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)
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.
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.
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.
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.
Accurate position estimation methods based on electrical impedance tomography measurements
Vergara, Samuel; Sbarbaro, Daniel; Johansen, T. A.
2017-08-01
Electrical impedance tomography (EIT) is a technology that estimates the electrical properties of a body or a cross section. Its main advantages are its non-invasiveness, low cost and operation free of radiation. The estimation of the conductivity field leads to low resolution images compared with other technologies, and high computational cost. However, in many applications the target information lies in a low intrinsic dimensionality of the conductivity field. The estimation of this low-dimensional information is addressed in this work. It proposes optimization-based and data-driven approaches for estimating this low-dimensional information. The accuracy of the results obtained with these approaches depends on modelling and experimental conditions. Optimization approaches are sensitive to model discretization, type of cost function and searching algorithms. Data-driven methods are sensitive to the assumed model structure and the data set used for parameter estimation. The system configuration and experimental conditions, such as number of electrodes and signal-to-noise ratio (SNR), also have an impact on the results. In order to illustrate the effects of all these factors, the position estimation of a circular anomaly is addressed. Optimization methods based on weighted error cost functions and derivate-free optimization algorithms provided the best results. Data-driven approaches based on linear models provided, in this case, good estimates, but the use of nonlinear models enhanced the estimation accuracy. The results obtained by optimization-based algorithms were less sensitive to experimental conditions, such as number of electrodes and SNR, than data-driven approaches. Position estimation mean squared errors for simulation and experimental conditions were more than twice for the optimization-based approaches compared with the data-driven ones. The experimental position estimation mean squared error of the data-driven models using a 16-electrode setup was less
The Software Cost Estimation Method Based on Fuzzy Ontology
Directory of Open Access Journals (Sweden)
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.
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...
Power system frequency estimation based on an orthogonal decomposition method
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.
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
An automatic iris occlusion estimation method based on high-dimensional density estimation.
Li, Yung-Hui; Savvides, Marios
2013-04-01
Iris masks play an important role in iris recognition. They indicate which part of the iris texture map is useful and which part is occluded or contaminated by noisy image artifacts such as eyelashes, eyelids, eyeglasses frames, and specular reflections. The accuracy of the iris mask is extremely important. The performance of the iris recognition system will decrease dramatically when the iris mask is inaccurate, even when the best recognition algorithm is used. Traditionally, people used the rule-based algorithms to estimate iris masks from iris images. However, the accuracy of the iris masks generated this way is questionable. In this work, we propose to use Figueiredo and Jain's Gaussian Mixture Models (FJ-GMMs) to model the underlying probabilistic distributions of both valid and invalid regions on iris images. We also explored possible features and found that Gabor Filter Bank (GFB) provides the most discriminative information for our goal. Finally, we applied Simulated Annealing (SA) technique to optimize the parameters of GFB in order to achieve the best recognition rate. Experimental results show that the masks generated by the proposed algorithm increase the iris recognition rate on both ICE2 and UBIRIS dataset, verifying the effectiveness and importance of our proposed method for iris occlusion estimation.
Improvement of Accuracy for Background Noise Estimation Method Based on TPE-AE
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.
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.
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)
Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity
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
A fast pulse phase estimation method for X-ray pulsar signals based on epoch folding
Directory of Open Access Journals (Sweden)
Xue Mengfan
2016-06-01
Full Text Available X-ray pulsar-based navigation (XPNAV is an attractive method for autonomous deep-space navigation in the future. The pulse phase estimation is a key task in XPNAV and its accuracy directly determines the navigation accuracy. State-of-the-art pulse phase estimation techniques either suffer from poor estimation accuracy, or involve the maximization of generally non-convex object function, thus resulting in a large computational cost. In this paper, a fast pulse phase estimation method based on epoch folding is presented. The statistical properties of the observed profile obtained through epoch folding are developed. Based on this, we recognize the joint probability distribution of the observed profile as the likelihood function and utilize a fast Fourier transform-based procedure to estimate the pulse phase. Computational complexity of the proposed estimator is analyzed as well. Experimental results show that the proposed estimator significantly outperforms the currently used cross-correlation (CC and nonlinear least squares (NLS estimators, while significantly reduces the computational complexity compared with NLS and maximum likelihood (ML estimators.
