maintaining the same significance even when including MS-related factors. Instead, the DN R2* values correlated only with age (p=0.003), and not with GBCA administrations (p=0.67). In a subgroup of 35 patients for whom the administered GBCA subtype was known, the effect of GBCA on DN R1 appeared mainly related to linear GBCA. In RR-MS patients, the number of previous GBCA administrations correlates with R1 relaxation rates of DN, while R2* values remain unaffected, suggesting that T1-shortening in these patients is related to the amount of Gadolinium given. (orig.)

H∞ state estimation of stochastic memristor-based neural networks with time-varying delays.

Science.gov (United States)

Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir

2018-03-01

This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Image-based change estimation for land cover and land use monitoring

Science.gov (United States)

Jeremy Webb; C. Kenneth Brewer; Nicholas Daniels; Chris Maderia; Randy Hamilton; Mark Finco; Kevin A. Megown; Andrew J. Lister

2012-01-01

The Image-based Change Estimation (ICE) project resulted from the need to provide estimates and information for land cover and land use change over large areas. The procedure uses Forest Inventory and Analysis (FIA) plot locations interpreted using two different dates of imagery from the National Agriculture Imagery Program (NAIP). In order to determine a suitable...

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

Science.gov (United States)

Zhang, Ke; Jiang, Bin; Shi, Peng

2017-02-01

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

An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

Directory of Open Access Journals (Sweden)

Tingting Jin

2017-04-01

Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

Guideline for Bayesian Net based Software Fault Estimation Method for Reactor Protection System

International Nuclear Information System (INIS)

Eom, Heung Seop; Park, Gee Yong; Jang, Seung Cheol

2011-01-01

The purpose of this paper is to provide a preliminary guideline for the estimation of software faults in a safety-critical software, for example, reactor protection system's software. As the fault estimation method is based on Bayesian Net which intensively uses subjective probability and informal data, it is necessary to define formal procedure of the method to minimize the variability of the results. The guideline describes assumptions, limitations and uncertainties, and the product of the fault estimation method. The procedure for conducting a software fault-estimation method is then outlined, highlighting the major tasks involved. The contents of the guideline are based on our own experience and a review of research guidelines developed for a PSA

Estimation of power lithium-ion battery SOC based on fuzzy optimal decision

Science.gov (United States)

He, Dongmei; Hou, Enguang; Qiao, Xin; Liu, Guangmin

2018-06-01

In order to improve vehicle performance and safety, need to accurately estimate the power lithium battery state of charge (SOC), analyzing the common SOC estimation methods, according to the characteristics open circuit voltage and Kalman filter algorithm, using T - S fuzzy model, established a lithium battery SOC estimation method based on the fuzzy optimal decision. Simulation results show that the battery model accuracy can be improved.

Adaptive Kalman filter based state of charge estimation algorithm for lithium-ion battery

International Nuclear Information System (INIS)

Zheng Hong; Liu Xu; Wei Min

2015-01-01

In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded. (paper)

Supporting Analogy-based Effort Estimation with the Use of Ontologies

Directory of Open Access Journals (Sweden)

Joanna Kowalska

2014-06-01

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

On estimation of time-dependent attributable fraction from population-based case-control studies.

Science.gov (United States)

Zhao, Wei; Chen, Ying Qing; Hsu, Li

2017-09-01

Population attributable fraction (PAF) is widely used to quantify the disease burden associated with a modifiable exposure in a population. It has been extended to a time-varying measure that provides additional information on when and how the exposure's impact varies over time for cohort studies. However, there is no estimation procedure for PAF using data that are collected from population-based case-control studies, which, because of time and cost efficiency, are commonly used for studying genetic and environmental risk factors of disease incidences. In this article, we show that time-varying PAF is identifiable from a case-control study and develop a novel estimator of PAF. Our estimator combines odds ratio estimates from logistic regression models and density estimates of the risk factor distribution conditional on failure times in cases from a kernel smoother. The proposed estimator is shown to be consistent and asymptotically normal with asymptotic variance that can be estimated empirically from the data. Simulation studies demonstrate that the proposed estimator performs well in finite sample sizes. Finally, the method is illustrated by a population-based case-control study of colorectal cancer. © 2017, The International Biometric Society.

Direction-of-Arrival Estimation for Coprime Array Using Compressive Sensing Based Array Interpolation

Directory of Open Access Journals (Sweden)

Aihua Liu

2017-01-01

Full Text Available A method of direction-of-arrival (DOA estimation using array interpolation is proposed in this paper to increase the number of resolvable sources and improve the DOA estimation performance for coprime array configuration with holes in its virtual array. The virtual symmetric nonuniform linear array (VSNLA of coprime array signal model is introduced, with the conventional MUSIC with spatial smoothing algorithm (SS-MUSIC applied on the continuous lags in the VSNLA; the degrees of freedom (DoFs for DOA estimation are obviously not fully exploited. To effectively utilize the extent of DoFs offered by the coarray configuration, a compressing sensing based array interpolation algorithm is proposed. The compressing sensing technique is used to obtain the coarse initial DOA estimation, and a modified iterative initial DOA estimation based interpolation algorithm (IMCA-AI is then utilized to obtain the final DOA estimation, which maps the sample covariance matrix of the VSNLA to the covariance matrix of a filled virtual symmetric uniform linear array (VSULA with the same aperture size. The proposed DOA estimation method can efficiently improve the DOA estimation performance. The numerical simulations are provided to demonstrate the effectiveness of the proposed method.

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 GIS-based methodology for the estimation of potential volcanic damage and its application to Tenerife Island, Spain

Science.gov (United States)

Scaini, C.; Felpeto, A.; Martí, J.; Carniel, R.

2014-05-01

This paper presents a GIS-based methodology to estimate damages produced by volcanic eruptions. The methodology is constituted by four parts: definition and simulation of eruptive scenarios, exposure analysis, vulnerability assessment and estimation of expected damages. Multi-hazard eruptive scenarios are defined for the Teide-Pico Viejo active volcanic complex, and simulated through the VORIS tool. The exposure analysis identifies the elements exposed to the hazard at stake and focuses on the relevant assets for the study area. The vulnerability analysis is based on previous studies on the built environment and complemented with the analysis of transportation and urban infrastructures. Damage assessment is performed associating a qualitative damage rating to each combination of hazard and vulnerability. This operation consists in a GIS-based overlap, performed for each hazardous phenomenon considered and for each element. The methodology is then automated into a GIS-based tool using an ArcGIS® program. Given the eruptive scenarios and the characteristics of the exposed elements, the tool produces expected damage maps. The tool is applied to the Icod Valley (North of Tenerife Island) which is likely to be affected by volcanic phenomena in case of eruption from both the Teide-Pico Viejo volcanic complex and North-West basaltic rift. Results are thematic maps of vulnerability and damage that can be displayed at different levels of detail, depending on the user preferences. The aim of the tool is to facilitate territorial planning and risk management in active volcanic areas.

