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Sample records for estimate method based

  1. 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)

  2. 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.

  3. Correction of Misclassifications Using a Proximity-Based Estimation Method

    Directory of Open Access Journals (Sweden)

    Shmulevich Ilya

    2004-01-01

    Full Text Available An estimation method for correcting misclassifications in signal and image processing is presented. The method is based on the use of context-based (temporal or spatial information in a sliding-window fashion. The classes can be purely nominal, that is, an ordering of the classes is not required. The method employs nonlinear operations based on class proximities defined by a proximity matrix. Two case studies are presented. In the first, the proposed method is applied to one-dimensional signals for processing data that are obtained by a musical key-finding algorithm. In the second, the estimation method is applied to two-dimensional signals for correction of misclassifications in images. In the first case study, the proximity matrix employed by the estimation method follows directly from music perception studies, whereas in the second case study, the optimal proximity matrix is obtained with genetic algorithms as the learning rule in a training-based optimization framework. Simulation results are presented in both case studies and the degree of improvement in classification accuracy that is obtained by the proposed method is assessed statistically using Kappa analysis.

  4. 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)

  5. 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)

  6. 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)

  7. 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...

  8. 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.

  9. 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.

  10. 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)

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation

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    Tianshuang Qiu

    2007-12-01

    Full Text Available This paper proposes a geometric method to locate a mobile station (MS in a mobile cellular network when both the range and angle measurements are corrupted by non-line-of-sight (NLOS errors. The MS location is restricted to an enclosed region by geometric constraints from the temporal-spatial characteristics of the radio propagation channel. A closed-form equation of the MS position, time of arrival (TOA, angle of arrival (AOA, and angle spread is provided. The solution space of the equation is very large because the angle spreads are random variables in nature. A constrained objective function is constructed to further limit the MS position. A Lagrange multiplier-based solution and a numerical solution are proposed to resolve the MS position. The estimation quality of the estimator in term of “biased” or “unbiased” is discussed. The scale factors, which may be used to evaluate NLOS propagation level, can be estimated by the proposed method. AOA seen at base stations may be corrected to some degree. The performance comparisons among the proposed method and other hybrid location methods are investigated on different NLOS error models and with two scenarios of cell layout. It is found that the proposed method can deal with NLOS error effectively, and it is attractive for location estimation in cellular networks.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Phase-Inductance-Based Position Estimation Method for Interior Permanent Magnet Synchronous Motors

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    Xin Qiu

    2017-12-01

    Full Text Available This paper presents a phase-inductance-based position estimation method for interior permanent magnet synchronous motors (IPMSMs. According to the characteristics of phase induction of IPMSMs, the corresponding relationship of the rotor position and the phase inductance is obtained. In order to eliminate the effect of the zero-sequence component of phase inductance and reduce the rotor position estimation error, the phase inductance difference is employed. With the iterative computation of inductance vectors, the position plane is further subdivided, and the rotor position is extracted by comparing the amplitudes of inductance vectors. To decrease the consumption of computer resources and increase the practicability, a simplified implementation is also investigated. In this method, the rotor position information is achieved easily, with several basic math operations and logical comparisons of phase inductances, without any coordinate transformation or trigonometric function calculation. Based on this position estimation method, the field orientated control (FOC strategy is established, and the detailed implementation is also provided. A series of experiment results from a prototype demonstrate the correctness and feasibility of the proposed method.

  2. The Software Cost Estimation Method Based on Fuzzy Ontology

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    Plecka Przemysław

    2014-12-01

    Full Text Available In the course of sales process of Enterprise Resource Planning (ERP Systems, it turns out that the standard system must be extended or changed (modified according to specific customer’s requirements. Therefore, suppliers face the problem of determining the cost of additional works. Most methods of cost estimation bring satisfactory results only at the stage of pre-implementation analysis. However, suppliers need to know the estimated cost as early as at the stage of trade talks. During contract negotiations, they expect not only the information about the costs of works, but also about the risk of exceeding these costs or about the margin of safety. One method that gives more accurate results at the stage of trade talks is the method based on the ontology of implementation costs. This paper proposes modification of the method involving the use of fuzzy attributes, classes, instances and relations in the ontology. The result provides not only the information about the value of work, but also about the minimum and maximum expected cost, and the most likely range of costs. This solution allows suppliers to effectively negotiate the contract and increase the chances of successful completion of the project.

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

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    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.

  4. Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

    Science.gov (United States)

    Gong, W.; Duan, Q.; Huo, X.

    2017-12-01

    Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

  5. Reliability analysis based on a novel density estimation method for structures with correlations

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    Baoyu LI

    2017-06-01

    Full Text Available Estimating the Probability Density Function (PDF of the performance function is a direct way for structural reliability analysis, and the failure probability can be easily obtained by integration in the failure domain. However, efficiently estimating the PDF is still an urgent problem to be solved. The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation, whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs. While in fact, structures with correlated inputs always exist in engineering, thus this paper improves the maximum entropy method, and applies the Unscented Transformation (UT technique to compute the fractional moments of the performance function for structures with correlations, which is a very efficient moment estimation method for models with any inputs. The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations. Besides, the number of function evaluations of the proposed method in reliability analysis, which is determined by UT, is really small. Several examples are employed to illustrate the accuracy and advantages of the proposed method.

  6. Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

    Directory of Open Access Journals (Sweden)

    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.

  7. 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

  8. 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...

  9. Inertial sensor-based methods in walking speed estimation: a systematic review.

    Science.gov (United States)

    Yang, Shuozhi; Li, Qingguo

    2012-01-01

    Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

  10. Inertial Sensor-Based Methods in Walking Speed Estimation: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Qingguo Li

    2012-05-01

    Full Text Available Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

  11. Estimation of the flow resistances exerted in coronary arteries using a vessel length-based method.

    Science.gov (United States)

    Lee, Kyung Eun; Kwon, Soon-Sung; Ji, Yoon Cheol; Shin, Eun-Seok; Choi, Jin-Ho; Kim, Sung Joon; Shim, Eun Bo

    2016-08-01

    Flow resistances exerted in the coronary arteries are the key parameters for the image-based computer simulation of coronary hemodynamics. The resistances depend on the anatomical characteristics of the coronary system. A simple and reliable estimation of the resistances is a compulsory procedure to compute the fractional flow reserve (FFR) of stenosed coronary arteries, an important clinical index of coronary artery disease. The cardiac muscle volume reconstructed from computed tomography (CT) images has been used to assess the resistance of the feeding coronary artery (muscle volume-based method). In this study, we estimate the flow resistances exerted in coronary arteries by using a novel method. Based on a physiological observation that longer coronary arteries have more daughter branches feeding a larger mass of cardiac muscle, the method measures the vessel lengths from coronary angiogram or CT images (vessel length-based method) and predicts the coronary flow resistances. The underlying equations are derived from the physiological relation among flow rate, resistance, and vessel length. To validate the present estimation method, we calculate the coronary flow division over coronary major arteries for 50 patients using the vessel length-based method as well as the muscle volume-based one. These results are compared with the direct measurements in a clinical study. Further proving the usefulness of the present method, we compute the coronary FFR from the images of optical coherence tomography.

  12. Power System Real-Time Monitoring by Using PMU-Based Robust State Estimation Method

    DEFF Research Database (Denmark)

    Zhao, Junbo; Zhang, Gexiang; Das, Kaushik

    2016-01-01

    Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions...... the system real-time states with good robustness and can address several kinds of BD.......-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track...

  13. Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification.

    Science.gov (United States)

    Caumes, Géraldine; Borrel, Alexandre; Abi Hussein, Hiba; Camproux, Anne-Claude; Regad, Leslie

    2017-09-01

    Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket-based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket-estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket-estimation methods on the results of pocket-based approaches. We focused on the effect of three pocket-estimation methods on a pocket-ligand (PL) classification. This pocket-based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket-estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket-estimation method choice in pocket-based approaches. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. A postprocessing method based on high-resolution spectral estimation for FDTD calculation of phononic band structures

    Energy Technology Data Exchange (ETDEWEB)

    Su Xiaoxing, E-mail: xxsu@bjtu.edu.c [School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044 (China); Li Jianbao; Wang Yuesheng [Institute of Engineering Mechanics, Beijing Jiaotong University, Beijing 100044 (China)

    2010-05-15

    If the energy bands of a phononic crystal are calculated by the finite difference time domain (FDTD) method combined with the fast Fourier transform (FFT), good estimation of the eigenfrequencies can only be ensured by the postprocessing of sufficiently long time series generated by a large number of FDTD iterations. In this paper, a postprocessing method based on the high-resolution spectral estimation via the Yule-Walker method is proposed to overcome this difficulty. Numerical simulation results for three-dimensional acoustic and two-dimensional elastic systems show that, compared with the classic FFT-based postprocessing method, the proposed method can give much better estimation of the eigenfrequencies when the FDTD is run with relatively few iterations.

  15. A postprocessing method based on high-resolution spectral estimation for FDTD calculation of phononic band structures

    International Nuclear Information System (INIS)

    Su Xiaoxing; Li Jianbao; Wang Yuesheng

    2010-01-01

    If the energy bands of a phononic crystal are calculated by the finite difference time domain (FDTD) method combined with the fast Fourier transform (FFT), good estimation of the eigenfrequencies can only be ensured by the postprocessing of sufficiently long time series generated by a large number of FDTD iterations. In this paper, a postprocessing method based on the high-resolution spectral estimation via the Yule-Walker method is proposed to overcome this difficulty. Numerical simulation results for three-dimensional acoustic and two-dimensional elastic systems show that, compared with the classic FFT-based postprocessing method, the proposed method can give much better estimation of the eigenfrequencies when the FDTD is run with relatively few iterations.

  16. Missing texture reconstruction method based on error reduction algorithm using Fourier transform magnitude estimation scheme.

    Science.gov (United States)

    Ogawa, Takahiro; Haseyama, Miki

    2013-03-01

    A missing texture reconstruction method based on an error reduction (ER) algorithm, including a novel estimation scheme of Fourier transform magnitudes is presented in this brief. In our method, Fourier transform magnitude is estimated for a target patch including missing areas, and the missing intensities are estimated by retrieving its phase based on the ER algorithm. Specifically, by monitoring errors converged in the ER algorithm, known patches whose Fourier transform magnitudes are similar to that of the target patch are selected from the target image. In the second approach, the Fourier transform magnitude of the target patch is estimated from those of the selected known patches and their corresponding errors. Consequently, by using the ER algorithm, we can estimate both the Fourier transform magnitudes and phases to reconstruct the missing areas.

  17. A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks.

    Science.gov (United States)

    Cui, Xuerong; Li, Juan; Wu, Chunlei; Liu, Jian-Hang

    2015-11-13

    Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments.

  18. A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks

    Directory of Open Access Journals (Sweden)

    Xuerong Cui

    2015-11-01

    Full Text Available Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR environments.

  19. An improved principal component analysis based region matching method for fringe direction estimation

    Science.gov (United States)

    He, A.; Quan, C.

    2018-04-01

    The principal component analysis (PCA) and region matching combined method is effective for fringe direction estimation. However, its mask construction algorithm for region matching fails in some circumstances, and the algorithm for conversion of orientation to direction in mask areas is computationally-heavy and non-optimized. We propose an improved PCA based region matching method for the fringe direction estimation, which includes an improved and robust mask construction scheme, and a fast and optimized orientation-direction conversion algorithm for the mask areas. Along with the estimated fringe direction map, filtered fringe pattern by automatic selective reconstruction modification and enhanced fast empirical mode decomposition (ASRm-EFEMD) is used for Hilbert spiral transform (HST) to demodulate the phase. Subsequently, windowed Fourier ridge (WFR) method is used for the refinement of the phase. The robustness and effectiveness of proposed method are demonstrated by both simulated and experimental fringe patterns.

  20. A Method of Nuclear Software Reliability Estimation

    International Nuclear Information System (INIS)

    Park, Gee Yong; Eom, Heung Seop; Cheon, Se Woo; Jang, Seung Cheol

    2011-01-01

    A method on estimating software reliability for nuclear safety software is proposed. This method is based on the software reliability growth model (SRGM) where the behavior of software failure is assumed to follow the non-homogeneous Poisson process. Several modeling schemes are presented in order to estimate and predict more precisely the number of software defects based on a few of software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating the software test cases into the model. It is identified that this method is capable of accurately estimating the remaining number of software defects which are on-demand type directly affecting safety trip functions. The software reliability can be estimated from a model equation and one method of obtaining the software reliability is proposed

  1. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien; Claudel, Christian G.

    2015-01-01

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  2. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien

    2015-12-30

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  3. Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations.

    Science.gov (United States)

    Checchi, Francesco; Stewart, Barclay T; Palmer, Jennifer J; Grundy, Chris

    2013-01-23

    Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Our method consisted of multiplying (i) manual counts of assumed residential structures on a satellite image and (ii) estimates of the mean number of people per structure (structure occupancy) obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons' camps and two urban neighbourhoods with a mixture of residents and displaced) ranging in population from 1,969 to 90,547, and compared these to "gold standard" reference population figures from census or other robust methods. Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of layout. For each site, estimates were produced in 2-5 working person-days. In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method's development.

  4. Costate Estimation of PMP-Based Control Strategy for PHEV Using Legendre Pseudospectral Method

    Directory of Open Access Journals (Sweden)

    Hanbing Wei

    2016-01-01

    Full Text Available Costate value plays a significant role in the application of PMP-based control strategy for PHEV. It is critical for terminal SOC of battery at destination and corresponding equivalent fuel consumption. However, it is not convenient to choose the approximate costate in real driving condition. In the paper, the optimal control problem of PHEV based on PMP has been converted to nonlinear programming problem. By means of KKT condition costate can be approximated as KKT multipliers of NLP divided by the LGL weights. A kind of general costate estimation approach is proposed for predefined driving condition in this way. Dynamic model has been established in Matlab/Simulink in order to prove the effectiveness of the method. Simulation results demonstrate that the method presented in the paper can deduce the closer value of global optimal value than constant initial costate value. This approach can be used for initial costate and jump condition estimation of PMP-based control strategy for PHEV.

  5. Feasibility Study on Tension Estimation Technique for Hanger Cables Using the FE Model-Based System Identification Method

    Directory of Open Access Journals (Sweden)

    Kyu-Sik Park

    2015-01-01

    Full Text Available Hanger cables in suspension bridges are partly constrained by horizontal clamps. So, existing tension estimation methods based on a single cable model are prone to higher errors as the cable gets shorter, making it more sensitive to flexural rigidity. Therefore, inverse analysis and system identification methods based on finite element models are suggested recently. In this paper, the applicability of system identification methods is investigated using the hanger cables of Gwang-An bridge. The test results show that the inverse analysis and systemic identification methods based on finite element models are more reliable than the existing string theory and linear regression method for calculating the tension in terms of natural frequency errors. However, the estimation error of tension can be varied according to the accuracy of finite element model in model based methods. In particular, the boundary conditions affect the results more profoundly when the cable gets shorter. Therefore, it is important to identify the boundary conditions through experiment if it is possible. The FE model-based tension estimation method using system identification method can take various boundary conditions into account. Also, since it is not sensitive to the number of natural frequency inputs, the availability of this system is high.

  6. A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

    Science.gov (United States)

    Cai, Jianhua

    2017-05-01

    The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

  7. 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.

  8. Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity

    NARCIS (Netherlands)

    Pellikaan, P.; van der Krogt, Marjolein; Carbone, Vincenzo; Fluit, René; Vigneron, L.M.; van Deun, J.; Verdonschot, Nicolaas Jacobus Joseph; Koopman, Hubertus F.J.M.

    2014-01-01

    To generate subject-specific musculoskeletal models for clinical use, the location of muscle attachment sites needs to be estimated with accurate, fast and preferably automated tools. For this purpose, an automatic method was used to estimate the muscle attachment sites of the lower extremity, based

  9. Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations

    KAUST Repository

    Asiri, Sharefa M.; Laleg-Kirati, Taous-Meriem

    2016-01-01

    In this paper, modulating functions-based method is proposed for estimating space–time-dependent unknowns in one-dimensional partial differential equations. The proposed method simplifies the problem into a system of algebraic equations linear

  10. A Novel Method Based on Oblique Projection Technology for Mixed Sources Estimation

    Directory of Open Access Journals (Sweden)

    Weijian Si

    2014-01-01

    Full Text Available Reducing the computational complexity of the near-field sources and far-field sources localization algorithms has been considered as a serious problem in the field of array signal processing. A novel algorithm caring for mixed sources location estimation based on oblique projection is proposed in this paper. The sources are estimated at two different stages and the sensor noise power is estimated and eliminated from the covariance which improve the accuracy of the estimation of mixed sources. Using the idea of compress, the range information of near-field sources is obtained by searching the partial area instead of the whole Fresnel area which can reduce the processing time. Compared with the traditional algorithms, the proposed algorithm has the lower computation complexity and has the ability to solve the two closed-spaced sources with high resolution and accuracy. The duplication of range estimation is also avoided. Finally, simulation results are provided to demonstrate the performance of the proposed method.

  11. An efficient modularized sample-based method to estimate the first-order Sobol' index

    International Nuclear Information System (INIS)

    Li, Chenzhao; Mahadevan, Sankaran

    2016-01-01

    Sobol' index is a prominent methodology in global sensitivity analysis. This paper aims to directly estimate the Sobol' index based only on available input–output samples, even if the underlying model is unavailable. For this purpose, a new method to calculate the first-order Sobol' index is proposed. The innovation is that the conditional variance and mean in the formula of the first-order index are calculated at an unknown but existing location of model inputs, instead of an explicit user-defined location. The proposed method is modularized in two aspects: 1) index calculations for different model inputs are separate and use the same set of samples; and 2) model input sampling, model evaluation, and index calculation are separate. Due to this modularization, the proposed method is capable to compute the first-order index if only input–output samples are available but the underlying model is unavailable, and its computational cost is not proportional to the dimension of the model inputs. In addition, the proposed method can also estimate the first-order index with correlated model inputs. Considering that the first-order index is a desired metric to rank model inputs but current methods can only handle independent model inputs, the proposed method contributes to fill this gap. - Highlights: • An efficient method to estimate the first-order Sobol' index. • Estimate the index from input–output samples directly. • Computational cost is not proportional to the number of model inputs. • Handle both uncorrelated and correlated model inputs.

  12. A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2015-12-01

    Full Text Available Estimating the residual capacity or state-of-charge (SoC of commercial batteries on-line without destroying them or interrupting the power supply, is quite a challenging task for electric vehicle (EV designers. Many Coulomb counting-based methods have been used to calculate the remaining capacity in EV batteries or other portable devices. The main disadvantages of these methods are the cumulative error and the time-varying Coulombic efficiency, which are greatly influenced by the operating state (SoC, temperature and current. To deal with this problem, we propose a lossy counting-based Coulomb counting method for estimating the available capacity or SoC. The initial capacity of the tested battery is obtained from the open circuit voltage (OCV. The charging/discharging efficiencies, used for compensating the Coulombic losses, are calculated by the lossy counting-based method. The measurement drift, resulting from the current sensor, is amended with the distorted Coulombic efficiency matrix. Simulations and experimental results show that the proposed method is both effective and convenient.

  13. Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity.

    Science.gov (United States)

    Pellikaan, P; van der Krogt, M M; Carbone, V; Fluit, R; Vigneron, L M; Van Deun, J; Verdonschot, N; Koopman, H F J M

    2014-03-21

    To generate subject-specific musculoskeletal models for clinical use, the location of muscle attachment sites needs to be estimated with accurate, fast and preferably automated tools. For this purpose, an automatic method was used to estimate the muscle attachment sites of the lower extremity, based on the assumption of a relation between the bone geometry and the location of muscle attachment sites. The aim of this study was to evaluate the accuracy of this morphing based method. Two cadaver dissections were performed to measure the contours of 72 muscle attachment sites on the pelvis, femur, tibia and calcaneus. The geometry of the bones including the muscle attachment sites was morphed from one cadaver to the other and vice versa. For 69% of the muscle attachment sites, the mean distance between the measured and morphed muscle attachment sites was smaller than 15 mm. Furthermore, the muscle attachment sites that had relatively large distances had shown low sensitivity to these deviations. Therefore, this morphing based method is a promising tool for estimating subject-specific muscle attachment sites in the lower extremity in a fast and automated manner. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Vce-based methods for temperature estimation of high power IGBT modules during power cycling - A comparison

    DEFF Research Database (Denmark)

    Amoiridis, Anastasios; Anurag, Anup; Ghimire, Pramod

    2015-01-01

    . This experimental work evaluates the validity and accuracy of two Vce based methods applied on high power IGBT modules during power cycling tests. The first method estimates the chip temperature when low sense current is applied and the second method when normal load current is present. Finally, a correction factor......Temperature estimation is of great importance for performance and reliability of IGBT power modules in converter operation as well as in active power cycling tests. It is common to be estimated through Thermo-Sensitive Electrical Parameters such as the forward voltage drop (Vce) of the chip...

  15. 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.

  16. A method for state of energy estimation of lithium-ion batteries based on neural network model

    International Nuclear Information System (INIS)

    Dong, Guangzhong; Zhang, Xu; Zhang, Chenbin; Chen, Zonghai

    2015-01-01

    The state-of-energy is an important evaluation index for energy optimization and management of power battery systems in electric vehicles. Unlike the state-of-charge which represents the residual energy of the battery in traditional applications, state-of-energy is integral result of battery power, which is the product of current and terminal voltage. On the other hand, like state-of-charge, the state-of-energy has an effect on terminal voltage. Therefore, it is hard to solve the nonlinear problems between state-of-energy and terminal voltage, which will complicate the estimation of a battery's state-of-energy. To address this issue, a method based on wavelet-neural-network-based battery model and particle filter estimator is presented for the state-of-energy estimation. The wavelet-neural-network based battery model is used to simulate the entire dynamic electrical characteristics of batteries. The temperature and discharge rate are also taken into account to improve model accuracy. Besides, in order to suppress the measurement noises of current and voltage, a particle filter estimator is applied to estimate cell state-of-energy. Experimental results on LiFePO_4 batteries indicate that the wavelet-neural-network based battery model simulates battery dynamics robustly with high accuracy and the estimation value based on the particle filter estimator converges to the real state-of-energy within an error of ±4%. - Highlights: • State-of-charge is replaced by state-of-energy to determine cells residual energy. • The battery state-space model is established based on a neural network. • Temperature and current influence are considered to improve the model accuracy. • The particle filter is used for state-of-energy estimation to improve accuracy. • The robustness of new method is validated under dynamic experimental conditions.

  17. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

    Science.gov (United States)

    Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

    2017-02-20

    In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  18. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

    Directory of Open Access Journals (Sweden)

    Anbang Zhao

    2017-02-01

    Full Text Available In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  19. A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

    2017-11-01

    In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.

  20. A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

    Science.gov (United States)

    Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

    2017-11-01

    In this study, a data-driven method for predicting CO 2 leaks and associated concentrations from geological CO 2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO 2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO 2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO 2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. A Parameter Estimation Method for Nonlinear Systems Based on Improved Boundary Chicken Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Shaolong Chen

    2016-01-01

    Full Text Available Parameter estimation is an important problem in nonlinear system modeling and control. Through constructing an appropriate fitness function, parameter estimation of system could be converted to a multidimensional parameter optimization problem. As a novel swarm intelligence algorithm, chicken swarm optimization (CSO has attracted much attention owing to its good global convergence and robustness. In this paper, a method based on improved boundary chicken swarm optimization (IBCSO is proposed for parameter estimation of nonlinear systems, demonstrated and tested by Lorenz system and a coupling motor system. Furthermore, we have analyzed the influence of time series on the estimation accuracy. Computer simulation results show it is feasible and with desirable performance for parameter estimation of nonlinear systems.

  2. Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research.

    Science.gov (United States)

    Wu, Hulin; Xue, Hongqi; Kumar, Arun

    2012-06-01

    Differential equations are extensively used for modeling dynamics of physical processes in many scientific fields such as engineering, physics, and biomedical sciences. Parameter estimation of differential equation models is a challenging problem because of high computational cost and high-dimensional parameter space. In this article, we propose a novel class of methods for estimating parameters in ordinary differential equation (ODE) models, which is motivated by HIV dynamics modeling. The new methods exploit the form of numerical discretization algorithms for an ODE solver to formulate estimating equations. First, a penalized-spline approach is employed to estimate the state variables and the estimated state variables are then plugged in a discretization formula of an ODE solver to obtain the ODE parameter estimates via a regression approach. We consider three different order of discretization methods, Euler's method, trapezoidal rule, and Runge-Kutta method. A higher-order numerical algorithm reduces numerical error in the approximation of the derivative, which produces a more accurate estimate, but its computational cost is higher. To balance the computational cost and estimation accuracy, we demonstrate, via simulation studies, that the trapezoidal discretization-based estimate is the best and is recommended for practical use. The asymptotic properties for the proposed numerical discretization-based estimators are established. Comparisons between the proposed methods and existing methods show a clear benefit of the proposed methods in regards to the trade-off between computational cost and estimation accuracy. We apply the proposed methods t an HIV study to further illustrate the usefulness of the proposed approaches. © 2012, The International Biometric Society.

  3. Power system frequency estimation based on an orthogonal decomposition method

    Science.gov (United States)

    Lee, Chih-Hung; Tsai, Men-Shen

    2018-06-01

    In recent years, several frequency estimation techniques have been proposed by which to estimate the frequency variations in power systems. In order to properly identify power quality issues under asynchronously-sampled signals that are contaminated with noise, flicker, and harmonic and inter-harmonic components, a good frequency estimator that is able to estimate the frequency as well as the rate of frequency changes precisely is needed. However, accurately estimating the fundamental frequency becomes a very difficult task without a priori information about the sampling frequency. In this paper, a better frequency evaluation scheme for power systems is proposed. This method employs a reconstruction technique in combination with orthogonal filters, which may maintain the required frequency characteristics of the orthogonal filters and improve the overall efficiency of power system monitoring through two-stage sliding discrete Fourier transforms. The results showed that this method can accurately estimate the power system frequency under different conditions, including asynchronously sampled signals contaminated by noise, flicker, and harmonic and inter-harmonic components. The proposed approach also provides high computational efficiency.

  4. Joint Pitch and DOA Estimation Using the ESPRIT method

    DEFF Research Database (Denmark)

    Wu, Yuntao; Amir, Leshem; Jensen, Jesper Rindom

    2015-01-01

    In this paper, the problem of joint multi-pitch and direction-of-arrival (DOA) estimation for multi-channel harmonic sinusoidal signals is considered. A spatio-temporal matrix signal model for a uniform linear array is defined, and then the ESPRIT method based on subspace techniques that exploits...... the invariance property in the time domain is first used to estimate the multi pitch frequencies of multiple harmonic signals. Followed by the estimated pitch frequencies, the DOA estimations based on the ESPRIT method are also presented by using the shift invariance structure in the spatial domain. Compared...... to the existing stateof-the-art algorithms, the proposed method based on ESPRIT without 2-D searching is computationally more efficient but performs similarly. An asymptotic performance analysis of the DOA and pitch estimation of the proposed method are also presented. Finally, the effectiveness of the proposed...

  5. MR-based water content estimation in cartilage: design and validation of a method

    DEFF Research Database (Denmark)

    Shiguetomi Medina, Juan Manuel; Kristiansen, Maja Sophie; Ringgaard, Steffen

    Purpose: Design and validation of an MR-based method that allows the calculation of the water content in cartilage tissue. Methods and Materials: Cartilage tissue T1 map based water content MR sequences were used on a 37 Celsius degree stable system. The T1 map intensity signal was analyzed on 6...... cartilage samples from living animals (pig) and on 8 gelatin samples which water content was already known. For the data analysis a T1 intensity signal map software analyzer used. Finally, the method was validated after measuring and comparing 3 more cartilage samples in a living animal (pig). The obtained...... map based water content sequences can provide information that, after being analyzed using a T1-map analysis software, can be interpreted as the water contained inside a cartilage tissue. The amount of water estimated using this method was similar to the one obtained at the dry-freeze procedure...

  6. Estimation of functional failure probability of passive systems based on subset simulation method

    International Nuclear Information System (INIS)

    Wang Dongqing; Wang Baosheng; Zhang Jianmin; Jiang Jing

    2012-01-01

    In order to solve the problem of multi-dimensional epistemic uncertainties and small functional failure probability of passive systems, an innovative reliability analysis algorithm called subset simulation based on Markov chain Monte Carlo was presented. The method is found on the idea that a small failure probability can be expressed as a product of larger conditional failure probabilities by introducing a proper choice of intermediate failure events. Markov chain Monte Carlo simulation was implemented to efficiently generate conditional samples for estimating the conditional failure probabilities. Taking the AP1000 passive residual heat removal system, for example, the uncertainties related to the model of a passive system and the numerical values of its input parameters were considered in this paper. And then the probability of functional failure was estimated with subset simulation method. The numerical results demonstrate that subset simulation method has the high computing efficiency and excellent computing accuracy compared with traditional probability analysis methods. (authors)

  7. Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations

    KAUST Repository

    Asiri, Sharefa M.

    2016-10-20

    In this paper, modulating functions-based method is proposed for estimating space–time-dependent unknowns in one-dimensional partial differential equations. The proposed method simplifies the problem into a system of algebraic equations linear in unknown parameters. The well-posedness of the modulating functions-based solution is proved. The wave and the fifth-order KdV equations are used as examples to show the effectiveness of the proposed method in both noise-free and noisy cases.

  8. A new anisotropic mesh adaptation method based upon hierarchical a posteriori error estimates

    Science.gov (United States)

    Huang, Weizhang; Kamenski, Lennard; Lang, Jens

    2010-03-01

    A new anisotropic mesh adaptation strategy for finite element solution of elliptic differential equations is presented. It generates anisotropic adaptive meshes as quasi-uniform ones in some metric space, with the metric tensor being computed based on hierarchical a posteriori error estimates. A global hierarchical error estimate is employed in this study to obtain reliable directional information of the solution. Instead of solving the global error problem exactly, which is costly in general, we solve it iteratively using the symmetric Gauß-Seidel method. Numerical results show that a few GS iterations are sufficient for obtaining a reasonably good approximation to the error for use in anisotropic mesh adaptation. The new method is compared with several strategies using local error estimators or recovered Hessians. Numerical results are presented for a selection of test examples and a mathematical model for heat conduction in a thermal battery with large orthotropic jumps in the material coefficients.

  9. Unemployment estimation: Spatial point referenced methods and models

    KAUST Repository

    Pereira, Soraia

    2017-06-26

    Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial distribution across any region. The labor force survey choose, according to an preestablished sampling criteria, a certain number of dwellings across the nation and survey the number of unemployed in these dwellings. Based on this survey, the National Statistical Institute of Portugal presently uses direct estimation methods to estimate the national unemployment figures. Recently, there has been increased interest in estimating these figures in smaller areas. Direct estimation methods, due to reduced sampling sizes in small areas, tend to produce fairly large sampling variations therefore model based methods, which tend to

  10. Residential building energy estimation method based on the application of artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, S.; Kajl, S.

    1999-07-01

    The energy requirements of a residential building five to twenty-five stories high can be measured using a newly proposed analytical method based on artificial intelligence. The method is fast and provides a wide range of results such as total energy consumption values, power surges, and heating or cooling consumption values. A series of database were created to take into account the particularities which influence the energy consumption of a building. In this study, DOE-2 software was created for use in 8 apartment models. A total of 27 neural networks were used, 3 for the estimation of energy consumption in the corridor, and 24 for inside the apartments. Three user interfaces were created to facilitate the estimation of energy consumption. These were named the Energy Estimation Assistance System (EEAS) interfaces and are only accessible using MATLAB software. The input parameters for EEAS are: climatic region, exterior wall resistance, roofing resistance, type of windows, infiltration, number of storeys, and corridor ventilation system operating schedule. By changing the parameters, the EEAS can determine annual heating, cooling and basic energy consumption levels for apartments and corridors. 2 tabs., 2 figs.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Hamideh Nouri

    2016-06-01

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

  13. [A method to estimate the short-term fractal dimension of heart rate variability based on wavelet transform].

    Science.gov (United States)

    Zhonggang, Liang; Hong, Yan

    2006-10-01

    A new method of calculating fractal dimension of short-term heart rate variability signals is presented. The method is based on wavelet transform and filter banks. The implementation of the method is: First of all we pick-up the fractal component from HRV signals using wavelet transform. Next, we estimate the power spectrum distribution of fractal component using auto-regressive model, and we estimate parameter 7 using the least square method. Finally according to formula D = 2- (gamma-1)/2 estimate fractal dimension of HRV signal. To validate the stability and reliability of the proposed method, using fractional brown movement simulate 24 fractal signals that fractal value is 1.6 to validate, the result shows that the method has stability and reliability.

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

    Science.gov (United States)

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

    2015-01-01

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

  15. An estimate of the terrestrial carbon budget of Russia using inventory-based, eddy covariance and inversion methods

    Directory of Open Access Journals (Sweden)

    A. J. Dolman

    2012-12-01

    Full Text Available We determine the net land to atmosphere flux of carbon in Russia, including Ukraine, Belarus and Kazakhstan, using inventory-based, eddy covariance, and inversion methods. Our high boundary estimate is −342 Tg C yr−1 from the eddy covariance method, and this is close to the upper bounds of the inventory-based Land Ecosystem Assessment and inverse models estimates. A lower boundary estimate is provided at −1350 Tg C yr−1 from the inversion models. The average of the three methods is −613.5 Tg C yr−1. The methane emission is estimated separately at 41.4 Tg C yr−1.

    These three methods agree well within their respective error bounds. There is thus good consistency between bottom-up and top-down methods. The forests of Russia primarily cause the net atmosphere to land flux (−692 Tg C yr−1 from the LEA. It remains however remarkable that the three methods provide such close estimates (−615, −662, −554 Tg C yr–1 for net biome production (NBP, given the inherent uncertainties in all of the approaches. The lack of recent forest inventories, the few eddy covariance sites and associated uncertainty with upscaling and undersampling of concentrations for the inversions are among the prime causes of the uncertainty. The dynamic global vegetation models (DGVMs suggest a much lower uptake at −91 Tg C yr−1, and we argue that this is caused by a high estimate of heterotrophic respiration compared to other methods.

  16. Comparative analysis of gradient-field-based orientation estimation methods and regularized singular-value decomposition for fringe pattern processing.

    Science.gov (United States)

    Sun, Qi; Fu, Shujun

    2017-09-20

    Fringe orientation is an important feature of fringe patterns and has a wide range of applications such as guiding fringe pattern filtering, phase unwrapping, and abstraction. Estimating fringe orientation is a basic task for subsequent processing of fringe patterns. However, various noise, singular and obscure points, and orientation data degeneration lead to inaccurate calculations of fringe orientation. Thus, to deepen the understanding of orientation estimation and to better guide orientation estimation in fringe pattern processing, some advanced gradient-field-based orientation estimation methods are compared and analyzed. At the same time, following the ideas of smoothing regularization and computing of bigger gradient fields, a regularized singular-value decomposition (RSVD) technique is proposed for fringe orientation estimation. To compare the performance of these gradient-field-based methods, quantitative results and visual effect maps of orientation estimation are given on simulated and real fringe patterns that demonstrate that the RSVD produces the best estimation results at a cost of relatively less time.

  17. Novel Direction Of Arrival Estimation Method Based on Coherent Accumulation Matrix Reconstruction

    Directory of Open Access Journals (Sweden)

    Li Lei

    2015-04-01

    Full Text Available Based on coherent accumulation matrix reconstruction, a novel Direction Of Arrival (DOA estimation decorrelation method of coherent signals is proposed using a small sample. First, the Signal to Noise Ratio (SNR is improved by performing coherent accumulation operation on an array of observed data. Then, according to the structure characteristics of the accumulated snapshot vector, the equivalent covariance matrix, whose rank is the same as the number of array elements, is constructed. The rank of this matrix is proved to be determined just by the number of incident signals, which realize the decorrelation of coherent signals. Compared with spatial smoothing method, the proposed method performs better by effectively avoiding aperture loss with high-resolution characteristics and low computational complexity. Simulation results demonstrate the efficiency of the proposed method.

  18. A SOFTWARE RELIABILITY ESTIMATION METHOD TO NUCLEAR SAFETY SOFTWARE

    Directory of Open Access Journals (Sweden)

    GEE-YONG PARK

    2014-02-01

    Full Text Available A method for estimating software reliability for nuclear safety software is proposed in this paper. This method is based on the software reliability growth model (SRGM, where the behavior of software failure is assumed to follow a non-homogeneous Poisson process. Two types of modeling schemes based on a particular underlying method are proposed in order to more precisely estimate and predict the number of software defects based on very rare software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating software test cases as a covariate into the model. It was identified that these models are capable of reasonably estimating the remaining number of software defects which directly affects the reactor trip functions. The software reliability might be estimated from these modeling equations, and one approach of obtaining software reliability value is proposed in this paper.

  19. Comparison of 3 estimation methods of mycophenolic acid AUC based on a limited sampling strategy in renal transplant patients.

    Science.gov (United States)

    Hulin, Anne; Blanchet, Benoît; Audard, Vincent; Barau, Caroline; Furlan, Valérie; Durrbach, Antoine; Taïeb, Fabrice; Lang, Philippe; Grimbert, Philippe; Tod, Michel

    2009-04-01

    A significant relationship between mycophenolic acid (MPA) area under the plasma concentration-time curve (AUC) and the risk for rejection has been reported. Based on 3 concentration measurements, 3 approaches have been proposed for the estimation of MPA AUC, involving either a multilinear regression approach model (MLRA) or a Bayesian estimation using either gamma absorption or zero-order absorption population models. The aim of the study was to compare the 3 approaches for the estimation of MPA AUC in 150 renal transplant patients treated with mycophenolate mofetil and tacrolimus. The population parameters were determined in 77 patients (learning study). The AUC estimation methods were compared in the learning population and in 73 patients from another center (validation study). In the latter study, the reference AUCs were estimated by the trapezoidal rule on 8 measurements. MPA concentrations were measured by liquid chromatography. The gamma absorption model gave the best fit. In the learning study, the AUCs estimated by both Bayesian methods were very similar, whereas the multilinear approach was highly correlated but yielded estimates about 20% lower than Bayesian methods. This resulted in dosing recommendations differing by 250 mg/12 h or more in 27% of cases. In the validation study, AUC estimates based on the Bayesian method with gamma absorption model and multilinear regression approach model were, respectively, 12% higher and 7% lower than the reference values. To conclude, the bicompartmental model with gamma absorption rate gave the best fit. The 3 AUC estimation methods are highly correlated but not concordant. For a given patient, the same estimation method should always be used.

  20. Model-based dynamic multi-parameter method for peak power estimation of lithium-ion batteries

    NARCIS (Netherlands)

    Sun, F.; Xiong, R.; He, H.; Li, W.; Aussems, J.E.E.

    2012-01-01

    A model-based dynamic multi-parameter method for peak power estimation is proposed for batteries and battery management systems (BMSs) used in hybrid electric vehicles (HEVs). The available power must be accurately calculated in order to not damage the battery by over charging or over discharging or

  1. Integration of sampling based battery state of health estimation method in electric vehicles

    International Nuclear Information System (INIS)

    Ozkurt, Celil; Camci, Fatih; Atamuradov, Vepa; Odorry, Christopher

    2016-01-01

    Highlights: • Presentation of a prototype system with full charge discharge cycling capability. • Presentation of SoH estimation results for systems degraded in the lab. • Discussion of integration alternatives of the presented method in EVs. • Simulation model based on presented SoH estimation for a real EV battery system. • Optimization of number of battery cells to be selected for SoH test. - Abstract: Battery cost is one of the crucial parameters affecting high deployment of Electric Vehicles (EVs) negatively. Accurate State of Health (SoH) estimation plays an important role in reducing the total ownership cost, availability, and safety of the battery avoiding early disposal of the batteries and decreasing unexpected failures. A circuit design for SoH estimation in a battery system that bases on selected battery cells and its integration to EVs are presented in this paper. A prototype microcontroller has been developed and used for accelerated aging tests for a battery system. The data collected in the lab tests have been utilized to simulate a real EV battery system. Results of accelerated aging tests and simulation have been presented in the paper. The paper also discusses identification of the best number of battery cells to be selected for SoH estimation test. In addition, different application options of the presented approach for EV batteries have been discussed in the paper.

  2. Differences in characteristics of raters who use the visual estimation method in hospitals based on their training experiences.