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
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.
Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries
Directory of Open Access Journals (Sweden)
Zhongyue Zou
2014-08-01
Full Text Available Four model-based State of Charge (SOC estimation methods for lithium-ion (Li-ion batteries are studied and evaluated in this paper. Different from existing literatures, this work evaluates different aspects of the SOC estimation, such as the estimation error distribution, the estimation rise time, the estimation time consumption, etc. The equivalent model of the battery is introduced and the state function of the model is deduced. The four model-based SOC estimation methods are analyzed first. Simulations and experiments are then established to evaluate the four methods. The urban dynamometer driving schedule (UDDS current profiles are applied to simulate the drive situations of an electrified vehicle, and a genetic algorithm is utilized to identify the model parameters to find the optimal parameters of the model of the Li-ion battery. The simulations with and without disturbance are carried out and the results are analyzed. A battery test workbench is established and a Li-ion battery is applied to test the hardware in a loop experiment. Experimental results are plotted and analyzed according to the four aspects to evaluate the four model-based SOC estimation methods.
A 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...
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.
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
Estimation of the flow resistances exerted in coronary arteries using a vessel length-based method.
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.
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...
A numerical integration-based yield estimation method for integrated circuits
International Nuclear Information System (INIS)
Liang Tao; Jia Xinzhang
2011-01-01
A novel integration-based yield estimation method is developed for yield optimization of integrated circuits. This method tries to integrate the joint probability density function on the acceptability region directly. To achieve this goal, the simulated performance data of unknown distribution should be converted to follow a multivariate normal distribution by using Box-Cox transformation (BCT). In order to reduce the estimation variances of the model parameters of the density function, orthogonal array-based modified Latin hypercube sampling (OA-MLHS) is presented to generate samples in the disturbance space during simulations. The principle of variance reduction of model parameters estimation through OA-MLHS together with BCT is also discussed. Two yield estimation examples, a fourth-order OTA-C filter and a three-dimensional (3D) quadratic function are used for comparison of our method with Monte Carlo based methods including Latin hypercube sampling and importance sampling under several combinations of sample sizes and yield values. Extensive simulations show that our method is superior to other methods with respect to accuracy and efficiency under all of the given cases. Therefore, our method is more suitable for parametric yield optimization. (semiconductor integrated circuits)
A numerical integration-based yield estimation method for integrated circuits
Energy Technology Data Exchange (ETDEWEB)
Liang Tao; Jia Xinzhang, E-mail: tliang@yahoo.cn [Key Laboratory of Ministry of Education for Wide Bandgap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi' an 710071 (China)
2011-04-15
A novel integration-based yield estimation method is developed for yield optimization of integrated circuits. This method tries to integrate the joint probability density function on the acceptability region directly. To achieve this goal, the simulated performance data of unknown distribution should be converted to follow a multivariate normal distribution by using Box-Cox transformation (BCT). In order to reduce the estimation variances of the model parameters of the density function, orthogonal array-based modified Latin hypercube sampling (OA-MLHS) is presented to generate samples in the disturbance space during simulations. The principle of variance reduction of model parameters estimation through OA-MLHS together with BCT is also discussed. Two yield estimation examples, a fourth-order OTA-C filter and a three-dimensional (3D) quadratic function are used for comparison of our method with Monte Carlo based methods including Latin hypercube sampling and importance sampling under several combinations of sample sizes and yield values. Extensive simulations show that our method is superior to other methods with respect to accuracy and efficiency under all of the given cases. Therefore, our method is more suitable for parametric yield optimization. (semiconductor integrated circuits)
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)
Reliability analysis based on a novel density estimation method for structures with correlations
Directory of Open Access Journals (Sweden)
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.