Evaluating the impact of spatio-temporal smoothness constraints on the BOLD hemodynamic response function estimation: an analysis based on Tikhonov regularization

International Nuclear Information System (INIS)

Casanova, R; Yang, L; Hairston, W D; Laurienti, P J; Maldjian, J A

2009-01-01

Recently we have proposed the use of Tikhonov regularization with temporal smoothness constraints to estimate the BOLD fMRI hemodynamic response function (HRF). The temporal smoothness constraint was imposed on the estimates by using second derivative information while the regularization parameter was selected based on the generalized cross-validation function (GCV). Using one-dimensional simulations, we previously found this method to produce reliable estimates of the HRF time course, especially its time to peak (TTP), being at the same time fast and robust to over-sampling in the HRF estimation. Here, we extend the method to include simultaneous temporal and spatial smoothness constraints. This method does not need Gaussian smoothing as a pre-processing step as usually done in fMRI data analysis. We carried out two-dimensional simulations to compare the two methods: Tikhonov regularization with temporal (Tik-GCV-T) and spatio-temporal (Tik-GCV-ST) smoothness constraints on the estimated HRF. We focus our attention on quantifying the influence of the Gaussian data smoothing and the presence of edges on the performance of these techniques. Our results suggest that the spatial smoothing introduced by regularization is less severe than that produced by Gaussian smoothing. This allows more accurate estimates of the response amplitudes while producing similar estimates of the TTP. We illustrate these ideas using real data. (note)

Determining root correspondence between previously and newly detected objects

Science.gov (United States)

Paglieroni, David W.; Beer, N Reginald

2014-06-17

A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

Channel and delay estimation for base-station–based cooperative communications in frequency-selective fading channels

Directory of Open Access Journals (Sweden)

Hongjun Xu

2011-07-01

Full Text Available A channel and delay estimation algorithm for both positive and negative delay, based on the distributed Alamouti scheme, has been recently discussed for base-station–based asynchronous cooperative systems in frequency-flat fading channels. This paper extends the algorithm, the maximum likelihood estimator, to work in frequency-selective fading channels. The minimum mean square error (MMSE performance of channel estimation for both packet schemes and normal schemes is discussed in this paper. The symbol error rate (SER performance of equalisation and detection for both time-reversal space-time block code (STBC and single-carrier STBC is also discussed in this paper. The MMSE simulation results demonstrated the superior performance of the packet scheme over the normal scheme with an improvement in performance of up to 6 dB when feedback was used in the frequency-selective channel at a MSE of 3 x 10^–2. The SER simulation results showed that, although both the normal and packet schemes achieved similar diversity orders, the packet scheme demonstrated a 1 dB coding gain over the normal scheme at a SER of 10^–5. Finally, the SER simulations showed that the frequency-selective fading system outperformed the frequency-flat fading system.

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.

Estimation of Supercapacitor Energy Storage Based on Fractional Differential Equations.

Science.gov (United States)

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.

Robust estimation of autoregressive processes using a mixture-based filter-bank

Czech Academy of Sciences Publication Activity Database

Šmídl, V.; Anthony, Q.; Kárný, Miroslav; Guy, Tatiana Valentine

2005-01-01

Roč. 54, č. 4 (2005), s. 315-323 ISSN 0167-6911 R&D Projects: GA AV ČR IBS1075351; GA ČR GA102/03/0049; GA ČR GP102/03/P010; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian estimation * probabilistic mixtures * recursive estimation Subject RIV: BC - Control Systems Theory Impact factor: 1.239, year: 2005 http://library.utia.cas.cz/separaty/historie/karny-robust estimation of autoregressive processes using a mixture-based filter- bank .pdf

Fast and accurate estimation of the covariance between pairwise maximum likelihood distances

Directory of Open Access Journals (Sweden)

Manuel Gil

2014-09-01

Full Text Available Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989 which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error.

Fast and accurate estimation of the covariance between pairwise maximum likelihood distances.

Science.gov (United States)

Gil, Manuel

2014-01-01

Pairwise evolutionary distances are a model-based summary statistic for a set of molecular sequences. They represent the leaf-to-leaf path lengths of the underlying phylogenetic tree. Estimates of pairwise distances with overlapping paths covary because of shared mutation events. It is desirable to take these covariance structure into account to increase precision in any process that compares or combines distances. This paper introduces a fast estimator for the covariance of two pairwise maximum likelihood distances, estimated under general Markov models. The estimator is based on a conjecture (going back to Nei & Jin, 1989) which links the covariance to path lengths. It is proven here under a simple symmetric substitution model. A simulation shows that the estimator outperforms previously published ones in terms of the mean squared error.

Life cycle assessment based environmental impact estimation model for pre-stressed concrete beam bridge in the early design phase

International Nuclear Information System (INIS)

Kim, Kyong Ju; Yun, Won Gun; Cho, Namho; Ha, Jikwang

2017-01-01

The late rise in global concern for environmental issues such as global warming and air pollution is accentuating the need for environmental assessments in the construction industry. Promptly evaluating the environmental loads of the various design alternatives during the early stages of a construction project and adopting the most environmentally sustainable candidate is therefore of large importance. Yet, research on the early evaluation of a construction project's environmental load in order to aid the decision making process is hitherto lacking. In light of this dilemma, this study proposes a model for estimating the environmental load by employing only the most basic information accessible during the early design phases of a project for the pre-stressed concrete (PSC) beam bridge, the most common bridge structure. Firstly, a life cycle assessment (LCA) was conducted on the data from 99 bridges by integrating the bills of quantities (BOQ) with a life cycle inventory (LCI) database. The processed data was then utilized to construct a case based reasoning (CBR) model for estimating the environmental load. The accuracy of the estimation model was then validated using five test cases; the model's mean absolute error rates (MAER) for the total environmental load was calculated as 7.09%. Such test results were shown to be superior compared to those obtained from a multiple-regression based model and a slab area base-unit analysis model. Henceforth application of this model during the early stages of a project is expected to highly complement environmentally friendly designs and construction by facilitating the swift evaluation of the environmental load from multiple standpoints. - Highlights: • This study is to develop the model of assessing the environmental impacts on LCA. • Bills of quantity from completed designs of PSC Beam were linked with the LCI DB. • Previous cases were used to estimate the environmental load of new case by CBR model. • CBR

Life cycle assessment based environmental impact estimation model for pre-stressed concrete beam bridge in the early design phase

Energy Technology Data Exchange (ETDEWEB)

Kim, Kyong Ju, E-mail: kjkim@cau.ac.kr; Yun, Won Gun, E-mail: ogun78@naver.com; Cho, Namho, E-mail: nhc51@cau.ac.kr; Ha, Jikwang, E-mail: wlrhkd29@gmail.com

2017-05-15

The late rise in global concern for environmental issues such as global warming and air pollution is accentuating the need for environmental assessments in the construction industry. Promptly evaluating the environmental loads of the various design alternatives during the early stages of a construction project and adopting the most environmentally sustainable candidate is therefore of large importance. Yet, research on the early evaluation of a construction project's environmental load in order to aid the decision making process is hitherto lacking. In light of this dilemma, this study proposes a model for estimating the environmental load by employing only the most basic information accessible during the early design phases of a project for the pre-stressed concrete (PSC) beam bridge, the most common bridge structure. Firstly, a life cycle assessment (LCA) was conducted on the data from 99 bridges by integrating the bills of quantities (BOQ) with a life cycle inventory (LCI) database. The processed data was then utilized to construct a case based reasoning (CBR) model for estimating the environmental load. The accuracy of the estimation model was then validated using five test cases; the model's mean absolute error rates (MAER) for the total environmental load was calculated as 7.09%. Such test results were shown to be superior compared to those obtained from a multiple-regression based model and a slab area base-unit analysis model. Henceforth application of this model during the early stages of a project is expected to highly complement environmentally friendly designs and construction by facilitating the swift evaluation of the environmental load from multiple standpoints. - Highlights: • This study is to develop the model of assessing the environmental impacts on LCA. • Bills of quantity from completed designs of PSC Beam were linked with the LCI DB. • Previous cases were used to estimate the environmental load of new case by CBR model. • CBR

Previously unknown species of Aspergillus.