    Science.gov (United States)

    Kawasaki, Yui; Tamaura, Yuki; Akamatsu, Rie; Sakai, Masashi; Fujiwara, Keiko

    2018-02-07

    Despite a clinical need, only a few studies have provided information concerning visual estimation training for raters to improve the validity of their evaluations. This study aims to describe the differences in the characteristics of raters who evaluated patients' dietary intake in hospitals using the visual estimation method based on their training experiences. We collected data from three hospitals in Tokyo from August to September 2016. The participants were 199 nursing staff members, and they completed a self-administered questionnaire on demographic data; working career; training in the visual estimation method; knowledge, attitude, and practice associated with nutritional care; and self-evaluation of method validity of and skills of visual estimation. We classified participants into two groups, experienced and inexperienced, based on whether they had received training. Square test, Mann-Whitney U test, and univariable and multivariable logistic regression analysis were used to describe the differences between these two groups in terms of their characteristics; knowledge, attitude, and practice associated with nutritional care; and self-evaluation of method validity and tips used in the visual estimation method. Of the 158 staff members (79.4%) (118 nurses and 40 nursing assistants) who agreed to participate in the analysis, thirty-three participants (20.9%) were trained in the visual estimation method. Participants who had received training had better knowledge (2.70 ± 0.81, score range was 1-5) than those who had not received any training (2.34 ± 0.74, p = 0.03). Score of self-evaluation of method validity of the visual estimation method was higher in the experienced group (3.78 ± 0.61, score range was 1-5) than the inexperienced group (3.40 ± 0.66, p trained had adequate knowledge (OR: 2.78, 95% CI: 1.05-7.35) and frequently used tips in visual estimation (OR: 1.85, 95% CI: 1.26-2.73). Trained participants had more required knowledge and

  3. A comparison of analysis methods to estimate contingency strength.

    Science.gov (United States)

    Lloyd, Blair P; Staubitz, Johanna L; Tapp, Jon T

    2018-05-09

    To date, several data analysis methods have been used to estimate contingency strength, yet few studies have compared these methods directly. To compare the relative precision and sensitivity of four analysis methods (i.e., exhaustive event-based, nonexhaustive event-based, concurrent interval, concurrent+lag interval), we applied all methods to a simulated data set in which several response-dependent and response-independent schedules of reinforcement were programmed. We evaluated the degree to which contingency strength estimates produced from each method (a) corresponded with expected values for response-dependent schedules and (b) showed sensitivity to parametric manipulations of response-independent reinforcement. Results indicated both event-based methods produced contingency strength estimates that aligned with expected values for response-dependent schedules, but differed in sensitivity to response-independent reinforcement. The precision of interval-based methods varied by analysis method (concurrent vs. concurrent+lag) and schedule type (continuous vs. partial), and showed similar sensitivities to response-independent reinforcement. Recommendations and considerations for measuring contingencies are identified. © 2018 Society for the Experimental Analysis of Behavior.

  4. Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method

    International Nuclear Information System (INIS)

    Azizipanah-Abarghooee, Rasoul; Niknam, Taher; Roosta, Alireza; Malekpour, Ahmad Reza; Zare, Mohsen

    2012-01-01

    In this paper, wind power generators are being incorporated in the multiobjective economic emission dispatch problem which minimizes wind-thermal electrical energy cost and emissions produced by fossil-fueled power plants, simultaneously. Large integration of wind energy sources necessitates an efficient model to cope with uncertainty arising from random wind variation. Hence, a multiobjective stochastic search algorithm based on 2m point estimated method is implemented to analyze the probabilistic wind-thermal economic emission dispatch problem considering both overestimation and underestimation of available wind power. 2m point estimated method handles the system uncertainties and renders the probability density function of desired variables efficiently. Moreover, a new population-based optimization algorithm called modified teaching-learning algorithm is proposed to determine the set of non-dominated optimal solutions. During the simulation, the set of non-dominated solutions are kept in an external memory (repository). Also, a fuzzy-based clustering technique is implemented to control the size of the repository. In order to select the best compromise solution from the repository, a niching mechanism is utilized such that the population will move toward a smaller search space in the Pareto-optimal front. In order to show the efficiency and feasibility of the proposed framework, three different test systems are represented as case studies. -- Highlights: ► WPGs are being incorporated in the multiobjective economic emission dispatch problem. ► 2m PEM handles the system uncertainties. ► A MTLBO is proposed to determine the set of non-dominated (Pareto) optimal solutions. ► A fuzzy-based clustering technique is implemented to control the size of the repository.

  5. Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data.

    Science.gov (United States)

    Luo, Laiping; Zhai, Qiuping; Su, Yanjun; Ma, Qin; Kelly, Maggi; Guo, Qinghua

    2018-05-14

    Crown base height (CBH) is an essential tree biophysical parameter for many applications in forest management, forest fuel treatment, wildfire modeling, ecosystem modeling and global climate change studies. Accurate and automatic estimation of CBH for individual trees is still a challenging task. Airborne light detection and ranging (LiDAR) provides reliable and promising data for estimating CBH. Various methods have been developed to calculate CBH indirectly using regression-based means from airborne LiDAR data and field measurements. However, little attention has been paid to directly calculate CBH at the individual tree scale in mixed-species forests without field measurements. In this study, we propose a new method for directly estimating individual-tree CBH from airborne LiDAR data. Our method involves two main strategies: 1) removing noise and understory vegetation for each tree; and 2) estimating CBH by generating percentile ranking profile for each tree and using a spline curve to identify its inflection points. These two strategies lend our method the advantages of no requirement of field measurements and being efficient and effective in mixed-species forests. The proposed method was applied to a mixed conifer forest in the Sierra Nevada, California and was validated by field measurements. The results showed that our method can directly estimate CBH at individual tree level with a root-mean-squared error of 1.62 m, a coefficient of determination of 0.88 and a relative bias of 3.36%. Furthermore, we systematically analyzed the accuracies among different height groups and tree species by comparing with field measurements. Our results implied that taller trees had relatively higher uncertainties than shorter trees. Our findings also show that the accuracy for CBH estimation was the highest for black oak trees, with an RMSE of 0.52 m. The conifer species results were also good with uniformly high R 2 ranging from 0.82 to 0.93. In general, our method has

  6. 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.

  7. 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.

  8. New methods of testing nonlinear hypothesis using iterative NLLS estimator

    Science.gov (United States)

    Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

    2017-11-01

    This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

  9. Fundamental Frequency Estimation using Polynomial Rooting of a Subspace-Based Method

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

    2010-01-01

    improvements compared to HMUSIC. First, by using the proposed method we can obtain an estimate of the fundamental frequency without doing a grid search like in HMUSIC. This is due to that the fundamental frequency is estimated as the argument of the root lying closest to the unit circle. Second, we obtain...... a higher spectral resolution compared to HMUSIC which is a property of polynomial rooting methods. Our simulation results show that the proposed method is applicable to real-life signals, and that we in most cases obtain a higher spectral resolution than HMUSIC....

  10. Sequential multi-nuclide emission rate estimation method based on gamma dose rate measurement for nuclear emergency management

    International Nuclear Information System (INIS)

    Zhang, Xiaole; Raskob, Wolfgang; Landman, Claudia; Trybushnyi, Dmytro; Li, Yu

    2017-01-01

    Highlights: • Sequentially reconstruct multi-nuclide emission using gamma dose rate measurements. • Incorporate a priori ratio of nuclides into the background error covariance matrix. • Sequentially augment and update the estimation and the background error covariance. • Suppress the generation of negative estimations for the sequential method. • Evaluate the new method with twin experiments based on the JRODOS system. - Abstract: In case of a nuclear accident, the source term is typically not known but extremely important for the assessment of the consequences to the affected population. Therefore the assessment of the potential source term is of uppermost importance for emergency response. A fully sequential method, derived from a regularized weighted least square problem, is proposed to reconstruct the emission and composition of a multiple-nuclide release using gamma dose rate measurement. The a priori nuclide ratios are incorporated into the background error covariance (BEC) matrix, which is dynamically augmented and sequentially updated. The negative estimations in the mathematical algorithm are suppressed by utilizing artificial zero-observations (with large uncertainties) to simultaneously update the state vector and BEC. The method is evaluated by twin experiments based on the JRodos system. The results indicate that the new method successfully reconstructs the emission and its uncertainties. Accurate a priori ratio accelerates the analysis process, which obtains satisfactory results with only limited number of measurements, otherwise it needs more measurements to generate reasonable estimations. The suppression of negative estimation effectively improves the performance, especially for the situation with poor a priori information, where it is more prone to the generation of negative values.

  11. Sequential multi-nuclide emission rate estimation method based on gamma dose rate measurement for nuclear emergency management

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xiaole, E-mail: zhangxiaole10@outlook.com [Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Karlsruhe, D-76021 (Germany); Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, 100084 (China); Raskob, Wolfgang; Landman, Claudia; Trybushnyi, Dmytro; Li, Yu [Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Karlsruhe, D-76021 (Germany)

    2017-03-05

    Highlights: • Sequentially reconstruct multi-nuclide emission using gamma dose rate measurements. • Incorporate a priori ratio of nuclides into the background error covariance matrix. • Sequentially augment and update the estimation and the background error covariance. • Suppress the generation of negative estimations for the sequential method. • Evaluate the new method with twin experiments based on the JRODOS system. - Abstract: In case of a nuclear accident, the source term is typically not known but extremely important for the assessment of the consequences to the affected population. Therefore the assessment of the potential source term is of uppermost importance for emergency response. A fully sequential method, derived from a regularized weighted least square problem, is proposed to reconstruct the emission and composition of a multiple-nuclide release using gamma dose rate measurement. The a priori nuclide ratios are incorporated into the background error covariance (BEC) matrix, which is dynamically augmented and sequentially updated. The negative estimations in the mathematical algorithm are suppressed by utilizing artificial zero-observations (with large uncertainties) to simultaneously update the state vector and BEC. The method is evaluated by twin experiments based on the JRodos system. The results indicate that the new method successfully reconstructs the emission and its uncertainties. Accurate a priori ratio accelerates the analysis process, which obtains satisfactory results with only limited number of measurements, otherwise it needs more measurements to generate reasonable estimations. The suppression of negative estimation effectively improves the performance, especially for the situation with poor a priori information, where it is more prone to the generation of negative values.

  12. Subspace Based Blind Sparse Channel Estimation

    DEFF Research Database (Denmark)

    Hayashi, Kazunori; Matsushima, Hiroki; Sakai, Hideaki

    2012-01-01

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

  13. [Cardiac Synchronization Function Estimation Based on ASM Level Set Segmentation Method].

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Tang, Liang; He, Ying; Zhang, Huie

    At present, there is no accurate and quantitative methods for the determination of cardiac mechanical synchronism, and quantitative determination of the synchronization function of the four cardiac cavities with medical images has a great clinical value. This paper uses the whole heart ultrasound image sequence, and segments the left & right atriums and left & right ventricles of each frame. After the segmentation, the number of pixels in each cavity and in each frame is recorded, and the areas of the four cavities of the image sequence are therefore obtained. The area change curves of the four cavities are further extracted, and the synchronous information of the four cavities is obtained. Because of the low SNR of Ultrasound images, the boundary lines of cardiac cavities are vague, so the extraction of cardiac contours is still a challenging problem. Therefore, the ASM model information is added to the traditional level set method to force the curve evolution process. According to the experimental results, the improved method improves the accuracy of the segmentation. Furthermore, based on the ventricular segmentation, the right and left ventricular systolic functions are evaluated, mainly according to the area changes. The synchronization of the four cavities of the heart is estimated based on the area changes and the volume changes.

  14. Hybrid islanding detection method by using grid impedance estimation in parallel-inverters-based microgrid

    DEFF Research Database (Denmark)

    Ghzaiel, Walid; Jebali-Ben Ghorbal, Manel; Slama-Belkhodja, Ilhem

    2014-01-01

    This paper presents a hybrid islanding detection algorithm integrated on the distributed generation unit more close to the point of common coupling of a Microgrid based on parallel inverters where one of them is responsible to control the system. The method is based on resonance excitation under...... parameters, both resistive and inductive parts, from the injected resonance frequency determination. Finally, the inverter will disconnect the microgrid from the faulty grid and reconnect the parallel inverter system to the controllable distributed system in order to ensure high power quality. This paper...... shows that grid impedance variation detection estimation can be an efficient method for islanding detection in microgrid systems. Theoretical analysis and simulation results are presented to validate the proposed method....

  15. Methods for estimating the semivariogram

    DEFF Research Database (Denmark)

    Lophaven, Søren Nymand; Carstensen, Niels Jacob; Rootzen, Helle

    2002-01-01

    . In the existing literature various methods for modelling the semivariogram have been proposed, while only a few studies have been made on comparing different approaches. In this paper we compare eight approaches for modelling the semivariogram, i.e. six approaches based on least squares estimation...... maximum likelihood performed better than the least squares approaches. We also applied maximum likelihood and least squares estimation to a real dataset, containing measurements of salinity at 71 sampling stations in the Kattegat basin. This showed that the calculation of spatial predictions...

  16. Estimation of geological formation thermal conductivity by using stochastic approximation method based on well-log temperature data

    International Nuclear Information System (INIS)

    Cheng, Wen-Long; Huang, Yong-Hua; Liu, Na; Ma, Ran

    2012-01-01

    Thermal conductivity is a key parameter for evaluating wellbore heat losses which plays an important role in determining the efficiency of steam injection processes. In this study, an unsteady formation heat-transfer model was established and a cost-effective in situ method by using stochastic approximation method based on well-log temperature data was presented. The proposed method was able to estimate the thermal conductivity and the volumetric heat capacity of geological formation simultaneously under the in situ conditions. The feasibility of the present method was assessed by a sample test, the results of which shown that the thermal conductivity and the volumetric heat capacity could be obtained with the relative errors of −0.21% and −0.32%, respectively. In addition, three field tests were conducted based on the easily obtainable well-log temperature data from the steam injection wells. It was found that the relative errors of thermal conductivity for the three field tests were within ±0.6%, demonstrating the excellent performance of the proposed method for calculating thermal conductivity. The relative errors of volumetric heat capacity ranged from −6.1% to −14.2% for the three field tests. Sensitivity analysis indicated that this was due to the low correlation between the volumetric heat capacity and the wellbore temperature, which was used to generate the judgment criterion. -- Highlights: ► A cost-effective in situ method for estimating thermal properties of formation was presented. ► Thermal conductivity and volumetric heat capacity can be estimated simultaneously by the proposed method. ► The relative error of thermal conductivity estimated was within ±0.6%. ► Sensitivity analysis was conducted to study the estimated results of thermal properties.

  17. A new lithium-ion battery internal temperature on-line estimate method based on electrochemical impedance spectroscopy measurement

    Science.gov (United States)

    Zhu, J. G.; Sun, Z. C.; Wei, X. Z.; Dai, H. F.

    2015-01-01

    The power battery thermal management problem in EV (electric vehicle) and HEV (hybrid electric vehicle) has been widely discussed, and EIS (electrochemical impedance spectroscopy) is an effective experimental method to test and estimate the status of the battery. Firstly, an electrochemical-based impedance matrix analysis for lithium-ion battery is developed to describe the impedance response of electrochemical impedance spectroscopy. Then a method, based on electrochemical impedance spectroscopy measurement, has been proposed to estimate the internal temperature of power lithium-ion battery by analyzing the phase shift and magnitude of impedance at different ambient temperatures. Respectively, the SoC (state of charge) and temperature have different effects on the impedance characteristics of battery at various frequency ranges in the electrochemical impedance spectroscopy experimental study. Also the impedance spectrum affected by SoH (state of health) is discussed in the paper preliminary. Therefore, the excitation frequency selected to estimate the inner temperature is in the frequency range which is significantly influenced by temperature without the SoC and SoH. The intrinsic relationship between the phase shift and temperature is established under the chosen excitation frequency. And the magnitude of impedance related to temperature is studied in the paper. In practical applications, through obtaining the phase shift and magnitude of impedance, the inner temperature estimation could be achieved. Then the verification experiments are conduced to validate the estimate method. Finally, an estimate strategy and an on-line estimation system implementation scheme utilizing battery management system are presented to describe the engineering value.

  18. Channel Estimation in DCT-Based OFDM

    Science.gov (United States)

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

    2014-01-01

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

  19. 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.

  20. Joint Spatio-Temporal Filtering Methods for DOA and Fundamental Frequency Estimation

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob

    2015-01-01

    some attention in the community and is quite promising for several applications. The proposed methods are based on optimal, adaptive filters that leave the desired signal, having a certain DOA and fundamental frequency, undistorted and suppress everything else. The filtering methods simultaneously...... operate in space and time, whereby it is possible resolve cases that are otherwise problematic for pitch estimators or DOA estimators based on beamforming. Several special cases and improvements are considered, including a method for estimating the covariance matrix based on the recently proposed...

  1. Cumulant-Based Coherent Signal Subspace Method for Bearing and Range Estimation

    Directory of Open Access Journals (Sweden)

    Bourennane Salah

    2007-01-01

    Full Text Available A new method for simultaneous range and bearing estimation for buried objects in the presence of an unknown Gaussian noise is proposed. This method uses the MUSIC algorithm with noise subspace estimated by using the slice fourth-order cumulant matrix of the received data. The higher-order statistics aim at the removal of the additive unknown Gaussian noise. The bilinear focusing operator is used to decorrelate the received signals and to estimate the coherent signal subspace. A new source steering vector is proposed including the acoustic scattering model at each sensor. Range and bearing of the objects at each sensor are expressed as a function of those at the first sensor. This leads to the improvement of object localization anywhere, in the near-field or in the far-field zone of the sensor array. Finally, the performances of the proposed method are validated on data recorded during experiments in a water tank.

  2. A citizen science based survey method for estimating the density of urban carnivores

    Science.gov (United States)

    Baker, Rowenna; Charman, Naomi; Karlsson, Heidi; Yarnell, Richard W.; Mill, Aileen C.; Smith, Graham C.; Tolhurst, Bryony A.

    2018-01-01

    Globally there are many examples of synanthropic carnivores exploiting growth in urbanisation. As carnivores can come into conflict with humans and are potential vectors of zoonotic disease, assessing densities in suburban areas and identifying factors that influence them are necessary to aid management and mitigation. However, fragmented, privately owned land restricts the use of conventional carnivore surveying techniques in these areas, requiring development of novel methods. We present a method that combines questionnaire distribution to residents with field surveys and GIS, to determine relative density of two urban carnivores in England, Great Britain. We determined the density of: red fox (Vulpes vulpes) social groups in 14, approximately 1km2 suburban areas in 8 different towns and cities; and Eurasian badger (Meles meles) social groups in three suburban areas of one city. Average relative fox group density (FGD) was 3.72 km-2, which was double the estimates for cities with resident foxes in the 1980’s. Density was comparable to an alternative estimate derived from trapping and GPS-tracking, indicating the validity of the method. However, FGD did not correlate with a national dataset based on fox sightings, indicating unreliability of the national data to determine actual densities or to extrapolate a national population estimate. Using species-specific clustering units that reflect social organisation, the method was additionally applied to suburban badgers to derive relative badger group density (BGD) for one city (Brighton, 2.41 km-2). We demonstrate that citizen science approaches can effectively obtain data to assess suburban carnivore density, however publicly derived national data sets need to be locally validated before extrapolations can be undertaken. The method we present for assessing densities of foxes and badgers in British towns and cities is also adaptable to other urban carnivores elsewhere. However this transferability is contingent on

  3. Motion estimation using point cluster method and Kalman filter.

    Science.gov (United States)

    Senesh, M; Wolf, A

    2009-05-01

    The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal

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

    Directory of Open Access Journals (Sweden)

    Lu Yang

    2018-01-01

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

  5. 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...

  6. Nonparametric methods for volatility density estimation

    NARCIS (Netherlands)

    Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

    2009-01-01

    Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

  7. 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....

  8. Advances in estimation methods of vegetation water content based on optical remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

  9. A Fast Soft Bit Error Rate Estimation Method

    Directory of Open Access Journals (Sweden)

    Ait-Idir Tarik

    2010-01-01

    Full Text Available We have suggested in a previous publication a method to estimate the Bit Error Rate (BER of a digital communications system instead of using the famous Monte Carlo (MC simulation. This method was based on the estimation of the probability density function (pdf of soft observed samples. The kernel method was used for the pdf estimation. In this paper, we suggest to use a Gaussian Mixture (GM model. The Expectation Maximisation algorithm is used to estimate the parameters of this mixture. The optimal number of Gaussians is computed by using Mutual Information Theory. The analytical expression of the BER is therefore simply given by using the different estimated parameters of the Gaussian Mixture. Simulation results are presented to compare the three mentioned methods: Monte Carlo, Kernel and Gaussian Mixture. We analyze the performance of the proposed BER estimator in the framework of a multiuser code division multiple access system and show that attractive performance is achieved compared with conventional MC or Kernel aided techniques. The results show that the GM method can drastically reduce the needed number of samples to estimate the BER in order to reduce the required simulation run-time, even at very low BER.

  10. 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.

  11. Pipeline heating method based on optimal control and state estimation

    Energy Technology Data Exchange (ETDEWEB)

    Vianna, F.L.V. [Dept. of Subsea Technology. Petrobras Research and Development Center - CENPES, Rio de Janeiro, RJ (Brazil)], e-mail: fvianna@petrobras.com.br; Orlande, H.R.B. [Dept. of Mechanical Engineering. POLI/COPPE, Federal University of Rio de Janeiro - UFRJ, Rio de Janeiro, RJ (Brazil)], e-mail: helcio@mecanica.ufrj.br; Dulikravich, G.S. [Dept. of Mechanical and Materials Engineering. Florida International University - FIU, Miami, FL (United States)], e-mail: dulikrav@fiu.edu

    2010-07-01

    In production of oil and gas wells in deep waters the flowing of hydrocarbon through pipeline is a challenging problem. This environment presents high hydrostatic pressures and low sea bed temperatures, which can favor the formation of solid deposits that in critical operating conditions, as unplanned shutdown conditions, may result in a pipeline blockage and consequently incur in large financial losses. There are different methods to protect the system, but nowadays thermal insulation and chemical injection are the standard solutions normally used. An alternative method of flow assurance is to heat the pipeline. This concept, which is known as active heating system, aims at heating the produced fluid temperature above a safe reference level in order to avoid the formation of solid deposits. The objective of this paper is to introduce a Bayesian statistical approach for the state estimation problem, in which the state variables are considered as the transient temperatures within a pipeline cross-section, and to use the optimal control theory as a design tool for a typical heating system during a simulated shutdown condition. An application example is presented to illustrate how Bayesian filters can be used to reconstruct the temperature field from temperature measurements supposedly available on the external surface of the pipeline. The temperatures predicted with the Bayesian filter are then utilized in a control approach for a heating system used to maintain the temperature within the pipeline above the critical temperature of formation of solid deposits. The physical problem consists of a pipeline cross section represented by a circular domain with four points over the pipe wall representing heating cables. The fluid is considered stagnant, homogeneous, isotropic and with constant thermo-physical properties. The mathematical formulation governing the direct problem was solved with the finite volume method and for the solution of the state estimation problem

  12. Integral-equation based methods for parameter estimation in output pulses of radiation detectors: Application in nuclear medicine and spectroscopy

    Science.gov (United States)

    Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar

    2018-04-01

    Model based analysis methods are relatively new approaches for processing the output data of radiation detectors in nuclear medicine imaging and spectroscopy. A class of such methods requires fast algorithms for fitting pulse models to experimental data. In order to apply integral-equation based methods for processing the preamplifier output pulses, this article proposes a fast and simple method for estimating the parameters of the well-known bi-exponential pulse model by solving an integral equation. The proposed method needs samples from only three points of the recorded pulse as well as its first and second order integrals. After optimizing the sampling points, the estimation results were calculated and compared with two traditional integration-based methods. Different noise levels (signal-to-noise ratios from 10 to 3000) were simulated for testing the functionality of the proposed method, then it was applied to a set of experimental pulses. Finally, the effect of quantization noise was assessed by studying different sampling rates. Promising results by the proposed method endorse it for future real-time applications.

  13. Direct diffusion tensor estimation using a model-based method with spatial and parametric constraints.

    Science.gov (United States)

    Zhu, Yanjie; Peng, Xi; Wu, Yin; Wu, Ed X; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

    2017-02-01

    To develop a new model-based method with spatial and parametric constraints (MB-SPC) aimed at accelerating diffusion tensor imaging (DTI) by directly estimating the diffusion tensor from highly undersampled k-space data. The MB-SPC method effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images using an L1-L2 norm and the smoothness of the diffusion tensor using a total variation seminorm. The undersampled k-space datasets were obtained from fully sampled DTI datasets of a simulated phantom and an ex-vivo experimental rat heart with acceleration factors ranging from 2 to 4. The diffusion tensor was directly reconstructed by solving a minimization problem with a nonlinear conjugate gradient descent algorithm. The reconstruction performance was quantitatively assessed using the normalized root mean square error (nRMSE) of the DTI indices. The MB-SPC method achieves acceptable DTI measures at an acceleration factor up to 4. Experimental results demonstrate that the proposed method can estimate the diffusion tensor more accurately than most existing methods operating at higher net acceleration factors. The proposed method can significantly reduce artifact, particularly at higher acceleration factors or lower SNRs. This method can easily be adapted to MR relaxometry parameter mapping and is thus useful in the characterization of biological tissue such as nerves, muscle, and heart tissue. © 2016 American Association of Physicists in Medicine.

  14. Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

    Directory of Open Access Journals (Sweden)

    Xin Lu

    2018-03-01

    Full Text Available In recent years, the fractional order model has been employed to state of charge (SOC estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation. The experimental results showed that the proposed iterative method can quickly estimate the SOC by several iterations while maintaining high estimation accuracy.

  15. Estimating the spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing

    Science.gov (United States)

    Gao, Shengguo; Zhu, Zhongli; Liu, Shaomin; Jin, Rui; Yang, Guangchao; Tan, Lei

    2014-10-01

    Soil moisture (SM) plays a fundamental role in the land-atmosphere exchange process. Spatial estimation based on multi in situ (network) data is a critical way to understand the spatial structure and variation of land surface soil moisture. Theoretically, integrating densely sampled auxiliary data spatially correlated with soil moisture into the procedure of spatial estimation can improve its accuracy. In this study, we present a novel approach to estimate the spatial pattern of soil moisture by using the BME method based on wireless sensor network data and auxiliary information from ASTER (Terra) land surface temperature measurements. For comparison, three traditional geostatistic methods were also applied: ordinary kriging (OK), which used the wireless sensor network data only, regression kriging (RK) and ordinary co-kriging (Co-OK) which both integrated the ASTER land surface temperature as a covariate. In Co-OK, LST was linearly contained in the estimator, in RK, estimator is expressed as the sum of the regression estimate and the kriged estimate of the spatially correlated residual, but in BME, the ASTER land surface temperature was first retrieved as soil moisture based on the linear regression, then, the t-distributed prediction interval (PI) of soil moisture was estimated and used as soft data in probability form. The results indicate that all three methods provide reasonable estimations. Co-OK, RK and BME can provide a more accurate spatial estimation by integrating the auxiliary information Compared to OK. RK and BME shows more obvious improvement compared to Co-OK, and even BME can perform slightly better than RK. The inherent issue of spatial estimation (overestimation in the range of low values and underestimation in the range of high values) can also be further improved in both RK and BME. We can conclude that integrating auxiliary data into spatial estimation can indeed improve the accuracy, BME and RK take better advantage of the auxiliary

  16. A Computationally Efficient Method for Polyphonic Pitch Estimation

    Directory of Open Access Journals (Sweden)

    Ruohua Zhou

    2009-01-01

    Full Text Available This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.

  17. An Estimation Method for number of carrier frequency

    Directory of Open Access Journals (Sweden)

    Xiong Peng

    2015-01-01

    Full Text Available This paper proposes a method that utilizes AR model power spectrum estimation based on Burg algorithm to estimate the number of carrier frequency in single pulse. In the modern electronic and information warfare, the pulse signal form of radar is complex and changeable, among which single pulse with multi-carrier frequencies is the most typical one, such as the frequency shift keying (FSK signal, the frequency shift keying with linear frequency (FSK-LFM hybrid modulation signal and the frequency shift keying with bi-phase shift keying (FSK-BPSK hybrid modulation signal. In view of this kind of single pulse which has multi-carrier frequencies, this paper adopts a method which transforms the complex signal into AR model, then takes power spectrum based on Burg algorithm to show the effect. Experimental results show that the estimation method still can determine the number of carrier frequencies accurately even when the signal noise ratio (SNR is very low.

  18. 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.

  19. 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.

  20. Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

    Directory of Open Access Journals (Sweden)

    Muqing Du

    2015-01-01

    Full Text Available The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC well defines this problem. For practical applications, a modified sensitivity analysis based (SAB method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples.

  1. 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.

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

    Science.gov (United States)

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

    2015-11-20

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

  3. Training Methods for Image Noise Level Estimation on Wavelet Components

    Directory of Open Access Journals (Sweden)

    A. De Stefano

    2004-12-01

    Full Text Available The estimation of the standard deviation of noise contaminating an image is a fundamental step in wavelet-based noise reduction techniques. The method widely used is based on the mean absolute deviation (MAD. This model-based method assumes specific characteristics of the noise-contaminated image component. Three novel and alternative methods for estimating the noise standard deviation are proposed in this work and compared with the MAD method. Two of these methods rely on a preliminary training stage in order to extract parameters which are then used in the application stage. The sets used for training and testing, 13 and 5 images, respectively, are fully disjoint. The third method assumes specific statistical distributions for image and noise components. Results showed the prevalence of the training-based methods for the images and the range of noise levels considered.

  4. Specialized Finite Set Statistics (FISST)-Based Estimation Methods to Enhance Space Situational Awareness in Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO)

    Science.gov (United States)

    2016-08-17

    Specialized Finite Set Statistics (FISST)-based Estimation Methods to Enhance Space Situational Awareness in Medium Earth Orbit (MEO) and Geostationary...terms of specialized Geostationary Earth Orbit (GEO) elements to estimate the state of resident space objects in the geostationary regime. Justification...AFRL-RV-PS- AFRL-RV-PS- TR-2016-0114 TR-2016-0114 SPECIALIZED FINITE SET STATISTICS (FISST)- BASED ESTIMATION METHODS TO ENHANCE SPACE SITUATIONAL

  5. Simple estimating method of damages of concrete gravity dam based on linear dynamic analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sasaki, T.; Kanenawa, K.; Yamaguchi, Y. [Public Works Research Institute, Tsukuba, Ibaraki (Japan). Hydraulic Engineering Research Group

    2004-07-01

    Due to the occurrence of large earthquakes like the Kobe Earthquake in 1995, there is a strong need to verify seismic resistance of dams against much larger earthquake motions than those considered in the present design standard in Japan. Problems exist in using nonlinear analysis to evaluate the safety of dams including: that the influence which the set material properties have on the results of nonlinear analysis is large, and that the results of nonlinear analysis differ greatly according to the damage estimation models or analysis programs. This paper reports the evaluation indices based on a linear dynamic analysis method and the characteristics of the progress of cracks in concrete gravity dams with different shapes using a nonlinear dynamic analysis method. The study concludes that if simple linear dynamic analysis is appropriately conducted to estimate tensile stress at potential locations of initiating cracks, the damage due to cracks would be predicted roughly. 4 refs., 1 tab., 13 figs.

  6. Yield Estimation of Sugar Beet Based on Plant Canopy Using Machine Vision Methods

    Directory of Open Access Journals (Sweden)

    S Latifaltojar

    2014-09-01

    Full Text Available Crop yield estimation is one of the most important parameters for information and resources management in precision agriculture. This information is employed for optimizing the field inputs for successive cultivations. In the present study, the feasibility of sugar beet yield estimation by means of machine vision was studied. For the field experiments stripped images were taken during the growth season with one month intervals. The image of horizontal view of plants canopy was prepared at the end of each month. At the end of growth season, beet roots were harvested and the correlation between the sugar beet canopy in each month of growth period and corresponding weight of the roots were investigated. Results showed that there was a strong correlation between the beet yield and green surface area of autumn cultivated sugar beets. The highest coefficient of determination was 0.85 at three months before harvest. In order to assess the accuracy of the final model, the second year of study was performed with the same methodology. The results depicted a strong relationship between the actual and estimated beet weights with R2=0.94. The model estimated beet yield with about 9 percent relative error. It is concluded that this method has appropriate potential for estimation of sugar beet yield based on band imaging prior to harvest

  7. Electrical estimating methods

    CERN Document Server

    Del Pico, Wayne J

    2014-01-01

    Simplify the estimating process with the latest data, materials, and practices Electrical Estimating Methods, Fourth Edition is a comprehensive guide to estimating electrical costs, with data provided by leading construction database RS Means. The book covers the materials and processes encountered by the modern contractor, and provides all the information professionals need to make the most precise estimate. The fourth edition has been updated to reflect the changing materials, techniques, and practices in the field, and provides the most recent Means cost data available. The complexity of el

  8. Low-cost extrapolation method for maximal LTE radio base station exposure estimation: test and validation.

    Science.gov (United States)

    Verloock, Leen; Joseph, Wout; Gati, Azeddine; Varsier, Nadège; Flach, Björn; Wiart, Joe; Martens, Luc

    2013-06-01

    An experimental validation of a low-cost method for extrapolation and estimation of the maximal electromagnetic-field exposure from long-term evolution (LTE) radio base station installations are presented. No knowledge on downlink band occupation or service characteristics is required for the low-cost method. The method is applicable in situ. It only requires a basic spectrum analyser with appropriate field probes without the need of expensive dedicated LTE decoders. The method is validated both in laboratory and in situ, for a single-input single-output antenna LTE system and a 2×2 multiple-input multiple-output system, with low deviations in comparison with signals measured using dedicated LTE decoders.

  9. Assessing methane emission estimation methods based on atmospheric measurements from oil and gas production using LES simulations

    Science.gov (United States)

    Saide, P. E.; Steinhoff, D.; Kosovic, B.; Weil, J.; Smith, N.; Blewitt, D.; Delle Monache, L.

    2017-12-01

    There are a wide variety of methods that have been proposed and used to estimate methane emissions from oil and gas production by using air composition and meteorology observations in conjunction with dispersion models. Although there has been some verification of these methodologies using controlled releases and concurrent atmospheric measurements, it is difficult to assess the accuracy of these methods for more realistic scenarios considering factors such as terrain, emissions from multiple components within a well pad, and time-varying emissions representative of typical operations. In this work we use a large-eddy simulation (LES) to generate controlled but realistic synthetic observations, which can be used to test multiple source term estimation methods, also known as an Observing System Simulation Experiment (OSSE). The LES is based on idealized simulations of the Weather Research & Forecasting (WRF) model at 10 m horizontal grid-spacing covering an 8 km by 7 km domain with terrain representative of a region located in the Barnett shale. Well pads are setup in the domain following a realistic distribution and emissions are prescribed every second for the components of each well pad (e.g., chemical injection pump, pneumatics, compressor, tanks, and dehydrator) using a simulator driven by oil and gas production volume, composition and realistic operational conditions. The system is setup to allow assessments under different scenarios such as normal operations, during liquids unloading events, or during other prescribed operational upset events. Methane and meteorology model output are sampled following the specifications of the emission estimation methodologies and considering typical instrument uncertainties, resulting in realistic observations (see Figure 1). We will show the evaluation of several emission estimation methods including the EPA Other Test Method 33A and estimates using the EPA AERMOD regulatory model. We will also show source estimation

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

    Science.gov (United States)

    Shirley, Natalie R; Ramirez Montes, Paula Andrea

    2015-01-01

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

  11. Reverse survival method of fertility estimation: An evaluation

    Directory of Open Access Journals (Sweden)

    Thomas Spoorenberg

    2014-07-01

    Full Text Available Background: For the most part, demographers have relied on the ever-growing body of sample surveys collecting full birth history to derive total fertility estimates in less statistically developed countries. Yet alternative methods of fertility estimation can return very consistent total fertility estimates by using only basic demographic information. Objective: This paper evaluates the consistency and sensitivity of the reverse survival method -- a fertility estimation method based on population data by age and sex collected in one census or a single-round survey. Methods: A simulated population was first projected over 15 years using a set of fertility and mortality age and sex patterns. The projected population was then reverse survived using the Excel template FE_reverse_4.xlsx, provided with Timæus and Moultrie (2012. Reverse survival fertility estimates were then compared for consistency to the total fertility rates used to project the population. The sensitivity was assessed by introducing a series of distortions in the projection of the population and comparing the difference implied in the resulting fertility estimates. Results: The reverse survival method produces total fertility estimates that are very consistent and hardly affected by erroneous assumptions on the age distribution of fertility or by the use of incorrect mortality levels, trends, and age patterns. The quality of the age and sex population data that is 'reverse survived' determines the consistency of the estimates. The contribution of the method for the estimation of past and present trends in total fertility is illustrated through its application to the population data of five countries characterized by distinct fertility levels and data quality issues. Conclusions: Notwithstanding its simplicity, the reverse survival method of fertility estimation has seldom been applied. The method can be applied to a large body of existing and easily available population data

  12. Markov chain-based mass estimation method for loose part monitoring system and its performance

    Directory of Open Access Journals (Sweden)

    Sung-Hwan Shin

    2017-10-01

    Full Text Available A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

  13. 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.

  14. 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

  15. Lithium-Ion Battery Capacity Estimation: A Method Based on Visual Cognition

    Directory of Open Access Journals (Sweden)

    Yujie Cheng

    2017-01-01

    Full Text Available This study introduces visual cognition into Lithium-ion battery capacity estimation. The proposed method consists of four steps. First, the acquired charging current or discharge voltage data in each cycle are arranged to form a two-dimensional image. Second, the generated image is decomposed into multiple spatial-frequency channels with a set of orientation subbands by using non-subsampled contourlet transform (NSCT. NSCT imitates the multichannel characteristic of the human visual system (HVS that provides multiresolution, localization, directionality, and shift invariance. Third, several time-domain indicators of the NSCT coefficients are extracted to form an initial high-dimensional feature vector. Similarly, inspired by the HVS manifold sensing characteristic, the Laplacian eigenmap manifold learning method, which is considered to reveal the evolutionary law of battery performance degradation within a low-dimensional intrinsic manifold, is used to further obtain a low-dimensional feature vector. Finally, battery capacity degradation is estimated using the geodesic distance on the manifold between the initial and the most recent features. Verification experiments were conducted using data obtained under different operating and aging conditions. Results suggest that the proposed visual cognition approach provides a highly accurate means of estimating battery capacity and thus offers a promising method derived from the emerging field of cognitive computing.

  16. A Low-Complexity ESPRIT-Based DOA Estimation Method for Co-Prime Linear Arrays.

    Science.gov (United States)

    Sun, Fenggang; Gao, Bin; Chen, Lizhen; Lan, Peng

    2016-08-25

    The problem of direction-of-arrival (DOA) estimation is investigated for co-prime array, where the co-prime array consists of two uniform sparse linear subarrays with extended inter-element spacing. For each sparse subarray, true DOAs are mapped into several equivalent angles impinging on the traditional uniform linear array with half-wavelength spacing. Then, by applying the estimation of signal parameters via rotational invariance technique (ESPRIT), the equivalent DOAs are estimated, and the candidate DOAs are recovered according to the relationship among equivalent and true DOAs. Finally, the true DOAs are estimated by combining the results of the two subarrays. The proposed method achieves a better complexity-performance tradeoff as compared to other existing methods.

  17. Low-cost extrapolation method for maximal lte radio base station exposure estimation: Test and validation

    International Nuclear Information System (INIS)

    Verloock, L.; Joseph, W.; Gati, A.; Varsier, N.; Flach, B.; Wiart, J.; Martens, L.

    2013-01-01

    An experimental validation of a low-cost method for extrapolation and estimation of the maximal electromagnetic-field exposure from long-term evolution (LTE) radio base station installations are presented. No knowledge on down-link band occupation or service characteristics is required for the low-cost method. The method is applicable in situ. It only requires a basic spectrum analyser with appropriate field probes without the need of expensive dedicated LTE decoders. The method is validated both in laboratory and in situ, for a single-input single-output antenna LTE system and a 2x2 multiple-input multiple-output system, with low deviations in comparison with signals measured using dedicated LTE decoders. (authors)

  18. Adaptive Methods for Permeability Estimation and Smart Well Management

    Energy Technology Data Exchange (ETDEWEB)

    Lien, Martha Oekland

    2005-04-01

    The main focus of this thesis is on adaptive regularization methods. We consider two different applications, the inverse problem of absolute permeability estimation and the optimal control problem of estimating smart well management. Reliable estimates of absolute permeability are crucial in order to develop a mathematical description of an oil reservoir. Due to the nature of most oil reservoirs, mainly indirect measurements are available. In this work, dynamic production data from wells are considered. More specifically, we have investigated into the resolution power of pressure data for permeability estimation. The inversion of production data into permeability estimates constitutes a severely ill-posed problem. Hence, regularization techniques are required. In this work, deterministic regularization based on adaptive zonation is considered, i.e. a solution approach with adaptive multiscale estimation in conjunction with level set estimation is developed for coarse scale permeability estimation. A good mathematical reservoir model is a valuable tool for future production planning. Recent developments within well technology have given us smart wells, which yield increased flexibility in the reservoir management. In this work, we investigate into the problem of finding the optimal smart well management by means of hierarchical regularization techniques based on multiscale parameterization and refinement indicators. The thesis is divided into two main parts, where Part I gives a theoretical background for a collection of research papers that has been written by the candidate in collaboration with others. These constitutes the most important part of the thesis, and are presented in Part II. A brief outline of the thesis follows below. Numerical aspects concerning calculations of derivatives will also be discussed. Based on the introduction to regularization given in Chapter 2, methods for multiscale zonation, i.e. adaptive multiscale estimation and refinement

  19. Comparison of methods for estimating premorbid intelligence

    OpenAIRE

    Bright, Peter; van der Linde, Ian

    2018-01-01

    To evaluate impact of neurological injury on cognitive performance it is typically necessary to derive a baseline (or ‘premorbid’) estimate of a patient’s general cognitive ability prior to the onset of impairment. In this paper, we consider a range of common methods for producing this estimate, including those based on current best performance, embedded ‘hold/no hold’ tests, demographic information, and word reading ability. Ninety-two neurologically healthy adult participants were assessed ...