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.
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.
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
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.
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.
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.
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 Ã¢Â€ÂœbiasedÃ¢Â€Â or Ã¢Â€ÂœunbiasedÃ¢Â€Â 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.
A Copula-Based Method for Estimating Shear Strength Parameters of Rock Mass
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Da Huang
2014-01-01
Full Text Available The shear strength parameters (i.e., the internal friction coefficient f and cohesion c are very important in rock engineering, especially for the stability analysis and reinforcement design of slopes and underground caverns. In this paper, a probabilistic method, Copula-based method, is proposed for estimating the shear strength parameters of rock mass. The optimal Copula functions between rock mass quality Q and f, Q and c for the marbles are established based on the correlation analyses of the results of 12 sets of in situ tests in the exploration adits of Jinping I-Stage Hydropower Station. Although the Copula functions are derived from the in situ tests for the marbles, they can be extended to be applied to other types of rock mass with similar geological and mechanical properties. For another 9 sets of in situ tests as an extensional application, by comparison with the results from Hoek-Brown criterion, the estimated values of f and c from the Copula-based method achieve better accuracy. Therefore, the proposed Copula-based method is an effective tool in estimating rock strength parameters.
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)
Inertial sensor-based methods in walking speed estimation: a systematic review.
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.
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.
A new anisotropic mesh adaptation method based upon hierarchical a posteriori error estimates
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.
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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.
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...
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.
Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity.
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.
Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods
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...
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.
A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles
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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.
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.
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.
A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks.
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.
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.
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.
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.
Data Based Parameter Estimation Method for Circular-scanning SAR Imaging
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Chen Gong-bo
2013-06-01
Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.
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.
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.
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....
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.
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
Yield Estimation of Sugar Beet Based on Plant Canopy Using Machine Vision Methods
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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
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.
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)
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.
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.
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.
Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods
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.
Institute of Scientific and Technical Information of China (English)
无
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.
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.
A citizen science based survey method for estimating the density of urban carnivores
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
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.
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
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
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...
Removing damped sinusoidal vibrations in adaptive optics systems using a DFT-based estimation method
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.
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.
Research on an estimation method of DOA for wireless location based on TD-SCDMA
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 .
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.
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.
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.
[Cardiac Synchronization Function Estimation Based on ASM Level Set Segmentation Method].
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.
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.
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
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.
Developing an objective evaluation method to estimate diabetes risk in community-based settings.
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.
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.
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
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.
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.
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...
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....
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.
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
A Low-Complexity ESPRIT-Based DOA Estimation Method for Co-Prime Linear Arrays.
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.
Estimation of Runoff for Ozat Catchment using RS and GIS Based SCS-CN Method
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...
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
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.
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...
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
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.
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.
An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging
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.
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.
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.
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.
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.
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.
Ge, Xinmin; Fan, Yiren; Liu, Jianyu; Zhang, Li; Han, Yujiao; Xing, Donghui
2017-10-01
Permeability is an important parameter in formation evaluation since it controls the fluid transportation of porous rocks. However, it is challengeable to compute the permeability of bioclastic limestone reservoirs by conventional methods linking petrophysical and geophysical data, due to the complex pore distributions. A new method is presented to estimate the permeability based on laboratory and downhole nuclear magnetic resonance (NMR) measurements. We divide the pore space into four intervals by the inflection points between the pore radius and the transversal relaxation time. Relationships between permeability and percentages of different pore intervals are investigated to investigate influential factors on the fluid transportation. Furthermore, an empirical model, which takes into account of the pore size distributions, is presented to compute the permeability. 212 core samples in our case show that the accuracy of permeability calculation is improved from 0.542 (SDR model), 0.507 (TIM model), 0.455 (conventional porosity-permeability regressions) to 0.803. To enhance the precision of downhole application of the new model, we developed a fluid correction algorithm to construct the water spectrum of in-situ NMR data, aiming to eliminate the influence of oil on the magnetization. The result reveals that permeability is positively correlated with percentages of mega-pores and macro-pores, but negatively correlated with the percentage of micro-pores. Poor correlation is observed between permeability and the percentage of meso-pores. NMR magnetizations and T 2 spectrums after the fluid correction agree well with laboratory results for samples saturated with water. Field application indicates that the improved method provides better performance than conventional models such as Schlumberger-Doll Research equation, Timur-Coates equation, and porosity-permeability regressions. Copyright © 2017 Elsevier Inc. All rights reserved.