Science.gov (United States)

Gautier, M; Normand, A-C; Ranque, S

2016-08-01

The use of multi-locus DNA sequence analysis has led to the description of previously unknown 'cryptic' Aspergillus species, whereas classical morphology-based identification of Aspergillus remains limited to the section or species-complex level. The current literature highlights two main features concerning these 'cryptic' Aspergillus species. First, the prevalence of such species in clinical samples is relatively high compared with emergent filamentous fungal taxa such as Mucorales, Scedosporium or Fusarium. Second, it is clearly important to identify these species in the clinical laboratory because of the high frequency of antifungal drug-resistant isolates of such Aspergillus species. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been shown to enable the identification of filamentous fungi with an accuracy similar to that of DNA sequence-based methods. As MALDI-TOF MS is well suited to the routine clinical laboratory workflow, it facilitates the identification of these 'cryptic' Aspergillus species at the routine mycology bench. The rapid establishment of enhanced filamentous fungi identification facilities will lead to a better understanding of the epidemiology and clinical importance of these emerging Aspergillus species. Based on routine MALDI-TOF MS-based identification results, we provide original insights into the key interpretation issues of a positive Aspergillus culture from a clinical sample. Which ubiquitous species that are frequently isolated from air samples are rarely involved in human invasive disease? Can both the species and the type of biological sample indicate Aspergillus carriage, colonization or infection in a patient? Highly accurate routine filamentous fungi identification is central to enhance the understanding of these previously unknown Aspergillus species, with a vital impact on further improved patient care. Copyright © 2016 European Society of Clinical Microbiology and

Estimation of net greenhouse gas balance using crop- and soil-based approaches: Two case studies

International Nuclear Information System (INIS)

Huang, Jianxiong; Chen, Yuanquan; Sui, Peng; Gao, Wansheng

2013-01-01

The net greenhouse gas balance (NGHGB), estimated by combining direct and indirect greenhouse gas (GHG) emissions, can reveal whether an agricultural system is a sink or source of GHGs. Currently, two types of methods, referred to here as crop-based and soil-based approaches, are widely used to estimate the NGHGB of agricultural systems on annual and seasonal crop timescales. However, the two approaches may produce contradictory results, and few studies have tested which approach is more reliable. In this study, we examined the two approaches using experimental data from an intercropping trial with straw removal and a tillage trial with straw return. The results of the two approaches provided different views of the two trials. In the intercropping trial, NGHGB estimated by the crop-based approach indicated that monocultured maize (M) was a source of GHGs (− 1315 kg CO 2 −eq ha −1 ), whereas maize–soybean intercropping (MS) was a sink (107 kg CO 2 −eq ha −1 ). When estimated by the soil-based approach, both cropping systems were sources (− 3410 for M and − 2638 kg CO 2 −eq ha −1 for MS). In the tillage trial, mouldboard ploughing (MP) and rotary tillage (RT) mitigated GHG emissions by 22,451 and 21,500 kg CO 2 −eq ha −1 , respectively, as estimated by the crop-based approach. However, by the soil-based approach, both tillage methods were sources of GHGs: − 3533 for MP and − 2241 kg CO 2 −eq ha −1 for RT. The crop-based approach calculates a GHG sink on the basis of the returned crop biomass (and other organic matter input) and estimates considerably more GHG mitigation potential than that calculated from the variations in soil organic carbon storage by the soil-based approach. These results indicate that the crop-based approach estimates higher GHG mitigation benefits compared to the soil-based approach and may overestimate the potential of GHG mitigation in agricultural systems. - Highlights: • Net greenhouse gas balance (NGHGB) of

Fan-out Estimation in Spin-based Quantum Computer Scale-up.

Science.gov (United States)

Nguyen, Thien; Hill, Charles D; Hollenberg, Lloyd C L; James, Matthew R

2017-10-17

Solid-state spin-based qubits offer good prospects for scaling based on their long coherence times and nexus to large-scale electronic scale-up technologies. However, high-threshold quantum error correction requires a two-dimensional qubit array operating in parallel, posing significant challenges in fabrication and control. While architectures incorporating distributed quantum control meet this challenge head-on, most designs rely on individual control and readout of all qubits with high gate densities. We analysed the fan-out routing overhead of a dedicated control line architecture, basing the analysis on a generalised solid-state spin qubit platform parameterised to encompass Coulomb confined (e.g. donor based spin qubits) or electrostatically confined (e.g. quantum dot based spin qubits) implementations. The spatial scalability under this model is estimated using standard electronic routing methods and present-day fabrication constraints. Based on reasonable assumptions for qubit control and readout we estimate 10 2 -10 5 physical qubits, depending on the quantum interconnect implementation, can be integrated and fanned-out independently. Assuming relatively long control-free interconnects the scalability can be extended. Ultimately, the universal quantum computation may necessitate a much higher number of integrated qubits, indicating that higher dimensional electronics fabrication and/or multiplexed distributed control and readout schemes may be the preferredstrategy for large-scale implementation.

Accounting for estimated IQ in neuropsychological test performance with regression-based techniques.

Science.gov (United States)

Testa, S Marc; Winicki, Jessica M; Pearlson, Godfrey D; Gordon, Barry; Schretlen, David J

2009-11-01

Regression-based normative techniques account for variability in test performance associated with multiple predictor variables and generate expected scores based on algebraic equations. Using this approach, we show that estimated IQ, based on oral word reading, accounts for 1-9% of the variability beyond that explained by individual differences in age, sex, race, and years of education for most cognitive measures. These results confirm that adding estimated "premorbid" IQ to demographic predictors in multiple regression models can incrementally improve the accuracy with which regression-based norms (RBNs) benchmark expected neuropsychological test performance in healthy adults. It remains to be seen whether the incremental variance in test performance explained by estimated "premorbid" IQ translates to improved diagnostic accuracy in patient samples. We describe these methods, and illustrate the step-by-step application of RBNs with two cases. We also discuss the rationale, assumptions, and caveats of this approach. More broadly, we note that adjusting test scores for age and other characteristics might actually decrease the accuracy with which test performance predicts absolute criteria, such as the ability to drive or live independently.

Estimates of reproductive potential of Greenland halibut (Reinhardtius hippoglossoides) in East Greenland based on an update of maturity status

DEFF Research Database (Denmark)

Kennedy, James; Hedeholm, Rasmus B.; Gundersen, Agnes C.

2014-01-01

When estimating reproductive potential (RP), correct interpretation of the maturity status is essential. It has now become apparent the presence of vitellogenic oocytes within the ovary of Greenland halibut (Reinhardtius hippoglossoides) does not necessarily indicate they will spawn within the next...... twelve months. This has led to a revision of the interpretation of the maturity scale where fish which contain only a developing cohort (DC) of oocytes are considered immature. Comparisons were made of estimates of L50 of female Greenland halibut in East Greenland using the previous interpretation......), respectively. Combining the maturity data with abundance data of Greenland halibut in East Greenland, spawning stock biomass (SSB) and total egg production (TEP) was estimated in four quadrants between 1998 and 2012 using both the previous and current interpretation of the maturity scale. Using the new...

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

Science.gov (United States)

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

2018-02-01

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

Reconciling estimates of the ratio of heat and salt fluxes at the ice-ocean interface

Science.gov (United States)

Keitzl, T.; Mellado, J. P.; Notz, D.

2016-12-01

The heat exchange between floating ice and the underlying ocean is determined by the interplay of diffusive fluxes directly at the ice-ocean interface and turbulent fluxes away from it. In this study, we examine this interplay through direct numerical simulations of free convection. Our results show that an estimation of the interface flux ratio based on direct measurements of the turbulent fluxes can be difficult because the flux ratio varies with depth. As an alternative, we present a consistent evaluation of the flux ratio based on the total heat and salt fluxes across the boundary layer. This approach allows us to reconcile previous estimates of the ice-ocean interface conditions. We find that the ratio of heat and salt fluxes directly at the interface is 83-100 rather than 33 as determined by previous turbulence measurements in the outer layer. This can cause errors in the estimated ice-ablation rate from field measurements of up to 40% if they are based on the three-equation formulation.