  20. A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China

    Directory of Open Access Journals (Sweden)

    Dengxiao Lang

    2017-09-01

    Full Text Available Potential evapotranspiration (PET is crucial for water resources assessment. In this regard, the FAO (Food and Agriculture Organization–Penman–Monteith method (PM is commonly recognized as a standard method for PET estimation. However, due to requirement of detailed meteorological data, the application of PM is often constrained in many regions. Under such circumstances, an alternative method with similar efficiency to that of PM needs to be identified. In this study, three radiation-based methods, Makkink (Mak, Abtew (Abt, and Priestley–Taylor (PT, and five temperature-based methods, Hargreaves–Samani (HS, Thornthwaite (Tho, Hamon (Ham, Linacre (Lin, and Blaney–Criddle (BC, were compared with PM at yearly and seasonal scale, using long-term (50 years data from 90 meteorology stations in southwest China. Indicators, viz. (videlicet Nash–Sutcliffe efficiency (NSE, relative error (Re, normalized root mean squared error (NRMSE, and coefficient of determination (R2 were used to evaluate the performance of PET estimations by the above-mentioned eight methods. The results showed that the performance of the methods in PET estimation varied among regions; HS, PT, and Abt overestimated PET, while others underestimated. In Sichuan basin, Mak, Abt and HS yielded similar estimations to that of PM, while, in Yun-Gui plateau, Abt, Mak, HS, and PT showed better performances. Mak performed the best in the east Tibetan Plateau at yearly and seasonal scale, while HS showed a good performance in summer and autumn. In the arid river valley, HS, Mak, and Abt performed better than the others. On the other hand, Tho, Ham, Lin, and BC could not be used to estimate PET in some regions. In general, radiation-based methods for PET estimation performed better than temperature-based methods among the selected methods in the study area. Among the radiation-based methods, Mak performed the best, while HS showed the best performance among the temperature-based

  1. Intent-Estimation- and Motion-Model-Based Collision Avoidance Method for Autonomous Vehicles in Urban Environments

    Directory of Open Access Journals (Sweden)

    Rulin Huang

    2017-04-01

    Full Text Available Existing collision avoidance methods for autonomous vehicles, which ignore the driving intent of detected vehicles, thus, cannot satisfy the requirements for autonomous driving in urban environments because of their high false detection rates of collisions with vehicles on winding roads and the missed detection rate of collisions with maneuvering vehicles. This study introduces an intent-estimation- and motion-model-based (IEMMB method to address these disadvantages. First, a state vector is constructed by combining the road structure and the moving state of detected vehicles. A Gaussian mixture model is used to learn the maneuvering patterns of vehicles from collected data, and the patterns are used to estimate the driving intent of the detected vehicles. Then, a desirable long-term trajectory is obtained by weighting time and comfort. The long-term trajectory and the short-term trajectory, which are predicted using a constant yaw rate motion model, are fused to achieve an accurate trajectory. Finally, considering the moving state of the autonomous vehicle, collisions can be detected and avoided. Experiments have shown that the intent estimation method performed well, achieving an accuracy of 91.7% on straight roads and an accuracy of 90.5% on winding roads, which is much higher than that achieved by the method that ignores the road structure. The average collision detection distance is increased by more than 8 m. In addition, the maximum yaw rate and acceleration during an evasive maneuver are decreased, indicating an improvement in the driving comfort.

  2. Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar

    Directory of Open Access Journals (Sweden)

    Shouguo Yang

    2015-12-01

    Full Text Available A novel spatio-temporal 2-dimensional (2-D processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD and direction of arrival (DOA, and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.

  3. A comparison study of size-specific dose estimate calculation methods

    Energy Technology Data Exchange (ETDEWEB)

    Parikh, Roshni A. [Rainbow Babies and Children' s Hospital, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Department of Radiology, Cleveland, OH (United States); University of Michigan Health System, Department of Radiology, Ann Arbor, MI (United States); Wien, Michael A.; Jordan, David W.; Ciancibello, Leslie; Berlin, Sheila C. [Rainbow Babies and Children' s Hospital, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Department of Radiology, Cleveland, OH (United States); Novak, Ronald D. [Rainbow Babies and Children' s Hospital, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Department of Radiology, Cleveland, OH (United States); Rebecca D. Considine Research Institute, Children' s Hospital Medical Center of Akron, Center for Mitochondrial Medicine Research, Akron, OH (United States); Klahr, Paul [CT Clinical Science, Philips Healthcare, Highland Heights, OH (United States); Soriano, Stephanie [Rainbow Babies and Children' s Hospital, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Department of Radiology, Cleveland, OH (United States); University of Washington, Department of Radiology, Seattle, WA (United States)

    2018-01-15

    The size-specific dose estimate (SSDE) has emerged as an improved metric for use by medical physicists and radiologists for estimating individual patient dose. Several methods of calculating SSDE have been described, ranging from patient thickness or attenuation-based (automated and manual) measurements to weight-based techniques. To compare the accuracy of thickness vs. weight measurement of body size to allow for the calculation of the size-specific dose estimate (SSDE) in pediatric body CT. We retrospectively identified 109 pediatric body CT examinations for SSDE calculation. We examined two automated methods measuring a series of level-specific diameters of the patient's body: method A used the effective diameter and method B used the water-equivalent diameter. Two manual methods measured patient diameter at two predetermined levels: the superior endplate of L2, where body width is typically most thin, and the superior femoral head or iliac crest (for scans that did not include the pelvis), where body width is typically most thick; method C averaged lateral measurements at these two levels from the CT projection scan, and method D averaged lateral and anteroposterior measurements at the same two levels from the axial CT images. Finally, we used body weight to characterize patient size, method E, and compared this with the various other measurement methods. Methods were compared across the entire population as well as by subgroup based on body width. Concordance correlation (ρ{sub c}) between each of the SSDE calculation methods (methods A-E) was greater than 0.92 across the entire population, although the range was wider when analyzed by subgroup (0.42-0.99). When we compared each SSDE measurement method with CTDI{sub vol,} there was poor correlation, ρ{sub c}<0.77, with percentage differences between 20.8% and 51.0%. Automated computer algorithms are accurate and efficient in the calculation of SSDE. Manual methods based on patient thickness provide

  4. Research on an estimation method of DOA for wireless location based on TD-SCDMA

    Science.gov (United States)

    Zhang, Yi; Luo, Yuan; Cheng, Shi-xin

    2004-03-01

    To meet the urgent need of personal communication and hign-speed data services,the standardization and products development for International Mobile Telecommunication-2000 (IMT-2000) have become a hot point in wordwide. The wireless location for mobile terminals has been an important research project. Unlike GPS which is located by 24 artificial satellities, it is based on the base-station of wireless cell network, and the research and development of it are correlative with IMT-2000. While the standard for the third generation mobile telecommunication (3G)-TD-SCDMA, which is proposed by China and the intellective property right of which is possessed by Chinese, is adopted by ITU-T at the first time, the research for wireless location based on TD-SCDMA has theoretic meaning, applied value and marketable foreground. First,the basic principle and method for wireless location, i.e. Direction of Angle(DOA), Time of Arrival(TOA) or Time Difference of Arrival(TDOA), hybridized location(TOA/DOA,TDOA/DOA,TDOA/DOA),etc. is introduced in the paper. So the research of DOA is very important in wireless location. Next, Main estimation methods of DOA for wireless location, i.e. ESPRIT, MUSIC, WSF, Min-norm, etc. are researched in the paper. In the end, the performances of DOA estimation for wireless location based on mobile telecommunication network are analyzed by the research of theory and simulation experiment and the contrast algorithms between and Cramer-Rao Bound. Its research results aren't only propitious to the choice of algorithms for wireless location, but also to the realization of new service of wireless location .

  5. Application of Modal Parameter Estimation Methods for Continuous Wavelet Transform-Based Damage Detection for Beam-Like Structures

    Directory of Open Access Journals (Sweden)

    Zhi Qiu

    2015-02-01

    Full Text Available This paper presents a hybrid damage detection method based on continuous wavelet transform (CWT and modal parameter identification techniques for beam-like structures. First, two kinds of mode shape estimation methods, herein referred to as the quadrature peaks picking (QPP and rational fraction polynomial (RFP methods, are used to identify the first four mode shapes of an intact beam-like structure based on the hammer/accelerometer modal experiment. The results are compared and validated using a numerical simulation with ABAQUS software. In order to determine the damage detection effectiveness between the QPP-based method and the RFP-based method when applying the CWT technique, the first two mode shapes calculated by the QPP and RFP methods are analyzed using CWT. The experiment, performed on different damage scenarios involving beam-like structures, shows that, due to the outstanding advantage of the denoising characteristic of the RFP-based (RFP-CWT technique, the RFP-CWT method gives a clearer indication of the damage location than the conventionally used QPP-based (QPP-CWT method. Finally, an overall evaluation of the damage detection is outlined, as the identification results suggest that the newly proposed RFP-CWT method is accurate and reliable in terms of detection of damage locations on beam-like structures.

  6. Stochastic LMP (Locational marginal price) calculation method in distribution systems to minimize loss and emission based on Shapley value and two-point estimate method

    International Nuclear Information System (INIS)

    Azad-Farsani, Ehsan; Agah, S.M.M.; Askarian-Abyaneh, Hossein; Abedi, Mehrdad; Hosseinian, S.H.

    2016-01-01

    LMP (Locational marginal price) calculation is a serious impediment in distribution operation when private DG (distributed generation) units are connected to the network. A novel policy is developed in this study to guide distribution company (DISCO) to exert its control over the private units when power loss and green-house gases emissions are minimized. LMP at each DG bus is calculated according to the contribution of the DG to the reduced amount of loss and emission. An iterative algorithm which is based on the Shapley value method is proposed to allocate loss and emission reduction. The proposed algorithm will provide a robust state estimation tool for DISCOs in the next step of operation. The state estimation tool provides the decision maker with the ability to exert its control over private DG units when loss and emission are minimized. Also, a stochastic approach based on the PEM (point estimate method) is employed to capture uncertainty in the market price and load demand. The proposed methodology is applied to a realistic distribution network, and efficiency and accuracy of the method are verified. - Highlights: • Reduction of the loss and emission at the same time. • Fair allocation of loss and emission reduction. • Estimation of the system state using an iterative algorithm. • Ability of DISCOs to control DG units via the proposed policy. • Modeling the uncertainties to calculate the stochastic LMP.

  7. A METHOD TO ESTIMATE TEMPORAL INTERACTION IN A CONDITIONAL RANDOM FIELD BASED APPROACH FOR CROP RECOGNITION

    Directory of Open Access Journals (Sweden)

    P. M. A. Diaz

    2016-06-01

    Full Text Available This paper presents a method to estimate the temporal interaction in a Conditional Random Field (CRF based approach for crop recognition from multitemporal remote sensing image sequences. This approach models the phenology of different crop types as a CRF. Interaction potentials are assumed to depend only on the class labels of an image site at two consecutive epochs. In the proposed method, the estimation of temporal interaction parameters is considered as an optimization problem, whose goal is to find the transition matrix that maximizes the CRF performance, upon a set of labelled data. The objective functions underlying the optimization procedure can be formulated in terms of different accuracy metrics, such as overall and average class accuracy per crop or phenological stages. To validate the proposed approach, experiments were carried out upon a dataset consisting of 12 co-registered LANDSAT images of a region in southeast of Brazil. Pattern Search was used as the optimization algorithm. The experimental results demonstrated that the proposed method was able to substantially outperform estimates related to joint or conditional class transition probabilities, which rely on training samples.

  8. Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

    Science.gov (United States)

    Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

    2015-01-01

    Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

  9. Developing an objective evaluation method to estimate diabetes risk in community-based settings.

    Science.gov (United States)

    Kenya, Sonjia; He, Qing; Fullilove, Robert; Kotler, Donald P

    2011-05-01

    Exercise interventions often aim to affect abdominal obesity and glucose tolerance, two significant risk factors for type 2 diabetes. Because of limited financial and clinical resources in community and university-based environments, intervention effects are often measured with interviews or questionnaires and correlated with weight loss or body fat indicated by body bioimpedence analysis (BIA). However, self-reported assessments are subject to high levels of bias and low levels of reliability. Because obesity and body fat are correlated with diabetes at different levels in various ethnic groups, data reflecting changes in weight or fat do not necessarily indicate changes in diabetes risk. To determine how exercise interventions affect diabetes risk in community and university-based settings, improved evaluation methods are warranted. We compared a noninvasive, objective measurement technique--regional BIA--with whole-body BIA for its ability to assess abdominal obesity and predict glucose tolerance in 39 women. To determine regional BIA's utility in predicting glucose, we tested the association between the regional BIA method and blood glucose levels. Regional BIA estimates of abdominal fat area were significantly correlated (r = 0.554, P < 0.003) with fasting glucose. When waist circumference and family history of diabetes were added to abdominal fat in multiple regression models, the association with glucose increased further (r = 0.701, P < 0.001). Regional BIA estimates of abdominal fat may predict fasting glucose better than whole-body BIA as well as provide an objective assessment of changes in diabetes risk achieved through physical activity interventions in community settings.

  10. 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.

  11. The probability estimate of the defects of the asynchronous motors based on the complex method of diagnostics

    Science.gov (United States)

    Zhukovskiy, Yu L.; Korolev, N. A.; Babanova, I. S.; Boikov, A. V.

    2017-10-01

    This article is devoted to the development of a method for probability estimate of failure of an asynchronous motor as a part of electric drive with a frequency converter. The proposed method is based on a comprehensive method of diagnostics of vibration and electrical characteristics that take into account the quality of the supply network and the operating conditions. The developed diagnostic system allows to increase the accuracy and quality of diagnoses by determining the probability of failure-free operation of the electromechanical equipment, when the parameters deviate from the norm. This system uses an artificial neural networks (ANNs). The results of the system for estimator the technical condition are probability diagrams of the technical state and quantitative evaluation of the defects of the asynchronous motor and its components.

  12. UD-DKF-based Parameters on-line Identification Method and AEKF-Based SOC Estimation Strategy of Lithium-ion Battery

    Directory of Open Access Journals (Sweden)

    Xuanju Dang

    2014-09-01

    Full Text Available State of charge (SOC is a significant parameter for the Battery Management System (BMS. The accurate estimation of the SOC can not only guarantee the SOC remaining within a reasonable scope of work, but also prevent the battery from being over or deeply-charged to extend the lifespan of battery. In this paper, the third-order RC equivalent circuit model is adopted to describe cell characteristics and the dual Kalman filter (DKF is used online to identify model parameters for battery. In order to avoid the impacts of rounding error calculation leading to the estimation error matrix loss of non-negative qualitative which result in the filtering divergence phenomenon, the UD decomposition method is applied for filtering time and state updates simultaneously to enhance the stability of the algorithm, reduce the computational complexity and improve the high recognition accuracy. Based on the obtained model parameters, Adaptive Extended Kalman Filter (AEKF is introduced to online estimate the SOC of battery. The simulation and experimental results demonstrate that the established third-order RC equivalent circuit model is effective, and the SOC estimation has a higher precision.

  13. Benchmarking Foot Trajectory Estimation Methods for Mobile Gait Analysis

    Directory of Open Access Journals (Sweden)

    Julius Hannink

    2017-08-01

    Full Text Available Mobile gait analysis systems based on inertial sensing on the shoe are applied in a wide range of applications. Especially for medical applications, they can give new insights into motor impairment in, e.g., neurodegenerative disease and help objectify patient assessment. One key component in these systems is the reconstruction of the foot trajectories from inertial data. In literature, various methods for this task have been proposed. However, performance is evaluated on a variety of datasets due to the lack of large, generally accepted benchmark datasets. This hinders a fair comparison of methods. In this work, we implement three orientation estimation and three double integration schemes for use in a foot trajectory estimation pipeline. All methods are drawn from literature and evaluated against a marker-based motion capture reference. We provide a fair comparison on the same dataset consisting of 735 strides from 16 healthy subjects. As a result, the implemented methods are ranked and we identify the most suitable processing pipeline for foot trajectory estimation in the context of mobile gait analysis.

  14. A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat—GLAS Footprints

    Directory of Open Access Journals (Sweden)

    Tianjin Huang

    2017-08-01

    Full Text Available We present in this paper a polynomial fitting method applicable to segments of footprints measured by the Geoscience Laser Altimeter System (GLAS to estimate glacier thickness change. Our modification makes the method applicable to complex topography, such as a large mountain glacier. After a full analysis of the planar fitting method to characterize errors of estimates due to complex topography, we developed an improved fitting method by adjusting a binary polynomial surface to local topography. The improved method and the planar fitting method were tested on the accumulation areas of the Naimona’nyi glacier and Yanong glacier on along-track facets with lengths of 1000 m, 1500 m, 2000 m, and 2500 m, respectively. The results show that the improved method gives more reliable estimates of changes in elevation than planar fitting. The improved method was also tested on Guliya glacier with a large and relatively flat area and the Chasku Muba glacier with very complex topography. The results in these test sites demonstrate that the improved method can give estimates of glacier thickness change on glaciers with a large area and a complex topography. Additionally, the improved method based on GLAS Data and Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM can give estimates of glacier thickness change from 2000 to 2008/2009, since it takes the 2000 SRTM-DEM as a reference, which is a longer period than 2004 to 2008/2009, when using the GLAS data only and the planar fitting method.

  15. Research on the method of information system risk state estimation based on clustering particle filter

    Directory of Open Access Journals (Sweden)

    Cui Jia

    2017-05-01

    Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  16. Research on the method of information system risk state estimation based on clustering particle filter

    Science.gov (United States)

    Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

    2017-05-01

    With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  17. Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods

    Science.gov (United States)

    Senay, G.B.; Leake, S.; Nagler, P.L.; Artan, G.; Dickinson, J.; Cordova, J.T.; Glenn, E.P.

    2011-01-01

    Evapotranspiration (ET) is an important hydrological process that can be studied and estimated at multiple spatial scales ranging from a leaf to a river basin. We present a review of methods in estimating basin scale ET and its applications in understanding basin water balance dynamics. The review focuses on two aspects of ET: (i) how the basin scale water balance approach is used to estimate ET; and (ii) how ‘direct’ measurement and modelling approaches are used to estimate basin scale ET. Obviously, the basin water balance-based ET requires the availability of good precipitation and discharge data to calculate ET as a residual on longer time scales (annual) where net storage changes are assumed to be negligible. ET estimated from such a basin water balance principle is generally used for validating the performance of ET models. On the other hand, many of the direct estimation methods involve the use of remotely sensed data to estimate spatially explicit ET and use basin-wide averaging to estimate basin scale ET. The direct methods can be grouped into soil moisture balance modelling, satellite-based vegetation index methods, and methods based on satellite land surface temperature measurements that convert potential ET into actual ET using a proportionality relationship. The review also includes the use of complementary ET estimation principles for large area applications. The review identifies the need to compare and evaluate the different ET approaches using standard data sets in basins covering different hydro-climatic regions of the world.

  18. Practical state of health estimation of power batteries based on Delphi method and grey relational grade analysis

    Science.gov (United States)

    Sun, Bingxiang; Jiang, Jiuchun; Zheng, Fangdan; Zhao, Wei; Liaw, Bor Yann; Ruan, Haijun; Han, Zhiqiang; Zhang, Weige

    2015-05-01

    The state of health (SOH) estimation is very critical to battery management system to ensure the safety and reliability of EV battery operation. Here, we used a unique hybrid approach to enable complex SOH estimations. The approach hybridizes the Delphi method known for its simplicity and effectiveness in applying weighting factors for complicated decision-making and the grey relational grade analysis (GRGA) for multi-factor optimization. Six critical factors were used in the consideration for SOH estimation: peak power at 30% state-of-charge (SOC), capacity, the voltage drop at 30% SOC with a C/3 pulse, the temperature rises at the end of discharge and charge at 1C; respectively, and the open circuit voltage at the end of charge after 1-h rest. The weighting of these factors for SOH estimation was scored by the 'experts' in the Delphi method, indicating the influencing power of each factor on SOH. The parameters for these factors expressing the battery state variations are optimized by GRGA. Eight battery cells were used to illustrate the principle and methodology to estimate the SOH by this hybrid approach, and the results were compared with those based on capacity and power capability. The contrast among different SOH estimations is discussed.

  19. Removing damped sinusoidal vibrations in adaptive optics systems using a DFT-based estimation method

    Science.gov (United States)

    Kania, Dariusz

    2017-06-01

    The problem of a vibrations rejection in adaptive optics systems is still present in publications. These undesirable signals emerge because of shaking the system structure, the tracking process, etc., and they usually are damped sinusoidal signals. There are some mechanical solutions to reduce the signals but they are not very effective. One of software solutions are very popular adaptive methods. An AVC (Adaptive Vibration Cancellation) method has been presented and developed in recent years. The method is based on the estimation of three vibrations parameters and values of frequency, amplitude and phase are essential to produce and adjust a proper signal to reduce or eliminate vibrations signals. This paper presents a fast (below 10 ms) and accurate estimation method of frequency, amplitude and phase of a multifrequency signal that can be used in the AVC method to increase the AO system performance. The method accuracy depends on several parameters: CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, THD, b - number of A/D converter bits in a real time system, γ - the damping ratio of the tested signal, φ - the phase of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value of systematic error for γ = 0.1%, CiR = 1.1 and N = 32 is approximately 10^-4 Hz/Hz. This paper focuses on systematic errors of and effect of the signal phase and values of γ on the results.

  20. 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...

  1. 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...

  2. 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.

  3. Fast Estimation Method of Space-Time Two-Dimensional Positioning Parameters Based on Hadamard Product

    Directory of Open Access Journals (Sweden)

    Haiwen Li

    2018-01-01

    Full Text Available The estimation speed of positioning parameters determines the effectiveness of the positioning system. The time of arrival (TOA and direction of arrival (DOA parameters can be estimated by the space-time two-dimensional multiple signal classification (2D-MUSIC algorithm for array antenna. However, this algorithm needs much time to complete the two-dimensional pseudo spectral peak search, which makes it difficult to apply in practice. Aiming at solving this problem, a fast estimation method of space-time two-dimensional positioning parameters based on Hadamard product is proposed in orthogonal frequency division multiplexing (OFDM system, and the Cramer-Rao bound (CRB is also presented. Firstly, according to the channel frequency domain response vector of each array, the channel frequency domain estimation vector is constructed using the Hadamard product form containing location information. Then, the autocorrelation matrix of the channel response vector for the extended array element in frequency domain and the noise subspace are calculated successively. Finally, by combining the closed-form solution and parameter pairing, the fast joint estimation for time delay and arrival direction is accomplished. The theoretical analysis and simulation results show that the proposed algorithm can significantly reduce the computational complexity and guarantee that the estimation accuracy is not only better than estimating signal parameters via rotational invariance techniques (ESPRIT algorithm and 2D matrix pencil (MP algorithm but also close to 2D-MUSIC algorithm. Moreover, the proposed algorithm also has certain adaptability to multipath environment and effectively improves the ability of fast acquisition of location parameters.

  4. Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

    Science.gov (United States)

    Zhaodi Guo; Jingyun Fang; Yude Pan; Richard. Birdsey

    2010-01-01

    Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to...

  5. 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.

  6. 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.

  7. TREEDE, Point Fluxes and Currents Based on Track Rotation Estimator by Monte-Carlo Method

    International Nuclear Information System (INIS)

    Dubi, A.

    1985-01-01

    1 - Description of problem or function: TREEDE is a Monte Carlo transport code based on the Track Rotation estimator, used, in general, to calculate fluxes and currents at a point. This code served as a test code in the development of the concept of the Track Rotation estimator, and therefore analogue Monte Carlo is used (i.e. no importance biasing). 2 - Method of solution: The basic idea is to follow the particle's track in the medium and then to rotate it such that it passes through the detector point. That is, rotational symmetry considerations (even in non-spherically symmetric configurations) are applied to every history, so that a very large fraction of the track histories can be rotated and made to pass through the point of interest; in this manner the 1/r 2 singularity in the un-collided flux estimator (next event estimator) is avoided. TREEDE, being a test code, is used to estimate leakage or in-medium fluxes at given points in a 3-dimensional finite box, where the source is an isotropic point source at the centre of the z = 0 surface. However, many of the constraints of geometry and source can be easily removed. The medium is assumed homogeneous with isotropic scattering, and one energy group only is considered. 3 - Restrictions on the complexity of the problem: One energy group, a homogeneous medium, isotropic scattering

  8. Estimating monthly temperature using point based interpolation techniques

    Science.gov (United States)

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

    2013-04-01

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

  9. Methods to estimate the genetic risk

    International Nuclear Information System (INIS)

    Ehling, U.H.

    1989-01-01

    The estimation of the radiation-induced genetic risk to human populations is based on the extrapolation of results from animal experiments. Radiation-induced mutations are stochastic events. The probability of the event depends on the dose; the degree of the damage dose not. There are two main approaches in making genetic risk estimates. One of these, termed the direct method, expresses risk in terms of expected frequencies of genetic changes induced per unit dose. The other, referred to as the doubling dose method or the indirect method, expresses risk in relation to the observed incidence of genetic disorders now present in man. The advantage of the indirect method is that not only can Mendelian mutations be quantified, but also other types of genetic disorders. The disadvantages of the method are the uncertainties in determining the current incidence of genetic disorders in human and, in addition, the estimasion of the genetic component of congenital anomalies, anomalies expressed later and constitutional and degenerative diseases. Using the direct method we estimated that 20-50 dominant radiation-induced mutations would be expected in 19 000 offspring born to parents exposed in Hiroshima and Nagasaki, but only a small proportion of these mutants would have been detected with the techniques used for the population study. These methods were used to predict the genetic damage from the fallout of the reactor accident at Chernobyl in the vicinity of Southern Germany. The lack of knowledge for the interaction of chemicals with ionizing radiation and the discrepancy between the high safety standards for radiation protection and the low level of knowledge for the toxicological evaluation of chemical mutagens will be emphasized. (author)

  10. A method for estimating age of medieval sub-adults from infancy to adulthood based on long bone length

    DEFF Research Database (Denmark)

    Primeau, Charlotte; Friis, Laila Saidane; Sejrsen, Birgitte

    2016-01-01

    OBJECTIVES: To develop a series of regression equations for estimating age from length of long bones for archaeological sub-adults when aging from dental development cannot be performed. Further, to compare derived ages when using these regression equations, and two other methods. MATERIAL AND ME...... as later than the medieval period, although this would require further testing. The quadratic equations are suggested to yield more accurate ages then using simply linear regression equations. Am J Phys Anthropol, 2015. © 2015 Wiley Periodicals, Inc.......OBJECTIVES: To develop a series of regression equations for estimating age from length of long bones for archaeological sub-adults when aging from dental development cannot be performed. Further, to compare derived ages when using these regression equations, and two other methods. MATERIAL...... AND METHODS: A total of 183 skeletal sub-adults from the Danish medieval period, were aged from radiographic images. Linear regression formulae were then produced for individual bones. Age was then estimated from the femur length using three different methods: equations developed in this study, data based...

  11. Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): a method for the estimation of climate using vegetation.

    Science.gov (United States)

    Harbert, Robert S; Nixon, Kevin C

    2015-08-01

    • Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate.• Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate.• Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ∼250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods.• CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies. © 2015 Botanical Society of America, Inc.

  12. A Method to Estimate the Size and Characteristics of HIV-positive Populations Using an Individual-based Stochastic Simulation Model

    DEFF Research Database (Denmark)

    Nakagawa, Fumiyo; van Sighem, Ard; Thiebaut, Rodolphe

    2016-01-01

    % plausibility range: 39,900-45,560) men who have sex with men were estimated to be living with HIV in the UK, of whom 10,400 (6,160-17,350) were undiagnosed. There were an estimated 3,210 (1,730-5,350) infections per year on average between 2010 and 2013. Sixty-two percent of the total HIV-positive population......It is important not only to collect epidemiologic data on HIV but to also fully utilize such information to understand the epidemic over time and to help inform and monitor the impact of policies and interventions. We describe and apply a novel method to estimate the size and characteristics of HIV-positive...... populations. The method was applied to data on men who have sex with men living in the UK and to a pseudo dataset to assess performance for different data availability. The individual-based simulation model was calibrated using an approximate Bayesian computation-based approach. In 2013, 48,310 (90...

  13. Differential estimates of southern flying squirrel (Glaucomys volans) population structure based on capture method

    Science.gov (United States)

    Kevin S. Laves; Susan C. Loeb

    2005-01-01

    It is commonly assumed that population estimates derived from trapping small mammals are accurate and unbiased or that estimates derived from different capture methods are comparable. We captured southern flying squirrels (Glaucmrtys volam) using two methods to study their effect on red-cockaded woodpecker (Picoides bumah) reproductive success. Southern flying...

  14. Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation

    Directory of Open Access Journals (Sweden)

    Sharad Damodar Gore

    2009-10-01

    Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.

  15. Evaluation of non cyanide methods for hemoglobin estimation

    Directory of Open Access Journals (Sweden)

    Vinaya B Shah

    2011-01-01

    Full Text Available Background: The hemoglobincyanide method (HiCN method for measuring hemoglobin is used extensively worldwide; its advantages are the ready availability of a stable and internationally accepted reference standard calibrator. However, its use may create a problem, as the waste disposal of large volumes of reagent containing cyanide constitutes a potential toxic hazard. Aims and Objective: As an alternative to drabkin`s method of Hb estimation, we attempted to estimate hemoglobin by other non-cyanide methods: alkaline hematin detergent (AHD-575 using Triton X-100 as lyser and alkaline- borax method using quarternary ammonium detergents as lyser. Materials and Methods: The hemoglobin (Hb results on 200 samples of varying Hb concentrations obtained by these two cyanide free methods were compared with a cyanmethemoglobin method on a colorimeter which is light emitting diode (LED based. Hemoglobin was also estimated in one hundred blood donors and 25 blood samples of infants and compared by these methods. Statistical analysis used was Pearson`s correlation coefficient. Results: The response of the non cyanide method is linear for serially diluted blood samples over the Hb concentration range from 3gm/dl -20 gm/dl. The non cyanide methods has a precision of + 0.25g/dl (coefficient of variation= (2.34% and is suitable for use with fixed wavelength or with colorimeters at wavelength- 530 nm and 580 nm. Correlation of these two methods was excellent (r=0.98. The evaluation has shown it to be as reliable and reproducible as HiCN for measuring hemoglobin at all concentrations. The reagents used in non cyanide methods are non-biohazardous and did not affect the reliability of data determination and also the cost was less than HiCN method. Conclusions: Thus, non cyanide methods of Hb estimation offer possibility of safe and quality Hb estimation and should prove useful for routine laboratory use. Non cyanide methods is easily incorporated in hemobloginometers

  16. Unrecorded Alcohol Consumption: Quantitative Methods of Estimation

    OpenAIRE

    Razvodovsky, Y. E.

    2010-01-01

    unrecorded alcohol; methods of estimation In this paper we focused on methods of estimation of unrecorded alcohol consumption level. Present methods of estimation of unrevorded alcohol consumption allow only approximate estimation of unrecorded alcohol consumption level. Tacking into consideration the extreme importance of such kind of data, further investigation is necessary to improve the reliability of methods estimation of unrecorded alcohol consumption.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  18. Permanent Magnet Flux Online Estimation Based on Zero-Voltage Vector Injection Method

    DEFF Research Database (Denmark)

    Xie, Ge; Lu, Kaiyuan; Kumar, Dwivedi Sanjeet

    2015-01-01

    In this paper, a simple signal injection method is proposed for sensorless control of PMSM at low speed, which ideally requires one voltage vector only for position estimation. The proposed method is easy to implement resulting in low computation burden. No filters are needed for extracting...

  19. A New Method for Estimation of Velocity Vectors

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt; Munk, Peter

    1998-01-01

    The paper describes a new method for determining the velocity vector of a remotely sensed object using either sound or electromagnetic radiation. The movement of the object is determined from a field with spatial oscillations in both the axial direction of the transducer and in one or two...... directions transverse to the axial direction. By using a number of pulse emissions, the inter-pulse movement can be estimated and the velocity found from the estimated movement and the time between pulses. The method is based on the principle of using transverse spatial modulation for making the received...

  20. HIGH-PRECISION ATTITUDE ESTIMATION METHOD OF STAR SENSORS AND GYRO BASED ON COMPLEMENTARY FILTER AND UNSCENTED KALMAN FILTER

    Directory of Open Access Journals (Sweden)

    C. Guo

    2017-07-01

    Full Text Available Determining the attitude of satellite at the time of imaging then establishing the mathematical relationship between image points and ground points is essential in high-resolution remote sensing image mapping. Star tracker is insensitive to the high frequency attitude variation due to the measure noise and satellite jitter, but the low frequency attitude motion can be determined with high accuracy. Gyro, as a short-term reference to the satellite’s attitude, is sensitive to high frequency attitude change, but due to the existence of gyro drift and integral error, the attitude determination error increases with time. Based on the opposite noise frequency characteristics of two kinds of attitude sensors, this paper proposes an on-orbit attitude estimation method of star sensors and gyro based on Complementary Filter (CF and Unscented Kalman Filter (UKF. In this study, the principle and implementation of the proposed method are described. First, gyro attitude quaternions are acquired based on the attitude kinematics equation. An attitude information fusion method is then introduced, which applies high-pass filtering and low-pass filtering to the gyro and star tracker, respectively. Second, the attitude fusion data based on CF are introduced as the observed values of UKF system in the process of measurement updating. The accuracy and effectiveness of the method are validated based on the simulated sensors attitude data. The obtained results indicate that the proposed method can suppress the gyro drift and measure noise of attitude sensors, improving the accuracy of the attitude determination significantly, comparing with the simulated on-orbit attitude and the attitude estimation results of the UKF defined by the same simulation parameters.

  1. Statistical Methods for Estimating the Uncertainty in the Best Basis Inventories

    International Nuclear Information System (INIS)

    WILMARTH, S.R.

    2000-01-01

    This document describes the statistical methods used to determine sample-based uncertainty estimates for the Best Basis Inventory (BBI). For each waste phase, the equation for the inventory of an analyte in a tank is Inventory (Kg or Ci) = Concentration x Density x Waste Volume. the total inventory is the sum of the inventories in the different waste phases. Using tanks sample data: statistical methods are used to obtain estimates of the mean concentration of an analyte the density of the waste, and their standard deviations. The volumes of waste in the different phases, and their standard deviations, are estimated based on other types of data. The three estimates are multiplied to obtain the inventory estimate. The standard deviations are combined to obtain a standard deviation of the inventory. The uncertainty estimate for the Best Basis Inventory (BBI) is the approximate 95% confidence interval on the inventory

  2. 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.

  3. A Method to Estimate Energy Demand in Existing Buildings Based on the Danish Building and Dwellings Register (BBR)

    DEFF Research Database (Denmark)

    Nielsen, Anker; Bertelsen, Niels Haldor; Wittchen, Kim Bjarne

    2013-01-01

    an energy label. The Danish Building Research Institute has described a method that can be used to estimate the energy demand in buildings specially dwellings. This is based on the information in the Danish Building and Dwelling Register (BBR) and information on building regulations at construction year......The Energy Performance Directive requires energy certifications for buildings. This is implemented in Denmark so that houses that are sold must have an energy performance label based on an evaluation from a visit to the building. The result is that only a small part of the existing houses has...... for the house. The result is an estimate for energy demand in each building with a variation. This makes it possible to make an automatic classification of all buildings. Then it is possible to find houses in need for thermal improvements. This method is tested for single family houses and flats. The paper...

  4. 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 ...

  5. Comparing writing style feature-based classification methods for estimating user reputations in social media.

    Science.gov (United States)

    Suh, Jong Hwan

    2016-01-01

    In recent years, the anonymous nature of the Internet has made it difficult to detect manipulated user reputations in social media, as well as to ensure the qualities of users and their posts. To deal with this, this study designs and examines an automatic approach that adopts writing style features to estimate user reputations in social media. Under varying ways of defining Good and Bad classes of user reputations based on the collected data, it evaluates the classification performance of the state-of-art methods: four writing style features, i.e. lexical, syntactic, structural, and content-specific, and eight classification techniques, i.e. four base learners-C4.5, Neural Network (NN), Support Vector Machine (SVM), and Naïve Bayes (NB)-and four Random Subspace (RS) ensemble methods based on the four base learners. When South Korea's Web forum, Daum Agora, was selected as a test bed, the experimental results show that the configuration of the full feature set containing content-specific features and RS-SVM combining RS and SVM gives the best accuracy for classification if the test bed poster reputations are segmented strictly into Good and Bad classes by portfolio approach. Pairwise t tests on accuracy confirm two expectations coming from the literature reviews: first, the feature set adding content-specific features outperform the others; second, ensemble learning methods are more viable than base learners. Moreover, among the four ways on defining the classes of user reputations, i.e. like, dislike, sum, and portfolio, the results show that the portfolio approach gives the highest accuracy.

  6. Research of Block-Based Motion Estimation Methods for Video Compression

    Directory of Open Access Journals (Sweden)

    Tropchenko Andrey

    2016-08-01

    Full Text Available This work is a review of the block-based algorithms used for motion estimation in video compression. It researches different types of block-based algorithms that range from the simplest named Full Search to the fast adaptive algorithms like Hierarchical Search. The algorithms evaluated in this paper are widely accepted by the video compressing community and have been used in implementing various standards, such as MPEG-4 Visual and H.264. The work also presents a very brief introduction to the entire flow of video compression.

  7. 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.

  8. A Group Contribution Method for Estimating Cetane and Octane Numbers

    Energy Technology Data Exchange (ETDEWEB)

    Kubic, William Louis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Process Modeling and Analysis Group

    2016-07-28

    Much of the research on advanced biofuels is devoted to the study of novel chemical pathways for converting nonfood biomass into liquid fuels that can be blended with existing transportation fuels. Many compounds under consideration are not found in the existing fuel supplies. Often, the physical properties needed to assess the viability of a potential biofuel are not available. The only reliable information available may be the molecular structure. Group contribution methods for estimating physical properties from molecular structure have been used for more than 60 years. The most common application is estimation of thermodynamic properties. More recently, group contribution methods have been developed for estimating rate dependent properties including cetane and octane numbers. Often, published group contribution methods are limited in terms of types of function groups and range of applicability. In this study, a new, broadly-applicable group contribution method based on an artificial neural network was developed to estimate cetane number research octane number, and motor octane numbers of hydrocarbons and oxygenated hydrocarbons. The new method is more accurate over a greater range molecular weights and structural complexity than existing group contribution methods for estimating cetane and octane numbers.

  9. Comparison of different methods in estimating potential evapotranspiration at Muda Irrigation Scheme of Malaysia

    Directory of Open Access Journals (Sweden)

    Sobri Harun

    2012-04-01

    Full Text Available Evapotranspiration (ET is a complex process in the hydrological cycle that influences the quantity of runoff and thus the irrigation water requirements. Numerous methods have been developed to estimate potential evapotranspiration (PET. Unfortunately, most of the reliable PET methods are parameter rich models and therefore, not feasible for application in data scarce regions. On the other hand, accuracy and reliability of simple PET models vary widely according to regional climate conditions. The objective of the present study was to evaluate the performance of three temperature-based and three radiation-based simple ET methods in estimating historical ET and projecting future ET at Muda Irrigation Scheme at Kedah, Malaysia. The performance was measured by comparing those methods with the parameter intensive Penman-Monteith Method. It was found that radiation based methods gave better performance compared to temperature-based methods in estimation of ET in the study area. Future ET simulated from projected climate data obtained through statistical downscaling technique also showed that radiation-based methods can project closer ET values to that projected by Penman-Monteith Method. It is expected that the study will guide in selecting suitable methods for estimating and projecting ET in accordance to availability of meteorological data.

  10. Novel Method for 5G Systems NLOS Channels Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Vladeta Milenkovic

    2017-01-01

    Full Text Available For the development of new 5G systems to operate in mm bands, there is a need for accurate radio propagation modelling at these bands. In this paper novel approach for NLOS channels parameter estimation will be presented. Estimation will be performed based on LCR performance measure, which will enable us to estimate propagation parameters in real time and to avoid weaknesses of ML and moment method estimation approaches.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-10-01

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

  12. 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...

  13. Uncertainty estimation with a small number of measurements, part II: a redefinition of uncertainty and an estimator method

    Science.gov (United States)

    Huang, Hening

    2018-01-01

    This paper is the second (Part II) in a series of two papers (Part I and Part II). Part I has quantitatively discussed the fundamental limitations of the t-interval method for uncertainty estimation with a small number of measurements. This paper (Part II) reveals that the t-interval is an ‘exact’ answer to a wrong question; it is actually misused in uncertainty estimation. This paper proposes a redefinition of uncertainty, based on the classical theory of errors and the theory of point estimation, and a modification of the conventional approach to estimating measurement uncertainty. It also presents an asymptotic procedure for estimating the z-interval. The proposed modification is to replace the t-based uncertainty with an uncertainty estimator (mean- or median-unbiased). The uncertainty estimator method is an approximate answer to the right question to uncertainty estimation. The modified approach provides realistic estimates of uncertainty, regardless of whether the population standard deviation is known or unknown, or if the sample size is small or large. As an application example of the modified approach, this paper presents a resolution to the Du-Yang paradox (i.e. Paradox 2), one of the three paradoxes caused by the misuse of the t-interval in uncertainty estimation.

  14. A robust method for estimating motorbike count based on visual information learning

    Science.gov (United States)

    Huynh, Kien C.; Thai, Dung N.; Le, Sach T.; Thoai, Nam; Hamamoto, Kazuhiko

    2015-03-01

    Estimating the number of vehicles in traffic videos is an important and challenging task in traffic surveillance, especially with a high level of occlusions between vehicles, e.g.,in crowded urban area with people and/or motorbikes. In such the condition, the problem of separating individual vehicles from foreground silhouettes often requires complicated computation [1][2][3]. Thus, the counting problem is gradually shifted into drawing statistical inferences of target objects density from their shape [4], local features [5], etc. Those researches indicate a correlation between local features and the number of target objects. However, they are inadequate to construct an accurate model for vehicles density estimation. In this paper, we present a reliable method that is robust to illumination changes and partial affine transformations. It can achieve high accuracy in case of occlusions. Firstly, local features are extracted from images of the scene using Speed-Up Robust Features (SURF) method. For each image, a global feature vector is computed using a Bag-of-Words model which is constructed from the local features above. Finally, a mapping between the extracted global feature vectors and their labels (the number of motorbikes) is learned. That mapping provides us a strong prediction model for estimating the number of motorbikes in new images. The experimental results show that our proposed method can achieve a better accuracy in comparison to others.