Ge, Xinmin; Fan, Yiren; Liu, Jianyu; Zhang, Li; Han, Yujiao; Xing, Donghui
2017-10-01
Permeability is an important parameter in formation evaluation since it controls the fluid transportation of porous rocks. However, it is challengeable to compute the permeability of bioclastic limestone reservoirs by conventional methods linking petrophysical and geophysical data, due to the complex pore distributions. A new method is presented to estimate the permeability based on laboratory and downhole nuclear magnetic resonance (NMR) measurements. We divide the pore space into four intervals by the inflection points between the pore radius and the transversal relaxation time. Relationships between permeability and percentages of different pore intervals are investigated to investigate influential factors on the fluid transportation. Furthermore, an empirical model, which takes into account of the pore size distributions, is presented to compute the permeability. 212 core samples in our case show that the accuracy of permeability calculation is improved from 0.542 (SDR model), 0.507 (TIM model), 0.455 (conventional porosity-permeability regressions) to 0.803. To enhance the precision of downhole application of the new model, we developed a fluid correction algorithm to construct the water spectrum of in-situ NMR data, aiming to eliminate the influence of oil on the magnetization. The result reveals that permeability is positively correlated with percentages of mega-pores and macro-pores, but negatively correlated with the percentage of micro-pores. Poor correlation is observed between permeability and the percentage of meso-pores. NMR magnetizations and T2 spectrums after the fluid correction agree well with laboratory results for samples saturated with water. Field application indicates that the improved method provides better performance than conventional models such as Schlumberger-Doll Research equation, Timur-Coates equation, and porosity-permeability regressions.
Institute of Scientific and Technical Information of China (English)
无
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.
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...
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
Estimation of structural film viscosity based on the bubble rise method in a nanofluid.
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.
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.
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)
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...
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.
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.
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.
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.
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.
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.
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.
A robust method for estimating motorbike count based on visual information learning
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.
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
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.
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.
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.
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.
Toma-Danila, Dragos; Florinela Manea, Elena; Ortanza Cioflan, Carmen
2014-05-01
Bucharest, capital of Romania (with 1678000 inhabitants in 2011), is one of the most exposed big cities in Europe to seismic damage. The major earthquakes affecting the city have their origin in the Vrancea region. The Vrancea intermediate-depth source generates, statistically, 2-3 shocks with moment magnitude >7.0 per century. Although the focal distance is greater than 170 km, the historical records (from the 1838, 1894, 1908, 1940 and 1977 events) reveal severe effects in the Bucharest area, e.g. intensities IX (MSK) for the case of 1940 event. During the 1977 earthquake, 1420 people were killed and 33 large buildings collapsed. The nowadays building stock is vulnerable both due to construction (material, age) and soil conditions (high amplification, generated within the weak consolidated Quaternary deposits, their thickness is varying 250-500m throughout the city). A number of 373 old buildings, out of 2563, evaluated by experts are more likely to experience severe damage/collapse in the next major earthquake. The total number of residential buildings, in 2011, was 113900. In order to guide the mitigation measures, different studies tried to estimate the seismic risk of Bucharest, in terms of buildings, population or economic damage probability. Unfortunately, most of them were based on incomplete sets of data, whether regarding the hazard or the building stock in detail. However, during the DACEA Project, the National Institute for Earth Physics, together with the Technical University of Civil Engineering Bucharest and NORSAR Institute managed to compile a database for buildings in southern Romania (according to the 1999 census), with 48 associated capacity and fragility curves. Until now, the developed real-time estimation system was not implemented for Bucharest. This paper presents more than an adaptation of this system to Bucharest; first, we analyze the previous seismic risk studies, from a SWOT perspective. This reveals that most of the studies don't use
An extensive study on a simple method estimating response spectrum based on a simulated spectrum
International Nuclear Information System (INIS)
Sato, H.; Komazaki, M.; Ohori, M.