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.)

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...

Mode extraction on wind turbine blades via phase-based video motion estimation

Science.gov (United States)

Sarrafi, Aral; Poozesh, Peyman; Niezrecki, Christopher; Mao, Zhu

2017-04-01

In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

Estimation of soil profile properties using field and laboratory VNIR spectroscopy

Science.gov (United States)

Diffuse reflectance spectroscopy (DRS) soil sensors have the potential to provide rapid, high-resolution estimation of multiple soil properties. Although many studies have focused on laboratory-based visible and near-infrared (VNIR) spectroscopy of dried soil samples, previous work has demonstrated ...

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

KAUST Repository

Asiri, Sharefa M.

2017-10-08

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

Online Kinematic and Dynamic-State Estimation for Constrained Multibody Systems Based on IMUs

Directory of Open Access Journals (Sweden)

José Luis Torres-Moreno

2016-03-01

Full Text Available This article addresses the problems of online estimations of kinematic and dynamic states of a mechanism from a sequence of noisy measurements. In particular, we focus on a planar four-bar linkage equipped with inertial measurement units (IMUs. Firstly, we describe how the position, velocity, and acceleration of all parts of the mechanism can be derived from IMU signals by means of multibody kinematics. Next, we propose the novel idea of integrating the generic multibody dynamic equations into two variants of Kalman filtering, i.e., the extended Kalman filter (EKF and the unscented Kalman filter (UKF, in a way that enables us to handle closed-loop, constrained mechanisms, whose state space variables are not independent and would normally prevent the direct use of such estimators. The proposal in this work is to apply those estimators over the manifolds of allowed positions and velocities, by means of estimating a subset of independent coordinates only. The proposed techniques are experimentally validated on a testbed equipped with encoders as a means of establishing the ground-truth. Estimators are run online in real-time, a feature not matched by any previous procedure of those reported in the literature on multibody dynamics.

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

Science.gov (United States)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis.

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Schenkl, Sebastian; Muggenthaler, Holger; Hubig, Michael; Erdmann, Bodo; Weiser, Martin; Zachow, Stefan; Heinrich, Andreas; Güttler, Felix Victor; Teichgräber, Ulf; Mall, Gita

2017-05-01

Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.

Improving North American forest biomass estimates from literature synthesis and meta-analysis of existing biomass equations

Science.gov (United States)

David C. Chojnacky; Jennifer C. Jenkins; Amanda K. Holland

2009-01-01

Thousands of published equations purport to estimate biomass of individual trees. These equations are often based on very small samples, however, and can provide widely different estimates for trees of the same species. We addressed this issue in a previous study by devising 10 new equations that estimated total aboveground biomass for all species in North America (...

Estimating the relative weights of visual and auditory tau versus heuristic-based cues for time-to-contact judgments in realistic, familiar scenes by older and younger adults.

Science.gov (United States)

Keshavarz, Behrang; Campos, Jennifer L; DeLucia, Patricia R; Oberfeld, Daniel

2017-04-01

Estimating time to contact (TTC) involves multiple sensory systems, including vision and audition. Previous findings suggested that the ratio of an object's instantaneous optical size/sound intensity to its instantaneous rate of change in optical size/sound intensity (τ) drives TTC judgments. Other evidence has shown that heuristic-based cues are used, including final optical size or final sound pressure level. Most previous studies have used decontextualized and unfamiliar stimuli (e.g., geometric shapes on a blank background). Here we evaluated TTC estimates by using a traffic scene with an approaching vehicle to evaluate the weights of visual and auditory TTC cues under more realistic conditions. Younger (18-39 years) and older (65+ years) participants made TTC estimates in three sensory conditions: visual-only, auditory-only, and audio-visual. Stimuli were presented within an immersive virtual-reality environment, and cue weights were calculated for both visual cues (e.g., visual τ, final optical size) and auditory cues (e.g., auditory τ, final sound pressure level). The results demonstrated the use of visual τ as well as heuristic cues in the visual-only condition. TTC estimates in the auditory-only condition, however, were primarily based on an auditory heuristic cue (final sound pressure level), rather than on auditory τ. In the audio-visual condition, the visual cues dominated overall, with the highest weight being assigned to visual τ by younger adults, and a more equal weighting of visual τ and heuristic cues in older adults. Overall, better characterizing the effects of combined sensory inputs, stimulus characteristics, and age on the cues used to estimate TTC will provide important insights into how these factors may affect everyday behavior.

Optical Method for Estimating the Chlorophyll Contents in Plant Leaves.

Science.gov (United States)

Pérez-Patricio, Madaín; Camas-Anzueto, Jorge Luis; Sanchez-Alegría, Avisaí; Aguilar-González, Abiel; Gutiérrez-Miceli, Federico; Escobar-Gómez, Elías; Voisin, Yvon; Rios-Rojas, Carlos; Grajales-Coutiño, Ruben

2018-02-22

This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD) meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica , Canavalia ensiforme , and Lycopersicon esculentum . Experimental results showed that-in terms of accuracy and processing speed-the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica , where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.

Optical Method for Estimating the Chlorophyll Contents in Plant Leaves

Directory of Open Access Journals (Sweden)

Madaín Pérez-Patricio

2018-02-01

Full Text Available This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance, a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica, Canavalia ensiforme, and Lycopersicon esculentum. Experimental results showed that—in terms of accuracy and processing speed—the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica, where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.

Hybrid fuzzy charged system search algorithm based state estimation in distribution networks

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Sachidananda Prasad

2017-06-01

Full Text Available This paper proposes a new hybrid charged system search (CSS algorithm based state estimation in radial distribution networks in fuzzy framework. The objective of the optimization problem is to minimize the weighted square of the difference between the measured and the estimated quantity. The proposed method of state estimation considers bus voltage magnitude and phase angle as state variable along with some equality and inequality constraints for state estimation in distribution networks. A rule based fuzzy inference system has been designed to control the parameters of the CSS algorithm to achieve better balance between the exploration and exploitation capability of the algorithm. The efficiency of the proposed fuzzy adaptive charged system search (FACSS algorithm has been tested on standard IEEE 33-bus system and Indian 85-bus practical radial distribution system. The obtained results have been compared with the conventional CSS algorithm, weighted least square (WLS algorithm and particle swarm optimization (PSO for feasibility of the algorithm.

Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters.

Science.gov (United States)

Song, Jin Woo; Park, Chan Gook

2018-04-21

An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms.

Ratio-based estimators for a change point in persistence.

Science.gov (United States)

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

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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.

Slip Control of Electric Vehicle Based on Tire-Road Friction Coefficient Estimation

Directory of Open Access Journals (Sweden)

Gaojian Cui

2017-01-01

Full Text Available The real-time change of tire-road friction coefficient is one of the important factors that influence vehicle safety performance. Besides, the vehicle wheels’ locking up has become an important issue. In order to solve these problems, this paper comes up with a novel slip control of electric vehicle (EV based on tire-road friction coefficient estimation. First and foremost, a novel method is proposed to estimate the tire-road friction coefficient, and then the reference slip ratio is determined based on the estimation results. Finally, with the reference slip ratio, a slip control based on model predictive control (MPC is designed to prevent the vehicle wheels from locking up. In this regard, the proposed controller guarantees the optimal braking torque on each wheel by individually controlling the slip ratio of each tire within the stable zone. Theoretical analyses and simulation show that the proposed controller is effective for better braking performance.

Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

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Chen Gong-bo

2013-06-01

Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.