  15. An iterative stochastic ensemble method for parameter estimation of subsurface flow models

    International Nuclear Information System (INIS)

    Elsheikh, Ahmed H.; Wheeler, Mary F.; Hoteit, Ibrahim

    2013-01-01

    Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss–Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates

  16. An iterative stochastic ensemble method for parameter estimation of subsurface flow models

    KAUST Repository

    Elsheikh, Ahmed H.

    2013-06-01

    Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss-Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates. © 2013 Elsevier Inc.

  17. Boundary methods for mode estimation

    Science.gov (United States)

    Pierson, William E., Jr.; Ulug, Batuhan; Ahalt, Stanley C.

    1999-08-01

    This paper investigates the use of Boundary Methods (BMs), a collection of tools used for distribution analysis, as a method for estimating the number of modes associated with a given data set. Model order information of this type is required by several pattern recognition applications. The BM technique provides a novel approach to this parameter estimation problem and is comparable in terms of both accuracy and computations to other popular mode estimation techniques currently found in the literature and automatic target recognition applications. This paper explains the methodology used in the BM approach to mode estimation. Also, this paper quickly reviews other common mode estimation techniques and describes the empirical investigation used to explore the relationship of the BM technique to other mode estimation techniques. Specifically, the accuracy and computational efficiency of the BM technique are compared quantitatively to the a mixture of Gaussian (MOG) approach and a k-means approach to model order estimation. The stopping criteria of the MOG and k-means techniques is the Akaike Information Criteria (AIC).

  18. Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery

    International Nuclear Information System (INIS)

    Hu, Chao; Jain, Gaurav; Zhang, Puqiang; Schmidt, Craig; Gomadam, Parthasarathy; Gorka, Tom

    2014-01-01

    Highlights: • We develop a data-driven method for the battery capacity estimation. • Five charge-related features that are indicative of the capacity are defined. • The kNN regression model captures the dependency of the capacity on the features. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the battery health condition by estimating the battery capacity over the life-time. This paper presents a data-driven method for estimating the capacity of Li-ion battery based on the charge voltage and current curves. The contributions of this paper are three-fold: (i) the definition of five characteristic features of the charge curves that are indicative of the capacity, (ii) the development of a non-linear kernel regression model, based on the k-nearest neighbor (kNN) regression, that captures the complex dependency of the capacity on the five features, and (iii) the adaptation of particle swarm optimization (PSO) to finding the optimal combination of feature weights for creating a kNN regression model that minimizes the cross validation (CV) error in the capacity estimation. Verification with 10 years’ continuous cycling data suggests that the proposed method is able to accurately estimate the capacity of Li-ion battery throughout the whole life-time

  19. 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:

  20. Estimating the impact of extreme events on crude oil price. An EMD-based event analysis method

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xun; Wang, Shouyang [Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); School of Mathematical Sciences, Graduate University of Chinese Academy of Sciences, Beijing 100190 (China); Yu, Lean [Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung [Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon (China)

    2009-09-15

    The impact of extreme events on crude oil markets is of great importance in crude oil price analysis due to the fact that those events generally exert strong impact on crude oil markets. For better estimation of the impact of events on crude oil price volatility, this study attempts to use an EMD-based event analysis approach for this task. In the proposed method, the time series to be analyzed is first decomposed into several intrinsic modes with different time scales from fine-to-coarse and an average trend. The decomposed modes respectively capture the fluctuations caused by the extreme event or other factors during the analyzed period. It is found that the total impact of an extreme event is included in only one or several dominant modes, but the secondary modes provide valuable information on subsequent factors. For overlapping events with influences lasting for different periods, their impacts are separated and located in different modes. For illustration and verification purposes, two extreme events, the Persian Gulf War in 1991 and the Iraq War in 2003, are analyzed step by step. The empirical results reveal that the EMD-based event analysis method provides a feasible solution to estimating the impact of extreme events on crude oil prices variation. (author)

  1. Estimating the impact of extreme events on crude oil price. An EMD-based event analysis method

    International Nuclear Information System (INIS)

    Zhang, Xun; Wang, Shouyang; Yu, Lean; Lai, Kin Keung

    2009-01-01

    The impact of extreme events on crude oil markets is of great importance in crude oil price analysis due to the fact that those events generally exert strong impact on crude oil markets. For better estimation of the impact of events on crude oil price volatility, this study attempts to use an EMD-based event analysis approach for this task. In the proposed method, the time series to be analyzed is first decomposed into several intrinsic modes with different time scales from fine-to-coarse and an average trend. The decomposed modes respectively capture the fluctuations caused by the extreme event or other factors during the analyzed period. It is found that the total impact of an extreme event is included in only one or several dominant modes, but the secondary modes provide valuable information on subsequent factors. For overlapping events with influences lasting for different periods, their impacts are separated and located in different modes. For illustration and verification purposes, two extreme events, the Persian Gulf War in 1991 and the Iraq War in 2003, are analyzed step by step. The empirical results reveal that the EMD-based event analysis method provides a feasible solution to estimating the impact of extreme events on crude oil prices variation. (author)

  2. Comparison of conventional, model-based quantitative planar, and quantitative SPECT image processing methods for organ activity estimation using In-111 agents

    International Nuclear Information System (INIS)

    He, Bin; Frey, Eric C

    2006-01-01

    Accurate quantification of organ radionuclide uptake is important for patient-specific dosimetry. The quantitative accuracy from conventional conjugate view methods is limited by overlap of projections from different organs and background activity, and attenuation and scatter. In this work, we propose and validate a quantitative planar (QPlanar) processing method based on maximum likelihood (ML) estimation of organ activities using 3D organ VOIs and a projector that models the image degrading effects. Both a physical phantom experiment and Monte Carlo simulation (MCS) studies were used to evaluate the new method. In these studies, the accuracies and precisions of organ activity estimates for the QPlanar method were compared with those from conventional planar (CPlanar) processing methods with various corrections for scatter, attenuation and organ overlap, and a quantitative SPECT (QSPECT) processing method. Experimental planar and SPECT projections and registered CT data from an RSD Torso phantom were obtained using a GE Millenium VH/Hawkeye system. The MCS data were obtained from the 3D NCAT phantom with organ activity distributions that modelled the uptake of 111 In ibritumomab tiuxetan. The simulations were performed using parameters appropriate for the same system used in the RSD torso phantom experiment. The organ activity estimates obtained from the CPlanar, QPlanar and QSPECT methods from both experiments were compared. From the results of the MCS experiment, even with ideal organ overlap correction and background subtraction, CPlanar methods provided limited quantitative accuracy. The QPlanar method with accurate modelling of the physical factors increased the quantitative accuracy at the cost of requiring estimates of the organ VOIs in 3D. The accuracy of QPlanar approached that of QSPECT, but required much less acquisition and computation time. Similar results were obtained from the physical phantom experiment. We conclude that the QPlanar method, based

  3. 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.

  4. 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.

  5. 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.

  6. An energy estimation framework for event-based methods in Non-Intrusive Load Monitoring

    International Nuclear Information System (INIS)

    Giri, Suman; Bergés, Mario

    2015-01-01

    Highlights: • Energy estimation is NILM has not yet accounted for complexity of appliance models. • We present a data-driven framework for appliance modeling in supervised NILM. • We test the framework on 3 houses and report average accuracies of 5.9–22.4%. • Appliance models facilitate the estimation of energy consumed by the appliance. - Abstract: Non-Intrusive Load Monitoring (NILM) is a set of techniques used to estimate the electricity consumed by individual appliances in a building from measurements of the total electrical consumption. Most commonly, NILM works by first attributing any significant change in the total power consumption (also known as an event) to a specific load and subsequently using these attributions (i.e. the labels for the events) to estimate energy for each load. For this last step, most published work in the field makes simplifying assumptions to make the problem more tractable. In this paper, we present a framework for creating appliance models based on classification labels and aggregate power measurements that can help to relax many of these assumptions. Our framework automatically builds models for appliances to perform energy estimation. The model relies on feature extraction, clustering via affinity propagation, perturbation of extracted states to ensure that they mimic appliance behavior, creation of finite state models, correction of any errors in classification that might violate the model, and estimation of energy based on corrected labels. We evaluate our framework on 3 houses from standard datasets in the field and show that the framework can learn data-driven models based on event labels and use that to estimate energy with lower error margins (e.g., 1.1–42.3%) than when using the heuristic models used by others

  7. V and V based Fault Estimation Method for Safety-Critical Software using BNs

    International Nuclear Information System (INIS)

    Eom, Heung Seop; Park, Gee Yong; Jang, Seung Cheol; Kang, Hyun Gook

    2011-01-01

    Quantitative software reliability measurement approaches have severe limitations in demonstrating the proper level of reliability for safety-critical software. These limitations can be overcome by using some other means of assessment. One of the promising candidates is based on the quality of the software development. Particularly in the nuclear industry, regulatory bodies in most countries do not accept the concept of quantitative goals as a sole means of meeting their regulations for the reliability of digital computers in NPPs, and use deterministic criteria for both hardware and software. The point of deterministic criteria is to assess the whole development process and its related activities during the software development life cycle for the acceptance of safety-critical software, and software V and V plays an important role in this process. In this light, we studied a V and V based fault estimation method using Bayesian Nets (BNs) to assess the reliability of safety-critical software, especially reactor protection system software in a NPP. The BNs in the study were made for an estimation of software faults and were based on the V and V frame, which governs the development of safety-critical software in the nuclear field. A case study was carried out for a reactor protection system that was developed as a part of the Korea Nuclear Instrumentation and Control System. The insight from the case study is that some important factors affecting the fault number of the target software include the residual faults in the system specification, maximum number of faults introduced in the development phase, ratio between process/function characteristic, uncertainty sizing, and fault elimination rate by inspection activities

  8. Fusion rule estimation using vector space methods

    International Nuclear Information System (INIS)

    Rao, N.S.V.

    1997-01-01

    In a system of N sensors, the sensor S j , j = 1, 2 .... N, outputs Y (j) element-of Re, according to an unknown probability distribution P (Y(j) /X) , corresponding to input X element-of [0, 1]. A training n-sample (X 1 , Y 1 ), (X 2 , Y 2 ), ..., (X n , Y n ) is given where Y i = (Y i (1) , Y i (2) , . . . , Y i N ) such that Y i (j) is the output of S j in response to input X i . The problem is to estimate a fusion rule f : Re N → [0, 1], based on the sample, such that the expected square error is minimized over a family of functions Y that constitute a vector space. The function f* that minimizes the expected error cannot be computed since the underlying densities are unknown, and only an approximation f to f* is feasible. We estimate the sample size sufficient to ensure that f provides a close approximation to f* with a high probability. The advantages of vector space methods are two-fold: (a) the sample size estimate is a simple function of the dimensionality of F, and (b) the estimate f can be easily computed by well-known least square methods in polynomial time. The results are applicable to the classical potential function methods and also (to a recently proposed) special class of sigmoidal feedforward neural networks

  9. Comparison of methods for estimating herbage intake in grazing dairy cows

    DEFF Research Database (Denmark)

    Hellwing, Anne Louise Frydendahl; Lund, Peter; Weisbjerg, Martin Riis

    2015-01-01

    Estimation of herbage intake is a challenge both under practical and experimental conditions. The aim of this study was to estimate herbage intake with different methods for cows grazing 7 h daily on either spring or autumn pastures. In order to generate variation between cows, the 20 cows per...... season, and the herbage intake was estimated twice during each season. Cows were on pasture from 8:00 until 15:00, and were subsequently housed inside and fed a mixed ration (MR) based on maize silage ad libitum. Herbage intake was estimated with nine different methods: (1) animal performance (2) intake...

  10. 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.

  11. 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.

  12. Residual-based a posteriori error estimation for multipoint flux mixed finite element methods

    KAUST Repository

    Du, Shaohong; Sun, Shuyu; Xie, Xiaoping

    2015-01-01

    A novel residual-type a posteriori error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimensions. The derived a posteriori error estimator for the velocity and pressure error in L-norm consists of discretization and quadrature indicators, and is shown to be reliable and efficient. The main tools of analysis are a locally postprocessed approximation to the pressure solution of an auxiliary problem and a quadrature error estimate. Numerical experiments are presented to illustrate the competitive behavior of the estimator.

  13. Residual-based a posteriori error estimation for multipoint flux mixed finite element methods

    KAUST Repository

    Du, Shaohong

    2015-10-26

    A novel residual-type a posteriori error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimensions. The derived a posteriori error estimator for the velocity and pressure error in L-norm consists of discretization and quadrature indicators, and is shown to be reliable and efficient. The main tools of analysis are a locally postprocessed approximation to the pressure solution of an auxiliary problem and a quadrature error estimate. Numerical experiments are presented to illustrate the competitive behavior of the estimator.

  14. Methods to estimate breeding values in honey bees

    NARCIS (Netherlands)

    Brascamp, E.W.; Bijma, P.

    2014-01-01

    Background Efficient methodologies based on animal models are widely used to estimate breeding values in farm animals. These methods are not applicable in honey bees because of their mode of reproduction. Observations are recorded on colonies, which consist of a single queen and thousands of workers

  15. Reliability of Estimation Pile Load Capacity Methods

    Directory of Open Access Journals (Sweden)

    Yudhi Lastiasih

    2014-04-01

    Full Text Available None of numerous previous methods for predicting pile capacity is known how accurate any of them are when compared with the actual ultimate capacity of piles tested to failure. The author’s of the present paper have conducted such an analysis, based on 130 data sets of field loading tests. Out of these 130 data sets, only 44 could be analysed, of which 15 were conducted until the piles actually reached failure. The pile prediction methods used were: Brinch Hansen’s method (1963, Chin’s method (1970, Decourt’s Extrapolation Method (1999, Mazurkiewicz’s method (1972, Van der Veen’s method (1953, and the Quadratic Hyperbolic Method proposed by Lastiasih et al. (2012. It was obtained that all the above methods were sufficiently reliable when applied to data from pile loading tests that loaded to reach failure. However, when applied to data from pile loading tests that loaded without reaching failure, the methods that yielded lower values for correction factor N are more recommended. Finally, the empirical method of Reese and O’Neill (1988 was found to be reliable enough to be used to estimate the Qult of a pile foundation based on soil data only.

  16. A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy

    International Nuclear Information System (INIS)

    Wang, Yujie; Zhang, Chenbin; Chen, Zonghai

    2015-01-01

    Highlights: • Build a multi-model switching SOC estimate method for Li-ion batteries. • Build an improved interpretative structural modeling method for model switching. • The feedback strategy of bus delay is applied to improve the real-time performance. • The EKF method is used for SOC estimation to improve the estimated accuracy. - Abstract: The accurate state-of-charge (SOC) estimation and real-time performance are critical evaluation indexes for Li-ion battery management systems (BMS). High accuracy algorithms often take long program execution time (PET) in the resource-constrained embedded application systems, which will undoubtedly lead to the decrease of the time slots of other processes, thereby reduce the overall performance of BMS. Considering the resource optimization and the computational load balance, this paper proposes a multi-model switching SOC estimation method for Li-ion batteries. Four typical battery models are employed to build a close-loop SOC estimation system. The extended Kalman filter (EKF) method is employed to eliminate the effect of the current noise and improve the accuracy of SOC. The experiments under dynamic current conditions are conducted to verify the accuracy and real-time performance of the proposed method. The experimental results indicate that accurate estimation results and reasonable PET can be obtained by the proposed method

  17. 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

  18. History based batch method preserving tally means

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Choi, Sung Hoon

    2012-01-01

    In the Monte Carlo (MC) eigenvalue calculations, the sample variance of a tally mean calculated from its cycle-wise estimates is biased because of the inter-cycle correlations of the fission source distribution (FSD). Recently, we proposed a new real variance estimation method named the history-based batch method in which a MC run is treated as multiple runs with small number of histories per cycle to generate independent tally estimates. In this paper, the history-based batch method based on the weight correction is presented to preserve the tally mean from the original MC run. The effectiveness of the new method is examined for the weakly coupled fissile array problem as a function of the dominance ratio and the batch size, in comparison with other schemes available

  19. A different approach to estimate nonlinear regression model using numerical methods

    Science.gov (United States)

    Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

    2017-11-01

    This research paper concerns with the computational methods namely the Gauss-Newton method, Gradient algorithm methods (Newton-Raphson method, Steepest Descent or Steepest Ascent algorithm method, the Method of Scoring, the Method of Quadratic Hill-Climbing) based on numerical analysis to estimate parameters of nonlinear regression model in a very different way. Principles of matrix calculus have been used to discuss the Gradient-Algorithm methods. Yonathan Bard [1] discussed a comparison of gradient methods for the solution of nonlinear parameter estimation problems. However this article discusses an analytical approach to the gradient algorithm methods in a different way. This paper describes a new iterative technique namely Gauss-Newton method which differs from the iterative technique proposed by Gorden K. Smyth [2]. Hans Georg Bock et.al [10] proposed numerical methods for parameter estimation in DAE’s (Differential algebraic equation). Isabel Reis Dos Santos et al [11], Introduced weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel. For large-scale non smooth convex minimization the Hager and Zhang (HZ) conjugate gradient Method and the modified HZ (MHZ) method were presented by Gonglin Yuan et al [12].

  20. Methods of albumin estimation in clinical biochemistry: Past, present, and future.

    Science.gov (United States)

    Kumar, Deepak; Banerjee, Dibyajyoti

    2017-06-01

    Estimation of serum and urinary albumin is routinely performed in clinical biochemistry laboratories. In the past, precipitation-based methods were popular for estimation of human serum albumin (HSA). Currently, dye-binding or immunochemical methods are widely practiced. Each of these methods has its limitations. Research endeavors to overcome such limitations are on-going. The current trends in methodological aspects of albumin estimation guiding the field have not been reviewed. Therefore, it is the need of the hour to review several aspects of albumin estimation. The present review focuses on the modern trends of research from a conceptual point of view and gives an overview of recent developments to offer the readers a comprehensive understanding of the subject. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. 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

  2. Estimation of subcriticality of TCA using 'indirect estimation method for calculation error'

    International Nuclear Information System (INIS)

    Naito, Yoshitaka; Yamamoto, Toshihiro; Arakawa, Takuya; Sakurai, Kiyoshi

    1996-01-01

    To estimate the subcriticality of neutron multiplication factor in a fissile system, 'Indirect Estimation Method for Calculation Error' is proposed. This method obtains the calculational error of neutron multiplication factor by correlating measured values with the corresponding calculated ones. This method was applied to the source multiplication and to the pulse neutron experiments conducted at TCA, and the calculation error of MCNP 4A was estimated. In the source multiplication method, the deviation of measured neutron count rate distributions from the calculated ones estimates the accuracy of calculated k eff . In the pulse neutron method, the calculation errors of prompt neutron decay constants give the accuracy of the calculated k eff . (author)

  3. Estimation of deuterium content in organic compounds by mass spectrometric methods

    International Nuclear Information System (INIS)

    Dave, S.M.; Goomer, N.C.

    1979-01-01

    Many organic sompounds are finding increasing importance in heavy water enrichment programme. New methods based on quantitative chemical conversion have been developed and standardized in for estimating deuterium contents of the exchanging organic molecules by mass spectrometry. The methods have been selected in such a way that the deuterium contents of both exchangeable as well as total hydrogens in the molecule can be conveniently estimated. (auth.)

  4. Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

    Science.gov (United States)

    Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

    2017-06-01

    Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

  5. Dual ant colony operational modal analysis parameter estimation method

    Science.gov (United States)

    Sitarz, Piotr; Powałka, Bartosz

    2018-01-01

    Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

  6. A test of the ADV-based Reynolds flux method for in situ estimation of sediment settling velocity in a muddy estuary

    Science.gov (United States)

    Cartwright, Grace M.; Friedrichs, Carl T.; Smith, S. Jarrell

    2013-12-01

    Under conditions common in muddy coastal and estuarine environments, acoustic Doppler velocimeters (ADVs) can serve to estimate sediment settling velocity ( w s) by assuming a balance between upward turbulent Reynolds flux and downward gravitational settling. Advantages of this method include simple instrument deployment, lack of flow disturbance, and relative insensitivity to biofouling and water column stratification. Although this method is being used with increasing frequency in coastal and estuarine environments, to date it has received little direct ground truthing. This study compared in situ estimates of w s inferred by a 5-MHz ADV to independent in situ observations from a high-definition video settling column over the course of a flood tide in the bottom boundary layer of the York River estuary, Virginia, USA. The ADV-based measurements were found to agree with those of the settling column when the current speed at about 40 cm above the bed was greater than about 20 cm/s. This corresponded to periods when the estimated magnitude of the settling term in the suspended sediment continuity equation was four or more times larger than the time rate of change of concentration. For ADV observations restricted to these conditions, ADV-based estimates of w s (mean 0.48±0.04 mm/s) were highly consistent with those observed by the settling column (mean 0.45±0.02 mm/s). However, the ADV-based method for estimating w s was sensitive to the prescribed concentration of the non-settling washload, C wash. In an objective operational definition, C wash can be set equal to the lowest suspended solids concentration observed around slack water.

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

    Directory of Open Access Journals (Sweden)

    Nizar Tayem

    2017-01-01

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

  8. The efficiency of different estimation methods of hydro-physical limits

    Directory of Open Access Journals (Sweden)

    Emma María Martínez

    2012-12-01

    Full Text Available The soil water available to crops is defined by specific values of water potential limits. Underlying the estimation of hydro-physical limits, identified as permanent wilting point (PWP and field capacity (FC, is the selection of a suitable method based on a multi-criteria analysis that is not always clear and defined. In this kind of analysis, the time required for measurements must be taken into consideration as well as other external measurement factors, e.g., the reliability and suitability of the study area, measurement uncertainty, cost, effort and labour invested. In this paper, the efficiency of different methods for determining hydro-physical limits is evaluated by using indices that allow for the calculation of efficiency in terms of effort and cost. The analysis evaluates both direct determination methods (pressure plate - PP and water activity meter - WAM and indirect estimation methods (pedotransfer functions - PTFs. The PTFs must be validated for the area of interest before use, but the time and cost associated with this validation are not included in the cost of analysis. Compared to the other methods, the combined use of PP and WAM to determine hydro-physical limits differs significantly in time and cost required and quality of information. For direct methods, increasing sample size significantly reduces cost and time. This paper assesses the effectiveness of combining a general analysis based on efficiency indices and more specific analyses based on the different influencing factors, which were considered separately so as not to mask potential benefits or drawbacks that are not evidenced in efficiency estimation.

  9. Improvement of economic potential estimation methods for enterprise with potential branch clusters use

    Directory of Open Access Journals (Sweden)

    V.Ya. Nusinov

    2017-08-01

    Full Text Available The research determines that the current existing methods of enterprise’s economic potential estimation are based on the use of additive, multiplicative and rating models. It is determined that the existing methods have a row of defects. For example, not all the methods take into account the branch features of the analysis, and also the level of development of the enterprise comparatively with other enterprises. It is suggested to level such defects by an account at the estimation of potential integral level not only by branch features of enterprises activity but also by the intra-account economic clusterization of such enterprises. Scientific works which are connected with the using of clusters for the estimation of economic potential are generalized. According to the results of generalization it is determined that it is possible to distinguish 9 scientific approaches in this direction: the use of natural clusterization of enterprises with the purpose of estimation and increase of region potential; the use of natural clusterization of enterprises with the purpose of estimation and increase of industry potential; use of artificial clusterization of enterprises with the purpose of estimation and increase of region potential; use of artificial clusterization of enterprises with the purpose of estimation and increase of industry potential; the use of artificial clusterization of enterprises with the purpose of clustering potential estimation; the use of artificial clusterization of enterprises with the purpose of estimation of clustering competitiveness potential; the use of natural (artificial clusterization for the estimation of clustering efficiency; the use of natural (artificial clusterization for the increase of level at region (industries development; the use of methods of economic potential of region (industries estimation or its constituents for the construction of the clusters. It is determined that the use of clusterization method in

  10. Investigation on method of estimating the excitation spectrum of vibration source

    International Nuclear Information System (INIS)

    Zhang Kun; Sun Lei; Lin Song

    2010-01-01

    In practical engineer area, it is hard to obtain the excitation spectrum of the auxiliary machines of nuclear reactor through direct measurement. To solve this problem, the general method of estimating the excitation spectrum of vibration source through indirect measurement is proposed. First, the dynamic transfer matrix between the virtual excitation points and the measure points is obtained through experiment. The matrix combined with the response spectrum at the measure points under practical work condition can be used to calculate the excitation spectrum acts on the virtual excitation points. Then a simplified method is proposed which is based on the assumption that the vibration machine can be regarded as rigid body. The method treats the centroid as the excitation point and the dynamic transfer matrix is derived by using the sub structure mobility synthesis method. Thus, the excitation spectrum can be obtained by the inverse of the transfer matrix combined with the response spectrum at the measure points. Based on the above method, a computing example is carried out to estimate the excitation spectrum acts on the centroid of a electrical pump. By comparing the input excitation and the estimated excitation, the reliability of this method is verified. (authors)

  11. Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

    Science.gov (United States)

    Mehdizadeh, Saeid

    2018-04-01

    Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external

  12. Simple method for quick estimation of aquifer hydrogeological parameters

    Science.gov (United States)

    Ma, C.; Li, Y. Y.

    2017-08-01

    Development of simple and accurate methods to determine the aquifer hydrogeological parameters was of importance for groundwater resources assessment and management. Aiming at the present issue of estimating aquifer parameters based on some data of the unsteady pumping test, a fitting function of Theis well function was proposed using fitting optimization method and then a unitary linear regression equation was established. The aquifer parameters could be obtained by solving coefficients of the regression equation. The application of the proposed method was illustrated, using two published data sets. By the error statistics and analysis on the pumping drawdown, it showed that the method proposed in this paper yielded quick and accurate estimates of the aquifer parameters. The proposed method could reliably identify the aquifer parameters from long distance observed drawdowns and early drawdowns. It was hoped that the proposed method in this paper would be helpful for practicing hydrogeologists and hydrologists.

  13. Heuristic introduction to estimation methods

    International Nuclear Information System (INIS)

    Feeley, J.J.; Griffith, J.M.

    1982-08-01

    The methods and concepts of optimal estimation and control have been very successfully applied in the aerospace industry during the past 20 years. Although similarities exist between the problems (control, modeling, measurements) in the aerospace and nuclear power industries, the methods and concepts have found only scant acceptance in the nuclear industry. Differences in technical language seem to be a major reason for the slow transfer of estimation and control methods to the nuclear industry. Therefore, this report was written to present certain important and useful concepts with a minimum of specialized language. By employing a simple example throughout the report, the importance of several information and uncertainty sources is stressed and optimal ways of using or allowing for these sources are presented. This report discusses optimal estimation problems. A future report will discuss optimal control problems

  14. Estimation method of state-of-charge for lithium-ion battery used in hybrid electric vehicles based on variable structure extended kalman filter

    Science.gov (United States)

    Sun, Yong; Ma, Zilin; Tang, Gongyou; Chen, Zheng; Zhang, Nong

    2016-07-01

    Since the main power source of hybrid electric vehicle(HEV) is supplied by the power battery, the predicted performance of power battery, especially the state-of-charge(SOC) estimation has attracted great attention in the area of HEV. However, the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected. A variable structure extended kalman filter(VSEKF)-based estimation method, which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition, is presented. First, the general lower-order battery equivalent circuit model(GLM), which includes column accumulation model, open circuit voltage model and the SOC output model, is established, and the off-line and online model parameters are calculated with hybrid pulse power characteristics(HPPC) test data. Next, a VSEKF estimation method of SOC, which integrates the ampere-hour(Ah) integration method and the extended Kalman filter(EKF) method, is executed with different adaptive weighting coefficients, which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes. According to the experimental analysis, the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV. The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method. In Summary, the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system, which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method. The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

  15. A Bayes linear Bayes method for estimation of correlated event rates.

    Science.gov (United States)

    Quigley, John; Wilson, Kevin J; Walls, Lesley; Bedford, Tim

    2013-12-01

    Typically, full Bayesian estimation of correlated event rates can be computationally challenging since estimators are intractable. When estimation of event rates represents one activity within a larger modeling process, there is an incentive to develop more efficient inference than provided by a full Bayesian model. We develop a new subjective inference method for correlated event rates based on a Bayes linear Bayes model under the assumption that events are generated from a homogeneous Poisson process. To reduce the elicitation burden we introduce homogenization factors to the model and, as an alternative to a subjective prior, an empirical method using the method of moments is developed. Inference under the new method is compared against estimates obtained under a full Bayesian model, which takes a multivariate gamma prior, where the predictive and posterior distributions are derived in terms of well-known functions. The mathematical properties of both models are presented. A simulation study shows that the Bayes linear Bayes inference method and the full Bayesian model provide equally reliable estimates. An illustrative example, motivated by a problem of estimating correlated event rates across different users in a simple supply chain, shows how ignoring the correlation leads to biased estimation of event rates. © 2013 Society for Risk Analysis.

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

    Directory of Open Access Journals (Sweden)

    SERGIO YÁÑEZ

    2010-01-01

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

  17. 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.

  18. Hydrological model uncertainty due to spatial evapotranspiration estimation methods

    Science.gov (United States)

    Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

    2016-05-01

    Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

  19. A method of incident angle estimation for high resolution spectral recovery in filter-array-based spectrometers

    Science.gov (United States)

    Kim, Cheolsun; Lee, Woong-Bi; Ju, Gun Wu; Cho, Jeonghoon; Kim, Seongmin; Oh, Jinkyung; Lim, Dongsung; Lee, Yong Tak; Lee, Heung-No

    2017-02-01

    In recent years, there has been an increasing interest in miniature spectrometers for research and development. Especially, filter-array-based spectrometers have advantages of low cost and portability, and can be applied in various fields such as biology, chemistry and food industry. Miniaturization in optical filters causes degradation of spectral resolution due to limitations on spectral responses and the number of filters. Nowadays, many studies have been reported that the filter-array-based spectrometers have achieved resolution improvements by using digital signal processing (DSP) techniques. The performance of the DSP-based spectral recovery highly depends on the prior information of transmission functions (TFs) of the filters. The TFs vary with respect to an incident angle of light onto the filter-array. Conventionally, it is assumed that the incident angle of light on the filters is fixed and the TFs are known to the DSP. However, the incident angle is inconstant according to various environments and applications, and thus TFs also vary, which leads to performance degradation of spectral recovery. In this paper, we propose a method of incident angle estimation (IAE) for high resolution spectral recovery in the filter-array-based spectrometers. By exploiting sparse signal reconstruction of the L1- norm minimization, IAE estimates an incident angle among all possible incident angles which minimizes the error of the reconstructed signal. Based on IAE, DSP effectively provides a high resolution spectral recovery in the filter-array-based spectrometers.

  20. Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

    DEFF Research Database (Denmark)

    Drews, Martin; Lauritzen, Bent; Madsen, Henrik

    2005-01-01

    A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model...... parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...

  1. Estimation of Cross-Lingual News Similarities Using Text-Mining Methods

    Directory of Open Access Journals (Sweden)

    Zhouhao Wang

    2018-01-01

    Full Text Available In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the Internet, and these are written not only in English but also in other languages such as Chinese, Japanese, French, etc. By taking advantage of multi-lingual text resources provided by Thomson Reuters News, we developed two estimation algorithms for extracting cross-lingual news pairs from multilingual text resources. In our first method, we propose a novel structure that uses the word information and the machine learning method effectively in this task. Simultaneously, we developed a bidirectional Long Short-Term Memory (LSTM based method to calculate cross-lingual semantic text similarity for long text and short text, respectively. Thus, when an important news article is published, users can read similar news articles that are written in their native language using our method.

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

    DEFF Research Database (Denmark)

    Lunde, Asger; Brix, Anne Floor

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

  3. Point Estimation Method of Electromagnetic Flowmeters Life Based on Randomly Censored Failure Data

    Directory of Open Access Journals (Sweden)

    Zhen Zhou

    2014-08-01

    Full Text Available This paper analyzes the characteristics of the enterprise after-sale service records for field failure data, and summarizes the types of field data. Maximum likelihood estimation method and the least squares method are presented for the complexity and difficulty of field failure data processing, and Monte Carlo simulation method is proposed. Monte Carlo simulation, the relatively simple calculation method, is an effective method, whose result is closed to that of the other two methods. Through the after-sale service records analysis of a specific electromagnetic flowmeter enterprises, this paper illustrates the effectiveness of field failure data processing methods.

  4. Source Estimation for the Damped Wave Equation Using Modulating Functions Method: Application to the Estimation of the Cerebral Blood Flow

    KAUST Repository

    Asiri, Sharefa M.

    2017-10-19

    In this paper, a method based on modulating functions is proposed to estimate the Cerebral Blood Flow (CBF). The problem is written in an input estimation problem for a damped wave equation which is used to model the spatiotemporal variations of blood mass density. The method is described and its performance is assessed through some numerical simulations. The robustness of the method in presence of noise is also studied.

  5. Improved stove programs need robust methods to estimate carbon offsets

    OpenAIRE

    Johnson, Michael; Edwards, Rufus; Masera, Omar

    2010-01-01

    Current standard methods result in significant discrepancies in carbon offset accounting compared to approaches based on representative community based subsamples, which provide more realistic assessments at reasonable cost. Perhaps more critically, neither of the currently approved methods incorporates uncertainties inherent in estimates of emission factors or non-renewable fuel usage (fNRB). Since emission factors and fNRB contribute 25% and 47%, respectively, to the overall uncertainty in ...

  6. 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.

  7. Improved Battery Parameter Estimation Method Considering Operating Scenarios for HEV/EV Applications

    Directory of Open Access Journals (Sweden)

    Jufeng Yang

    2016-12-01

    Full Text Available This paper presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.

  8. 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...

  9. 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...

  10. Extended Kalman filter-based methods for pose estimation using visual, inertial and magnetic sensors: comparative analysis and performance evaluation.

    Science.gov (United States)

    Ligorio, Gabriele; Sabatini, Angelo Maria

    2013-02-04

    In this paper measurements from a monocular vision system are fused with inertial/magnetic measurements from an Inertial Measurement Unit (IMU) rigidly connected to the camera. Two Extended Kalman filters (EKFs) were developed to estimate the pose of the IMU/camera sensor moving relative to a rigid scene (ego-motion), based on a set of fiducials. The two filters were identical as for the state equation and the measurement equations of the inertial/magnetic sensors. The DLT-based EKF exploited visual estimates of the ego-motion using a variant of the Direct Linear Transformation (DLT) method; the error-driven EKF exploited pseudo-measurements based on the projection errors from measured two-dimensional point features to the corresponding three-dimensional fiducials. The two filters were off-line analyzed in different experimental conditions and compared to a purely IMU-based EKF used for estimating the orientation of the IMU/camera sensor. The DLT-based EKF was more accurate than the error-driven EKF, less robust against loss of visual features, and equivalent in terms of computational complexity. Orientation root mean square errors (RMSEs) of 1° (1.5°), and position RMSEs of 3.5 mm (10 mm) were achieved in our experiments by the DLT-based EKF (error-driven EKF); by contrast, orientation RMSEs of 1.6° were achieved by the purely IMU-based EKF.

  11. New proposal of moderator temperature coefficient estimation method using gray-box model in NPP, (1)

    International Nuclear Information System (INIS)

    Mori, Michitsugu; Kagami, Yuichi; Kanemoto, Shigeru; Enomoto, Mitsuhiro; Tamaoki, Tetsuo; Kawamura, Shinichiro

    2004-01-01

    The purpose of the present paper is to establish a new void reactivity coefficient (VRC) estimation method based on gray box modeling concept. The gray box model consists of a point kinetics model as the first principle model and a fitting model of moderator temperature kinetics. Applying Kalman filter and maximum likehood estimation algorithms to the gray box model, MTC can be estimated. The verification test is done by Monte Carlo simulation, and, it is shown that the present method gives the best estimation results comparing with the conventional methods from the viewpoints of non-biased and smallest scattering estimation performance. Furthermore, the method is verified via real plant data analysis. The reason of good performance of the present method is explained by proper definition of likelihood function based on explicit expression of observation and system noise in the gray box model. (author)

  12. 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.

  13. Development of Quadratic Programming Algorithm Based on Interior Point Method with Estimation Mechanism of Active Constraints

    Science.gov (United States)

    Hashimoto, Hiroyuki; Takaguchi, Yusuke; Nakamura, Shizuka

    Instability of calculation process and increase of calculation time caused by increasing size of continuous optimization problem remain the major issues to be solved to apply the technique to practical industrial systems. This paper proposes an enhanced quadratic programming algorithm based on interior point method mainly for improvement of calculation stability. The proposed method has dynamic estimation mechanism of active constraints on variables, which fixes the variables getting closer to the upper/lower limit on them and afterwards releases the fixed ones as needed during the optimization process. It is considered as algorithm-level integration of the solution strategy of active-set method into the interior point method framework. We describe some numerical results on commonly-used bench-mark problems called “CUTEr” to show the effectiveness of the proposed method. Furthermore, the test results on large-sized ELD problem (Economic Load Dispatching problems in electric power supply scheduling) are also described as a practical industrial application.

  14. Public-Private Investment Partnerships: Efficiency Estimation Methods

    Directory of Open Access Journals (Sweden)

    Aleksandr Valeryevich Trynov

    2016-06-01

    Full Text Available The article focuses on assessing the effectiveness of investment projects implemented on the principles of public-private partnership (PPP. This article puts forward the hypothesis that the inclusion of multiplicative economic effects will increase the attractiveness of public-private partnership projects, which in turn will contribute to the more efficient use of budgetary resources. The author proposed a methodological approach and methods of evaluating the economic efficiency of PPP projects. The author’s technique is based upon the synthesis of approaches to evaluation of the project implemented in the private and public sector and in contrast to the existing methods allows taking into account the indirect (multiplicative effect arising during the implementation of project. In the article, to estimate the multiplier effect, the model of regional economy — social accounting matrix (SAM was developed. The matrix is based on the data of the Sverdlovsk region for 2013. In the article, the genesis of the balance models of economic systems is presented. The evolution of balance models in the Russian (Soviet and foreign sources from their emergence up to now are observed. It is shown that SAM is widely used in the world for a wide range of applications, primarily to assess the impact on the regional economy of various exogenous factors. In order to clarify the estimates of multiplicative effects, the disaggregation of the account of the “industry” of the matrix of social accounts was carried out in accordance with the All-Russian Classifier of Types of Economic Activities (OKVED. This step allows to consider the particular characteristics of the industry of the estimated investment project. The method was tested on the example of evaluating the effectiveness of the construction of a toll road in the Sverdlovsk region. It is proved that due to the multiplier effect, the more capital-intensive version of the project may be more beneficial in

  15. TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, S; Politte, D; O’Sullivan, J [Washington University in St. Louis, St. Louis, MO (United States); Han, D; Porras-Chaverri, M; Williamson, J [Virginia Commonwealth University, Richmond, VA (United States); Whiting, B [University of Pittsburgh, Pittsburgh, PA (United States)

    2016-06-15

    Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philips Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantom materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional

  16. Method-related estimates of sperm vitality.

    Science.gov (United States)

    Cooper, Trevor G; Hellenkemper, Barbara

    2009-01-01

    Comparison of methods that estimate viability of human spermatozoa by monitoring head membrane permeability revealed that wet preparations (whether using positive or negative phase-contrast microscopy) generated significantly higher percentages of nonviable cells than did air-dried eosin-nigrosin smears. Only with the latter method did the sum of motile (presumed live) and stained (presumed dead) preparations never exceed 100%, making this the method of choice for sperm viability estimates.

  17. Methods for dependency estimation and system unavailability evaluation based on failure data statistics

    International Nuclear Information System (INIS)

    Azarm, M.A.; Hsu, F.; Martinez-Guridi, G.; Vesely, W.E.

    1993-07-01

    This report introduces a new perspective on the basic concept of dependent failures where the definition of dependency is based on clustering in failure times of similar components. This perspective has two significant implications: first, it relaxes the conventional assumption that dependent failures must be simultaneous and result from a severe shock; second, it allows the analyst to use all the failures in a time continuum to estimate the potential for multiple failures in a window of time (e.g., a test interval), therefore arriving at a more accurate value for system unavailability. In addition, the models developed here provide a method for plant-specific analysis of dependency, reflecting the plant-specific maintenance practices that reduce or increase the contribution of dependent failures to system unavailability. The proposed methodology can be used for screening analysis of failure data to estimate the fraction of dependent failures among the failures. In addition, the proposed method can evaluate the impact of the observed dependency on system unavailability and plant risk. The formulations derived in this report have undergone various levels of validations through computer simulation studies and pilot applications. The pilot applications of these methodologies showed that the contribution of dependent failures of diesel generators in one plant was negligible, while in another plant was quite significant. It also showed that in the plant with significant contribution of dependency to Emergency Power System (EPS) unavailability, the contribution changed with time. Similar findings were reported for the Containment Fan Cooler breakers. Drawing such conclusions about system performance would not have been possible with any other reported dependency methodologies

  18. A comparison and accuracy analysis of impedance-based temperature estimation methods for Li-ion batteries

    NARCIS (Netherlands)

    Beelen, H.P.G.J.; Raijmakers, L.H.J.; Donkers, M.C.F.; Notten, P.H.L.; Bergveld, H.J.

    2016-01-01

    In order to guarantee safe and proper use of Lithium-ion batteries during operation, an accurate estimate of the battery temperature is of paramount importance. Electrochemical Impedance Spectroscopy (EIS) can be used to estimate the battery temperature and several EIS-based temperature estimation

  19. 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.