1977-01-01
The basic description of the procedure will be briefly described in the paper. Corresponding to peaks of the response spectrum for the earthquake motion the component of the respective ground predominant period was taken. The acceleration amplification factor of a building structure for the respective predominant period above taken was obtained from the spectrum for the simulated earthquake with single predominant period. The rate of the respective component in summing these amplification factors was given by satisfying the ratio among the magnitude of the peaks of the spectrum. The summation was made by the principle of the square root of sum of squares. The procedure was easily applied to estimate the spectrum of the building appendage structure. The method is attempted to extend for multi-storey building structure and appendage to this building. Analysis is made as for a two storey structure system the mode of which for the first natural frequency is that the amplitude ratio of the upper mass to the lower is 2 to 1, so that the mode shape is a reversed triangle. The behavior of the system is dealt with by the normal coordinate. The amplification factors due to two ground predominant periods are estimated for the system with the first natural frequency. In this procedure the method developed for the single-degree-of-freedom system is directly applicable. The same method is used for the system with the second natural frequency. Thus estimated amplification factor for the mode of the respective natural frequency is summed again due to the principle of the square root of sum of squares after multiplying the excitation coefficient of each mode by the corresponding factor
MR-based Water Content Estimation in Cartilage: Design and Validation of a Method
DEFF Research Database (Denmark)
Shiguetomi Medina, Juan Manuel; Kristiansen, Maja Sofie; Ringgaard, Steffen
2012-01-01
Objective Design and validation of an MR-based method that allows the calculation of the water content in cartilage tissue. Material and Methods We modified and adapted to cartilage tissue T1 map based water content MR sequences commonly used in the neurology field. Using a 37 Celsius degree stable...... was costumed and programmed. Finally, we validated the method after measuring and comparing 3 more cartilage samples in a living animal (pig). The obtained data was analyzed and the water content calculated. Then, the same samples were freeze-dried (this technique allows to take out all the water that a tissue...... contains) and we measured the water they contained. Results We could reproduce twice the 37 Celsius degree system and could perform the measurements in a similar way. We found that the MR T1 map based water content sequences can provide information that, after being analyzed with a special software, can...
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.
Hashiguchi, Takuhei; Watanabe, Masayuki; Goda, Tadahiro; Mitani, Yasunori; Saeki, Osamu; Hojo, Masahide; Ukai, Hiroyuki
Open access and deregulation have been introduced into Japan and some independent power producers (IPP) and power producer and suppliers (PPS) are participating in the power generation business, which is possible to makes power system dynamics more complex. To maintain power system condition under various situations, it is essential that a real time measurement system over wide area is available. Therefore we started a project to construct an original measurement system by the use of phasor measurement units (PMU) in Japan. This paper describes the estimation method of a center of inertia frequency by applying actual measurement data. The application of this method enables us to extract power system oscillations from measurement data appropriately. Moreover, the analysis of power system dynamics for power system oscillations occurring in western Japan 60Hz system is shown. These results will lead to the clarification of power system dynamics and may make it possible to realize the monitoring of power system oscillations associated with power system stability.
Estimation of pattern shape based on CD-SEM image by using MPPC method
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.
A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires
Directory of Open Access Journals (Sweden)
Daniel Garcia-Pozuelo
2017-02-01
Full Text Available The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic.