Low-dose computed tomography image restoration using previous normal-dose scan

International Nuclear Information System (INIS)

Ma, Jianhua; Huang, Jing; Feng, Qianjin; Zhang, Hua; Lu, Hongbing; Liang, Zhengrong; Chen, Wufan

2011-01-01

Purpose: In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series. Methods: Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols. Results: Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use

An RSS based location estimation technique for cognitive relay networks

KAUST Repository

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.

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

Science.gov (United States)

Ghosh, Dibakar; Bhattacharyya, Bidyut K.

2011-09-01

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

Timing-based location estimation for OFDM signals with applications in LTE, WLAN and Wimax Timing-based location estimation for OFDM signals with applications in LTE, WLAN and Wimax Timing-based location estimation for OFDM signals with applications in LTE, WLAN and Wimax

OpenAIRE

Juárez Leria, Víctor

2012-01-01

Projecte realitzat en el marc d'un programa de mobilitat amb la Tampere University of Technology (Tampereen Teknillinen Yliopisto) [ANGLÈS] Literature study of various preamble-based and non-preamble-based timing synchronization algorithms in OFDM - Implementation (in Matlab) of the following preamble-based algorithms: Schmidl, Minn, Park, Kim, Ren and Kang. Implementation (in Matlab) of Correlation-Based Timing Synchronization and MUltiple SIgnal Classification estimators. Comparison of v...

SU-E-T-365: Estimation of Neutron Ambient Dose Equivalents for Radioprotection Exposed Workers in Radiotherapy Facilities Based On Characterization Patient Risk Estimation

Energy Technology Data Exchange (ETDEWEB)

Irazola, L; Terron, J; Sanchez-Doblado, F [Departamento de Fisiologia Medica y Biofisica, Universidad de Sevilla (Spain); Servicio de Radiofisica, Hospital Universitario Virgen Macarena, Sevilla (Spain); Domingo, C; Romero-Exposito, M [Departament de Fisica, Universitat Autonoma de Barcelona, Bellaterra (Spain); Garcia-Fuste, M [Health and Safety Department, ALBA Synchrotron Light Source, Cerdanyola del Valles (Spain); Sanchez-Nieto, B [Instituto de Fisica, Pontificia Universidad Catolica de Chile, Santiago (Chile); Bedogni, R [Laboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare (INFN) (Italy)

2015-06-15

Purpose: Previous measurements with Bonner spheres{sup 1} showed that normalized neutron spectra are equal for the majority of the existing linacs{sup 2}. This information, in addition to thermal neutron fluences obtained in the characterization procedure{sup 3}3, would allow to estimate neutron doses accidentally received by exposed workers, without the need of an extra experimental measurement. Methods: Monte Carlo (MC) simulations demonstrated that the thermal neutron fluence distribution inside the bunker is quite uniform, as a consequence of multiple scatter in the walls{sup 4}. Although inverse square law is approximately valid for the fast component, a more precise calculation could be obtained with a generic fast fluence distribution map around the linac, from MC simulations{sup 4}. Thus, measurements of thermal neutron fluences performed during the characterization procedure{sup 3}, together with a generic unitary spectra{sup 2}, would allow to estimate the total neutron fluences and H*(10) at any point{sup 5}. As an example, we compared estimations with Bonner sphere measurements{sup 1}, for two points in five facilities: 3 Siemens (15–23 MV), Elekta (15 MV) and Varian (15 MV). Results: Thermal neutron fluences obtained from characterization, are within (0.2–1.6×10{sup 6}) cm−{sup 2}•Gy{sup −1} for the five studied facilities. This implies ambient equivalent doses ranging from (0.27–2.01) mSv/Gy 50 cm far from the isocenter and (0.03–0.26) mSv/Gy at detector location with an average deviation of ±12.1% respect to Bonner measurements. Conclusion: The good results obtained demonstrate that neutron fluence and H*(10) can be estimated based on: (a) characterization procedure established for patient risk estimation in each facility, (b) generic unitary neutron spectrum and (c) generic MC map distribution of the fast component. [1] Radiat. Meas (2010) 45: 1391 – 1397; [2] Phys. Med. Biol (2012) 5 7:6167–6191; [3] Med. Phys (2015) 42

Gradient-based stochastic estimation of the density matrix

Science.gov (United States)

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.

Research on bathymetry estimation by Worldview-2 based with the semi-analytical model

Science.gov (United States)

Sheng, L.; Bai, J.; Zhou, G.-W.; Zhao, Y.; Li, Y.-C.

2015-04-01

South Sea Islands of China are far away from the mainland, the reefs takes more than 95% of south sea, and most reefs scatter over interested dispute sensitive area. Thus, the methods of obtaining the reefs bathymetry accurately are urgent to be developed. Common used method, including sonar, airborne laser and remote sensing estimation, are limited by the long distance, large area and sensitive location. Remote sensing data provides an effective way for bathymetry estimation without touching over large area, by the relationship between spectrum information and bathymetry. Aimed at the water quality of the south sea of China, our paper develops a bathymetry estimation method without measured water depth. Firstly the semi-analytical optimization model of the theoretical interpretation models has been studied based on the genetic algorithm to optimize the model. Meanwhile, OpenMP parallel computing algorithm has been introduced to greatly increase the speed of the semi-analytical optimization model. One island of south sea in China is selected as our study area, the measured water depth are used to evaluate the accuracy of bathymetry estimation from Worldview-2 multispectral images. The results show that: the semi-analytical optimization model based on genetic algorithm has good results in our study area;the accuracy of estimated bathymetry in the 0-20 meters shallow water area is accepted.Semi-analytical optimization model based on genetic algorithm solves the problem of the bathymetry estimation without water depth measurement. Generally, our paper provides a new bathymetry estimation method for the sensitive reefs far away from mainland.

Validity of food frequency questionnaire-based estimates of long-term long-chain n-3 polyunsaturated fatty acid intake.

Science.gov (United States)

Wallin, Alice; Di Giuseppe, Daniela; Burgaz, Ann; Håkansson, Niclas; Cederholm, Tommy; Michaëlsson, Karl; Wolk, Alicja

2014-01-01

To evaluate how long-term dietary intake of long-chain n-3 polyunsaturated fatty acids (LCn-3 PUFAs), estimated by repeated food frequency questionnaires (FFQs) over 15 years, is correlated with LCn-3 PUFAs in adipose tissue (AT). Subcutaneous adipose tissue was obtained in 2003-2004 (AT-03) from 239 randomly selected women, aged 55-75 years, after completion of a 96-item FFQ (FFQ-03). All participants had previously returned an identical FFQ in 1997 (FFQ-97) and a 67-item version in 1987-1990 (FFQ-87). Pearson product-moment correlations were used to evaluate associations between intake of total and individual LCn-3 PUFAs as estimated by the three FFQ assessments and AT-03 content (% of total fatty acids). FFQ-estimated mean relative intake of LCn-3 PUFAs (% of total fat intake) increased between all three assessments (FFQ-87, 0.55 ± 0.34; FFQ-97, 0.74 ± 0.64; FFQ-03, 0.88 ± 0.56). Validity, in terms of Pearson correlations between FFQ-03 estimates and AT-03 content, was 0.41 (95% CI 0.30-0.51) for total LCn-3 PUFA and ranged from 0.29 to 0.48 for individual fatty acids; lower correlation was observed among participants with higher percentage body fat. With regard to long-term intake estimates, past dietary intake was also correlated with AT-03 content, with correlation coefficients in the range of 0.21-0.33 and 0.21-0.34 for FFQ-97 and FFQ-87, respectively. The correlations were improved by using average estimates from two or more FFQ assessments. Exclusion of fish oil supplement users (14%) did not alter the correlations. These data indicate reasonable validity of FFQ-based estimates of long-term (up to 15 years) LCn-3 PUFA intake, justifying their use in studies of diet-disease associations.