  20. State Estimation-based Transmission line parameter identification

    Directory of Open Access Journals (Sweden)

    Fredy Andrés Olarte Dussán

    2010-01-01

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

  1. pyParticleEst: A Python Framework for Particle-Based Estimation Methods

    Directory of Open Access Journals (Sweden)

    Jerker Nordh

    2017-06-01

    Full Text Available Particle methods such as the particle filter and particle smoothers have proven very useful for solving challenging nonlinear estimation problems in a wide variety of fields during the last decade. However, there are still very few existing tools available to support and assist researchers and engineers in applying the vast number of methods in this field to their own problems. This paper identifies the common operations between the methods and describes a software framework utilizing this information to provide a flexible and extensible foundation which can be used to solve a large variety of problems in this domain, thereby allowing code reuse to reduce the implementation burden and lowering the barrier of entry for applying this exciting field of methods. The software implementation presented in this paper is freely available and permissively licensed under the GNU Lesser General Public License, and runs on a large number of hardware and software platforms, making it usable for a large variety of scenarios.

  2. Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values.

    Science.gov (United States)

    McMillan, Kyle; Bostani, Maryam; Cagnon, Christopher H; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H; McNitt-Gray, Michael F

    2017-08-01

    The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose. Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating

  3. Conventional estimating method of earthquake response of mechanical appendage system

    International Nuclear Information System (INIS)

    Aoki, Shigeru; Suzuki, Kohei

    1981-01-01

    Generally, for the estimation of the earthquake response of appendage structure system installed in main structure system, the method of floor response analysis using the response spectra at the point of installing the appendage system has been used. On the other hand, the research on the estimation of the earthquake response of appendage system by the statistical procedure based on probability process theory has been reported. The development of a practical method for simply estimating the response is an important subject in aseismatic engineering. In this study, the method of estimating the earthquake response of appendage system in the general case that the natural frequencies of both structure systems were different was investigated. First, it was shown that floor response amplification factor was able to be estimated simply by giving the ratio of the natural frequencies of both structure systems, and its statistical property was clarified. Next, it was elucidated that the procedure of expressing acceleration, velocity and displacement responses with tri-axial response spectra simultaneously was able to be applied to the expression of FRAF. The applicability of this procedure to nonlinear system was examined. (Kako, I.)

  4. Estimation of water percolation by different methods using TDR

    Directory of Open Access Journals (Sweden)

    Alisson Jadavi Pereira da Silva

    2014-02-01

    Full Text Available Detailed knowledge on water percolation into the soil in irrigated areas is fundamental for solving problems of drainage, pollution and the recharge of underground aquifers. The aim of this study was to evaluate the percolation estimated by time-domain-reflectometry (TDR in a drainage lysimeter. We used Darcy's law with K(θ functions determined by field and laboratory methods and by the change in water storage in the soil profile at 16 points of moisture measurement at different time intervals. A sandy clay soil was saturated and covered with plastic sheet to prevent evaporation and an internal drainage trial in a drainage lysimeter was installed. The relationship between the observed and estimated percolation values was evaluated by linear regression analysis. The results suggest that percolation in the field or laboratory can be estimated based on continuous monitoring with TDR, and at short time intervals, of the variations in soil water storage. The precision and accuracy of this approach are similar to those of the lysimeter and it has advantages over the other evaluated methods, of which the most relevant are the possibility of estimating percolation in short time intervals and exemption from the predetermination of soil hydraulic properties such as water retention and hydraulic conductivity. The estimates obtained by the Darcy-Buckingham equation for percolation levels using function K(θ predicted by the method of Hillel et al. (1972 provided compatible water percolation estimates with those obtained in the lysimeter at time intervals greater than 1 h. The methods of Libardi et al. (1980, Sisson et al. (1980 and van Genuchten (1980 underestimated water percolation.

  5. Improvement of Source Number Estimation Method for Single Channel Signal.

    Directory of Open Access Journals (Sweden)

    Zhi Dong

    Full Text Available Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin's disk estimation (GDE and minimum description length (MDL, are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely.

  6. Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study.

    Science.gov (United States)

    Fan, Ming; Kuwahara, Hiroyuki; Wang, Xiaolei; Wang, Suojin; Gao, Xin

    2015-11-01

    Parameter estimation is a challenging computational problem in the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter estimation of gene circuit models from such time-series mRNA data has become an important method for quantitatively dissecting the regulation of gene expression. By focusing on the modeling of gene circuits, we examine here the performance of three types of state-of-the-art parameter estimation methods: population-based methods, online methods and model-decomposition-based methods. Our results show that certain population-based methods are able to generate high-quality parameter solutions. The performance of these methods, however, is heavily dependent on the size of the parameter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, online methods and model decomposition-based methods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fast methods with local search as a subsequent refinement procedure can substantially increase the quality of their parameter estimates to the level on par with the best solution obtained from the population-based methods while maintaining high computational speed. These suggest that such hybrid methods can be a promising alternative to the more commonly used population-based methods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatory mechanisms makes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  7. A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Deyu Cui

    2018-04-01

    Full Text Available State of charge (SOC estimation is becoming increasingly important, along with electric vehicle (EV rapid development, while SOC is one of the most significant parameters for the battery management system, indicating remaining energy and ensuring the safety and reliability of EV. In this paper, a hybrid wavelet neural network (WNN model combining the discrete wavelet transform (DWT method and adaptive WNN is proposed to estimate the SOC of lithium-ion batteries. The WNN model is trained by Levenberg-Marquardt (L-M algorithm, whose inputs are processed by discrete wavelet decomposition and reconstitution. Compared with back-propagation neural network (BPNN, L-M based BPNN (LMBPNN, L-M based WNN (LMWNN, DWT with L-M based BPNN (DWTLMBPNN and extend Kalman filter (EKF, the proposed intelligent SOC estimation method is validated and proved to be effective. Under the New European Driving Cycle (NEDC, the mean absolute error and maximum error can be reduced to 0.59% and 3.13%, respectively. The characteristics of high accuracy and strong robustness of the proposed method are verified by comparison study and robustness evaluation results (e.g., measurement noise test and untrained driving cycle test.

  8. Estimating Rooftop Suitability for PV: A Review of Methods, Patents, and Validation Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Melius, J. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Margolis, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Ong, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    A number of methods have been developed using remote sensing data to estimate rooftop area suitable for the installation of photovoltaics (PV) at various geospatial resolutions. This report reviews the literature and patents on methods for estimating rooftop-area appropriate for PV, including constant-value methods, manual selection methods, and GIS-based methods. This report also presents NREL's proposed method for estimating suitable rooftop area for PV using Light Detection and Ranging (LiDAR) data in conjunction with a GIS model to predict areas with appropriate slope, orientation, and sunlight. NREL's method is validated against solar installation data from New Jersey, Colorado, and California to compare modeled results to actual on-the-ground measurements.

  9. 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.

  10. Information-theoretic methods for estimating of complicated probability distributions

    CERN Document Server

    Zong, Zhi

    2006-01-01

    Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur

  11. Source Estimation for the Damped Wave Equation Using Modulating Functions Method: Application to the Estimation of the Cerebral Blood Flow

    KAUST Repository

    Asiri, Sharefa M.; Laleg-Kirati, Taous-Meriem

    2017-01-01

    In this paper, a method based on modulating functions is proposed to estimate the Cerebral Blood Flow (CBF). The problem is written in an input estimation problem for a damped wave equation which is used to model the spatiotemporal variations

  12. 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.

  13. Evaluation and comparison of estimation methods for failure rates and probabilities

    Energy Technology Data Exchange (ETDEWEB)

    Vaurio, Jussi K. [Fortum Power and Heat Oy, P.O. Box 23, 07901 Loviisa (Finland)]. E-mail: jussi.vaurio@fortum.com; Jaenkaelae, Kalle E. [Fortum Nuclear Services, P.O. Box 10, 00048 Fortum (Finland)

    2006-02-01

    An updated parametric robust empirical Bayes (PREB) estimation methodology is presented as an alternative to several two-stage Bayesian methods used to assimilate failure data from multiple units or plants. PREB is based on prior-moment matching and avoids multi-dimensional numerical integrations. The PREB method is presented for failure-truncated and time-truncated data. Erlangian and Poisson likelihoods with gamma prior are used for failure rate estimation, and Binomial data with beta prior are used for failure probability per demand estimation. Combined models and assessment uncertainties are accounted for. One objective is to compare several methods with numerical examples and show that PREB works as well if not better than the alternative more complex methods, especially in demanding problems of small samples, identical data and zero failures. False claims and misconceptions are straightened out, and practical applications in risk studies are presented.

  14. Estimation of functional failure probability of passive systems based on adaptive importance sampling method

    International Nuclear Information System (INIS)

    Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

    2012-01-01

    In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

  15. Research on the Method of Noise Error Estimation of Atomic Clocks

    Science.gov (United States)

    Song, H. J.; Dong, S. W.; Li, W.; Zhang, J. H.; Jing, Y. J.

    2017-05-01

    The simulation methods of different noises of atomic clocks are given. The frequency flicker noise of atomic clock is studied by using the Markov process theory. The method for estimating the maximum interval error of the frequency white noise is studied by using the Wiener process theory. Based on the operation of 9 cesium atomic clocks in the time frequency reference laboratory of NTSC (National Time Service Center), the noise coefficients of the power-law spectrum model are estimated, and the simulations are carried out according to the noise models. Finally, the maximum interval error estimates of the frequency white noises generated by the 9 cesium atomic clocks have been acquired.

  16. Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images

    Directory of Open Access Journals (Sweden)

    Hui Meng

    2017-02-01

    Full Text Available The image intensities of low-backscattering areas in synthetic aperture radar (SAR images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.

  17. An Overview and Comparison of Online Implementable SOC Estimation Methods for Lithium-ion Battery

    DEFF Research Database (Denmark)

    Meng, Jinhao; Ricco, Mattia; Luo, Guangzhao

    2018-01-01

    . Many SOC estimation methods have been proposed in the literature. However, only a few of them consider the real-time applicability. This paper reviews recently proposed online SOC estimation methods and classifies them into five categories. Their principal features are illustrated, and the main pros...... and cons are provided. The SOC estimation methods are compared and discussed in terms of accuracy, robustness, and computation burden. Afterward, as the most popular type of model based SOC estimation algorithms, seven nonlinear filters existing in literature are compared in terms of their accuracy...

  18. A Practical Torque Estimation Method for Interior Permanent Magnet Synchronous Machine in Electric Vehicles.

    Science.gov (United States)

    Wu, Zhihong; Lu, Ke; Zhu, Yuan

    2015-01-01

    The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment.

  19. Methods for estimation of internal dose of the public from dietary

    International Nuclear Information System (INIS)

    Zhu Hongda

    1987-01-01

    Following the issue of its Publication 26, ICRP has successively published its Publication 30 to meet the great changes and improvements made in the Basic Recommendations since July of 1979. In Part 1 of Publcation 30, ICRP recommended a new method for internal dose estimation and pressented some important data. In this report, comparison is made among methods for estimation of internal dose for the public from dietary. They include: (1) the new method suggested by ICRP; (2) the simple and convenient method using transfer factors under equilibrium conditions; (3) the methods based on the similarities of several radionuclides to their chemical analogs. It is concluded that the first method is better than the others and should be used from now on

  20. Fatigue Damage Estimation and Data-based Control for Wind Turbines

    DEFF Research Database (Denmark)

    Barradas Berglind, Jose de Jesus; Wisniewski, Rafal; Soltani, Mohsen

    2015-01-01

    based on hysteresis operators, which can be used in control loops. The authors propose a data-based model predictive control (MPC) strategy that incorporates an online fatigue estimation method through the objective function, where the ultimate goal in mind is to reduce the fatigue damage of the wind......The focus of this work is on fatigue estimation and data-based controller design for wind turbines. The main purpose is to include a model of the fatigue damage of the wind turbine components in the controller design and synthesis process. This study addresses an online fatigue estimation method...... turbine components. The outcome is an adaptive or self-tuning MPC strategy for wind turbine fatigue damage reduction, which relies on parameter identification on previous measurement data. The results of the proposed strategy are compared with a baseline model predictive controller....

  1. A simple and rapid method to estimate radiocesium in man

    International Nuclear Information System (INIS)

    Kindl, P.; Steger, F.

    1990-09-01

    A simple and rapid method for monitoring internal contamination of radiocesium in man was developed. This method is based on measurements of the γ-rays emitted from the muscular parts between the thights by a simple NaJ(Tl)-system. The experimental procedure, the calibration, the estimation of the body activity and results are explained and discussed. (Authors)

  2. Instantaneous spectrum estimation of earthquake ground motions based on unscented Kalman filter method

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Representing earthquake ground motion as time varying ARMA model, the instantaneous spectrum can only be determined by the time varying coefficients of the corresponding ARMA model. In this paper, unscented Kalman filter is applied to estimate the time varying coefficients. The comparison between the estimation results of unscented Kalman filter and Kalman filter methods shows that unscented Kalman filter can more precisely represent the distribution of the spectral peaks in time-frequency plane than Kalman filter, and its time and frequency resolution is finer which ensures its better ability to track the local properties of earthquake ground motions and to identify the systems with nonlinearity or abruptness. Moreover, the estimation results of ARMA models with different orders indicate that the theoretical frequency resolving power ofARMA model which was usually ignored in former studies has great effect on the estimation precision of instantaneous spectrum and it should be taken as one of the key factors in order selection of ARMA model.

  3. A HYBRID METHOD IN VEGETATION HEIGHT ESTIMATION USING POLINSAR IMAGES OF CAMPAIGN BIOSAR

    Directory of Open Access Journals (Sweden)

    S. Dehnavi

    2015-12-01

    Full Text Available Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy. Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

  4. a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar

    Science.gov (United States)

    Dehnavi, S.; Maghsoudi, Y.

    2015-12-01

    Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

  5. Similar estimates of temperature impacts on global wheat yield by three independent methods

    DEFF Research Database (Denmark)

    Liu, Bing; Asseng, Senthold; Müller, Christoph

    2016-01-01

    The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produ......-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.......The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce...... similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries...

  6. Performance Evaluation of Methods for Estimating Achievable Throughput on Cellular Connections

    DEFF Research Database (Denmark)

    Mikkelsen, Lars Møller; Højholt, Nikolaj Bove; Madsen, Tatiana Kozlova

    2015-01-01

    The continuous increase in always connected devices and the advance in capabilities of networks and services offered via the network is evident. The target group of most of these devices and services is users, so how users perceive the network performance is of great importance. Estimating achiev...... AT, due to its much reduced resource consumption. Based on real-life measurements of the two methods we conclude that TOPP is a good candidate to estimate AT, based on similarity in results with BTC....

  7. Development of method for evaluating estimated inundation area by using river flood analysis based on multiple flood scenarios

    Science.gov (United States)

    Ono, T.; Takahashi, T.

    2017-12-01

    Non-structural mitigation measures such as flood hazard map based on estimated inundation area have been more important because heavy rains exceeding the design rainfall frequently occur in recent years. However, conventional method may lead to an underestimation of the area because assumed locations of dike breach in river flood analysis are limited to the cases exceeding the high-water level. The objective of this study is to consider the uncertainty of estimated inundation area with difference of the location of dike breach in river flood analysis. This study proposed multiple flood scenarios which can set automatically multiple locations of dike breach in river flood analysis. The major premise of adopting this method is not to be able to predict the location of dike breach correctly. The proposed method utilized interval of dike breach which is distance of dike breaches placed next to each other. That is, multiple locations of dike breach were set every interval of dike breach. The 2D shallow water equations was adopted as the governing equation of river flood analysis, and the leap-frog scheme with staggered grid was used. The river flood analysis was verified by applying for the 2015 Kinugawa river flooding, and the proposed multiple flood scenarios was applied for the Akutagawa river in Takatsuki city. As the result of computation in the Akutagawa river, a comparison with each computed maximum inundation depth of dike breaches placed next to each other proved that the proposed method enabled to prevent underestimation of estimated inundation area. Further, the analyses on spatial distribution of inundation class and maximum inundation depth in each of the measurement points also proved that the optimum interval of dike breach which can evaluate the maximum inundation area using the minimum assumed locations of dike breach. In brief, this study found the optimum interval of dike breach in the Akutagawa river, which enabled estimated maximum inundation area

  8. Method to Locate Contaminant Source and Estimate Emission Strength

    Directory of Open Access Journals (Sweden)

    Qu Hongquan

    2013-01-01

    Full Text Available People greatly concern the issue of air quality in some confined spaces, such as spacecraft, aircraft, and submarine. With the increase of residence time in such confined space, contaminant pollution has become a main factor which endangers life. It is urgent to identify a contaminant source rapidly so that a prompt remedial action can be taken. A procedure of source identification should be able to locate the position and to estimate the emission strength of the contaminant source. In this paper, an identification method was developed to realize these two aims. This method was developed based on a discrete concentration stochastic model. With this model, a sensitivity analysis algorithm was induced to locate the source position, and a Kalman filter was used to further estimate the contaminant emission strength. This method could track and predict the source strength dynamically. Meanwhile, it can predict the distribution of contaminant concentration. Simulation results have shown the virtues of the method.

  9. 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.

  10. Estimating building energy consumption using extreme learning machine method

    International Nuclear Information System (INIS)

    Naji, Sareh; Keivani, Afram; Shamshirband, Shahaboddin; Alengaram, U. Johnson; Jumaat, Mohd Zamin; Mansor, Zulkefli; Lee, Malrey

    2016-01-01

    The current energy requirements of buildings comprise a large percentage of the total energy consumed around the world. The demand of energy, as well as the construction materials used in buildings, are becoming increasingly problematic for the earth's sustainable future, and thus have led to alarming concern. The energy efficiency of buildings can be improved, and in order to do so, their operational energy usage should be estimated early in the design phase, so that buildings are as sustainable as possible. An early energy estimate can greatly help architects and engineers create sustainable structures. This study proposes a novel method to estimate building energy consumption based on the ELM (Extreme Learning Machine) method. This method is applied to building material thicknesses and their thermal insulation capability (K-value). For this purpose up to 180 simulations are carried out for different material thicknesses and insulation properties, using the EnergyPlus software application. The estimation and prediction obtained by the ELM model are compared with GP (genetic programming) and ANNs (artificial neural network) models for accuracy. The simulation results indicate that an improvement in predictive accuracy is achievable with the ELM approach in comparison with GP and ANN. - Highlights: • Buildings consume huge amounts of energy for operation. • Envelope materials and insulation influence building energy consumption. • Extreme learning machine is used to estimate energy usage of a sample building. • The key effective factors in this study are insulation thickness and K-value.

  11. Stress estimation in reservoirs using an integrated inverse method

    Science.gov (United States)

    Mazuyer, Antoine; Cupillard, Paul; Giot, Richard; Conin, Marianne; Leroy, Yves; Thore, Pierre

    2018-05-01

    Estimating the stress in reservoirs and their surroundings prior to the production is a key issue for reservoir management planning. In this study, we propose an integrated inverse method to estimate such initial stress state. The 3D stress state is constructed with the displacement-based finite element method assuming linear isotropic elasticity and small perturbations in the current geometry of the geological structures. The Neumann boundary conditions are defined as piecewise linear functions of depth. The discontinuous functions are determined with the CMA-ES (Covariance Matrix Adaptation Evolution Strategy) optimization algorithm to fit wellbore stress data deduced from leak-off tests and breakouts. The disregard of the geological history and the simplified rheological assumptions mean that only the stress field, statically admissible and matching the wellbore data should be exploited. The spatial domain of validity of this statement is assessed by comparing the stress estimations for a synthetic folded structure of finite amplitude with a history constructed assuming a viscous response.

  12. EQPlanar: a maximum-likelihood method for accurate organ activity estimation from whole body planar projections

    International Nuclear Information System (INIS)

    Song, N; Frey, E C; He, B; Wahl, R L

    2011-01-01

    Optimizing targeted radionuclide therapy requires patient-specific estimation of organ doses. The organ doses are estimated from quantitative nuclear medicine imaging studies, many of which involve planar whole body scans. We have previously developed the quantitative planar (QPlanar) processing method and demonstrated its ability to provide more accurate activity estimates than conventional geometric-mean-based planar (CPlanar) processing methods using physical phantom and simulation studies. The QPlanar method uses the maximum likelihood-expectation maximization algorithm, 3D organ volume of interests (VOIs), and rigorous models of physical image degrading factors to estimate organ activities. However, the QPlanar method requires alignment between the 3D organ VOIs and the 2D planar projections and assumes uniform activity distribution in each VOI. This makes application to patients challenging. As a result, in this paper we propose an extended QPlanar (EQPlanar) method that provides independent-organ rigid registration and includes multiple background regions. We have validated this method using both Monte Carlo simulation and patient data. In the simulation study, we evaluated the precision and accuracy of the method in comparison to the original QPlanar method. For the patient studies, we compared organ activity estimates at 24 h after injection with those from conventional geometric mean-based planar quantification using a 24 h post-injection quantitative SPECT reconstruction as the gold standard. We also compared the goodness of fit of the measured and estimated projections obtained from the EQPlanar method to those from the original method at four other time points where gold standard data were not available. In the simulation study, more accurate activity estimates were provided by the EQPlanar method for all the organs at all the time points compared with the QPlanar method. Based on the patient data, we concluded that the EQPlanar method provided a

  13. Estimation of biological parameters of marine organisms using linear and nonlinear acoustic scattering model-based inversion methods.

    Science.gov (United States)

    Chu, Dezhang; Lawson, Gareth L; Wiebe, Peter H

    2016-05-01

    The linear inversion commonly used in fisheries and zooplankton acoustics assumes a constant inversion kernel and ignores the uncertainties associated with the shape and behavior of the scattering targets, as well as other relevant animal parameters. Here, errors of the linear inversion due to uncertainty associated with the inversion kernel are quantified. A scattering model-based nonlinear inversion method is presented that takes into account the nonlinearity of the inverse problem and is able to estimate simultaneously animal abundance and the parameters associated with the scattering model inherent to the kernel. It uses sophisticated scattering models to estimate first, the abundance, and second, the relevant shape and behavioral parameters of the target organisms. Numerical simulations demonstrate that the abundance, size, and behavior (tilt angle) parameters of marine animals (fish or zooplankton) can be accurately inferred from the inversion by using multi-frequency acoustic data. The influence of the singularity and uncertainty in the inversion kernel on the inversion results can be mitigated by examining the singular values for linear inverse problems and employing a non-linear inversion involving a scattering model-based kernel.

  14. A Method for Estimating View Transformations from Image Correspondences Based on the Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Erik Cuevas

    2015-01-01

    Full Text Available In this paper, a new method for robustly estimating multiple view relations from point correspondences is presented. The approach combines the popular random sampling consensus (RANSAC algorithm and the evolutionary method harmony search (HS. With this combination, the proposed method adopts a different sampling strategy than RANSAC to generate putative solutions. Under the new mechanism, at each iteration, new candidate solutions are built taking into account the quality of the models generated by previous candidate solutions, rather than purely random as it is the case of RANSAC. The rules for the generation of candidate solutions (samples are motivated by the improvisation process that occurs when a musician searches for a better state of harmony. As a result, the proposed approach can substantially reduce the number of iterations still preserving the robust capabilities of RANSAC. The method is generic and its use is illustrated by the estimation of homographies, considering synthetic and real images. Additionally, in order to demonstrate the performance of the proposed approach within a real engineering application, it is employed to solve the problem of position estimation in a humanoid robot. Experimental results validate the efficiency of the proposed method in terms of accuracy, speed, and robustness.

  15. A generic method for estimating system reliability using Bayesian networks

    International Nuclear Information System (INIS)

    Doguc, Ozge; Ramirez-Marquez, Jose Emmanuel

    2009-01-01

    This study presents a holistic method for constructing a Bayesian network (BN) model for estimating system reliability. BN is a probabilistic approach that is used to model and predict the behavior of a system based on observed stochastic events. The BN model is a directed acyclic graph (DAG) where the nodes represent system components and arcs represent relationships among them. Although recent studies on using BN for estimating system reliability have been proposed, they are based on the assumption that a pre-built BN has been designed to represent the system. In these studies, the task of building the BN is typically left to a group of specialists who are BN and domain experts. The BN experts should learn about the domain before building the BN, which is generally very time consuming and may lead to incorrect deductions. As there are no existing studies to eliminate the need for a human expert in the process of system reliability estimation, this paper introduces a method that uses historical data about the system to be modeled as a BN and provides efficient techniques for automated construction of the BN model, and hence estimation of the system reliability. In this respect K2, a data mining algorithm, is used for finding associations between system components, and thus building the BN model. This algorithm uses a heuristic to provide efficient and accurate results while searching for associations. Moreover, no human intervention is necessary during the process of BN construction and reliability estimation. The paper provides a step-by-step illustration of the method and evaluation of the approach with literature case examples

  16. A generic method for estimating system reliability using Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Doguc, Ozge [Stevens Institute of Technology, Hoboken, NJ 07030 (United States); Ramirez-Marquez, Jose Emmanuel [Stevens Institute of Technology, Hoboken, NJ 07030 (United States)], E-mail: jmarquez@stevens.edu

    2009-02-15

    This study presents a holistic method for constructing a Bayesian network (BN) model for estimating system reliability. BN is a probabilistic approach that is used to model and predict the behavior of a system based on observed stochastic events. The BN model is a directed acyclic graph (DAG) where the nodes represent system components and arcs represent relationships among them. Although recent studies on using BN for estimating system reliability have been proposed, they are based on the assumption that a pre-built BN has been designed to represent the system. In these studies, the task of building the BN is typically left to a group of specialists who are BN and domain experts. The BN experts should learn about the domain before building the BN, which is generally very time consuming and may lead to incorrect deductions. As there are no existing studies to eliminate the need for a human expert in the process of system reliability estimation, this paper introduces a method that uses historical data about the system to be modeled as a BN and provides efficient techniques for automated construction of the BN model, and hence estimation of the system reliability. In this respect K2, a data mining algorithm, is used for finding associations between system components, and thus building the BN model. This algorithm uses a heuristic to provide efficient and accurate results while searching for associations. Moreover, no human intervention is necessary during the process of BN construction and reliability estimation. The paper provides a step-by-step illustration of the method and evaluation of the approach with literature case examples.

  17. 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.

  18. Sparse Method for Direction of Arrival Estimation Using Denoised Fourth-Order Cumulants Vector.

    Science.gov (United States)

    Fan, Yangyu; Wang, Jianshu; Du, Rui; Lv, Guoyun

    2018-06-04

    Fourth-order cumulants (FOCs) vector-based direction of arrival (DOA) estimation methods of non-Gaussian sources may suffer from poor performance for limited snapshots or difficulty in setting parameters. In this paper, a novel FOCs vector-based sparse DOA estimation method is proposed. Firstly, by utilizing the concept of a fourth-order difference co-array (FODCA), an advanced FOCs vector denoising or dimension reduction procedure is presented for arbitrary array geometries. Then, a novel single measurement vector (SMV) model is established by the denoised FOCs vector, and efficiently solved by an off-grid sparse Bayesian inference (OGSBI) method. The estimation errors of FOCs are integrated in the SMV model, and are approximately estimated in a simple way. A necessary condition regarding the number of identifiable sources of our method is presented that, in order to uniquely identify all sources, the number of sources K must fulfill K ≤ ( M 4 - 2 M 3 + 7 M 2 - 6 M ) / 8 . The proposed method suits any geometry, does not need prior knowledge of the number of sources, is insensitive to associated parameters, and has maximum identifiability O ( M 4 ) , where M is the number of sensors in the array. Numerical simulations illustrate the superior performance of the proposed method.

  19. 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

  20. 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

  1. A Proposal of Estimation Methodology to Improve Calculation Efficiency of Sampling-based Method in Nuclear Data Sensitivity and Uncertainty Analysis

    International Nuclear Information System (INIS)

    Song, Myung Sub; Kim, Song Hyun; Kim, Jong Kyung; Noh, Jae Man

    2014-01-01

    The uncertainty with the sampling-based method is evaluated by repeating transport calculations with a number of cross section data sampled from the covariance uncertainty data. In the transport calculation with the sampling-based method, the transport equation is not modified; therefore, all uncertainties of the responses such as k eff , reaction rates, flux and power distribution can be directly obtained all at one time without code modification. However, a major drawback with the sampling-based method is that it requires expensive computational load for statistically reliable results (inside confidence level 0.95) in the uncertainty analysis. The purpose of this study is to develop a method for improving the computational efficiency and obtaining highly reliable uncertainty result in using the sampling-based method with Monte Carlo simulation. The proposed method is a method to reduce the convergence time of the response uncertainty by using the multiple sets of sampled group cross sections in a single Monte Carlo simulation. The proposed method was verified by estimating GODIVA benchmark problem and the results were compared with that of conventional sampling-based method. In this study, sampling-based method based on central limit theorem is proposed to improve calculation efficiency by reducing the number of repetitive Monte Carlo transport calculation required to obtain reliable uncertainty analysis results. Each set of sampled group cross sections is assigned to each active cycle group in a single Monte Carlo simulation. The criticality uncertainty for the GODIVA problem is evaluated by the proposed and previous method. The results show that the proposed sampling-based method can efficiently decrease the number of Monte Carlo simulation required for evaluate uncertainty of k eff . It is expected that the proposed method will improve computational efficiency of uncertainty analysis with sampling-based method

  2. 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

  3. 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.

  4. 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

  5. Statistical parameters of random heterogeneity estimated by analysing coda waves based on finite difference method

    Science.gov (United States)

    Emoto, K.; Saito, T.; Shiomi, K.

    2017-12-01

    Short-period (2 s) seismograms. We found that the energy of the coda of long-period seismograms shows a spatially flat distribution. This phenomenon is well known in short-period seismograms and results from the scattering by small-scale heterogeneities. We estimate the statistical parameters that characterize the small-scale random heterogeneity by modelling the spatiotemporal energy distribution of long-period seismograms. We analyse three moderate-size earthquakes that occurred in southwest Japan. We calculate the spatial distribution of the energy density recorded by a dense seismograph network in Japan at the period bands of 8-16 s, 4-8 s and 2-4 s and model them by using 3-D finite difference (FD) simulations. Compared to conventional methods based on statistical theories, we can calculate more realistic synthetics by using the FD simulation. It is not necessary to assume a uniform background velocity, body or surface waves and scattering properties considered in general scattering theories. By taking the ratio of the energy of the coda area to that of the entire area, we can separately estimate the scattering and the intrinsic absorption effects. Our result reveals the spectrum of the random inhomogeneity in a wide wavenumber range including the intensity around the corner wavenumber as P(m) = 8πε2a3/(1 + a2m2)2, where ε = 0.05 and a = 3.1 km, even though past studies analysing higher-frequency records could not detect the corner. Finally, we estimate the intrinsic attenuation by modelling the decay rate of the energy. The method proposed in this study is suitable for quantifying the statistical properties of long-wavelength subsurface random inhomogeneity, which leads the way to characterizing a wider wavenumber range of spectra, including the corner wavenumber.

  6. Stoichiometry-based estimates of ferric iron in calcic, sodic-calcic and sodic amphiboles: a comparison of various methods

    Directory of Open Access Journals (Sweden)

    Gualda Guilherme A.R.

    2005-01-01

    Full Text Available An important drawback of the electron microprobe is its inability to quantify Fe3+/Fe2+ ratios in routine work. Although these ratios can be calculated, there is no unique criterion that can be applied to all amphiboles. Using a large data set of calcic, sodic-calcic, and sodic amphibole analysis from A-type granites and syenites from southern Brazil, weassess the choices made by the method of Schumacher (1997, Canadian Mineralogist, 35: 238-246, which uses the average between selected maximum and minimum estimates. Maximum estimates selected most frequently are: 13 cations excluding Ca, Na, and K (13eCNK - 66%; sum of Si and Al equal to 8 (8SiAl - 17%; 15 cations excluding K (15eK - 8%. These selections are appropriate based on crystallochemical considerations. Minimum estimates are mostly all iron as Fe2+ (all Fe2 - 71%, and are clearly inadequate. Hence, maximum estimates should better approximate the actual values. To test this, complete analyses were selected from the literature, and calculated and measured values were compared. 13eCNK and maximum estimates are precise and accurate (concordance correlation coefficient- r c " 0.85. As expected, averages yield poor estimates (r c = 0.56. We recommend, thus, that maximum estimates be used for calcic, sodic-calcic, and sodic amphiboles.

  7. Seasonal adjustment methods and real time trend-cycle estimation

    CERN Document Server

    Bee Dagum, Estela

    2016-01-01

    This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportat...

  8. Estimating incidence from prevalence in generalised HIV epidemics: methods and validation.

    Directory of Open Access Journals (Sweden)

    Timothy B Hallett

    2008-04-01

    Full Text Available HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence.Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured.It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data.

  9. Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota

    Science.gov (United States)

    Lorenz, David L.; Ziegeweid, Jeffrey R.

    2016-03-14

    Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats (http://streamstats.usgs.gov/), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.

  10. Estimation of Runoff for Ozat Catchment using RS and GIS Based SCS-CN Method

    OpenAIRE

    Dipesh B. Chavda1,; Jaydip J. Makwana*2,; Hitesh V. Parmar3; Arvind N. Kunapara2; Girish V. Prajapati

    2016-01-01

    Estimation of runoff in a watershed is a prerequisite for design of hydraulic structures, reservoir operation and for soil erosion control measures. Water resource planning and management is important and critical issue in arid and semi-arid regions. Runoff from a watershed affected by several geo-morphological parameters and for a particular watershed land use change can affect the runoff volume and runoff rate significantly. Several methods are investigated to estimate the surface runoff fr...

  11. 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.

  12. An Improved Method of Pose Estimation for Lighthouse Base Station Extension.

    Science.gov (United States)

    Yang, Yi; Weng, Dongdong; Li, Dong; Xun, Hang

    2017-10-22

    In 2015, HTC and Valve launched a virtual reality headset empowered with Lighthouse, the cutting-edge space positioning technology. Although Lighthouse is superior in terms of accuracy, latency and refresh rate, its algorithms do not support base station expansion, and is flawed concerning occlusion in moving targets, that is, it is unable to calculate their poses with a small set of sensors, resulting in the loss of optical tracking data. In view of these problems, this paper proposes an improved pose estimation algorithm for cases where occlusion is involved. Our algorithm calculates the pose of a given object with a unified dataset comprising of inputs from sensors recognized by all base stations, as long as three or more sensors detect a signal in total, no matter from which base station. To verify our algorithm, HTC official base stations and autonomous developed receivers are used for prototyping. The experiment result shows that our pose calculation algorithm can achieve precise positioning when a few sensors detect the signal.

  13. A pose estimation method for unmanned ground vehicles in GPS denied environments

    Science.gov (United States)

    Tamjidi, Amirhossein; Ye, Cang

    2012-06-01

    This paper presents a pose estimation method based on the 1-Point RANSAC EKF (Extended Kalman Filter) framework. The method fuses the depth data from a LIDAR and the visual data from a monocular camera to estimate the pose of a Unmanned Ground Vehicle (UGV) in a GPS denied environment. Its estimation framework continuy updates the vehicle's 6D pose state and temporary estimates of the extracted visual features' 3D positions. In contrast to the conventional EKF-SLAM (Simultaneous Localization And Mapping) frameworks, the proposed method discards feature estimates from the extended state vector once they are no longer observed for several steps. As a result, the extended state vector always maintains a reasonable size that is suitable for online calculation. The fusion of laser and visual data is performed both in the feature initialization part of the EKF-SLAM process and in the motion prediction stage. A RANSAC pose calculation procedure is devised to produce pose estimate for the motion model. The proposed method has been successfully tested on the Ford campus's LIDAR-Vision dataset. The results are compared with the ground truth data of the dataset and the estimation error is ~1.9% of the path length.

  14. An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging

    Science.gov (United States)

    Flores-Tapia, Daniel; Pistorius, Stephen

    2010-12-01

    During the last forty years, Subsurface Radar (SR) has been used in an increasing number of noninvasive/nondestructive imaging applications, ranging from landmine detection to breast imaging. To properly assess the dimensions and locations of the targets within the scan area, SR data sets have to be reconstructed. This process usually requires the knowledge of the propagation speed in the medium, which is usually obtained by performing an offline measurement from a representative sample of the materials that form the scan region. Nevertheless, in some novel near-field SR scenarios, such as Microwave Wood Inspection (MWI) and Breast Microwave Radar (BMR), the extraction of a representative sample is not an option due to the noninvasive requirements of the application. A novel technique to determine the propagation speed of the medium based on the use of an information theory metric is proposed in this paper. The proposed method uses the Shannon entropy of the reconstructed images as the focal quality metric to generate an estimate of the propagation speed in a given scan region. The performance of the proposed algorithm was assessed using data sets collected from experimental setups that mimic the dielectric contrast found in BMI and MWI scenarios. The proposed method yielded accurate results and exhibited an execution time in the order of seconds.

  15. 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.

  16. Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

    Science.gov (United States)

    Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; hide

    2016-01-01

    The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

  17. Similar estimates of temperature impacts on global wheat yield by three independent methods

    Science.gov (United States)

    Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

    2016-12-01

    The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

  18. 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

  19. Lake and Reservoir Evaporation Estimation: Sensitivity Analysis and Ranking Existing Methods

    Directory of Open Access Journals (Sweden)

    maysam majidi

    2016-02-01

    Full Text Available Introduction: Water when harvested is commonly stored in dams, but approximately up to half of it may be lost due to evaporation leading to a huge waste of our resources. Estimating evaporation from lakes and reservoirs is not a simple task as there are a number of factors that can affect the evaporation rate, notably the climate and physiography of the water body and its surroundings. Several methods are currently used to predict evaporation from meteorological data in open water reservoirs. Based on the accuracy and simplicity of the application, each of these methods has advantages and disadvantages. Although evaporation pan method is well known to have significant uncertainties both in magnitude and timing, it is extensively used in Iran because of its simplicity. Evaporation pan provides a measurement of the combined effect of temperature, humidity, wind speed and solar radiation on the evaporation. However, they may not be adequate for the reservoir operations/development and water accounting strategies for managing drinking water in arid and semi-arid conditions which require accurate evaporation estimates. However, there has not been a consensus on which methods were better to employ due to the lack of important long-term measured data such as temperature profile, radiation and heat fluxes in most lakes and reservoirs in Iran. Consequently, we initiated this research to find the best cost−effective evaporation method with possibly fewer data requirements in our study area, i.e. the Doosti dam reservoir which is located in a semi-arid region of Iran. Materials and Methods: Our study site was the Doosti dam reservoir located between Iran and Turkmenistan borders, which was constructed by the Ministry of Water and Land Reclamation of the Republic of Turkmenistan and the Khorasan Razavi Regional Water Board of the Islamic Republic of Iran. Meteorological data including maximum and minimum air temperature and evaporation from class A pan

  20. 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.

  1. Estimation of the size of the female sex worker population in Rwanda using three different methods.

    Science.gov (United States)

    Mutagoma, Mwumvaneza; Kayitesi, Catherine; Gwiza, Aimé; Ruton, Hinda; Koleros, Andrew; Gupta, Neil; Balisanga, Helene; Riedel, David J; Nsanzimana, Sabin

    2015-10-01

    HIV prevalence is disproportionately high among female sex workers compared to the general population. Many African countries lack useful data on the size of female sex worker populations to inform national HIV programmes. A female sex worker size estimation exercise using three different venue-based methodologies was conducted among female sex workers in all provinces of Rwanda in August 2010. The female sex worker national population size was estimated using capture-recapture and enumeration methods, and the multiplier method was used to estimate the size of the female sex worker population in Kigali. A structured questionnaire was also used to supplement the data. The estimated number of female sex workers by the capture-recapture method was 3205 (95% confidence interval: 2998-3412). The female sex worker size was estimated at 3348 using the enumeration method. In Kigali, the female sex worker size was estimated at 2253 (95% confidence interval: 1916-2524) using the multiplier method. Nearly 80% of all female sex workers in Rwanda were found to be based in the capital, Kigali. This study provided a first-time estimate of the female sex worker population size in Rwanda using capture-recapture, enumeration, and multiplier methods. The capture-recapture and enumeration methods provided similar estimates of female sex worker in Rwanda. Combination of such size estimation methods is feasible and productive in low-resource settings and should be considered vital to inform national HIV programmes. © The Author(s) 2015.

  2. 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.

  3. Statistically Efficient Methods for Pitch and DOA Estimation

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

    2013-01-01

    , it was recently considered to estimate the DOA and pitch jointly. In this paper, we propose two novel methods for DOA and pitch estimation. They both yield maximum-likelihood estimates in white Gaussian noise scenar- ios, where the SNR may be different across channels, as opposed to state-of-the-art methods......Traditionally, direction-of-arrival (DOA) and pitch estimation of multichannel, periodic sources have been considered as two separate problems. Separate estimation may render the task of resolving sources with similar DOA or pitch impossible, and it may decrease the estimation accuracy. Therefore...

  4. 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...

  5. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

    Science.gov (United States)

    Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

    2017-12-06

    Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

  6. A Theoretically Consistent Method for Minimum Mean-Square Error Estimation of Mel-Frequency Cepstral Features

    DEFF Research Database (Denmark)

    Jensen, Jesper; Tan, Zheng-Hua

    2014-01-01

    We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features for noise robust automatic speech recognition (ASR). The method is based on a minimum number of well-established statistical assumptions; no assumptions are made which are inconsistent with others....... The strength of the proposed method is that it allows MMSE estimation of mel-frequency cepstral coefficients (MFCC's), cepstral mean-subtracted MFCC's (CMS-MFCC's), velocity, and acceleration coefficients. Furthermore, the method is easily modified to take into account other compressive non-linearities than...... the logarithmic which is usually used for MFCC computation. The proposed method shows estimation performance which is identical to or better than state-of-the-art methods. It further shows comparable ASR performance, where the advantage of being able to use mel-frequency speech features based on a power non...