Model-based dynamic multi-parameter method for peak power estimation of lithium-ion batteries
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
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...
An Improved Method of Pose Estimation for Lighthouse Base Station Extension.
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.
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.
A Study on the Estimation Method of Risk Based Area for Jetty Safety Monitoring
Directory of Open Access Journals (Sweden)
Byeong-Wook Nam
2015-09-01
Full Text Available Recently, the importance of safety-monitoring systems was highlighted by the unprecedented collision between a ship and a jetty in Yeosu. Accordingly, in this study, we introduce the concept of risk based area and develop a methodology for a jetty safety-monitoring system. By calculating the risk based areas for a ship and a jetty, the risk of collision was evaluated. To calculate the risk based areas, we employed an automatic identification system for the ship, stopping-distance equations, and the regulation velocity near the jetty. In this paper, we suggest a risk calculation method for jetty safety monitoring that can determine the collision probability in real time and predict collisions using the amount of overlap between the two calculated risk based areas. A test was conducted at a jetty control center at GS Caltex, and the effectiveness of the proposed risk calculation method was verified. The method is currently applied to the jetty-monitoring system at GS Caltex in Yeosu for the prevention of collisions.
Apostol, Izydor; Kelner, Drew; Jiang, Xinzhao Grace; Huang, Gang; Wypych, Jette; Zhang, Xin; Gastwirt, Jessica; Chen, Kenneth; Fodor, Szilan; Hapuarachchi, Suminda; Meriage, Dave; Ye, Frank; Poppe, Leszek; Szpankowski, Wojciech
2012-12-01
To predict precision and other performance characteristics of chromatographic purity methods, which represent the most widely used form of analysis in the biopharmaceutical industry. We have conducted a comprehensive survey of purity methods, and show that all performance characteristics fall within narrow measurement ranges. This observation was used to develop a model called Uncertainty Based on Current Information (UBCI), which expresses these performance characteristics as a function of the signal and noise levels, hardware specifications, and software settings. We applied the UCBI model to assess the uncertainty of purity measurements, and compared the results to those from conventional qualification. We demonstrated that the UBCI model is suitable to dynamically assess method performance characteristics, based on information extracted from individual chromatograms. The model provides an opportunity for streamlining qualification and validation studies by implementing a "live validation" of test results utilizing UBCI as a concurrent assessment of measurement uncertainty. Therefore, UBCI can potentially mitigate the challenges associated with laborious conventional method validation and facilitates the introduction of more advanced analytical technologies during the method lifecycle.
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.
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.
Stand-scale soil respiration estimates based on chamber methods in a Bornean tropical rainforest
Kume, T.; Katayama, A.; Komatsu, H.; Ohashi, M.; Nakagawa, M.; Yamashita, M.; Otsuki, K.; Suzuki, M.; Kumagai, T.
2009-12-01
This study was undertaken to estimate stand-scale soil respiration in an aseasonal tropical rainforest on Borneo Island. To this aim, we identified critical and practical factors explaining spatial variations in soil respiration based on the soil respiration measurements conducted at 25 points in a 40 × 40 m subplot of a 4 ha study plot for five years in relation to soil, root, and forest structural factors. Consequently, we found significant positive correlation between the soil respiration and forest structural parameters. The most important factor was the mean DBH within 6 m of the measurement points, which had a significant linear relationship with soil respiration. Using the derived linear regression and an inventory dataset, we estimated the 4 ha-scale soil respiration. The 4 ha-scale estimation (6.0 μmol m-2 s-1) was nearly identical to the subplot scale measurements (5.7 μmol m-2 s-1), which were roughly comparable to the nocturnal CO2 fluxes calculated using the eddy covariance technique. To confirm the spatial representativeness of soil respiration estimates in the subplot, we performed variogram analysis. Semivariance of DBH(6) in the 4 ha plot showed that there was autocorrelation within the separation distance of about 20 m, and that the spatial dependence was unclear at a separation distance of greater than 20 m. This ascertained that the 40 × 40 m subplot could represent the whole forest structure in the 4 ha plot. In addition, we discuss characteristics of the stand-scale soil respiration at this site by comparing with those of other forests reported in previous literature in terms of the soil C balance. Soil respiration at our site was noticeably greater, relative to the incident litterfall amount, than soil respiration in other tropical and temperate forests probably owing to the larger total belowground C allocation by emergent trees. Overall, this study suggests the arrangement of emergent trees and their bellow ground C allocation could be
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
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.