Can we improve C IV-based single epoch black hole mass estimations?

Science.gov (United States)

Mejía-Restrepo, J. E.; Trakhtenbrot, B.; Lira, P.; Netzer, H.

2018-05-01

In large optical surveys at high redshifts (z > 2), the C IV broad emission line is the most practical alternative to estimate the mass (MBH) of active super-massive black holes (SMBHs). However, mass determinations obtained with this line are known to be highly uncertain. In this work we use the Sloan Digital Sky Survey Data Release 7 and 12 quasar catalogues to statistically test three alternative methods put forward in the literature to improve C IV-based MBH estimations. These methods are constructed from correlations between the ratio of the C IV line-width to the low ionization line-widths (Hα, Hβ and Mg II) and several other properties of rest-frame UV emission lines. Our analysis suggests that these correction methods are of limited applicability, mostly because all of them depend on correlations that are driven by the linewidth of the C IV profile itself and not by an interconnection between the linewidth of the C IV line with the linewidth of the low ionization lines. Our results show that optical C IV-based mass estimates at high redshift cannot be a proper replacement for estimates based on IR spectroscopy of low ionization lines like Hα, Hβ and Mg II.

Point Cloud Based Relative Pose Estimation of a Satellite in Close Range

Directory of Open Access Journals (Sweden)

Lujiang Liu

2016-06-01

Full Text Available Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective.

A simple method to estimate interwell autocorrelation

Energy Technology Data Exchange (ETDEWEB)

Pizarro, J.O.S.; Lake, L.W. [Univ. of Texas, Austin, TX (United States)

1997-08-01

The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.

Variable disparity estimation based intermediate view reconstruction in dynamic flow allocation over EPON-based access networks

Science.gov (United States)

Bae, Kyung-Hoon; Lee, Jungjoon; Kim, Eun-Soo

2008-06-01

In this paper, a variable disparity estimation (VDE)-based intermediate view reconstruction (IVR) in dynamic flow allocation (DFA) over an Ethernet passive optical network (EPON)-based access network is proposed. In the proposed system, the stereoscopic images are estimated by a variable block-matching algorithm (VBMA), and they are transmitted to the receiver through DFA over EPON. This scheme improves a priority-based access network by converting it to a flow-based access network with a new access mechanism and scheduling algorithm, and then 16-view images are synthesized by the IVR using VDE. Some experimental results indicate that the proposed system improves the peak-signal-to-noise ratio (PSNR) to as high as 4.86 dB and reduces the processing time to 3.52 s. Additionally, the network service provider can provide upper limits of transmission delays by the flow. The modeling and simulation results, including mathematical analyses, from this scheme are also provided.

Maximum Likelihood-Based Methods for Target Velocity Estimation with Distributed MIMO Radar

Directory of Open Access Journals (Sweden)

Zhenxin Cao

2018-02-01

Full Text Available The estimation problem for target velocity is addressed in this in the scenario with a distributed multi-input multi-out (MIMO radar system. A maximum likelihood (ML-based estimation method is derived with the knowledge of target position. Then, in the scenario without the knowledge of target position, an iterative method is proposed to estimate the target velocity by updating the position information iteratively. Moreover, the Carmér-Rao Lower Bounds (CRLBs for both scenarios are derived, and the performance degradation of velocity estimation without the position information is also expressed. Simulation results show that the proposed estimation methods can approach the CRLBs, and the velocity estimation performance can be further improved by increasing either the number of radar antennas or the information accuracy of the target position. Furthermore, compared with the existing methods, a better estimation performance can be achieved.

A dissociative electron attachment cross-section estimator

International Nuclear Information System (INIS)

Munro, James J; Harrison, Stephen; Fujimoto, Milton M; Tennyson, Jonathan

2012-01-01

Dissociative electron attachment (DEA) is the major process where molecules are destroyed in low-energy plasmas. DEA cross sections are therefore important for a whole variety of applications but are both hard to measure or compute accurately. A method for estimating DEA cross sections based a simple resonance plus survival model is presented. Test results are presented for DEA of molecular oxygen and molecular chlorine, for which experimental measurements are available for comparison, and SiBr and SiBr 2 , for which no previous data is available. The estimator has been implemented as part of Quantemol-N expert system which uses the R-matrix method to predict resonance positions and widths.

A Copula-Based Method for Estimating Shear Strength Parameters of Rock Mass

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Da Huang

2014-01-01

Full Text Available The shear strength parameters (i.e., the internal friction coefficient f and cohesion c are very important in rock engineering, especially for the stability analysis and reinforcement design of slopes and underground caverns. In this paper, a probabilistic method, Copula-based method, is proposed for estimating the shear strength parameters of rock mass. The optimal Copula functions between rock mass quality Q and f, Q and c for the marbles are established based on the correlation analyses of the results of 12 sets of in situ tests in the exploration adits of Jinping I-Stage Hydropower Station. Although the Copula functions are derived from the in situ tests for the marbles, they can be extended to be applied to other types of rock mass with similar geological and mechanical properties. For another 9 sets of in situ tests as an extensional application, by comparison with the results from Hoek-Brown criterion, the estimated values of f and c from the Copula-based method achieve better accuracy. Therefore, the proposed Copula-based method is an effective tool in estimating rock strength parameters.

PMICALC: an R code-based software for estimating post-mortem interval (PMI) compatible with Windows, Mac and Linux operating systems.

Science.gov (United States)

Muñoz-Barús, José I; Rodríguez-Calvo, María Sol; Suárez-Peñaranda, José M; Vieira, Duarte N; Cadarso-Suárez, Carmen; Febrero-Bande, Manuel

2010-01-30

In legal medicine the correct determination of the time of death is of utmost importance. Recent advances in estimating post-mortem interval (PMI) have made use of vitreous humour chemistry in conjunction with Linear Regression, but the results are questionable. In this paper we present PMICALC, an R code-based freeware package which estimates PMI in cadavers of recent death by measuring the concentrations of potassium ([K+]), hypoxanthine ([Hx]) and urea ([U]) in the vitreous humor using two different regression models: Additive Models (AM) and Support Vector Machine (SVM), which offer more flexibility than the previously used Linear Regression. The results from both models are better than those published to date and can give numerical expression of PMI with confidence intervals and graphic support within 20 min. The program also takes into account the cause of death. 2009 Elsevier Ireland Ltd. All rights reserved.

Markov Chain-Based Acute Effect Estimation of Air Pollution on Elder Asthma Hospitalization

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Li Luo

2017-01-01

Full Text Available Background. Asthma caused substantial economic and health care burden and is susceptible to air pollution. Particularly, when it comes to elder asthma patient (older than 65, the phenomenon is more significant. The aim of this study is to investigate the Markov-based acute effects of air pollution on elder asthma hospitalizations, in forms of transition probabilities. Methods. A retrospective, population-based study design was used to assess temporal patterns in hospitalizations for asthma in a region of Sichuan province, China. Approximately 12 million residents were covered during this period. Relative risk analysis and Markov chain model were employed on daily hospitalization state estimation. Results. Among PM2.5, PM10, NO2, and SO2, only SO2 was significant. When air pollution is severe, the transition probability from a low-admission state (previous day to high-admission state (next day is 35.46%, while it is 20.08% when air pollution is mild. In particular, for female-cold subgroup, the counterparts are 30.06% and 0.01%, respectively. Conclusions. SO2 was a significant risk factor for elder asthma hospitalization. When air pollution worsened, the transition probabilities from each state to high admission states increase dramatically. This phenomenon appeared more evidently, especially in female-cold subgroup (which is in cold season for female admissions. Based on our work, admission amount forecast, asthma intervention, and corresponding healthcare allocation can be done.