  7. 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

  8. An Efficient Acoustic Density Estimation Method with Human Detectors Applied to Gibbons in Cambodia.

    Directory of Open Access Journals (Sweden)

    Darren Kidney

    Full Text Available Some animal species are hard to see but easy to hear. Standard visual methods for estimating population density for such species are often ineffective or inefficient, but methods based on passive acoustics show more promise. We develop spatially explicit capture-recapture (SECR methods for territorial vocalising species, in which humans act as an acoustic detector array. We use SECR and estimated bearing data from a single-occasion acoustic survey of a gibbon population in northeastern Cambodia to estimate the density of calling groups. The properties of the estimator are assessed using a simulation study, in which a variety of survey designs are also investigated. We then present a new form of the SECR likelihood for multi-occasion data which accounts for the stochastic availability of animals. In the context of gibbon surveys this allows model-based estimation of the proportion of groups that produce territorial vocalisations on a given day, thereby enabling the density of groups, instead of the density of calling groups, to be estimated. We illustrate the performance of this new estimator by simulation. We show that it is possible to estimate density reliably from human acoustic detections of visually cryptic species using SECR methods. For gibbon surveys we also show that incorporating observers' estimates of bearings to detected groups substantially improves estimator performance. Using the new form of the SECR likelihood we demonstrate that estimates of availability, in addition to population density and detection function parameters, can be obtained from multi-occasion data, and that the detection function parameters are not confounded with the availability parameter. This acoustic SECR method provides a means of obtaining reliable density estimates for territorial vocalising species. It is also efficient in terms of data requirements since since it only requires routine survey data. We anticipate that the low-tech field requirements will

  9. Advances in Time Estimation Methods for Molecular Data.

    Science.gov (United States)

    Kumar, Sudhir; Hedges, S Blair

    2016-04-01

    Molecular dating has become central to placing a temporal dimension on the tree of life. Methods for estimating divergence times have been developed for over 50 years, beginning with the proposal of molecular clock in 1962. We categorize the chronological development of these methods into four generations based on the timing of their origin. In the first generation approaches (1960s-1980s), a strict molecular clock was assumed to date divergences. In the second generation approaches (1990s), the equality of evolutionary rates between species was first tested and then a strict molecular clock applied to estimate divergence times. The third generation approaches (since ∼2000) account for differences in evolutionary rates across the tree by using a statistical model, obviating the need to assume a clock or to test the equality of evolutionary rates among species. Bayesian methods in the third generation require a specific or uniform prior on the speciation-process and enable the inclusion of uncertainty in clock calibrations. The fourth generation approaches (since 2012) allow rates to vary from branch to branch, but do not need prior selection of a statistical model to describe the rate variation or the specification of speciation model. With high accuracy, comparable to Bayesian approaches, and speeds that are orders of magnitude faster, fourth generation methods are able to produce reliable timetrees of thousands of species using genome scale data. We found that early time estimates from second generation studies are similar to those of third and fourth generation studies, indicating that methodological advances have not fundamentally altered the timetree of life, but rather have facilitated time estimation by enabling the inclusion of more species. Nonetheless, we feel an urgent need for testing the accuracy and precision of third and fourth generation methods, including their robustness to misspecification of priors in the analysis of large phylogenies and data

  10. A Novel Method for Remote Depth Estimation of Buried Radioactive Contamination.

    Science.gov (United States)

    Ukaegbu, Ikechukwu Kevin; Gamage, Kelum A A

    2018-02-08

    Existing remote radioactive contamination depth estimation methods for buried radioactive wastes are either limited to less than 2 cm or are based on empirical models that require foreknowledge of the maximum penetrable depth of the contamination. These severely limits their usefulness in some real life subsurface contamination scenarios. Therefore, this work presents a novel remote depth estimation method that is based on an approximate three-dimensional linear attenuation model that exploits the benefits of using multiple measurements obtained from the surface of the material in which the contamination is buried using a radiation detector. Simulation results showed that the proposed method is able to detect the depth of caesium-137 and cobalt-60 contamination buried up to 40 cm in both sand and concrete. Furthermore, results from experiments show that the method is able to detect the depth of caesium-137 contamination buried up to 12 cm in sand. The lower maximum depth recorded in the experiment is due to limitations in the detector and the low activity of the caesium-137 source used. Nevertheless, both results demonstrate the superior capability of the proposed method compared to existing methods.

  11. 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.

  12. Initial position estimation method for permanent magnet synchronous motor based on improved pulse voltage injection

    DEFF Research Database (Denmark)

    Wang, Z.; Lu, K.; Ye, Y.

    2011-01-01

    According to saliency of permanent magnet synchronous motor (PMSM), the information of rotor position is implied in performance of stator inductances due to the magnetic saturation effect. Researches focused on the initial rotor position estimation of PMSM by injecting modulated pulse voltage...... vectors. The relationship between the inductance variations and voltage vector positions was studied. The inductance variation effect on estimation accuracy was studied as well. An improved five-pulses injection method was proposed, to improve the estimation accuracy by choosing optimaized voltage vectors...

  13. Coalescent methods for estimating phylogenetic trees.

    Science.gov (United States)

    Liu, Liang; Yu, Lili; Kubatko, Laura; Pearl, Dennis K; Edwards, Scott V

    2009-10-01

    We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.

  14. Statistical error estimation of the Feynman-α method using the bootstrap method

    International Nuclear Information System (INIS)

    Endo, Tomohiro; Yamamoto, Akio; Yagi, Takahiro; Pyeon, Cheol Ho

    2016-01-01

    Applicability of the bootstrap method is investigated to estimate the statistical error of the Feynman-α method, which is one of the subcritical measurement techniques on the basis of reactor noise analysis. In the Feynman-α method, the statistical error can be simply estimated from multiple measurements of reactor noise, however it requires additional measurement time to repeat the multiple times of measurements. Using a resampling technique called 'bootstrap method' standard deviation and confidence interval of measurement results obtained by the Feynman-α method can be estimated as the statistical error, using only a single measurement of reactor noise. In order to validate our proposed technique, we carried out a passive measurement of reactor noise without any external source, i.e. with only inherent neutron source by spontaneous fission and (α,n) reactions in nuclear fuels at the Kyoto University Criticality Assembly. Through the actual measurement, it is confirmed that the bootstrap method is applicable to approximately estimate the statistical error of measurement results obtained by the Feynman-α method. (author)

  15. Regional and longitudinal estimation of product lifespan distribution: a case study for automobiles and a simplified estimation method.

    Science.gov (United States)

    Oguchi, Masahiro; Fuse, Masaaki

    2015-02-03

    Product lifespan estimates are important information for understanding progress toward sustainable consumption and estimating the stocks and end-of-life flows of products. Publications reported actual lifespan of products; however, quantitative data are still limited for many countries and years. This study presents regional and longitudinal estimation of lifespan distribution of consumer durables, taking passenger cars as an example, and proposes a simplified method for estimating product lifespan distribution. We estimated lifespan distribution parameters for 17 countries based on the age profile of in-use cars. Sensitivity analysis demonstrated that the shape parameter of the lifespan distribution can be replaced by a constant value for all the countries and years. This enabled a simplified estimation that does not require detailed data on the age profile. Applying the simplified method, we estimated the trend in average lifespans of passenger cars from 2000 to 2009 for 20 countries. Average lifespan differed greatly between countries (9-23 years) and was increasing in many countries. This suggests consumer behavior differs greatly among countries and has changed over time, even in developed countries. The results suggest that inappropriate assumptions of average lifespan may cause significant inaccuracy in estimating the stocks and end-of-life flows of products.

  16. 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)

  17. Dual respiratory and cardiac motion estimation in PET imaging: Methods design and quantitative evaluation.

    Science.gov (United States)

    Feng, Tao; Wang, Jizhe; Tsui, Benjamin M W

    2018-04-01

    The goal of this study was to develop and evaluate four post-reconstruction respiratory and cardiac (R&C) motion vector field (MVF) estimation methods for cardiac 4D PET data. In Method 1, the dual R&C motions were estimated directly from the dual R&C gated images. In Method 2, respiratory motion (RM) and cardiac motion (CM) were separately estimated from the respiratory gated only and cardiac gated only images. The effects of RM on CM estimation were modeled in Method 3 by applying an image-based RM correction on the cardiac gated images before CM estimation, the effects of CM on RM estimation were neglected. Method 4 iteratively models the mutual effects of RM and CM during dual R&C motion estimations. Realistic simulation data were generated for quantitative evaluation of four methods. Almost noise-free PET projection data were generated from the 4D XCAT phantom with realistic R&C MVF using Monte Carlo simulation. Poisson noise was added to the scaled projection data to generate additional datasets of two more different noise levels. All the projection data were reconstructed using a 4D image reconstruction method to obtain dual R&C gated images. The four dual R&C MVF estimation methods were applied to the dual R&C gated images and the accuracy of motion estimation was quantitatively evaluated using the root mean square error (RMSE) of the estimated MVFs. Results show that among the four estimation methods, Methods 2 performed the worst for noise-free case while Method 1 performed the worst for noisy cases in terms of quantitative accuracy of the estimated MVF. Methods 4 and 3 showed comparable results and achieved RMSE lower by up to 35% than that in Method 1 for noisy cases. In conclusion, we have developed and evaluated 4 different post-reconstruction R&C MVF estimation methods for use in 4D PET imaging. Comparison of the performance of four methods on simulated data indicates separate R&C estimation with modeling of RM before CM estimation (Method 3) to be

  18. Verification of rapid method for estimation of added food colorant type in boiled sausages based on measurement of cross section color

    Science.gov (United States)

    Jovanović, J.; Petronijević, R. B.; Lukić, M.; Karan, D.; Parunović, N.; Branković-Lazić, I.

    2017-09-01

    During the previous development of a chemometric method for estimating the amount of added colorant in meat products, it was noticed that the natural colorant most commonly added to boiled sausages, E 120, has different CIE-LAB behavior compared to artificial colors that are used for the same purpose. This has opened the possibility of transforming the developed method into a method for identifying the addition of natural or synthetic colorants in boiled sausages based on the measurement of the color of the cross-section. After recalibration of the CIE-LAB method using linear discriminant analysis, verification was performed on 76 boiled sausages, of either frankfurters or Parisian sausage types. The accuracy and reliability of the classification was confirmed by comparison with the standard HPLC method. Results showed that the LDA + CIE-LAB method can be applied with high accuracy, 93.42 %, to estimate food color type in boiled sausages. Natural orange colors can give false positive results. Pigments from spice mixtures had no significant effect on CIE-LAB results.

  19. Comparison of methods for estimating production of methane from whole plant maize silage

    OpenAIRE

    Zbigniew Podkówka; Witold Podkówka

    2014-01-01

    Laboratory methods to measure the amount of methane gas evolved in the fermentation process require specialized equipment and are long-lasting and expensive. Therefore a number of methods are developed to estimate the efficiency of biogas and methane from the chemical composition of the substrate. The aim of this study was to compare different methods to estimate the efficiency of methane from the silages made from whole plant corn. The study was based on test results of silage from whole pla...

  20. Model-Based Method for Sensor Validation

    Science.gov (United States)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  1. A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

    NARCIS (Netherlands)

    MIKOSCH, T; WANG, QA

    We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.

  2. Methods for estimating low-flow statistics for Massachusetts streams

    Science.gov (United States)

    Ries, Kernell G.; Friesz, Paul J.

    2000-01-01

    Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The

  3. 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

  4. Ratio-based vs. model-based methods to correct for urinary creatinine concentrations.

    Science.gov (United States)

    Jain, Ram B

    2016-08-01

    Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.

  5. 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.

  6. Methods of valuing air pollution and estimated monetary values of air pollutants in various U.S. regions

    Energy Technology Data Exchange (ETDEWEB)

    Wang, M.Q.; Santini, D.J.; Warinner, S.A.

    1994-12-01

    Air pollutant emission values are used to determine the social costs of various technologies that cause air pollution and to estimate the benefits of emission control technologies. In this report, the authors present two methods of estimating air pollutant emission values--the damage value method and the control cost method--and review 15 recent studies in which these methods were employed to estimate emission values. The reviewed studies derived emission values for only a limited number of areas; emission value estimates are needed for other US regions. Using the emission values estimated in the reviewed studies, they establish regression relationships between emission values, air pollutant concentrations, and total population exposed, and apply the established relationships to 17 US metropolitan areas to estimate damage-based and control-cost-based emission values for reactive organic gases, nitrogen oxides, particulate matter measuring less than 10 microns, sulfur oxides, and carbon monoxide in these areas. Their estimates show significant variations in emission values across the 17 regions.

  7. Accuracy of two simple methods for estimation of thyroidal 131I kinetics for dosimetry-based treatment of Graves' disease

    International Nuclear Information System (INIS)

    Traino, A. C.; Xhafa, B.

    2009-01-01

    One of the major challenges to the more widespread use of individualized, dosimetry-based radioiodine treatment of Graves' disease is the development of a reasonably fast, simple, and cost-effective method to measure thyroidal 131 I kinetics in patients. Even though the fixed activity administration method does not optimize the therapy, giving often too high or too low a dose to the gland, it provides effective treatment for almost 80% of patients without consuming excessive time and resources. In this article two simple methods for the evaluation of the kinetics of 131 I in the thyroid gland are presented and discussed. The first is based on two measurements 4 and 24 h after a diagnostic 131 I administration and the second on one measurement 4 h after such an administration and a linear correlation between this measurement and the maximum uptake in the thyroid. The thyroid absorbed dose calculated by each of the two methods is compared to that calculated by a more complete 131 I kinetics evaluation, based on seven thyroid uptake measurements for 35 patients at various times after the therapy administration. There are differences in the thyroid absorbed doses between those derived by each of the two simpler methods and the ''reference'' value (derived by more complete uptake measurements following the therapeutic 131 I administration), with 20% median and 40% 90-percentile differences for the first method (i.e., based on two thyroid uptake measurements at 4 and 24 h after 131 I administration) and 25% median and 45% 90-percentile differences for the second method (i.e., based on one measurement at 4 h post-administration). Predictably, although relatively fast and convenient, neither of these simpler methods appears to be as accurate as thyroid dose estimates based on more complete kinetic data.

  8. Source signature estimation from multimode surface waves via mode-separated virtual real source method

    Science.gov (United States)

    Gao, Lingli; Pan, Yudi

    2018-05-01

    The correct estimation of the seismic source signature is crucial to exploration geophysics. Based on seismic interferometry, the virtual real source (VRS) method provides a model-independent way for source signature estimation. However, when encountering multimode surface waves, which are commonly seen in the shallow seismic survey, strong spurious events appear in seismic interferometric results. These spurious events introduce errors in the virtual-source recordings and reduce the accuracy of the source signature estimated by the VRS method. In order to estimate a correct source signature from multimode surface waves, we propose a mode-separated VRS method. In this method, multimode surface waves are mode separated before seismic interferometry. Virtual-source recordings are then obtained by applying seismic interferometry to each mode individually. Therefore, artefacts caused by cross-mode correlation are excluded in the virtual-source recordings and the estimated source signatures. A synthetic example showed that a correct source signature can be estimated with the proposed method, while strong spurious oscillation occurs in the estimated source signature if we do not apply mode separation first. We also applied the proposed method to a field example, which verified its validity and effectiveness in estimating seismic source signature from shallow seismic shot gathers containing multimode surface waves.

  9. A Generalized Autocovariance Least-Squares Method for Covariance Estimation

    DEFF Research Database (Denmark)

    Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

    2007-01-01

    A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter.......A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter....

  10. Task-oriented comparison of power spectral density estimation methods for quantifying acoustic attenuation in diagnostic ultrasound using a reference phantom method.

    Science.gov (United States)

    Rosado-Mendez, Ivan M; Nam, Kibo; Hall, Timothy J; Zagzebski, James A

    2013-07-01

    Reported here is a phantom-based comparison of methods for determining the power spectral density (PSD) of ultrasound backscattered signals. Those power spectral density values are then used to estimate parameters describing α(f), the frequency dependence of the acoustic attenuation coefficient. Phantoms were scanned with a clinical system equipped with a research interface to obtain radiofrequency echo data. Attenuation, modeled as a power law α(f)= α0 f (β), was estimated using a reference phantom method. The power spectral density was estimated using the short-time Fourier transform (STFT), Welch's periodogram, and Thomson's multitaper technique, and performance was analyzed when limiting the size of the parameter-estimation region. Errors were quantified by the bias and standard deviation of the α0 and β estimates, and by the overall power-law fit error (FE). For parameter estimation regions larger than ~34 pulse lengths (~1 cm for this experiment), an overall power-law FE of 4% was achieved with all spectral estimation methods. With smaller parameter estimation regions as in parametric image formation, the bias and standard deviation of the α0 and β estimates depended on the size of the parameter estimation region. Here, the multitaper method reduced the standard deviation of the α0 and β estimates compared with those using the other techniques. The results provide guidance for choosing methods for estimating the power spectral density in quantitative ultrasound methods.

  11. Review of methods for level density estimation from resonance parameters

    International Nuclear Information System (INIS)

    Froehner, F.H.

    1983-01-01

    A number of methods are available for statistical analysis of resonance parameter sets, i.e. for estimation of level densities and average widths with account of missing levels. The main categories are (i) methods based on theories of level spacings (orthogonal-ensemble theory, Dyson-Mehta statistics), (ii) methods based on comparison with simulated cross section curves (Monte Carlo simulation, Garrison's autocorrelation method), (iii) methods exploiting the observed neutron width distribution by means of Bayesian or more approximate procedures such as maximum-likelihood, least-squares or moment methods, with various recipes for the treatment of detection thresholds and resolution effects. The present review will concentrate on (iii) with the aim of clarifying the basic mathematical concepts and the relationship between the various techniques. Recent theoretical progress in the treatment of resolution effects, detectability thresholds and p-wave admixture is described. (Auth.)

  12. Background estimation in short-wave region during determination of total sample composition by x-ray fluorescence method

    International Nuclear Information System (INIS)

    Simakov, V.A.; Kordyukov, S.V.; Petrov, E.N.

    1988-01-01

    Method of background estimation in short-wave spectral region during determination of total sample composition by X-ray fluorescence method is described. 13 types of different rocks with considerable variations of base composition and Zr, Nb, Th, U content below 7x10 -3 % are investigated. The suggested method of background accounting provides for a less statistical error of the background estimation than direct isolated measurement and reliability of its determination in a short-wave region independent on the sample base. Possibilities of suggested method for artificial mixtures conforming by the content of main component to technological concemtrates - niobium, zirconium, tantalum are estimated

  13. 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.

  14. An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging

    Directory of Open Access Journals (Sweden)

    Pistorius Stephen

    2010-01-01

    Full Text Available During the last forty years, Subsurface Radar (SR has been used in an increasing number of noninvasive/nondestructive imaging applications, ranging from landmine detection to breast imaging. To properly assess the dimensions and locations of the targets within the scan area, SR data sets have to be reconstructed. This process usually requires the knowledge of the propagation speed in the medium, which is usually obtained by performing an offline measurement from a representative sample of the materials that form the scan region. Nevertheless, in some novel near-field SR scenarios, such as Microwave Wood Inspection (MWI and Breast Microwave Radar (BMR, the extraction of a representative sample is not an option due to the noninvasive requirements of the application. A novel technique to determine the propagation speed of the medium based on the use of an information theory metric is proposed in this paper. The proposed method uses the Shannon entropy of the reconstructed images as the focal quality metric to generate an estimate of the propagation speed in a given scan region. The performance of the proposed algorithm was assessed using data sets collected from experimental setups that mimic the dielectric contrast found in BMI and MWI scenarios. The proposed method yielded accurate results and exhibited an execution time in the order of seconds.

  15. New methods for estimating follow-up rates in cohort studies

    Directory of Open Access Journals (Sweden)

    Xiaonan Xue

    2017-12-01

    Full Text Available Abstract Background The follow-up rate, a standard index of the completeness of follow-up, is important for assessing the validity of a cohort study. A common method for estimating the follow-up rate, the “Percentage Method”, defined as the fraction of all enrollees who developed the event of interest or had complete follow-up, can severely underestimate the degree of follow-up. Alternatively, the median follow-up time does not indicate the completeness of follow-up, and the reverse Kaplan-Meier based method and Clark’s Completeness Index (CCI also have limitations. Methods We propose a new definition for the follow-up rate, the Person-Time Follow-up Rate (PTFR, which is the observed person-time divided by total person-time assuming no dropouts. The PTFR cannot be calculated directly since the event times for dropouts are not observed. Therefore, two estimation methods are proposed: a formal person-time method (FPT in which the expected total follow-up time is calculated using the event rate estimated from the observed data, and a simplified person-time method (SPT that avoids estimation of the event rate by assigning full follow-up time to all events. Simulations were conducted to measure the accuracy of each method, and each method was applied to a prostate cancer recurrence study dataset. Results Simulation results showed that the FPT has the highest accuracy overall. In most situations, the computationally simpler SPT and CCI methods are only slightly biased. When applied to a retrospective cohort study of cancer recurrence, the FPT, CCI and SPT showed substantially greater 5-year follow-up than the Percentage Method (92%, 92% and 93% vs 68%. Conclusions The Person-time methods correct a systematic error in the standard Percentage Method for calculating follow-up rates. The easy to use SPT and CCI methods can be used in tandem to obtain an accurate and tight interval for PTFR. However, the FPT is recommended when event rates and

  16. Validation of a spectrophotometer-based method for estimating daily sperm production and deferent duct transit.

    Science.gov (United States)

    Froman, D P; Rhoads, D D

    2012-10-01

    The objectives of the present work were 3-fold. First, a new method for estimating daily sperm production was validated. This method, in turn, was used to evaluate testis output as well as deferent duct throughput. Next, this analytical approach was evaluated in 2 experiments. The first experiment compared left and right reproductive tracts within roosters. The second experiment compared reproductive tract throughput in roosters from low and high sperm mobility lines. Standard curves were constructed from which unknown concentrations of sperm cells and sperm nuclei could be predicted from observed absorbance. In each case, the independent variable was based upon hemacytometer counts, and absorbance was a linear function of concentration. Reproductive tracts were excised, semen recovered from each duct, and the extragonadal sperm reserve determined by multiplying volume by sperm cell concentration. Testicular sperm nuclei were procured by homogenization of a whole testis, overlaying a 20-mL volume of homogenate upon 15% (wt/vol) Accudenz (Accurate Chemical and Scientific Corporation, Westbury, NY), and then washing nuclei by centrifugation through the Accudenz layer. Daily sperm production was determined by dividing the predicted number of sperm nuclei within the homogenate by 4.5 d (i.e., the time sperm with elongated nuclei spend within the testis). Sperm transit through the deferent duct was estimated by dividing the extragonadal reserve by daily sperm production. Neither the efficiency of sperm production (sperm per gram of testicular parenchyma per day) nor deferent duct transit differed between left and right reproductive tracts (P > 0.05). Whereas efficiency of sperm production did not differ (P > 0.05) between low and high sperm mobility lines, deferent duct transit differed between lines (P < 0.001). On average, this process required 2.2 and 1.0 d for low and high lines, respectively. In summary, we developed and then tested a method for quantifying male

  17. Estimation of pattern shape based on CD-SEM image by using MPPC method

    Science.gov (United States)

    Onozuka, T.; Ojima, Y.; Meessen, J.; Rijpers, B.

    2006-03-01

    This study demonstrates the MPPC (Multiple Parameters Profile Characterization) measurement method utilizing ArF photo resist patterns. MPPC is a technique for estimating the three dimensional profile of patterns which are imaged and measured on the CD-SEM (critical dimension scanning electron microscope). MPPC utilizes the secondary electron signal to calculate several indices including top CD, peak CD, top rounding, bottom footing, etc. This primary focused of this study is to understand the variations in pattern profile caused by changes in exposure condition. The results demonstrate the ability to extract pattern profile shape information by MPPC measurement that could not otherwise be detected by a conventional bottom CD measurement method. Furthermore, the results were compared to cross sectional images collected by STEM (scanning transmission electron microscope) to verify the accuracy of the MPPC technique. The peak CD results accurately estimate the pattern width when the sidewall angle of the feature is nearly vertical. Additionally, line edge roughness (LER) caused by pattern profile variations was evaluated utilizing MPPC. The results suggest that MPPC may be utilized to evaluate the roughness over the entire profile.

  18. 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...

  19. Flexible and efficient estimating equations for variogram estimation

    KAUST Repository

    Sun, Ying; Chang, Xiaohui; Guan, Yongtao

    2018-01-01

    Variogram estimation plays a vastly important role in spatial modeling. Different methods for variogram estimation can be largely classified into least squares methods and likelihood based methods. A general framework to estimate the variogram through a set of estimating equations is proposed. This approach serves as an alternative approach to likelihood based methods and includes commonly used least squares approaches as its special cases. The proposed method is highly efficient as a low dimensional representation of the weight matrix is employed. The statistical efficiency of various estimators is explored and the lag effect is examined. An application to a hydrology dataset is also presented.

  20. Flexible and efficient estimating equations for variogram estimation

    KAUST Repository

    Sun, Ying

    2018-01-11

    Variogram estimation plays a vastly important role in spatial modeling. Different methods for variogram estimation can be largely classified into least squares methods and likelihood based methods. A general framework to estimate the variogram through a set of estimating equations is proposed. This approach serves as an alternative approach to likelihood based methods and includes commonly used least squares approaches as its special cases. The proposed method is highly efficient as a low dimensional representation of the weight matrix is employed. The statistical efficiency of various estimators is explored and the lag effect is examined. An application to a hydrology dataset is also presented.

  1. Improved vertical streambed flux estimation using multiple diurnal temperature methods in series

    Science.gov (United States)

    Irvine, Dylan J.; Briggs, Martin A.; Cartwright, Ian; Scruggs, Courtney; Lautz, Laura K.

    2017-01-01

    Analytical solutions that use diurnal temperature signals to estimate vertical fluxes between groundwater and surface water based on either amplitude ratios (Ar) or phase shifts (Δϕ) produce results that rarely agree. Analytical solutions that simultaneously utilize Ar and Δϕ within a single solution have more recently been derived, decreasing uncertainty in flux estimates in some applications. Benefits of combined (ArΔϕ) methods also include that thermal diffusivity and sensor spacing can be calculated. However, poor identification of either Ar or Δϕ from raw temperature signals can lead to erratic parameter estimates from ArΔϕ methods. An add-on program for VFLUX 2 is presented to address this issue. Using thermal diffusivity selected from an ArΔϕ method during a reliable time period, fluxes are recalculated using an Ar method. This approach maximizes the benefits of the Ar and ArΔϕ methods. Additionally, sensor spacing calculations can be used to identify periods with unreliable flux estimates, or to assess streambed scour. Using synthetic and field examples, the use of these solutions in series was particularly useful for gaining conditions where fluxes exceeded 1 m/d.

  2. Sediment Curve Uncertainty Estimation Using GLUE and Bootstrap Methods

    Directory of Open Access Journals (Sweden)

    aboalhasan fathabadi

    2017-02-01

    Full Text Available Introduction: In order to implement watershed practices to decrease soil erosion effects it needs to estimate output sediment of watershed. Sediment rating curve is used as the most conventional tool to estimate sediment. Regarding to sampling errors and short data, there are some uncertainties in estimating sediment using sediment curve. In this research, bootstrap and the Generalized Likelihood Uncertainty Estimation (GLUE resampling techniques were used to calculate suspended sediment loads by using sediment rating curves. Materials and Methods: The total drainage area of the Sefidrood watershed is about 560000 km2. In this study uncertainty in suspended sediment rating curves was estimated in four stations including Motorkhane, Miyane Tonel Shomare 7, Stor and Glinak constructed on Ayghdamosh, Ghrangho, GHezelOzan and Shahrod rivers, respectively. Data were randomly divided into a training data set (80 percent and a test set (20 percent by Latin hypercube random sampling.Different suspended sediment rating curves equations were fitted to log-transformed values of sediment concentration and discharge and the best fit models were selected based on the lowest root mean square error (RMSE and the highest correlation of coefficient (R2. In the GLUE methodology, different parameter sets were sampled randomly from priori probability distribution. For each station using sampled parameter sets and selected suspended sediment rating curves equation suspended sediment concentration values were estimated several times (100000 to 400000 times. With respect to likelihood function and certain subjective threshold, parameter sets were divided into behavioral and non-behavioral parameter sets. Finally using behavioral parameter sets the 95% confidence intervals for suspended sediment concentration due to parameter uncertainty were estimated. In bootstrap methodology observed suspended sediment and discharge vectors were resampled with replacement B (set to

  3. ξ common cause failure model and method for defense effectiveness estimation

    International Nuclear Information System (INIS)

    Li Zhaohuan

    1991-08-01

    Two issues have been dealt. One is to develop an event based parametric model called ξ-CCF model. Its parameters are expressed in the fraction of the progressive multiplicities of failure events. By these expressions, the contribution of each multiple failure can be presented more clearly. It can help to select defense tactics against common cause failures. The other is to provide a method which is based on the operational experience and engineering judgement to estimate the effectiveness of defense tactics. It is expressed in terms of reduction matrix for a given tactics on a specific plant in the event by event form. The application of practical example shows that the model in cooperation with the method can simply estimate the effectiveness of defense tactics. It can be easily used by the operators and its application may be extended

  4. Testing a statistical method of global mean palotemperature estimations in a long climate simulation

    Energy Technology Data Exchange (ETDEWEB)

    Zorita, E.; Gonzalez-Rouco, F. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Hydrophysik

    2001-07-01

    Current statistical methods of reconstructing the climate of the last centuries are based on statistical models linking climate observations (temperature, sea-level-pressure) and proxy-climate data (tree-ring chronologies, ice-cores isotope concentrations, varved sediments, etc.). These models are calibrated in the instrumental period, and the longer time series of proxy data are then used to estimate the past evolution of the climate variables. Using such methods the global mean temperature of the last 600 years has been recently estimated. In this work this method of reconstruction is tested using data from a very long simulation with a climate model. This testing allows to estimate the errors of the estimations as a function of the number of proxy data and the time scale at which the estimations are probably reliable. (orig.)

  5. 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.

  6. Comparison of two methods for estimating the number of undocumented Mexican adults in Los Angeles County.

    Science.gov (United States)

    Heer, D M; Passel, J F

    1987-01-01

    This article compares 2 different methods for estimating the number of undocumented Mexican adults in Los Angeles County. The 1st method, the survey-based method, uses a combination of 1980 census data and the results of a survey conducted in Los Angeles County in 1980 and 1981. A sample was selected from babies born in Los Angeles County who had a mother or father of Mexican origin. The survey included questions about the legal status of the baby's parents and certain other relatives. The resulting estimates of undocumented Mexican immigrants are for males aged 18-44 and females aged 18-39. The 2nd method, the residual method, involves comparison of census figures for aliens counted with estimates of legally-resident aliens developed principally with data from the Immigration and Naturalization Service (INS). For this study, estimates by age, sex, and period of entry were produced for persons born in Mexico and living in Los Angeles County. The results of this research indicate that it is possible to measure undocumented immigration with different techniques, yet obtain results that are similar. Both techniques presented here are limited in that they represent estimates of undocumented aliens based on the 1980 census. The number of additional undocumented aliens not counted remains a subject of conjecture. The fact that the proportions undocumented shown in the survey (228,700) are quite similar to the residual estimates (317,800) suggests that the number of undocumented aliens not counted in the census may not be an extremely large fraction of the undocumented population. The survey-based estimates have some significant advantages over the residual estimates. The survey provides tabulations of the undocumented population by characteristics other than the limited demographic information provided by the residual technique. On the other hand, the survey-based estimates require that a survey be conducted and, if national or regional estimates are called for, they may

  7. Hexographic Method of Complex Town-Planning Terrain Estimate

    Science.gov (United States)

    Khudyakov, A. Ju

    2017-11-01

    The article deals with the vital problem of a complex town-planning analysis based on the “hexographic” graphic analytic method, makes a comparison with conventional terrain estimate methods and contains the method application examples. It discloses a procedure of the author’s estimate of restrictions and building of a mathematical model which reflects not only conventional town-planning restrictions, but also social and aesthetic aspects of the analyzed territory. The method allows one to quickly get an idea of the territory potential. It is possible to use an unlimited number of estimated factors. The method can be used for the integrated assessment of urban areas. In addition, it is possible to use the methods of preliminary evaluation of the territory commercial attractiveness in the preparation of investment projects. The technique application results in simple informative graphics. Graphical interpretation is straightforward from the experts. A definite advantage is the free perception of the subject results as they are not prepared professionally. Thus, it is possible to build a dialogue between professionals and the public on a new level allowing to take into account the interests of various parties. At the moment, the method is used as a tool for the preparation of integrated urban development projects at the Department of Architecture in Federal State Autonomous Educational Institution of Higher Education “South Ural State University (National Research University)”, FSAEIHE SUSU (NRU). The methodology is included in a course of lectures as the material on architectural and urban design for architecture students. The same methodology was successfully tested in the preparation of business strategies for the development of some territories in the Chelyabinsk region. This publication is the first in a series of planned activities developing and describing the methodology of hexographical analysis in urban and architectural practice. It is also

  8. 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.

  9. A novel method for estimating soil precompression stress from uniaxial confined compression tests

    DEFF Research Database (Denmark)

    Lamandé, Mathieu; Schjønning, Per; Labouriau, Rodrigo

    2017-01-01

    . Stress-strain curves were obtained by performing uniaxial, confined compression tests on undisturbed soil cores for three soil types at three soil water potentials. The new method performed better than the Gompertz fitting method in estimating precompression stress. The values of precompression stress...... obtained from the new method were linearly related to the maximum stress experienced by the soil samples prior to the uniaxial, confined compression test at each soil condition with a slope close to 1. Precompression stress determined with the new method was not related to soil type or dry bulk density......The concept of precompression stress is used for estimating soil strength of relevance to fieldtraffic. It represents the maximum stress experienced by the soil. The most recently developed fitting method to estimate precompression stress (Gompertz) is based on the assumption of an S-shape stress...

  10. Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

    Directory of Open Access Journals (Sweden)

    Chaoyang Shi

    2017-12-01

    Full Text Available Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

  11. Comparison of methods for estimating carbon in harvested wood products

    International Nuclear Information System (INIS)

    Claudia Dias, Ana; Louro, Margarida; Arroja, Luis; Capela, Isabel

    2009-01-01

    There is a great diversity of methods for estimating carbon storage in harvested wood products (HWP) and, therefore, it is extremely important to agree internationally on the methods to be used in national greenhouse gas inventories. This study compares three methods for estimating carbon accumulation in HWP: the method suggested by Winjum et al. (Winjum method), the tier 2 method proposed by the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (GPG LULUCF) (GPG tier 2 method) and a method consistent with GPG LULUCF tier 3 methods (GPG tier 3 method). Carbon accumulation in HWP was estimated for Portugal under three accounting approaches: stock-change, production and atmospheric-flow. The uncertainty in the estimates was also evaluated using Monte Carlo simulation. The estimates of carbon accumulation in HWP obtained with the Winjum method differed substantially from the estimates obtained with the other methods, because this method tends to overestimate carbon accumulation with the stock-change and the production approaches and tends to underestimate carbon accumulation with the atmospheric-flow approach. The estimates of carbon accumulation provided by the GPG methods were similar, but the GPG tier 3 method reported the lowest uncertainties. For the GPG methods, the atmospheric-flow approach produced the largest estimates of carbon accumulation, followed by the production approach and the stock-change approach, by this order. A sensitivity analysis showed that using the ''best'' available data on production and trade of HWP produces larger estimates of carbon accumulation than using data from the Food and Agriculture Organization. (author)

  12. Permeability Estimation of Rock Reservoir Based on PCA and Elman Neural Networks

    Science.gov (United States)

    Shi, Ying; Jian, Shaoyong

    2018-03-01

    an intelligent method which based on fuzzy neural networks with PCA algorithm, is proposed to estimate the permeability of rock reservoir. First, the dimensionality reduction process is utilized for these parameters by principal component analysis method. Further, the mapping relationship between rock slice characteristic parameters and permeability had been found through fuzzy neural networks. The estimation validity and reliability for this method were tested with practical data from Yan’an region in Ordos Basin. The result showed that the average relative errors of permeability estimation for this method is 6.25%, and this method had the better convergence speed and more accuracy than other. Therefore, by using the cheap rock slice related information, the permeability of rock reservoir can be estimated efficiently and accurately, and it is of high reliability, practicability and application prospect.

  13. 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.

  14. 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.

  15. Evaluation of Different Estimation Methods for Accuracy and Precision in Biological Assay Validation.

    Science.gov (United States)

    Yu, Binbing; Yang, Harry

    2017-01-01

    Biological assays ( bioassays ) are procedures to estimate the potency of a substance by studying its effects on living organisms, tissues, and cells. Bioassays are essential tools for gaining insight into biologic systems and processes including, for example, the development of new drugs and monitoring environmental pollutants. Two of the most important parameters of bioassay performance are relative accuracy (bias) and precision. Although general strategies and formulas are provided in USP, a comprehensive understanding of the definitions of bias and precision remain elusive. Additionally, whether there is a beneficial use of data transformation in estimating intermediate precision remains unclear. Finally, there are various statistical estimation methods available that often pose a dilemma for the analyst who must choose the most appropriate method. To address these issues, we provide both a rigorous definition of bias and precision as well as three alternative methods for calculating relative standard deviation (RSD). All methods perform similarly when the RSD ≤10%. However, the USP estimates result in larger bias and root-mean-square error (RMSE) compared to the three proposed methods when the actual variation was large. Therefore, the USP method should not be used for routine analysis. For data with moderate skewness and deviation from normality, the estimates based on the original scale perform well. The original scale method is preferred, and the method based on log-transformation may be used for noticeably skewed data. LAY ABSTRACT: Biological assays, or bioassays, are essential in the development and manufacture of biopharmaceutical products for potency testing and quality monitoring. Two important parameters of assay performance are relative accuracy (bias) and precision. The definitions of bias and precision in USP 〈1033〉 are elusive and confusing. Another complicating issue is whether log-transformation should be used for calculating the

  16. A new DOD and DOA estimation method for MIMO radar

    Science.gov (United States)

    Gong, Jian; Lou, Shuntian; Guo, Yiduo

    2018-04-01

    The battlefield electromagnetic environment is becoming more and more complex, and MIMO radar will inevitably be affected by coherent and non-stationary noise. To solve this problem, an angle estimation method based on oblique projection operator and Teoplitz matrix reconstruction is proposed. Through the reconstruction of Toeplitz, nonstationary noise is transformed into Gauss white noise, and then the oblique projection operator is used to separate independent and correlated sources. Finally, simulations are carried out to verify the performance of the proposed algorithm in terms of angle estimation performance and source overload.

  17. A recursive Monte Carlo method for estimating importance functions in deep penetration problems

    International Nuclear Information System (INIS)

    Goldstein, M.

    1980-04-01

    A pratical recursive Monte Carlo method for estimating the importance function distribution, aimed at importance sampling for the solution of deep penetration problems in three-dimensional systems, was developed. The efficiency of the recursive method was investigated for sample problems including one- and two-dimensional, monoenergetic and and multigroup problems, as well as for a practical deep-penetration problem with streaming. The results of the recursive Monte Carlo calculations agree fairly well with Ssub(n) results. It is concluded that the recursive Monte Carlo method promises to become a universal method for estimating the importance function distribution for the solution of deep-penetration problems, in all kinds of systems: for many systems the recursive method is likely to be more efficient than previously existing methods; for three-dimensional systems it is the first method that can estimate the importance function with the accuracy required for an efficient solution based on importance sampling of neutron deep-penetration problems in those systems

  18. A method to estimate stellar ages from kinematical data

    Science.gov (United States)

    Almeida-Fernandes, F.; Rocha-Pinto, H. J.

    2018-05-01

    We present a method to build a probability density function (PDF) for the age of a star based on its peculiar velocities U, V, and W and its orbital eccentricity. The sample used in this work comes from the Geneva-Copenhagen Survey (GCS) that contains the spatial velocities, orbital eccentricities, and isochronal ages for about 14 000 stars. Using the GCS stars, we fitted the parameters that describe the relations between the distributions of kinematical properties and age. This parametrization allows us to obtain an age probability from the kinematical data. From this age PDF, we estimate an individual average age for the star using the most likely age and the expected age. We have obtained the stellar age PDF for the age of 9102 stars from the GCS and have shown that the distribution of individual ages derived from our method is in good agreement with the distribution of isochronal ages. We also observe a decline in the mean metallicity with our ages for stars younger than 7 Gyr, similar to the one observed for isochronal ages. This method can be useful for the estimation of rough stellar ages for those stars that fall in areas of the Hertzsprung-Russell diagram where isochrones are tightly crowded. As an example of this method, we estimate the age of Trappist-1, which is a M8V star, obtaining the age of t(UVW) = 12.50(+0.29 - 6.23) Gyr.

  19. Blind third-order dispersion estimation based on fractional Fourier transformation for coherent optical communication

    Science.gov (United States)

    Yang, Lin; Guo, Peng; Yang, Aiying; Qiao, Yaojun

    2018-02-01

    In this paper, we propose a blind third-order dispersion estimation method based on fractional Fourier transformation (FrFT) in optical fiber communication system. By measuring the chromatic dispersion (CD) at different wavelengths, this method can estimation dispersion slope and further calculate the third-order dispersion. The simulation results demonstrate that the estimation error is less than 2 % in 28GBaud dual polarization quadrature phase-shift keying (DP-QPSK) and 28GBaud dual polarization 16 quadrature amplitude modulation (DP-16QAM) system. Through simulations, the proposed third-order dispersion estimation method is shown to be robust against nonlinear and amplified spontaneous emission (ASE) noise. In addition, to reduce the computational complexity, searching step with coarse and fine granularity is chosen to search optimal order of FrFT. The third-order dispersion estimation method based on FrFT can be used to monitor the third-order dispersion in optical fiber system.