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.

Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

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Jinlei Sun

2015-05-01

Full Text Available The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharge experiments under different current rates are carried out on the same battery to verify the estimation results. The internal and surface temperatures are measured with thermocouples for result validation and model construction. The accuracy of the estimated result is validated with a maximum estimation error of around 1 K.

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 ...

An RSS based location estimation technique for cognitive relay networks

KAUST Repository

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

Rocket Based Combined Cycle Exchange Inlet Performance Estimation at Supersonic Speeds

Science.gov (United States)

Murzionak, Aliaksandr

A method to estimate the performance of an exchange inlet for a Rocket Based Combined Cycle engine is developed. This method is to be used for exchange inlet geometry optimization and as such should be able to predict properties that can be used in the design process within a reasonable amount of time to allow multiple configurations to be evaluated. The method is based on a curve fit of the shocks developed around the major components of the inlet using solutions for shocks around sharp cones and 2D estimations of the shocks around wedges with blunt leading edges. The total pressure drop across the estimated shocks as well as the mass flow rate through the exchange inlet are calculated. The estimations for a selected range of free-stream Mach numbers between 1.1 and 7 are compared against numerical finite volume method simulations which were performed using available commercial software (Ansys-CFX). The total pressure difference between the two methods is within 10% for the tested Mach numbers of 5 and below, while for the Mach 7 test case the difference is 30%. The mass flow rate on average differs by less than 5% for all tested cases with the maximum difference not exceeding 10%. The estimation method takes less than 3 seconds on 3.0 GHz single core processor to complete the calculations for a single flight condition as oppose to over 5 days on 8 cores at 2.4 GHz system while using 3D finite volume method simulation with 1.5 million elements mesh. This makes the estimation method suitable for the use with exchange inlet geometry optimization algorithm.

An automatic iris occlusion estimation method based on high-dimensional density estimation.

Science.gov (United States)

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.

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

Directory of Open Access Journals (Sweden)

Michael F Sloma

2017-11-01

Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

Science.gov (United States)

Sloma, Michael F; Mathews, David H

2017-11-01

Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

Power system state estimation using an iteratively reweighted least squares method for sequential L{sub 1}-regression

Energy Technology Data Exchange (ETDEWEB)

Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)

2006-02-15

This paper presents an implementation of the least absolute value (LAV) power system state estimator based on obtaining a sequence of solutions to the L{sub 1}-regression problem using an iteratively reweighted least squares (IRLS{sub L1}) method. The proposed implementation avoids reformulating the regression problem into standard linear programming (LP) form and consequently does not require the use of common methods of LP, such as those based on the simplex method or interior-point methods. It is shown that the IRLS{sub L1} method is equivalent to solving a sequence of linear weighted least squares (LS) problems. Thus, its implementation presents little additional effort since the sparse LS solver is common to existing LS state estimators. Studies on the termination criteria of the IRLS{sub L1} method have been carried out to determine a procedure for which the proposed estimator is more computationally efficient than a previously proposed non-linear iteratively reweighted least squares (IRLS) estimator. Indeed, it is revealed that the proposed method is a generalization of the previously reported IRLS estimator, but is based on more rigorous theory. (author)

HIV Model Parameter Estimates from Interruption Trial Data including Drug Efficacy and Reservoir Dynamics

Science.gov (United States)

Luo, Rutao; Piovoso, Michael J.; Martinez-Picado, Javier; Zurakowski, Ryan

2012-01-01

Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3–5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients. PMID:22815727

An estimator-based distributed voltage-predictive control strategy for ac islanded microgrids

DEFF Research Database (Denmark)

Wang, Yanbo; Chen, Zhe; Wang, Xiongfei

2015-01-01

This paper presents an estimator-based voltage predictive control strategy for AC islanded microgrids, which is able to perform voltage control without any communication facilities. The proposed control strategy is composed of a network voltage estimator and a voltage predictive controller for each...... and has a good capability to reject uncertain perturbations of islanded microgrids....

Optical and Acoustic Sensor-Based 3D Ball Motion Estimation for Ball Sport Simulators †

Directory of Open Access Journals (Sweden)

Sang-Woo Seo

2018-04-01

Full Text Available Estimation of the motion of ball-shaped objects is essential for the operation of ball sport simulators. In this paper, we propose an estimation system for 3D ball motion, including speed and angle of projection, by using acoustic vector and infrared (IR scanning sensors. Our system is comprised of three steps to estimate a ball motion: sound-based ball firing detection, sound source localization, and IR scanning for motion analysis. First, an impulsive sound classification based on the mel-frequency cepstrum and feed-forward neural network is introduced to detect the ball launch sound. An impulsive sound source localization using a 2D microelectromechanical system (MEMS microphones and delay-and-sum beamforming is presented to estimate the firing position. The time and position of a ball in 3D space is determined from a high-speed infrared scanning method. Our experimental results demonstrate that the estimation of ball motion based on sound allows a wider activity area than similar camera-based methods. Thus, it can be practically applied to various simulations in sports such as soccer and baseball.

Estimating individual listeners’ auditory-filter bandwidth in simultaneous and non-simultaneous masking

DEFF Research Database (Denmark)

Buchholz, Jörg; Caminade, Sabine; Strelcyk, Olaf

2010-01-01

Frequency selectivity in the human auditory system is often measured using simultaneous masking of tones presented in notched noise. Based on such masking data, the equivalent rectangular bandwidth (ERB) of the auditory filters can be derived by applying the power spectrum model of masking....... Considering bandwidth estimates from previous studies based on forward masking, only average data across a number of subjects have been considered. The present study is concerned with bandwidth estimates in simultaneous and forward masking in individual normal-hearing subjects. In order to investigate...... the reliability of the individual estimates, a statistical resampling method is applied. It is demonstrated that a rather large set of experimental data is required to reliably estimate auditory filter bandwidth, particularly in the case of simultaneous masking. The poor overall reliability of the filter...

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Prediction of successful trial of labour in patients with a previous caesarean section

International Nuclear Information System (INIS)

Shaheen, N.; Khalil, S.; Iftikhar, P.

2014-01-01

Objective: To determine the prediction rate of success in trial of labour after one previous caesarean section. Methods: The cross-sectional study was conducted at the Department of Obstetrics and Gynaecology, Cantonment General Hospital, Rawalpindi, from January 1, 2012 to January 31, 2013, and comprised women with one previous Caesarean section and with single alive foetus at 37-41 weeks of gestation. Women with more than one Caesarean section, unknown site of uterine scar, bony pelvic deformity, placenta previa, intra-uterine growth restriction, deep transverse arrest in previous labour and non-reassuring foetal status at the time of admission were excluded. Intrapartum risk assessment included Bishop score at admission, rate of cervical dilatation and scar tenderness. SPSS 21 was used for statistical analysis. Results: Out of a total of 95 women, the trial was successful in 68 (71.6%). Estimated foetal weight and number of prior vaginal deliveries had a high predictive value for successful trial of labour after Caesarean section. Estimated foetal weight had an odds ratio of 0.46 (p<0.001), while number of prior vaginal deliveries had an odds ratio of 0.85 with (p=0.010). Other factors found to be predictive of successful trial included Bishop score at the time of admission (p<0.037) and rate of cervical dilatation in the first stage of labour (p<0.021). Conclusion: History of prior vaginal deliveries, higher Bishop score at the time of admission, rapid rate of cervical dilatation and lower estimated foetal weight were predictive of a successful trial of labour after Caesarean section. (author)

Measurements for kinetic parameters estimation in the RA-0 research reactor

International Nuclear Information System (INIS)