  20. 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.

  1. Optimizing CT radiation dose based on patient size and image quality: the size-specific dose estimate method

    Energy Technology Data Exchange (ETDEWEB)

    Larson, David B. [Stanford University School of Medicine, Department of Radiology, Stanford, CA (United States)

    2014-10-15

    The principle of ALARA (dose as low as reasonably achievable) calls for dose optimization rather than dose reduction, per se. Optimization of CT radiation dose is accomplished by producing images of acceptable diagnostic image quality using the lowest dose method available. Because it is image quality that constrains the dose, CT dose optimization is primarily a problem of image quality rather than radiation dose. Therefore, the primary focus in CT radiation dose optimization should be on image quality. However, no reliable direct measure of image quality has been developed for routine clinical practice. Until such measures become available, size-specific dose estimates (SSDE) can be used as a reasonable image-quality estimate. The SSDE method of radiation dose optimization for CT abdomen and pelvis consists of plotting SSDE for a sample of examinations as a function of patient size, establishing an SSDE threshold curve based on radiologists' assessment of image quality, and modifying protocols to consistently produce doses that are slightly above the threshold SSDE curve. Challenges in operationalizing CT radiation dose optimization include data gathering and monitoring, managing the complexities of the numerous protocols, scanners and operators, and understanding the relationship of the automated tube current modulation (ATCM) parameters to image quality. Because CT manufacturers currently maintain their ATCM algorithms as secret for proprietary reasons, prospective modeling of SSDE for patient populations is not possible without reverse engineering the ATCM algorithm and, hence, optimization by this method requires a trial-and-error approach. (orig.)

  2. An unbiased stereological method for efficiently quantifying the innervation of the heart and other organs based on total length estimations

    DEFF Research Database (Denmark)

    Mühlfeld, Christian; Papadakis, Tamara; Krasteva, Gabriela

    2010-01-01

    Quantitative information about the innervation is essential to analyze the structure-function relationships of organs. So far, there has been no unbiased stereological tool for this purpose. This study presents a new unbiased and efficient method to quantify the total length of axons in a given...... reference volume, illustrated on the left ventricle of the mouse heart. The method is based on the following steps: 1) estimation of the reference volume; 2) randomization of location and orientation using appropriate sampling techniques; 3) counting of nerve fiber profiles hit by a defined test area within...

  3. Modeling, estimation and identification methods for static shape determination of flexible structures. [for large space structure design

    Science.gov (United States)

    Rodriguez, G.; Scheid, R. E., Jr.

    1986-01-01

    This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

  4. Fine-tuning satellite-based rainfall estimates

    Science.gov (United States)

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

    2018-05-01

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

  5. 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.

  6. Setting the light conditions for measuring root transparency for age-at-death estimation methods.

    Science.gov (United States)

    Adserias-Garriga, Joe; Nogué-Navarro, Laia; Zapico, Sara C; Ubelaker, Douglas H

    2018-03-01

    Age-at-death estimation is one of the main goals in forensic identification, being an essential parameter to determine the biological profile, narrowing the possibility of identification in cases involving missing persons and unidentified bodies. The study of dental tissues has been long considered as a proper tool for age estimation with several age estimation methods based on them. Dental age estimation methods can be divided into three categories: tooth formation and development, post-formation changes, and histological changes. While tooth formation and growth changes are important for fetal and infant consideration, when the end of dental and skeletal growth is achieved, post-formation or biochemical changes can be applied. Lamendin et al. in J Forensic Sci 37:1373-1379, (1992) developed an adult age estimation method based on root transparency and periodontal recession. The regression formula demonstrated its accuracy of use for 40 to 70-year-old individuals. Later on, Prince and Ubelaker in J Forensic Sci 47(1):107-116, (2002) evaluated the effects of ancestry and sex and incorporated root height into the equation, developing four new regression formulas for males and females of African and European ancestry. Even though root transparency is a key element in the method, the conditions for measuring this element have not been established. The aim of the present study is to set the light conditions measured in lumens that offer greater accuracy when applying the Lamendin et al. method modified by Prince and Ubelaker. The results must be also taken into account in the application of other age estimation methodologies using root transparency to estimate age-at-death.

  7. 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)

  8. Methods for estimating water consumption for thermoelectric power plants in the United States

    Science.gov (United States)

    Diehl, Timothy H.; Harris, Melissa; Murphy, Jennifer C.; Hutson, Susan S.; Ladd, David E.

    2013-01-01

    Water consumption at thermoelectric power plants represents a small but substantial share of total water consumption in the U.S. However, currently available thermoelectric water consumption data are inconsistent and incomplete, and coefficients used to estimate consumption are contradictory. The U.S. Geological Survey (USGS) has resumed the estimation of thermoelectric water consumption, last done in 1995, based on the use of linked heat and water budgets to complement reported water consumption. This report presents the methods used to estimate freshwater consumption at a study set of 1,284 power plants based on 2010 plant characteristics and operations data.

  9. Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

    Science.gov (United States)

    Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

    2014-12-01

    Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

  10. 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.

  11. 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.

  12. Several key issues on using 137Cs method for soil erosion estimation

    Science.gov (United States)

    This work was to examine several key issues of using the cesium-137 method to estimate soil erosion rates in order to improve and standardize the method. Based on the comprehensive review and synthesis of a large body of published literature and the author’s extensive research experience, several k...

  13. 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

  14. Methods to estimate irrigated reference crop evapotranspiration - a review.

    Science.gov (United States)

    Kumar, R; Jat, M K; Shankar, V

    2012-01-01

    Efficient water management of crops requires accurate irrigation scheduling which, in turn, requires the accurate measurement of crop water requirement. Irrigation is applied to replenish depleted moisture for optimum plant growth. Reference evapotranspiration plays an important role for the determination of water requirements for crops and irrigation scheduling. Various models/approaches varying from empirical to physically base distributed are available for the estimation of reference evapotranspiration. Mathematical models are useful tools to estimate the evapotranspiration and water requirement of crops, which is essential information required to design or choose best water management practices. In this paper the most commonly used models/approaches, which are suitable for the estimation of daily water requirement for agricultural crops grown in different agro-climatic regions, are reviewed. Further, an effort has been made to compare the accuracy of various widely used methods under different climatic conditions.

  15. A simple method for estimation of phosphorous in urine

    International Nuclear Information System (INIS)

    Chaudhary, Seema; Gondane, Sonali; Sawant, Pramilla D.; Rao, D.D.

    2016-01-01

    Following internal contamination of 32 P, it is preferentially eliminated from the body in urine. It is estimated by in-situ precipitation of ammonium molybdo-phosphate (AMP) in urine followed by gross beta counting. The amount of AMP formed in-situ depends on the amount of stable phosphorous (P) present in the urine and hence, it was essential to generate information regarding urinary excretion of stable P. If amount of P excreted is significant then the amount of AMP formed would correspondingly increase leading to absorption of some of the β particles. The present study was taken up for the estimation of daily urinary excretion of P using the phospho-molybdate spectrophotometry method. Few urine samples received from radiation workers were analyzed and based on the observed range of stable P in urine; volume of sample required for 32 P estimation was finalized

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

    Science.gov (United States)

    Shimojo, M.

    2012-08-01

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

  17. Estimating the Technical Potential of Grid-Connected PV Systems in Indonesia : A Comparison of a Method Based on Open Access Data with a Method Based on GIS

    NARCIS (Netherlands)

    Kunaifi, Kunaifi; Reinders, Angelina H.M.E.; Smets, Arno

    2017-01-01

    In this paper, we compare two methods for estimating the technical potential of grid-connected PV systems in Indonesia. One was a method developed by Veldhuis and Renders [1] and the other is a new method using Geographic Information System (GIS) and multi-criteria decision making (MCDM). The first

  18. Combining the triangle method with thermal inertia to estimate regional evapotranspiration

    DEFF Research Database (Denmark)

    Stisen, Simon; Sandholt, Inge; Nørgaard, Anette

    2008-01-01

    Spatially distributed estimates of evaporative fraction and actual evapotranspiration are pursued using a simple remote sensing technique based on a remotely sensed vegetation index (NDVI) and diurnal changes in land surface temperature. The technique, known as the triangle method, is improved by...

  19. A comparison of some methods to estimate the fatigue life of plain dents

    Energy Technology Data Exchange (ETDEWEB)

    Martins, Ricardo R.; Noronha Junior, Dauro B. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)

    2009-12-19

    This paper describes a method under development at PETROBRAS R and D Center (CENPES) to estimate the fatigue life of plain dents. This method uses the API Publication 1156 as a base to estimate the fatigue life of dome shaped plain dents and the Pipeline Defect Assessment Manual (PDAM) approach to take into account the uncertainty inherent in the fatigue phenomenon. CENPES method, an empirical and a semi-empirical method available in the literature were employed to estimate the fatigue lives of 10 plain dents specimens of Year 1 of an ongoing test program carried out by BMT Fleet Technology Limited, with the support of the Pipeline Research Council International (PRCI). The results obtained with the different methods are presented and compared. Furthermore some details are given on the numerical methodology proposed by PETROBRAS that have been used to describe the behavior of plain dents. (author)

  20. SU-F-T-450: The Investigation of Radiotherapy Quality Assurance and Automatic Treatment Planning Based On the Kernel Density Estimation Method

    Energy Technology Data Exchange (ETDEWEB)

    Fan, J; Fan, J; Hu, W; Wang, J [Fudan University Shanghai Cancer Center, Shanghai, Shanghai (China)

    2016-06-15

    Purpose: To develop a fast automatic algorithm based on the two dimensional kernel density estimation (2D KDE) to predict the dose-volume histogram (DVH) which can be employed for the investigation of radiotherapy quality assurance and automatic treatment planning. Methods: We propose a machine learning method that uses previous treatment plans to predict the DVH. The key to the approach is the framing of DVH in a probabilistic setting. The training consists of estimating, from the patients in the training set, the joint probability distribution of the dose and the predictive features. The joint distribution provides an estimation of the conditional probability of the dose given the values of the predictive features. For the new patient, the prediction consists of estimating the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimation of the DVH. The 2D KDE is implemented to predict the joint probability distribution of the training set and the distribution of the predictive features for the new patient. Two variables, including the signed minimal distance from each OAR (organs at risk) voxel to the target boundary and its opening angle with respect to the origin of voxel coordinate, are considered as the predictive features to represent the OAR-target spatial relationship. The feasibility of our method has been demonstrated with the rectum, breast and head-and-neck cancer cases by comparing the predicted DVHs with the planned ones. Results: The consistent result has been found between these two DVHs for each cancer and the average of relative point-wise differences is about 5% within the clinical acceptable extent. Conclusion: According to the result of this study, our method can be used to predict the clinical acceptable DVH and has ability to evaluate the quality and consistency of the treatment planning.

  1. SU-F-T-450: The Investigation of Radiotherapy Quality Assurance and Automatic Treatment Planning Based On the Kernel Density Estimation Method

    International Nuclear Information System (INIS)

    Fan, J; Fan, J; Hu, W; Wang, J

    2016-01-01

    Purpose: To develop a fast automatic algorithm based on the two dimensional kernel density estimation (2D KDE) to predict the dose-volume histogram (DVH) which can be employed for the investigation of radiotherapy quality assurance and automatic treatment planning. Methods: We propose a machine learning method that uses previous treatment plans to predict the DVH. The key to the approach is the framing of DVH in a probabilistic setting. The training consists of estimating, from the patients in the training set, the joint probability distribution of the dose and the predictive features. The joint distribution provides an estimation of the conditional probability of the dose given the values of the predictive features. For the new patient, the prediction consists of estimating the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimation of the DVH. The 2D KDE is implemented to predict the joint probability distribution of the training set and the distribution of the predictive features for the new patient. Two variables, including the signed minimal distance from each OAR (organs at risk) voxel to the target boundary and its opening angle with respect to the origin of voxel coordinate, are considered as the predictive features to represent the OAR-target spatial relationship. The feasibility of our method has been demonstrated with the rectum, breast and head-and-neck cancer cases by comparing the predicted DVHs with the planned ones. Results: The consistent result has been found between these two DVHs for each cancer and the average of relative point-wise differences is about 5% within the clinical acceptable extent. Conclusion: According to the result of this study, our method can be used to predict the clinical acceptable DVH and has ability to evaluate the quality and consistency of the treatment planning.

  2. Bayesian Inference Methods for Sparse Channel Estimation

    DEFF Research Database (Denmark)

    Pedersen, Niels Lovmand

    2013-01-01

    This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...

  3. Estimating health expectancies from two cross-sectional surveys: The intercensal method

    Directory of Open Access Journals (Sweden)

    Michel Guillot

    2009-10-01

    Full Text Available Health expectancies are key indicators for monitoring the health of populations, as well as for informing debates about compression or expansion of morbidity. However, current methodologies for estimating them are not entirely satisfactory. They are either of limited applicability because of high data requirements (the multistate method or based on questionable assumptions (the Sullivan method. This paper proposes a new method, called the "intercensal" method, which relies on the multistate framework but uses widely available data. The method uses age-specific proportions "healthy" at two successive, independent cross-sectional health surveys, and, together with information on general mortality, solves for the set of transition probabilities that produces the observed sequence of proportions healthy. The system is solved by making realistic parametric assumptions about the age patterns of transition probabilities. Using data from the Health and Retirement Survey (HRS and from the National Health Interview Survey (NHIS, the method is tested against both the multistate method and the Sullivan method. We conclude that the intercensal approach is a promising framework for the indirect estimation of health expectancies.

  4. Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

    Directory of Open Access Journals (Sweden)

    Yanting Du

    2018-02-01

    Full Text Available In order to estimate the diesel particulate filter (DPF soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF. The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods.

  5. Experimental verification of a GPC-LPV method with RLS and P1-TS fuzzy-based estimation for limiting the transient and residual vibration of a crane system

    Science.gov (United States)

    Smoczek, Jaroslaw

    2015-10-01

    The paper deals with the problem of reducing the residual vibration and limiting the transient oscillations of a flexible and underactuated system with respect to the variation of operating conditions. The comparative study of generalized predictive control (GPC) and fuzzy scheduling scheme developed based on the P1-TS fuzzy theory, local pole placement method and interval analysis of closed-loop system polynomial coefficients is addressed to the problem of flexible crane control. The two alternatives of a GPC-based method are proposed that enable to realize this technique either with or without a sensor of payload deflection. The first control technique is based on the recursive least squares (RLS) method applied to on-line estimate the parameters of a linear parameter varying (LPV) model of a crane dynamic system. The second GPC-based approach is based on a payload deflection feedback estimated using a pendulum model with the parameters interpolated using the P1-TS fuzzy system. Feasibility and applicability of the developed methods were confirmed through experimental verification performed on a laboratory scaled overhead crane.

  6. NEW COMPLETENESS METHODS FOR ESTIMATING EXOPLANET DISCOVERIES BY DIRECT DETECTION

    International Nuclear Information System (INIS)

    Brown, Robert A.; Soummer, Remi

    2010-01-01

    We report on new methods for evaluating realistic observing programs that search stars for planets by direct imaging, where observations are selected from an optimized star list and stars can be observed multiple times. We show how these methods bring critical insight into the design of the mission and its instruments. These methods provide an estimate of the outcome of the observing program: the probability distribution of discoveries (detection and/or characterization) and an estimate of the occurrence rate of planets (η). We show that these parameters can be accurately estimated from a single mission simulation, without the need for a complete Monte Carlo mission simulation, and we prove the accuracy of this new approach. Our methods provide tools to define a mission for a particular science goal; for example, a mission can be defined by the expected number of discoveries and its confidence level. We detail how an optimized star list can be built and how successive observations can be selected. Our approach also provides other critical mission attributes, such as the number of stars expected to be searched and the probability of zero discoveries. Because these attributes depend strongly on the mission scale (telescope diameter, observing capabilities and constraints, mission lifetime, etc.), our methods are directly applicable to the design of such future missions and provide guidance to the mission and instrument design based on scientific performance. We illustrate our new methods with practical calculations and exploratory design reference missions for the James Webb Space Telescope (JWST) operating with a distant starshade to reduce scattered and diffracted starlight on the focal plane. We estimate that five habitable Earth-mass planets would be discovered and characterized with spectroscopy, with a probability of zero discoveries of 0.004, assuming a small fraction of JWST observing time (7%), η = 0.3, and 70 observing visits, limited by starshade fuel.

  7. Video-Quality Estimation Based on Reduced-Reference Model Employing Activity-Difference

    Science.gov (United States)

    Yamada, Toru; Miyamoto, Yoshihiro; Senda, Yuzo; Serizawa, Masahiro

    This paper presents a Reduced-reference based video-quality estimation method suitable for individual end-user quality monitoring of IPTV services. With the proposed method, the activity values for individual given-size pixel blocks of an original video are transmitted to end-user terminals. At the end-user terminals, the video quality of a received video is estimated on the basis of the activity-difference between the original video and the received video. Psychovisual weightings and video-quality score adjustments for fatal degradations are applied to improve estimation accuracy. In addition, low-bit-rate transmission is achieved by using temporal sub-sampling and by transmitting only the lower six bits of each activity value. The proposed method achieves accurate video quality estimation using only low-bit-rate original video information (15kbps for SDTV). The correlation coefficient between actual subjective video quality and estimated quality is 0.901 with 15kbps side information. The proposed method does not need computationally demanding spatial and gain-and-offset registrations. Therefore, it is suitable for real-time video-quality monitoring in IPTV services.

  8. 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 ...

  9. Order statistics & inference estimation methods

    CERN Document Server

    Balakrishnan, N

    1991-01-01

    The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A co

  10. Investigation of MLE in nonparametric estimation methods of reliability function

    International Nuclear Information System (INIS)

    Ahn, Kwang Won; Kim, Yoon Ik; Chung, Chang Hyun; Kim, Kil Yoo

    2001-01-01

    There have been lots of trials to estimate a reliability function. In the ESReDA 20 th seminar, a new method in nonparametric way was proposed. The major point of that paper is how to use censored data efficiently. Generally there are three kinds of approach to estimate a reliability function in nonparametric way, i.e., Reduced Sample Method, Actuarial Method and Product-Limit (PL) Method. The above three methods have some limits. So we suggest an advanced method that reflects censored information more efficiently. In many instances there will be a unique maximum likelihood estimator (MLE) of an unknown parameter, and often it may be obtained by the process of differentiation. It is well known that the three methods generally used to estimate a reliability function in nonparametric way have maximum likelihood estimators that are uniquely exist. So, MLE of the new method is derived in this study. The procedure to calculate a MLE is similar just like that of PL-estimator. The difference of the two is that in the new method, the mass (or weight) of each has an influence of the others but the mass in PL-estimator not

  11. The PolyMAX Frequency-Domain Method: A New Standard for Modal Parameter Estimation?

    Directory of Open Access Journals (Sweden)

    Bart Peeters

    2004-01-01

    Full Text Available Recently, a new non-iterative frequency-domain parameter estimation method was proposed. It is based on a (weighted least-squares approach and uses multiple-input-multiple-output frequency response functions as primary data. This so-called “PolyMAX” or polyreference least-squares complex frequency-domain method can be implemented in a very similar way as the industry standard polyreference (time-domain least-squares complex exponential method: in a first step a stabilisation diagram is constructed containing frequency, damping and participation information. Next, the mode shapes are found in a second least-squares step, based on the user selection of stable poles. One of the specific advantages of the technique lies in the very stable identification of the system poles and participation factors as a function of the specified system order, leading to easy-to-interpret stabilisation diagrams. This implies a potential for automating the method and to apply it to “difficult” estimation cases such as high-order and/or highly damped systems with large modal overlap. Some real-life automotive and aerospace case studies are discussed. PolyMAX is compared with classical methods concerning stability, accuracy of the estimated modal parameters and quality of the frequency response function synthesis.

  12. A method of estimating log weights.

    Science.gov (United States)

    Charles N. Mann; Hilton H. Lysons

    1972-01-01

    This paper presents a practical method of estimating the weights of logs before they are yarded. Knowledge of log weights is required to achieve optimum loading of modern yarding equipment. Truckloads of logs are weighed and measured to obtain a local density index (pounds per cubic foot) for a species of logs. The density index is then used to estimate the weights of...

  13. [Estimation with the capture-recapture method of the number of economic immigrants in Mallorca].

    Science.gov (United States)

    Ramos Monserrat, M; March Cerdá, J C

    2002-05-15

    estimate the number of irregular economic immigrants in Mallorca. We used the capture-recapture method, an indirect method based on contrasts of data from two or more sources. Data were obtained from the Delegación de Gobierno (police and immigration authority), Comisiones Obreras (labor union), and institutions that provide health-related services to immigrants. Individuals were identified by birth date and country of origin. The total number of economic immigrants estimated with this method was 39 392. According to the Delegación de Gobierno data, the number of regular immigrants on the date of our inquiry was 9000. With the capture-recapture method, the number of irregular immigrants in Mallorca was therefore estimated at 30 000. The capture-recapture method can be useful to estimate the population of irregular immigrants in a given area at a given time, if sufficiently precise information on the identity of each individual can be obtained.

  14. 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

  15. A New Method for the 2D DOA Estimation of Coherently Distributed Sources

    Directory of Open Access Journals (Sweden)

    Liang Zhou

    2014-03-01

    Full Text Available The purpose of this paper is to develop a new technique for estimating the two- dimensional (2D direction-of-arrivals (DOAs of coherently distributed (CD sources, which can estimate effectively the central azimuth and central elevation of CD sources at the cost of less computational cost. Using the special L-shape array, a new approach for parametric estimation of CD sources is proposed. The proposed method is based on two rotational invariance relations under small angular approximation, and estimates two rotational matrices which depict the relations, using propagator technique. And then the central DOA estimations are obtained by utilizing the primary diagonal elements of two rotational matrices. Simulation results indicate that the proposed method can exhibit a good performance under small angular spread and be applied to the multisource scenario where different sources may have different angular distribution shapes. Without any peak-finding search and the eigendecomposition of the high-dimensional sample covariance matrix, the proposed method has significantly reduced the computational cost compared with the existing methods, and thus is beneficial to real-time processing and engineering realization. In addition, our approach is also a robust estimator which does not depend on the angular distribution shape of CD sources.

  16. Comparison of different methods for estimation of potential evapotranspiration

    International Nuclear Information System (INIS)

    Nazeer, M.

    2010-01-01

    Evapotranspiration can be estimated with different available methods. The aim of this research study to compare and evaluate the originally measured potential evapotranspiration from Class A pan with the Hargreaves equation, the Penman equation, the Penman-Montheith equation, and the FAO56 Penman-Monteith equation. The evaporation rate from pan recorded greater than stated methods. For each evapotranspiration method, results were compared against mean monthly potential evapotranspiration (PET) from Pan data according to FAO (ET/sub o/=K/sub pan X E/sub pan)), from daily measured recorded data of the twenty-five years (1984-2008). On the basis of statistical analysis between the pan data and the FAO56- Penman-Monteith method are not considered to be very significant (=0.98) at 95% confidence and prediction intervals. All methods required accurate weather data for precise results, for the purpose of this study the past twenty five years data were analyzed and used including maximum and minimum air temperature, relative humidity, wind speed, sunshine duration and rainfall. Based on linear regression analysis results the FAO56 PMM ranked first (R/sup 2/=0.98) followed by Hergreaves method (R/sup 2/=0.96), Penman-Monteith method (R/sup 2/=0.94) and Penman method (=0.93). Obviously, using FAO56 Penman Monteith method with precise climatic variables for ET/sub o/ estimation is more reliable than the other alternative methods, Hergreaves is more simple and rely only on air temperatures data and can be used alternative of FAO56 Penman-Monteith method if other climatic data are missing or unreliable. (author)

  17. 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.

  18. 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.

  19. A Fast LMMSE Channel Estimation Method for OFDM Systems

    Directory of Open Access Journals (Sweden)

    Zhou Wen

    2009-01-01

    Full Text Available A fast linear minimum mean square error (LMMSE channel estimation method has been proposed for Orthogonal Frequency Division Multiplexing (OFDM systems. In comparison with the conventional LMMSE channel estimation, the proposed channel estimation method does not require the statistic knowledge of the channel in advance and avoids the inverse operation of a large dimension matrix by using the fast Fourier transform (FFT operation. Therefore, the computational complexity can be reduced significantly. The normalized mean square errors (NMSEs of the proposed method and the conventional LMMSE estimation have been derived. Numerical results show that the NMSE of the proposed method is very close to that of the conventional LMMSE method, which is also verified by computer simulation. In addition, computer simulation shows that the performance of the proposed method is almost the same with that of the conventional LMMSE method in terms of bit error rate (BER.

  20. 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.

  1. Methods for estimating heterocyclic amine concentrations in cooked meats in the US diet.

    Science.gov (United States)

    Keating, G A; Bogen, K T

    2001-01-01

    Heterocyclic amines (HAs) are formed in numerous cooked foods commonly consumed in the diet. A method was developed to estimate dietary HA levels using HA concentrations in experimentally cooked meats reported in the literature and meat consumption data obtained from a national dietary survey. Cooking variables (meat internal temperature and weight loss, surface temperature and time) were used to develop relationships for estimating total HA concentrations in six meat types. Concentrations of five individual HAs were estimated for specific meat type/cooking method combinations based on linear regression of total and individual HA values obtained from the literature. Using these relationships, total and individual HA concentrations were estimated for 21 meat type/cooking method combinations at four meat doneness levels. Reported consumption of the 21 meat type/cooking method combinations was obtained from a national dietary survey and the age-specific daily HA intake calculated using the estimated HA concentrations (ng/g) and reported meat intakes. Estimated mean daily total HA intakes for children (to age 15 years) and adults (30+ years) were 11 and 7.0 ng/kg/day, respectively, with 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) estimated to comprise approximately 65% of each intake. Pan-fried meats were the largest source of HA in the diet and chicken the largest source of HAs among the different meat types.

  2. A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter

    Directory of Open Access Journals (Sweden)

    Bizhong Xia

    2015-11-01

    Full Text Available The estimation of state of charge (SOC is a crucial evaluation index in a battery management system (BMS. The value of SOC indicates the remaining capacity of a battery, which provides a good guarantee of safety and reliability of battery operation. It is difficult to get an accurate value of the SOC, being one of the inner states. In this paper, a strong tracking cubature Kalman filter (STCKF based on the cubature Kalman filter is presented to perform accurate and reliable SOC estimation. The STCKF algorithm can adjust gain matrix online by introducing fading factor to the state estimation covariance matrix. The typical second-order resistor-capacitor model is used as the battery’s equivalent circuit model to dynamically simulate characteristics of the battery. The exponential-function fitting method accomplishes the task of relevant parameters identification. Then, the developed STCKF algorithm has been introduced in detail and verified under different operation current profiles such as Dynamic Stress Test (DST and New European Driving Cycle (NEDC. Making a comparison with extended Kalman filter (EKF and CKF algorithm, the experimental results show the merits of the STCKF algorithm in SOC estimation accuracy and robustness.

  3. Experimental Quasi-Microwave Whole-Body Averaged SAR Estimation Method Using Cylindrical-External Field Scanning

    Science.gov (United States)

    Kawamura, Yoshifumi; Hikage, Takashi; Nojima, Toshio

    The aim of this study is to develop a new whole-body averaged specific absorption rate (SAR) estimation method based on the external-cylindrical field scanning technique. This technique is adopted with the goal of simplifying the dosimetry estimation of human phantoms that have different postures or sizes. An experimental scaled model system is constructed. In order to examine the validity of the proposed method for realistic human models, we discuss the pros and cons of measurements and numerical analyses based on the finite-difference time-domain (FDTD) method. We consider the anatomical European human phantoms and plane-wave in the 2GHz mobile phone frequency band. The measured whole-body averaged SAR results obtained by the proposed method are compared with the results of the FDTD analyses.

  4. Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

    International Nuclear Information System (INIS)

    Ng, Kong Soon; Moo, Chin-Sien; Chen, Yi-Ping; Hsieh, Yao-Ching

    2009-01-01

    The coulomb counting method is expedient for state-of-charge (SOC) estimation of lithium-ion batteries with high charging and discharging efficiencies. The charging and discharging characteristics are investigated and reveal that the coulomb counting method is convenient and accurate for estimating the SOC of lithium-ion batteries. A smart estimation method based on coulomb counting is proposed to improve the estimation accuracy. The corrections are made by considering the charging and operating efficiencies. Furthermore, the state-of-health (SOH) is evaluated by the maximum releasable capacity. Through the experiments that emulate practical operations, the SOC estimation method is verified to demonstrate the effectiveness and accuracy.

  5. A Comparative Study of Distribution System Parameter Estimation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

    2016-07-17

    In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.

  6. Evaluation of three paediatric weight estimation methods in Singapore.

    Science.gov (United States)

    Loo, Pei Ying; Chong, Shu-Ling; Lek, Ngee; Bautista, Dianne; Ng, Kee Chong

    2013-04-01

    Rapid paediatric weight estimation methods in the emergency setting have not been evaluated for South East Asian children. This study aims to assess the accuracy and precision of three such methods in Singapore children: Broselow-Luten (BL) tape, Advanced Paediatric Life Support (APLS) (estimated weight (kg) = 2 (age + 4)) and Luscombe (estimated weight (kg) = 3 (age) + 7) formulae. We recruited 875 patients aged 1-10 years in a Paediatric Emergency Department in Singapore over a 2-month period. For each patient, true weight and height were determined. True height was cross-referenced to the BL tape markings and used to derive estimated weight (virtual BL tape method), while patient's round-down age (in years) was used to derive estimated weights using APLS and Luscombe formulae, respectively. The percentage difference between the true and estimated weights was calculated. For each method, the bias and extent of agreement were quantified using Bland-Altman method (mean percentage difference (MPD) and 95% limits of agreement (LOA)). The proportion of weight estimates within 10% of true weight (p₁₀) was determined. The BL tape method marginally underestimated weights (MPD +0.6%; 95% LOA -26.8% to +28.1%; p₁₀ 58.9%). The APLS formula underestimated weights (MPD +7.6%; 95% LOA -26.5% to +41.7%; p₁₀ 45.7%). The Luscombe formula overestimated weights (MPD -7.4%; 95% LOA -51.0% to +36.2%; p₁₀ 37.7%). Of the three methods we evaluated, the BL tape method provided the most accurate and precise weight estimation for Singapore children. The APLS and Luscombe formulae underestimated and overestimated the children's weights, respectively, and were considerably less precise. © 2013 The Authors. Journal of Paediatrics and Child Health © 2013 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

  7. A Simple Plasma Retinol Isotope Ratio Method for Estimating β-Carotene Relative Bioefficacy in Humans: Validation with the Use of Model-Based Compartmental Analysis.

    Science.gov (United States)

    Ford, Jennifer Lynn; Green, Joanne Balmer; Lietz, Georg; Oxley, Anthony; Green, Michael H

    2017-09-01

    Background: Provitamin A carotenoids are an important source of dietary vitamin A for many populations. Thus, accurate and simple methods for estimating carotenoid bioefficacy are needed to evaluate the vitamin A value of test solutions and plant sources. β-Carotene bioefficacy is often estimated from the ratio of the areas under plasma isotope response curves after subjects ingest labeled β-carotene and a labeled retinyl acetate reference dose [isotope reference method (IRM)], but to our knowledge, the method has not yet been evaluated for accuracy. Objectives: Our objectives were to develop and test a physiologically based compartmental model that includes both absorptive and postabsorptive β-carotene bioconversion and to use the model to evaluate the accuracy of the IRM and a simple plasma retinol isotope ratio [(RIR), labeled β-carotene-derived retinol/labeled reference-dose-derived retinol in one plasma sample] for estimating relative bioefficacy. Methods: We used model-based compartmental analysis (Simulation, Analysis and Modeling software) to develop and apply a model that provided known values for β-carotene bioefficacy. Theoretical data for 10 subjects were generated by the model and used to determine bioefficacy by RIR and IRM; predictions were compared with known values. We also applied RIR and IRM to previously published data. Results: Plasma RIR accurately predicted β-carotene relative bioefficacy at 14 d or later. IRM also accurately predicted bioefficacy by 14 d, except that, when there was substantial postabsorptive bioconversion, IRM underestimated bioefficacy. Based on our model, 1-d predictions of relative bioefficacy include absorptive plus a portion of early postabsorptive conversion. Conclusion: The plasma RIR is a simple tracer method that accurately predicts β-carotene relative bioefficacy based on analysis of one blood sample obtained at ≥14 d after co-ingestion of labeled β-carotene and retinyl acetate. The method also provides

  8. A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

    KAUST Repository

    Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

    2017-01-01

    The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

  9. A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

    KAUST Repository

    Hu, Zongliang

    2017-09-27

    The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

  10. A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.

    Science.gov (United States)

    Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

    2017-09-21

    The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

  11. Estimation of Bouguer Density Precision: Development of Method for Analysis of La Soufriere Volcano Gravity Data

    Directory of Open Access Journals (Sweden)

    Hendra Gunawan

    2014-06-01

    Full Text Available http://dx.doi.org/10.17014/ijog.vol3no3.20084The precision of topographic density (Bouguer density estimation by the Nettleton approach is based on a minimum correlation of Bouguer gravity anomaly and topography. The other method, the Parasnis approach, is based on a minimum correlation of Bouguer gravity anomaly and Bouguer correction. The precision of Bouguer density estimates was investigated by both methods on simple 2D syntetic models and under an assumption free-air anomaly consisting of an effect of topography, an effect of intracrustal, and an isostatic compensation. Based on simulation results, Bouguer density estimates were then investigated for a gravity survey of 2005 on La Soufriere Volcano-Guadeloupe area (Antilles Islands. The Bouguer density based on the Parasnis approach is 2.71 g/cm3 for the whole area, except the edifice area where average topography density estimates are 2.21 g/cm3 where Bouguer density estimates from previous gravity survey of 1975 are 2.67 g/cm3. The Bouguer density in La Soufriere Volcano was uncertainly estimated to be 0.1 g/cm3. For the studied area, the density deduced from refraction seismic data is coherent with the recent Bouguer density estimates. New Bouguer anomaly map based on these Bouguer density values allows to a better geological intepretation.    

  12. Comparison of regional index flood estimation procedures based on the extreme value type I distribution

    DEFF Research Database (Denmark)

    Kjeldsen, Thomas Rodding; Rosbjerg, Dan

    2002-01-01

    the prediction uncertainty and that the presence of intersite correlation tends to increase the uncertainty. A simulation study revealed that in regional index-flood estimation the method of probability weighted moments is preferable to method of moment estimation with regard to bias and RMSE.......A comparison of different methods for estimating T-year events is presented, all based on the Extreme Value Type I distribution. Series of annual maximum flood from ten gauging stations at the New Zealand South island have been used. Different methods of predicting the 100-year event...... and the connected uncertainty have been applied: At-site estimation and regional index-flood estimation with and without accounting for intersite correlation using either the method of moments or the method of probability weighted moments for parameter estimation. Furthermore, estimation at ungauged sites were...

  13. 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.

  14. [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.

  15. Are rapid population estimates accurate? A field trial of two different assessment methods.

    Science.gov (United States)

    Grais, Rebecca F; Coulombier, Denis; Ampuero, Julia; Lucas, Marcelino E S; Barretto, Avertino T; Jacquier, Guy; Diaz, Francisco; Balandine, Serge; Mahoudeau, Claude; Brown, Vincent

    2006-09-01

    Emergencies resulting in large-scale displacement often lead to populations resettling in areas where basic health services and sanitation are unavailable. To plan relief-related activities quickly, rapid population size estimates are needed. The currently recommended Quadrat method estimates total population by extrapolating the average population size living in square blocks of known area to the total site surface. An alternative approach, the T-Square, provides a population estimate based on analysis of the spatial distribution of housing units taken throughout a site. We field tested both methods and validated the results against a census in Esturro Bairro, Beira, Mozambique. Compared to the census (population: 9,479), the T-Square yielded a better population estimate (9,523) than the Quadrat method (7,681; 95% confidence interval: 6,160-9,201), but was more difficult for field survey teams to implement. Although applicable only to similar sites, several general conclusions can be drawn for emergency planning.

  16. An improved segmentation-based HMM learning method for Condition-based Maintenance

    International Nuclear Information System (INIS)

    Liu, T; Lemeire, J; Cartella, F; Meganck, S

    2012-01-01

    In the domain of condition-based maintenance (CBM), persistence of machine states is a valid assumption. Based on this assumption, we present an improved Hidden Markov Model (HMM) learning algorithm for the assessment of equipment states. By a good estimation of initial parameters, more accurate learning can be achieved than by regular HMM learning methods which start with randomly chosen initial parameters. It is also better in avoiding getting trapped in local maxima. The data is segmented with a change-point analysis method which uses a combination of cumulative sum charts (CUSUM) and bootstrapping techniques. The method determines a confidence level that a state change happens. After the data is segmented, in order to label and combine the segments corresponding to the same states, a clustering technique is used based on a low-pass filter or root mean square (RMS) values of the features. The segments with their labelled hidden state are taken as 'evidence' to estimate the parameters of an HMM. Then, the estimated parameters are served as initial parameters for the traditional Baum-Welch (BW) learning algorithms, which are used to improve the parameters and train the model. Experiments on simulated and real data demonstrate that both performance and convergence speed is improved.

  17. METAPHOR: Probability density estimation for machine learning based photometric redshifts

    Science.gov (United States)

    Amaro, V.; Cavuoti, S.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.

    2017-06-01

    We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).

  18. A new rapid method for rockfall energies and distances estimation

    Science.gov (United States)

    Giacomini, Anna; Ferrari, Federica; Thoeni, Klaus; Lambert, Cedric

    2016-04-01

    Rockfalls are characterized by long travel distances and significant energies. Over the last decades, three main methods have been proposed in the literature to assess the rockfall runout: empirical, process-based and GIS-based methods (Dorren, 2003). Process-based methods take into account the physics of rockfall by simulating the motion of a falling rock along a slope and they are generally based on a probabilistic rockfall modelling approach that allows for taking into account the uncertainties associated with the rockfall phenomenon. Their application has the advantage of evaluating the energies, bounce heights and distances along the path of a falling block, hence providing valuable information for the design of mitigation measures (Agliardi et al., 2009), however, the implementation of rockfall simulations can be time-consuming and data-demanding. This work focuses on the development of a new methodology for estimating the expected kinetic energies and distances of the first impact at the base of a rock cliff, subject to the conditions that the geometry of the cliff and the properties of the representative block are known. The method is based on an extensive two-dimensional sensitivity analysis, conducted by means of kinematic simulations based on probabilistic modelling of two-dimensional rockfall trajectories (Ferrari et al., 2016). To take into account for the uncertainty associated with the estimation of the input parameters, the study was based on 78400 rockfall scenarios performed by systematically varying the input parameters that are likely to affect the block trajectory, its energy and distance at the base of the rock wall. The variation of the geometry of the rock cliff (in terms of height and slope angle), the roughness of the rock surface and the properties of the outcropping material were considered. A simplified and idealized rock wall geometry was adopted. The analysis of the results allowed finding empirical laws that relate impact energies

  19. Performance evaluation of the spectral centroid downshift method for attenuation estimation.

    Science.gov (United States)

    Samimi, Kayvan; Varghese, Tomy

    2015-05-01

    Estimation of frequency-dependent ultrasonic attenuation is an important aspect of tissue characterization. Along with other acoustic parameters studied in quantitative ultrasound, the attenuation coefficient can be used to differentiate normal and pathological tissue. The spectral centroid downshift (CDS) method is one the most common frequencydomain approaches applied to this problem. In this study, a statistical analysis of this method's performance was carried out based on a parametric model of the signal power spectrum in the presence of electronic noise. The parametric model used for the power spectrum of received RF data assumes a Gaussian spectral profile for the transmit pulse, and incorporates effects of attenuation, windowing, and electronic noise. Spectral moments were calculated and used to estimate second-order centroid statistics. A theoretical expression for the variance of a maximum likelihood estimator of attenuation coefficient was derived in terms of the centroid statistics and other model parameters, such as transmit pulse center frequency and bandwidth, RF data window length, SNR, and number of regression points. Theoretically predicted estimation variances were compared with experimentally estimated variances on RF data sets from both computer-simulated and physical tissue-mimicking phantoms. Scan parameter ranges for this study were electronic SNR from 10 to 70 dB, transmit pulse standard deviation from 0.5 to 4.1 MHz, transmit pulse center frequency from 2 to 8 MHz, and data window length from 3 to 17 mm. Acceptable agreement was observed between theoretical predictions and experimentally estimated values with differences smaller than 0.05 dB/cm/MHz across the parameter ranges investigated. This model helps predict the best attenuation estimation variance achievable with the CDS method, in terms of said scan parameters.

  20. A new method for estimating insolation based on PV-module currents in a cluster of stand-alone solar systems

    NARCIS (Netherlands)

    Nieuwenhout, F; van der Borg, N; van Sark, W.G.J.H.M.; Turkenburg, W.C.

    2007-01-01

    In order to evaluate the performance of solar home systems (SHSs), data on local insolation is a prerequisite. We present a new method to estimate insolation if direct measurements are unavailable. This method comprises estimation of daily irradiation by correlating photovoltaic (PV) module currents

  1. Interactions Between Indirect DC-Voltage Estimation and Circulating Current Controllers of MMC-Based HVDC Transmission Systems

    DEFF Research Database (Denmark)

    Wickramasinghe, Harith R.; Konstantinou, Georgios; Pou, Josep

    2018-01-01

    Estimation-based indirect dc-voltage control in MMCs interacts with circulating current control methods. This paper proposes an estimation-based indirect dc-voltage control method for MMC-HVDC systems and analyzes its performance compared to alternative estimations. The interactions between......-state and transient performance is demonstrated using a benchmark MMC-HVDC transmission system, implemented in a real-time digital simulator. The results verify the theoretical evaluations and illustrate the operation and performance of the proposed indirect dc-voltage control method....

  2. A theory of timing in scintillation counters based on maximum likelihood estimation

    International Nuclear Information System (INIS)

    Tomitani, Takehiro

    1982-01-01

    A theory of timing in scintillation counters based on the maximum likelihood estimation is presented. An optimum filter that minimizes the variance of timing is described. A simple formula to estimate the variance of timing is presented as a function of photoelectron number, scintillation decay constant and the single electron transit time spread in the photomultiplier. The present method was compared with the theory by E. Gatti and V. Svelto. The proposed method was applied to two simple models and rough estimations of potential time resolution of several scintillators are given. The proposed method is applicable to the timing in Cerenkov counters and semiconductor detectors as well. (author)

  3. Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

    Science.gov (United States)

    Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

    2013-12-01

    In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example

  4. 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.

  5. 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.

  6. ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou

    2016-06-01

    Full Text Available Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, deforestation, and plant diseases — occur worldwide at unknown times and locations. Timely detection and characterization of these disturbances is of importance for land cover monitoring. Recently, many time-series-analysis methods have been developed for near real-time or online disturbance detection, using satellite image time series. However, the detection results were only labelled with “Change/ No change” by most of the present methods, while few methods focus on estimating reliability (or confidence level of the detected disturbances in image time series. To this end, this paper propose a statistical analysis method for estimating reliability of disturbances in new available remote sensing image time series, through analysis of full temporal information laid in time series data. The method consists of three main steps. (1 Segmenting and modelling of historical time series data based on Breaks for Additive Seasonal and Trend (BFAST. (2 Forecasting and detecting disturbances in new time series data. (3 Estimating reliability of each detected disturbance using statistical analysis based on Confidence Interval (CI and Confidence Levels (CL. The method was validated by estimating reliability of disturbance regions caused by a recent severe flooding occurred around the border of Russia and China. Results demonstrated that the method can estimate reliability of disturbances detected in satellite image with estimation error less than 5% and overall accuracy up to 90%.

  7. Human Age Estimation Method Robust to Camera Sensor and/or Face Movement

    Directory of Open Access Journals (Sweden)

    Dat Tien Nguyen

    2015-08-01

    Full Text Available Human age can be employed in many useful real-life applications, such as customer service systems, automatic vending machines, entertainment, etc. In order to obtain age information, image-based age estimation systems have been developed using information from the human face. However, limitations exist for current age estimation systems because of the various factors of camera motion and optical blurring, facial expressions, gender, etc. Motion blurring can usually be presented on face images by the movement of the camera sensor and/or the movement of the face during image acquisition. Therefore, the facial feature in captured images can be transformed according to the amount of motion, which causes performance degradation of age estimation systems. In this paper, the problem caused by motion blurring is addressed and its solution is proposed in order to make age estimation systems robust to the effects of motion blurring. Experiment results show that our method is more efficient for enhancing age estimation performance compared with systems that do not employ our method.

  8. Methods for cost estimation in software project management

    Science.gov (United States)

    Briciu, C. V.; Filip, I.; Indries, I. I.

    2016-02-01

    The speed in which the processes used in software development field have changed makes it very difficult the task of forecasting the overall costs for a software project. By many researchers, this task has been considered unachievable, but there is a group of scientist for which this task can be solved using the already known mathematical methods (e.g. multiple linear regressions) and the new techniques as genetic programming and neural networks. The paper presents a solution for building a model for the cost estimation models in the software project management using genetic algorithms starting from the PROMISE datasets related COCOMO 81 model. In the first part of the paper, a summary of the major achievements in the research area of finding a model for estimating the overall project costs is presented together with the description of the existing software development process models. In the last part, a basic proposal of a mathematical model of a genetic programming is proposed including here the description of the chosen fitness function and chromosome representation. The perspective of model described it linked with the current reality of the software development considering as basis the software product life cycle and the current challenges and innovations in the software development area. Based on the author's experiences and the analysis of the existing models and product lifecycle it was concluded that estimation models should be adapted with the new technologies and emerging systems and they depend largely by the chosen software development method.

  9. Method for estimating capacity and predicting remaining useful life of lithium-ion battery

    International Nuclear Information System (INIS)

    Hu, Chao; Jain, Gaurav; Tamirisa, Prabhakar; Gorka, Tom

    2014-01-01

    Highlights: • We develop an integrated method for the capacity estimation and RUL prediction. • A state projection scheme is derived for capacity estimation. • The Gauss–Hermite particle filter technique is used for the RUL prediction. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the capacity of Li-ion battery and predict the remaining useful life (RUL) throughout the whole life-time. This paper presents an integrated method for the capacity estimation and RUL prediction of Li-ion battery used in implantable medical devices. A state projection scheme from the author’s previous study is used for the capacity estimation. Then, based on the capacity estimates, the Gauss–Hermite particle filter technique is used to project the capacity fade to the end-of-service (EOS) value (or the failure limit) for the RUL prediction. Results of 10 years’ continuous cycling test on Li-ion prismatic cells in the lab suggest that the proposed method achieves good accuracy in the capacity estimation and captures the uncertainty in the RUL prediction. Post-explant weekly cycling data obtained from field cells with 4–7 implant years further verify the effectiveness of the proposed method in the capacity estimation

  10. Time difference of arrival estimation of microseismic signals based on alpha-stable distribution

    Science.gov (United States)

    Jia, Rui-Sheng; Gong, Yue; Peng, Yan-Jun; Sun, Hong-Mei; Zhang, Xing-Li; Lu, Xin-Ming

    2018-05-01

    Microseismic signals are generally considered to follow the Gauss distribution. A comparison of the dynamic characteristics of sample variance and the symmetry of microseismic signals with the signals which follow α-stable distribution reveals that the microseismic signals have obvious pulse characteristics and that the probability density curve of the microseismic signal is approximately symmetric. Thus, the hypothesis that microseismic signals follow the symmetric α-stable distribution is proposed. On the premise of this hypothesis, the characteristic exponent α of the microseismic signals is obtained by utilizing the fractional low-order statistics, and then a new method of time difference of arrival (TDOA) estimation of microseismic signals based on fractional low-order covariance (FLOC) is proposed. Upon applying this method to the TDOA estimation of Ricker wavelet simulation signals and real microseismic signals, experimental results show that the FLOC method, which is based on the assumption of the symmetric α-stable distribution, leads to enhanced spatial resolution of the TDOA estimation relative to the generalized cross correlation (GCC) method, which is based on the assumption of the Gaussian distribution.

  11. Distance Based Method for Outlier Detection of Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Haibin Zhang

    2016-01-01

    Full Text Available We propose a distance based method for the outlier detection of body sensor networks. Firstly, we use a Kernel Density Estimation (KDE to calculate the probability of the distance to k nearest neighbors for diagnosed data. If the probability is less than a threshold, and the distance of this data to its left and right neighbors is greater than a pre-defined value, the diagnosed data is decided as an outlier. Further, we formalize a sliding window based method to improve the outlier detection performance. Finally, to estimate the KDE by training sensor readings with errors, we introduce a Hidden Markov Model (HMM based method to estimate the most probable ground truth values which have the maximum probability to produce the training data. Simulation results show that the proposed method possesses a good detection accuracy with a low false alarm rate.

  12. Comparison of least squares and exponential sine sweep methods for Parallel Hammerstein Models estimation

    Science.gov (United States)

    Rebillat, Marc; Schoukens, Maarten

    2018-05-01

    Linearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, Parallel Hammerstein Models (PHM) are interesting as they are at the same time easy to interpret as well as to estimate. One way to estimate PHM relies on the fact that the estimation problem is linear in the parameters and thus that classical least squares (LS) estimation algorithms can be used. In that area, this article introduces a regularized LS estimation algorithm inspired on some of the recently developed regularized impulse response estimation techniques. Another mean to estimate PHM consists in using parametric or non-parametric exponential sine sweeps (ESS) based methods. These methods (LS and ESS) are founded on radically different mathematical backgrounds but are expected to tackle the same issue. A methodology is proposed here to compare them with respect to (i) their accuracy, (ii) their computational cost, and (iii) their robustness to noise. Tests are performed on simulated systems for several values of methods respective parameters and of signal to noise ratio. Results show that, for a given set of data points, the ESS method is less demanding in computational resources than the LS method but that it is also less accurate. Furthermore, the LS method needs parameters to be set in advance whereas the ESS method is not subject to conditioning issues and can be fully non-parametric. In summary, for a given set of data points, ESS method can provide a first, automatic, and quick overview of a nonlinear system than can guide more computationally demanding and precise methods, such as the regularized LS one proposed here.

  13. A method for estimation of plasma albumin concentration from the buffering properties of whole blood

    DEFF Research Database (Denmark)

    Rees, Stephen Edward; Diemer, Tue; Kristensen, Søren Risom

    2012-01-01

    measurements of acid-base and oxygenation status. This article presents and evaluates a new method for doing so. MATERIALS AND METHODS: The mathematical method for estimating plasma albumin concentration is described. To evaluate the method at numerous albumin concentrations, blood from 19 healthy subjects......PURPOSE: Hypoalbuminemia is strongly associated with poor clinical outcome. Albumin is usually measured at the central laboratory rather than point of care, but in principle, information exists in the buffering properties of whole blood to estimate plasma albumin concentration from point of care...

  14. Comparison of two perturbation methods to estimate the land surface modeling uncertainty

    Science.gov (United States)

    Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

    2007-12-01

    In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

  15. A sensor-based energy balance method for the distributed estimation of evaporation over the North American Great Lakes

    Science.gov (United States)

    Fries, K. J.; Kerkez, B.; Gronewold, A.; Lenters, J. D.

    2014-12-01

    We introduce a novel energy balance method to estimate evaporation across large lakes using real-time data from moored buoys and mobile, satellite-tracked drifters. Our work is motivated by the need to improve our understanding of the water balance of the Laurentian Great Lakes basin, a complex hydrologic system that comprises 90% of the United States' and 20% of the world's fresh surface water. Recently, the lakes experienced record-setting water level drops despite above-average precipitation, and given that lake surface area comprises nearly one third of the entire basin, evaporation is suspected to be the primary driver behind the decrease in water levels. There has historically been a need to measure evaporation over the Great Lakes, and recent hydrological phenomena (including not only record low levels, but also extreme changes in ice cover and surface water temperatures) underscore the urgency of addressing that need. Our method tracks the energy fluxes of the lake system - namely net radiation, heat storage and advection, and Bowen ratio. By measuring each of these energy budget terms and combining the results with mass-transfer based estimates, we can calculate real-time evaporation rates on sub-hourly timescales. To mitigate the cost prohibitive nature of large-scale, distributed energy flux measurements, we present a novel approach in which we leverage existing investments in seasonal buoys (which, while providing intensive, high quality data, are costly and sparsely distributed across the surface of the Great Lakes) and then integrate data from less costly satellite-tracked drifter data. The result is an unprecedented, hierarchical sensor and modeling architecture that can be used to derive estimates of evaporation in real-time through cloud-based computing. We discuss recent deployments of sensor-equipped buoys and drifters, which are beginning to provide us with some of the first in situ measurements of overlake evaporation from Earth's largest lake

  16. Errors in the estimation method for the rejection of vibrations in adaptive optics systems

    Science.gov (United States)

    Kania, Dariusz

    2017-06-01

    In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.

  17. 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.)

  18. 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

  19. Joint DOA and Fundamental Frequency Estimation Methods based on 2-D Filtering

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

    2010-01-01

    of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed...

  20. Population Estimation with Mark and Recapture Method Program

    International Nuclear Information System (INIS)

    Limohpasmanee, W.; Kaewchoung, W.

    1998-01-01

    Population estimation is the important information which required for the insect control planning especially the controlling with SIT. Moreover, It can be used to evaluate the efficiency of controlling method. Due to the complexity of calculation, the population estimation with mark and recapture methods were not used widely. So that, this program is developed with Qbasic on the purpose to make it accuracy and easier. The program evaluation consists with 6 methods; follow Seber's, Jolly-seber's, Jackson's Ito's, Hamada's and Yamamura's methods. The results are compared with the original methods, found that they are accuracy and more easier to applied

  1. Estimation of Handgrip Force from SEMG Based on Wavelet Scale Selection.

    Science.gov (United States)

    Wang, Kai; Zhang, Xianmin; Ota, Jun; Huang, Yanjiang

    2018-02-24

    This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the force-varying analysis task. We performed a computational sensitivity analysis on the initial nonlinear SEMG-handgrip force model. To explore the nonlinear correlation between ten wavelet scales and handgrip force, a large-scale iteration based on the Monte Carlo simulation was conducted. To choose a suitable combination of scales, we proposed a rule to combine wavelet scales based on the sensitivity of each scale and selected the appropriate combination of wavelet scales based on sequence combination analysis (SCA). The results of SCA indicated that the scale combination VI is suitable for estimating force from the extensors and the combination V is suitable for the flexors. The proposed method was compared to two former methods through prolonged static and force-varying contraction tasks. The experiment results showed that the root mean square errors derived by the proposed method for both static and force-varying contraction tasks were less than 20%. The accuracy and robustness of the handgrip force derived by the proposed method is better than that obtained by the former methods.

  2. Data-based depth estimation of an incoming autonomous underwater vehicle.

    Science.gov (United States)

    Yang, T C; Xu, Wen

    2016-10-01

    The data-based method for estimating the depth of a moving source is demonstrated experimentally for an incoming autonomous underwater vehicle traveling toward a vertical line array (VLA) of receivers at constant speed/depth. The method assumes no information on the sound-speed and bottom profile. Performing a wavenumber analysis of a narrowband signal for each hydrophone, the energy of the (modal) spectral peaks as a function of the receiver depth is used to estimate the depth of the source, traveling within the depth span of the VLA. This paper reviews the theory, discusses practical implementation issues, and presents the data analysis results.

  3. Compressive Video Recovery Using Block Match Multi-Frame Motion Estimation Based on Single Pixel Cameras

    Directory of Open Access Journals (Sweden)

    Sheng Bi

    2016-03-01

    Full Text Available Compressive sensing (CS theory has opened up new paths for the development of signal processing applications. Based on this theory, a novel single pixel camera architecture has been introduced to overcome the current limitations and challenges of traditional focal plane arrays. However, video quality based on this method is limited by existing acquisition and recovery methods, and the method also suffers from being time-consuming. In this paper, a multi-frame motion estimation algorithm is proposed in CS video to enhance the video quality. The proposed algorithm uses multiple frames to implement motion estimation. Experimental results show that using multi-frame motion estimation can improve the quality of recovered videos. To further reduce the motion estimation time, a block match algorithm is used to process motion estimation. Experiments demonstrate that using the block match algorithm can reduce motion estimation time by 30%.

  4. A simplified dynamic method for field capacity estimation and its parameter analysis

    Institute of Scientific and Technical Information of China (English)

    Zhen-tao CONG; Hua-fang LÜ; Guang-heng NI

    2014-01-01

    This paper presents a simplified dynamic method based on the definition of field capacity. Two soil hydraulic characteristics models, the Brooks-Corey (BC) model and the van Genuchten (vG) model, and four soil data groups were used in this study. The relative drainage rate, which is a unique parameter and independent of the soil type in the simplified dynamic method, was analyzed using the pressure-based method with a matric potential of−1/3 bar and the flux-based method with a drainage flux of 0.005 cm/d. As a result, the relative drainage rate of the simplified dynamic method was determined to be 3% per day. This was verified by the similar field capacity results estimated with the three methods for most soils suitable for cultivating plants. In addition, the drainage time calculated with the simplified dynamic method was two to three days, which agrees with the classical definition of field capacity. We recommend the simplified dynamic method with a relative drainage rate of 3% per day due to its simple application and clearly physically-based concept.

  5. Modified generalized method of moments for a robust estimation of polytomous logistic model

    Directory of Open Access Journals (Sweden)

    Xiaoshan Wang

    2014-07-01

    Full Text Available The maximum likelihood estimation (MLE method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.

  6. Experimental Quasi-Microwave Whole-Body Averaged SAR Estimation Method Using Cylindrical-External Field Scanning

    OpenAIRE

    Kawamura, Yoshifumi; Hikage, Takashi; Nojima, Toshio

    2010-01-01

    The aim of this study is to develop a new whole-body averaged specific absorption rate (SAR) estimation method based on the external-cylindrical field scanning technique. This technique is adopted with the goal of simplifying the dosimetry estimation of human phantoms that have different postures or sizes. An experimental scaled model system is constructed. In order to examine the validity of the proposed method for realistic human models, we discuss the pros and cons of measurements and nume...

  7. Estimation of oil reservoir thermal properties through temperature log data using inversion method

    International Nuclear Information System (INIS)

    Cheng, Wen-Long; Nian, Yong-Le; Li, Tong-Tong; Wang, Chang-Long

    2013-01-01

    Oil reservoir thermal properties not only play an important role in steam injection well heat transfer, but also are the basic parameters for evaluating the oil saturation in reservoir. In this study, for estimating reservoir thermal properties, a novel heat and mass transfer model of steam injection well was established at first, this model made full analysis on the wellbore-reservoir heat and mass transfer as well as the wellbore-formation, and the simulated results by the model were quite consistent with the log data. Then this study presented an effective inversion method for estimating the reservoir thermal properties through temperature log data. This method is based on the heat transfer model in steam injection wells, and can be used to predict the thermal properties as a stochastic approximation method. The inversion method was applied to estimate the reservoir thermal properties of two steam injection wells, it was found that the relative error of thermal conductivity for the two wells were 2.9% and 6.5%, and the relative error of volumetric specific heat capacity were 6.7% and 7.0%,which demonstrated the feasibility of the proposed method for estimating the reservoir thermal properties. - Highlights: • An effective inversion method for predicting the oil reservoir thermal properties was presented. • A novel model for steam injection well made full study on the wellbore-reservoir heat and mass transfer. • The wellbore temperature field and steam parameters can be simulated by the model efficiently. • Both reservoirs and formation thermal properties could be estimated simultaneously by the proposed method. • The estimated steam temperature was quite consistent with the field data

  8. portfolio optimization based on nonparametric estimation methods

    Directory of Open Access Journals (Sweden)

    mahsa ghandehari

    2017-03-01

    Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.

  9. 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...

  10. Application of model-based and knowledge-based measuring methods as analytical redundancy

    International Nuclear Information System (INIS)

    Hampel, R.; Kaestner, W.; Chaker, N.; Vandreier, B.

    1997-01-01

    The safe operation of nuclear power plants requires the application of modern and intelligent methods of signal processing for the normal operation as well as for the management of accident conditions. Such modern and intelligent methods are model-based and knowledge-based ones being founded on analytical knowledge (mathematical models) as well as experiences (fuzzy information). In addition to the existing hardware redundancies analytical redundancies will be established with the help of these modern methods. These analytical redundancies support the operating staff during the decision-making. The design of a hybrid model-based and knowledge-based measuring method will be demonstrated by the example of a fuzzy-supported observer. Within the fuzzy-supported observer a classical linear observer is connected with a fuzzy-supported adaptation of the model matrices of the observer model. This application is realized for the estimation of the non-measurable variables as steam content and mixture level within pressure vessels with water-steam mixture during accidental depressurizations. For this example the existing non-linearities will be classified and the verification of the model will be explained. The advantages of the hybrid method in comparison to the classical model-based measuring methods will be demonstrated by the results of estimation. The consideration of the parameters which have an important influence on the non-linearities requires the inclusion of high-dimensional structures of fuzzy logic within the model-based measuring methods. Therefore methods will be presented which allow the conversion of these high-dimensional structures to two-dimensional structures of fuzzy logic. As an efficient solution of this problem a method based on cascaded fuzzy controllers will be presented. (author). 2 refs, 12 figs, 5 tabs

  11. Estimation of structural film viscosity based on the bubble rise method in a nanofluid.

    Science.gov (United States)

    Cho, Heon Ki; Nikolov, Alex D; Wasan, Darsh T

    2018-04-15

    When a single bubble moves at a very low capillary number (10 -7 ) through a liquid with dispersed nanoparticles (nanofluid) inside a vertical tube/capillary, a film is formed between the bubble surface and the tube wall and the nanoparticles self-layer inside the confined film. We measured the film thickness using reflected light interferometry. We calculated the film structural energy isotherm vs. the film thickness from the film-meniscus contact angle measurements using the reflected light interferometric method. Based on the experimental measurement of the film thickness and the calculated values of the film structural energy barrier, we estimated the structural film viscosity vs. the film thickness using the Frenkel approach. Because of the nanoparticle film self-layering phenomenon, we observed a gradual increase in the film viscosity with the decreasing film thickness. However, we observed a significant increase in the film viscosity accompanied by a step-wise decrease in the bubble velocity when the film thickness decreased from 3 to 2 particle layers due to the structural transition in the film. Copyright © 2018 Elsevier Inc. All rights reserved.

  12. Estimation of Bouguer Density Precision: Development of Method for Analysis of La Soufriere Volcano Gravity Data

    OpenAIRE

    Gunawan, Hendra; Micheldiament, Micheldiament; Mikhailov, Valentin

    2008-01-01

    http://dx.doi.org/10.17014/ijog.vol3no3.20084The precision of topographic density (Bouguer density) estimation by the Nettleton approach is based on a minimum correlation of Bouguer gravity anomaly and topography. The other method, the Parasnis approach, is based on a minimum correlation of Bouguer gravity anomaly and Bouguer correction. The precision of Bouguer density estimates was investigated by both methods on simple 2D syntetic models and under an assumption free-air anomaly consisting ...

  13. An applicable method for efficiency estimation of operating tray distillation columns and its comparison with the methods utilized in HYSYS and Aspen Plus

    Science.gov (United States)

    Sadeghifar, Hamidreza

    2015-10-01

    Developing general methods that rely on column data for the efficiency estimation of operating (existing) distillation columns has been overlooked in the literature. Most of the available methods are based on empirical mass transfer and hydraulic relations correlated to laboratory data. Therefore, these methods may not be sufficiently accurate when applied to industrial columns. In this paper, an applicable and accurate method was developed for the efficiency estimation of distillation columns filled with trays. This method can calculate efficiency as well as mass and heat transfer coefficients without using any empirical mass transfer or hydraulic correlations and without the need to estimate operational or hydraulic parameters of the column. E.g., the method does not need to estimate tray interfacial area, which can be its most important advantage over all the available methods. The method can be used for the efficiency prediction of any trays in distillation columns. For the efficiency calculation, the method employs the column data and uses the true rates of the mass and heat transfers occurring inside the operating column. It is highly emphasized that estimating efficiency of an operating column has to be distinguished from that of a column being designed.

  14. The use of maturity method in estimating concrete strength

    International Nuclear Information System (INIS)

    Salama, A.E.; Abd El-Baky, S.M.; Ali, E.E.; Ghanem, G.M.

    2005-01-01

    Prediction of the early age strength of concrete is essential for modernized concrete for construction as well as for manufacturing of structural parts. Safe and economic scheduling of such critical operations as form removal and re shoring, application of post-tensioning or other mechanical treatment, and in process transportation and rapid delivery of products all should be based upon a good grasp of the strength development of the concrete in use. For many years, it has been proposed that the strength of concrete can be related to a simple mathematical function of time and temperature so that strength could be assessed by calculation without mechanical testing. Such functions are used to compute what is called the m aturity o f concrete, and the computed value is believed to obtain a correlation with the strength of concrete. With its simplicity and low cost, the application of maturity concept as in situ testing method has received wide attention and found its use in engineering practice. This research work investigates the use of M aturity method' in estimating the concrete strength. An experimental program is designed to estimate the concrete strength by using the maturity method. Using different concrete mixes, with available local materials. Ordinary Portland Cement, crushed stone, silica fume, fly ash and admixtures with different contents are used . All the specimens were exposed to different curing temperatures (10, 25 and 40 degree C), in order to get a simplified expression of maturity that fits in with the influence of temperature. Mix designs and charts obtained from this research can be used as guide information for estimating concrete strength by using the maturity method

  15. 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

  16. A method for estimation of fatigue properties from hardness of materials through construction of expert system

    International Nuclear Information System (INIS)

    Jeon, Woo Soo; Song, Ji Ho

    2001-01-01

    An expert system for estimation of fatigue properties from simple tensile data of material is developed, considering nearly all important estimation methods proposed so far, i.e., 7 estimation methods. The expert system is developed to utilize for the case of only hardness data available. The knowledge base is constructed with production rules and frames using an expert system shell, UNIK. Forward chaining is employed as a reasoning method. The expert system has three functions including the function to update the knowledge base. The performance of the expert system is tested using the 54 ε-N curves consisting of 381 ε-N data points obtained for 22 materials. It is found that the expert system developed has excellent performance especially for steel materials, and reasonably good for aluminum alloys

  17. 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.

  18. Matrix-based system reliability method and applications to bridge networks

    International Nuclear Information System (INIS)

    Kang, W.-H.; Song Junho; Gardoni, Paolo

    2008-01-01

    Using a matrix-based system reliability (MSR) method, one can estimate the probabilities of complex system events by simple matrix calculations. Unlike existing system reliability methods whose complexity depends highly on that of the system event, the MSR method describes any general system event in a simple matrix form and therefore provides a more convenient way of handling the system event and estimating its probability. Even in the case where one has incomplete information on the component probabilities and/or the statistical dependence thereof, the matrix-based framework enables us to estimate the narrowest bounds on the system failure probability by linear programming. This paper presents the MSR method and applies it to a transportation network consisting of bridge structures. The seismic failure probabilities of bridges are estimated by use of the predictive fragility curves developed by a Bayesian methodology based on experimental data and existing deterministic models of the seismic capacity and demand. Using the MSR method, the probability of disconnection between each city/county and a critical facility is estimated. The probability mass function of the number of failed bridges is computed as well. In order to quantify the relative importance of bridges, the MSR method is used to compute the conditional probabilities of bridge failures given that there is at least one city disconnected from the critical facility. The bounds on the probability of disconnection are also obtained for cases with incomplete information

  19. Reliability estimation of safety-critical software-based systems using Bayesian networks

    International Nuclear Information System (INIS)

    Helminen, A.

    2001-06-01

    Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of software-based safety-critical automation systems in nuclear power plants. In the research project 'Programmable automation system safety integrity assessment (PASSI)', belonging to the Finnish Nuclear Safety Research Programme (FINNUS, 1999-2002), various safety assessment methods and tools for software based systems are developed and evaluated. The project is financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT). In this report the applicability of Bayesian networks to the reliability estimation of software-based systems is studied. The applicability is evaluated by building Bayesian network models for the systems of interest and performing simulations for these models. In the simulations hypothetical evidence is used for defining the parameter relations and for determining the ability to compensate disparate evidence in the models. Based on the experiences from modelling and simulations we are able to conclude that Bayesian networks provide a good method for the reliability estimation of software-based systems. (orig.)

  20. 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.

  1. A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects.

    Science.gov (United States)

    Boyd, James H; Guiver, Tenniel; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Anderson, Phil; Dickinson, Teresa

    2016-05-17

    Record linkage techniques allow different data collections to be brought together to provide a wider picture of the health status of individuals. Ensuring high linkage quality is important to guarantee the quality and integrity of research. Current methods for measuring linkage quality typically focus on precision (the proportion of incorrect links), given the difficulty of measuring the proportion of false negatives. The aim of this work is to introduce and evaluate a sampling based method to estimate both precision and recall following record linkage. In the sampling based method, record-pairs from each threshold (including those below the identified cut-off for acceptance) are sampled and clerically reviewed. These results are then applied to the entire set of record-pairs, providing estimates of false positives and false negatives. This method was evaluated on a synthetically generated dataset, where the true match status (which records belonged to the same person) was known. The sampled estimates of linkage quality were relatively close to actual linkage quality metrics calculated for the whole synthetic dataset. The precision and recall measures for seven reviewers were very consistent with little variation in the clerical assessment results (overall agreement using the Fleiss Kappa statistics was 0.601). This method presents as a possible means of accurately estimating matching quality and refining linkages in population level linkage studies. The sampling approach is especially important for large project linkages where the number of record pairs produced may be very large often running into millions.

  2. Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms.

    Science.gov (United States)

    Liu, Quan; Vo-Dinh, Tuan

    2009-10-01

    Hemoglobin concentration and oxygenation in tissue are important biomarkers that are useful in both research and clinical diagnostics of a wide variety of diseases such as cancer. The authors aim to develop simple ratiometric method based on the spectral filtering modulation (SFM) of fluorescence spectra to estimate the total hemoglobin concentration and oxygenation in tissue using only a single fluorescence emission spectrum, which will eliminate the need of diffuse reflectance measurements and prolonged data processing as required by most current methods, thus enabling rapid clinical measurements. The proposed method consists of two steps. In the first step, the total hemoglobin concentration is determined by comparing a ratio of fluorescence intensities at two emission wavelengths to a calibration curve. The second step is to estimate oxygen saturation by comparing a double ratio that involves three emission wavelengths to another calibration curve that is a function of oxygen saturation for known total hemoglobin concentration. Theoretical derivation shows that the ratio in the first step is linearly proportional to the total hemoglobin concentrations and the double ratio in the second step is related to both total hemoglobin concentration and hemoglobin oxygenation for the chosen fiber-optic probe geometry. Experiments on synthetic fluorescent tissue phantoms, which included hemoglobin with both constant and varying oxygenation as the absorber, polystyrene spheres as scatterers, and flavin adenine dinucleotide as the fluorophore, were carried out to validate the theoretical prediction. Tissue phantom experiments confirm that the ratio in the first step is linearly proportional to the total hemoglobin concentration and the double ratio in the second step is related to both total hemoglobin concentrations and hemoglobin oxygenation. Furthermore, the relations between the two ratios and the total hemoglobin concentration and hemoglobin oxygenation are insensitive

  3. 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.

  4. Three methods for estimating a range of vehicular interactions

    Science.gov (United States)

    Krbálek, Milan; Apeltauer, Jiří; Apeltauer, Tomáš; Szabová, Zuzana

    2018-02-01

    We present three different approaches how to estimate the number of preceding cars influencing a decision-making procedure of a given driver moving in saturated traffic flows. The first method is based on correlation analysis, the second one evaluates (quantitatively) deviations from the main assumption in the convolution theorem for probability, and the third one operates with advanced instruments of the theory of counting processes (statistical rigidity). We demonstrate that universally-accepted premise on short-ranged traffic interactions may not be correct. All methods introduced have revealed that minimum number of actively-followed vehicles is two. It supports an actual idea that vehicular interactions are, in fact, middle-ranged. Furthermore, consistency between the estimations used is surprisingly credible. In all cases we have found that the interaction range (the number of actively-followed vehicles) drops with traffic density. Whereas drivers moving in congested regimes with lower density (around 30 vehicles per kilometer) react on four or five neighbors, drivers moving in high-density flows respond to two predecessors only.

  5. Estimation methods for nonlinear state-space models in ecology

    DEFF Research Database (Denmark)

    Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

    2011-01-01

    The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

  6. Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

    Science.gov (United States)

    Liou, Jyun-you; Smith, Elliot H.; Bateman, Lisa M.; McKhann, Guy M., II; Goodman, Robert R.; Greger, Bradley; Davis, Tyler S.; Kellis, Spencer S.; House, Paul A.; Schevon, Catherine A.

    2017-08-01

    Objective. Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking. Approach. We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing. Main results. Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators. Significance. Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically

  7. A comparison of short-term dispersion estimates resulting from various atmospheric stability classification methods

    International Nuclear Information System (INIS)

    Mitchell, A.E. Jr.

    1982-01-01

    Four methods of classifying atmospheric stability class are applied at four sites to make short-term (1-h) dispersion estimates from a ground-level source based on a model consistent with U.S. Nuclear Regulatory Commission practice. The classification methods include vertical temperature gradient, standard deviation of horizontal wind direction fluctuations (sigma theta), Pasquill-Turner, and modified sigma theta which accounts for meander. Results indicate that modified sigma theta yields reasonable dispersion estimates compared to those produced using methods of vertical temperature gradient and Pasquill-Turner, and can be considered as a potential economic alternative in establishing onsite monitoring programs. (author)

  8. A Web-Based Model to Estimate the Impact of Best Management Practices

    Directory of Open Access Journals (Sweden)

    Youn Shik Park

    2014-03-01

    Full Text Available The Spreadsheet Tool for the Estimation of Pollutant Load (STEPL can be used for Total Maximum Daily Load (TMDL processes, since the model is capable of simulating the impacts of various best management practices (BMPs and low impact development (LID practices. The model computes average annual direct runoff using the Soil Conservation Service Curve Number (SCS-CN method with average rainfall per event, which is not a typical use of the SCS-CN method. Five SCS-CN-based approaches to compute average annual direct runoff were investigated to explore estimated differences in average annual direct runoff computations using daily precipitation data collected from the National Climate Data Center and generated by the CLIGEN model for twelve stations in Indiana. Compared to the average annual direct runoff computed for the typical use of the SCS-CN method, the approaches to estimate average annual direct runoff within EPA STEPL showed large differences. A web-based model (STEPL WEB was developed with a corrected approach to estimate average annual direct runoff. Moreover, the model was integrated with the Web-based Load Duration Curve Tool, which identifies the least cost BMPs for each land use and optimizes BMP selection to identify the most cost-effective BMP implementations. The integrated tools provide an easy to use approach for performing TMDL analysis and identifying cost-effective approaches for controlling nonpoint source pollution.

  9. The Pose Estimation of Mobile Robot Based on Improved Point Cloud Registration

    Directory of Open Access Journals (Sweden)

    Yanzi Miao

    2016-03-01

    Full Text Available Due to GPS restrictions, an inertial sensor is usually used to estimate the location of indoor mobile robots. However, it is difficult to achieve high-accuracy localization and control by inertial sensors alone. In this paper, a new method is proposed to estimate an indoor mobile robot pose with six degrees of freedom based on an improved 3D-Normal Distributions Transform algorithm (3D-NDT. First, point cloud data are captured by a Kinect sensor and segmented according to the distance to the robot. After the segmentation, the input point cloud data are processed by the Approximate Voxel Grid Filter algorithm in different sized voxel grids. Second, the initial registration and precise registration are performed respectively according to the distance to the sensor. The most distant point cloud data use the 3D-Normal Distributions Transform algorithm (3D-NDT with large-sized voxel grids for initial registration, based on the transformation matrix from the odometry method. The closest point cloud data use the 3D-NDT algorithm with small-sized voxel grids for precise registration. After the registrations above, a final transformation matrix is obtained and coordinated. Based on this transformation matrix, the pose estimation problem of the indoor mobile robot is solved. Test results show that this method can obtain accurate robot pose estimation and has better robustness.

  10. A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum

    Directory of Open Access Journals (Sweden)

    Pan Liu

    2017-05-01

    Full Text Available This paper presents a wavelet-based Gaussian method (WGM for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF. The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.

  11. A general framework and review of scatter correction methods in cone beam CT. Part 2: Scatter estimation approaches

    International Nuclear Information System (INIS)

    Ruehrnschopf and, Ernst-Peter; Klingenbeck, Klaus

    2011-01-01

    The main components of scatter correction procedures are scatter estimation and a scatter compensation algorithm. This paper completes a previous paper where a general framework for scatter compensation was presented under the prerequisite that a scatter estimation method is already available. In the current paper, the authors give a systematic review of the variety of scatter estimation approaches. Scatter estimation methods are based on measurements, mathematical-physical models, or combinations of both. For completeness they present an overview of measurement-based methods, but the main topic is the theoretically more demanding models, as analytical, Monte-Carlo, and hybrid models. Further classifications are 3D image-based and 2D projection-based approaches. The authors present a system-theoretic framework, which allows to proceed top-down from a general 3D formulation, by successive approximations, to efficient 2D approaches. A widely useful method is the beam-scatter-kernel superposition approach. Together with the review of standard methods, the authors discuss their limitations and how to take into account the issues of object dependency, spatial variance, deformation of scatter kernels, external and internal absorbers. Open questions for further investigations are indicated. Finally, the authors refer on some special issues and applications, such as bow-tie filter, offset detector, truncated data, and dual-source CT.

  12. Dispersion curve estimation via a spatial covariance method with ultrasonic wavefield imaging.

    Science.gov (United States)

    Chong, See Yenn; Todd, Michael D

    2018-05-01

    Numerous Lamb wave dispersion curve estimation methods have been developed to support damage detection and localization strategies in non-destructive evaluation/structural health monitoring (NDE/SHM) applications. In this paper, the covariance matrix is used to extract features from an ultrasonic wavefield imaging (UWI) scan in order to estimate the phase and group velocities of S0 and A0 modes. A laser ultrasonic interrogation method based on a Q-switched laser scanning system was used to interrogate full-field ultrasonic signals in a 2-mm aluminum plate at five different frequencies. These full-field ultrasonic signals were processed in three-dimensional space-time domain. Then, the time-dependent covariance matrices of the UWI were obtained based on the vector variables in Cartesian and polar coordinate spaces for all time samples. A spatial covariance map was constructed to show spatial correlations within the full wavefield. It was observed that the variances may be used as a feature for S0 and A0 mode properties. The phase velocity and the group velocity were found using a variance map and an enveloped variance map, respectively, at five different frequencies. This facilitated the estimation of Lamb wave dispersion curves. The estimated dispersion curves of the S0 and A0 modes showed good agreement with the theoretical dispersion curves. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone

    Directory of Open Access Journals (Sweden)

    Rifat Zaman

    2017-02-01

    Full Text Available We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.

  14. Multiuser Carrier Frequency Offset Estimation for OFDMA Uplink Based on Multi-Antenna

    Science.gov (United States)

    Zhang, Weile; Wang, Junsong; Yin, Qinye; Feng, Ang

    In this letter, a novel method is proposed for carrier-frequency offset (CFO) estimation for multiple users in orthogonal frequency division multiple access (OFDMA) uplink with the generalized carrier assignment scheme (GCAS). The base station (BS) is equipped with multiple antennas, and each user's CFO can be estimated by the ESPRIT-like method that utilizes the rotation invariance of the space-domain snapshot matrix. The method is still effective even in fully loaded system with all subcarriers allocated to users. Simulation results illustrate the high performance of the proposed algorithm.

  15. Experimental study on the plant state estimation for the condition-based maintenance

    International Nuclear Information System (INIS)

    Harada, J. I.; Takahashi, M.; Kitamura, M.; Wakabayashi, T.

    2006-01-01

    A framework of maintenance support system based on the plant state estimation using diverse methods has been proposed and the validity of the plant state estimation methods has been experimentally evaluated. The focus has been set on the construction of the BN for the objective system with the scale and complexity as same as real world systems. Another focus has been set on the other functions for maintenance support system such as signal processing tool and similarity matching. The validity of the proposed inference method has been confirmed through numerical experiments. (authors)

  16. Bin mode estimation methods for Compton camera imaging

    International Nuclear Information System (INIS)

    Ikeda, S.; Odaka, H.; Uemura, M.; Takahashi, T.; Watanabe, S.; Takeda, S.

    2014-01-01

    We study the image reconstruction problem of a Compton camera which consists of semiconductor detectors. The image reconstruction is formulated as a statistical estimation problem. We employ a bin-mode estimation (BME) and extend an existing framework to a Compton camera with multiple scatterers and absorbers. Two estimation algorithms are proposed: an accelerated EM algorithm for the maximum likelihood estimation (MLE) and a modified EM algorithm for the maximum a posteriori (MAP) estimation. Numerical simulations demonstrate the potential of the proposed methods

  17. Methods for the estimation of uranium ore reserves

    International Nuclear Information System (INIS)

    1985-01-01

    The Manual is designed mainly to provide assistance in uranium ore reserve estimation methods to mining engineers and geologists with limited experience in estimating reserves, especially to those working in developing countries. This Manual deals with the general principles of evaluation of metalliferous deposits but also takes into account the radioactivity of uranium ores. The methods presented have been generally accepted in the international uranium industry

  18. A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

    Science.gov (United States)

    Liu, Huawei; Li, Baoqing; Yuan, Xiaobing; Zhou, Qianwei; Huang, Jingchang

    2018-03-27

    Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.

  19. Drogue pose estimation for unmanned aerial vehicle autonomous aerial refueling system based on infrared vision sensor

    Science.gov (United States)

    Chen, Shanjun; Duan, Haibin; Deng, Yimin; Li, Cong; Zhao, Guozhi; Xu, Yan

    2017-12-01

    Autonomous aerial refueling is a significant technology that can significantly extend the endurance of unmanned aerial vehicles. A reliable method that can accurately estimate the position and attitude of the probe relative to the drogue is the key to such a capability. A drogue pose estimation method based on infrared vision sensor is introduced with the general goal of yielding an accurate and reliable drogue state estimate. First, by employing direct least squares ellipse fitting and convex hull in OpenCV, a feature point matching and interference point elimination method is proposed. In addition, considering the conditions that some infrared LEDs are damaged or occluded, a missing point estimation method based on perspective transformation and affine transformation is designed. Finally, an accurate and robust pose estimation algorithm improved by the runner-root algorithm is proposed. The feasibility of the designed visual measurement system is demonstrated by flight test, and the results indicate that our proposed method enables precise and reliable pose estimation of the probe relative to the drogue, even in some poor conditions.

  20. 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.