Gomez, A; Bellino, P A

2012-01-01

In the present work, measurements based on the neutron noise technique and the inverse kinetic method were performed to estimate the different kinetic parameters of the reactor in its critical state. By means of the neutron noise technique, we obtained the current calibration factor of the ionization chamber M6 belonging to the power range channels of the reactor instrumentation. The maximum current allowed compatible with the maximum power authorized by the operation license was also obtained. Using the neutron noise technique, the reduced mean reproduction time (Λ*) was estimated. This parameter plays a fundamental role in the deterministic analysis of criticality accidents. Comparison with previous values justified performing new measurements to study systematic trends in the value of Λ*. Using the inverse kinetics method, the reactivity worth of the control rods was estimated, confirming the existence of spatial effects and trends previously observed (author)

Estimating solar irradiation in the Arctic

Directory of Open Access Journals (Sweden)

Babar Bilal

2016-01-01

Full Text Available Solar radiation data plays an important role in pre-feasibility studies of solar electricity and/or thermal system installations. Measured solar radiation data is scarcely available due to the high cost of installing and maintaining high quality solar radiation sensors (pyranometers. Indirect measured radiation data received from geostationary satellites is unreliable at latitudes above 60 degrees due to the resulting flat viewing angle. In this paper, an empirical method to estimate solar radiation based on minimum climatological data is proposed. Eight sites in Norway are investigated, all of which lie above 60 N. The estimations by the model are compared to the ground measured values and a correlation coefficient of 0.88 was found while over all percentage error was −1.1%. The proposed models is 0.2% efficient on diurnal and 10.8% better in annual estimations than previous models.

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 application of particle filters in single trial event-related potential estimation

International Nuclear Information System (INIS)

Mohseni, Hamid R; Nazarpour, Kianoush; Sanei, Saeid; Wilding, Edward L

2009-01-01

In this paper, an approach for the estimation of single trial event-related potentials (ST-ERPs) using particle filters (PFs) is presented. The method is based on recursive Bayesian mean square estimation of ERP wavelet coefficients using their previous estimates as prior information. To enable a performance evaluation of the approach in the Gaussian and non-Gaussian distributed noise conditions, we added Gaussian white noise (GWN) and real electroencephalogram (EEG) signals recorded during rest to the simulated ERPs. The results were compared to that of the Kalman filtering (KF) approach demonstrating the robustness of the PF over the KF to the added GWN noise. The proposed method also outperforms the KF when the assumption about the Gaussianity of the noise is violated. We also applied this technique to real EEG potentials recorded in an odd-ball paradigm and investigated the correlation between the amplitude and the latency of the estimated ERP components. Unlike the KF method, for the PF there was a statistically significant negative correlation between amplitude and latency of the estimated ERPs, matching previous neurophysiological findings

Comparison of Prevalence- and Smoking Impact Ratio-Based Methods of Estimating Smoking-Attributable Fractions of Deaths

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Kyoung Ae Kong

2016-04-01

Full Text Available Background: Smoking is a major modifiable risk factor for premature mortality. Estimating the smoking-attributable burden is important for public health policy. Typically, prevalence- or smoking impact ratio (SIR-based methods are used to derive estimates, but there is controversy over which method is more appropriate for country-specific estimates. We compared smoking-attributable fractions (SAFs of deaths estimated by these two methods. Methods: To estimate SAFs in 2012, we used several different prevalence-based approaches using no lag and 10- and 20-year lags. For the SIR-based method, we obtained lung cancer mortality rates from the Korean Cancer Prevention Study (KCPS and from the United States-based Cancer Prevention Study-II (CPS-II. The relative risks for the diseases associated with smoking were also obtained from these cohort studies. Results: For males, SAFs obtained using KCPS-derived SIRs were similar to those obtained using prevalence-based methods. For females, SAFs obtained using KCPS-derived SIRs were markedly greater than all prevalence-based SAFs. Differences in prevalence-based SAFs by time-lag period were minimal among males, but SAFs obtained using longer-lagged prevalence periods were significantly larger among females. SAFs obtained using CPS-II-based SIRs were lower than KCPS-based SAFs by >15 percentage points for most diseases, with the exceptions of lung cancer and chronic obstructive pulmonary disease. Conclusions: SAFs obtained using prevalence- and SIR-based methods were similar for males. However, neither prevalence-based nor SIR-based methods resulted in precise SAFs among females. The characteristics of the study population should be carefully considered when choosing a method to estimate SAF.

Direction-of-Arrival Estimation Based on Sparse Recovery with Second-Order Statistics

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H. Chen

2015-04-01

Full Text Available Traditional direction-of-arrival (DOA estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an $ell_1$ minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal.

Archimedean copula estimation of distribution algorithm based on artificial bee colony algorithm

Institute of Scientific and Technical Information of China (English)

Haidong Xu; Mingyan Jiang; Kun Xu

2015-01-01

The artificial bee colony (ABC) algorithm is a com-petitive stochastic population-based optimization algorithm. How-ever, the ABC algorithm does not use the social information and lacks the knowledge of the problem structure, which leads to in-sufficiency in both convergent speed and searching precision. Archimedean copula estimation of distribution algorithm (ACEDA) is a relatively simple, time-economic and multivariate correlated EDA. This paper proposes a novel hybrid algorithm based on the ABC algorithm and ACEDA cal ed Archimedean copula estima-tion of distribution based on the artificial bee colony (ACABC) algorithm. The hybrid algorithm utilizes ACEDA to estimate the distribution model and then uses the information to help artificial bees to search more efficiently in the search space. Six bench-mark functions are introduced to assess the performance of the ACABC algorithm on numerical function optimization. Experimen-tal results show that the ACABC algorithm converges much faster with greater precision compared with the ABC algorithm, ACEDA and the global best (gbest)-guided ABC (GABC) algorithm in most of the experiments.

Stand-scale soil respiration estimates based on chamber methods in a Bornean tropical rainforest

Science.gov (United States)

Kume, T.; Katayama, A.; Komatsu, H.; Ohashi, M.; Nakagawa, M.; Yamashita, M.; Otsuki, K.; Suzuki, M.; Kumagai, T.

2009-12-01

This study was undertaken to estimate stand-scale soil respiration in an aseasonal tropical rainforest on Borneo Island. To this aim, we identified critical and practical factors explaining spatial variations in soil respiration based on the soil respiration measurements conducted at 25 points in a 40 × 40 m subplot of a 4 ha study plot for five years in relation to soil, root, and forest structural factors. Consequently, we found significant positive correlation between the soil respiration and forest structural parameters. The most important factor was the mean DBH within 6 m of the measurement points, which had a significant linear relationship with soil respiration. Using the derived linear regression and an inventory dataset, we estimated the 4 ha-scale soil respiration. The 4 ha-scale estimation (6.0 μmol m-2 s-1) was nearly identical to the subplot scale measurements (5.7 μmol m-2 s-1), which were roughly comparable to the nocturnal CO2 fluxes calculated using the eddy covariance technique. To confirm the spatial representativeness of soil respiration estimates in the subplot, we performed variogram analysis. Semivariance of DBH(6) in the 4 ha plot showed that there was autocorrelation within the separation distance of about 20 m, and that the spatial dependence was unclear at a separation distance of greater than 20 m. This ascertained that the 40 × 40 m subplot could represent the whole forest structure in the 4 ha plot. In addition, we discuss characteristics of the stand-scale soil respiration at this site by comparing with those of other forests reported in previous literature in terms of the soil C balance. Soil respiration at our site was noticeably greater, relative to the incident litterfall amount, than soil respiration in other tropical and temperate forests probably owing to the larger total belowground C allocation by emergent trees. Overall, this study suggests the arrangement of emergent trees and their bellow ground C allocation could be