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.
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.
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.
New graphic AUC-based method to estimate overall survival benefit: pomalidomide reanalysis.
Fenix-Caballero, S; Diaz-Navarro, J; Prieto-Callejero, B; Rios-Sanchez, E; Alegre-del Rey, E J; Borrero-Rubio, J M
2016-02-01
Difference in median survival is an erratic measure and sometimes does not provide a good assessment of survival benefit. The aim of this study was to reanalyse the overall survival benefit of pomalidomide from pivotal clinical trial using a new area under curve (AUC)-based method. In the pivotal trial, pomalidomide plus low-dose dexamethasone showed a significant survival benefit over high-dose dexamethasone, with a difference between medians of 4.6 months. The new AUC method applied to the survival curves, obtained an overall survival benefit of 2.6 months for the pomalidomide treatment. This average difference in OS was calculated for the 61.5% of patients for whom the time to event is reliable enough. This 2-month differential would have major clinical and pharmacoeconomic implications, on both cost-effectiveness studies and on the willingness of the healthcare systems to pay for this treatment. © 2015 John Wiley & Sons Ltd.
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.
Grid impedance estimation based hybrid islanding detection method for AC microgrids
DEFF Research Database (Denmark)
Ghzaiel, Walid; Jebali-Ben Ghorbal, Manel; Slama-Belkhodja, Ilhem
2017-01-01
This paper focuses on a hybrid islanding detection algorithm for parallel-inverters-based microgrids. The proposed algorithm is implemented on the unit ensuring the control of the intelligent bypass switch connecting or disconnecting the microgrid from the utility. This method employs a grid...... to avoid interactions with other units. The selected inverter will be the one closest to the controllable distributed generation system or to a healthy grid side in case of meshed microgrid with multiple-grid connections. The detection algorithm is applied to quickly detect the resonance phenomena, so...
Multiple estimation channel decoupling and optimization method based on inverse system
Wu, Peng; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng
2018-03-01
This paper addressed the intelligent autonomous navigation request of intelligent deformation missile, based on the intelligent deformation missile dynamics and kinematics modeling, navigation subsystem solution method and error modeling, and then focuses on the corresponding data fusion and decision fusion technology, decouples the sensitive channel of the filter input through the inverse system of design dynamics to reduce the influence of sudden change of the measurement information on the filter input. Then carrying out a series of simulation experiments, which verified the feasibility of the inverse system decoupling algorithm effectiveness.
Size of the coming solar cycle 24 based on Ohl's Precursor Method, final estimate
Directory of Open Access Journals (Sweden)
R. P. Kane
2010-07-01
Full Text Available In Ohl's Precursor Method (Ohl, 1966, 1976, the geomagnetic activity during the declining phase of a sunspot cycle is shown to be well correlated with the size (maximum sunspot number Rz(max of the next cycle. For solar cycle 24, Kane (2007a used aa(min=15.5 (12-month running mean, which occurred during March–May of 2006 and made a preliminary estimate Rz(max=124±26 (12-month running mean. However, in the next few months, the aa index first increased and then decreased to a new low value of 14.8 in July 2007. With this new low value, the prediction was Rz(max=117±26 (12-month running mean. However, even this proved a false signal. Since then, the aa values have decreased considerably and the last 12-monthly value is 8.7, centered at May 2009. For solar cycle 24, using aa(min=8.7, the latest prediction is, Rz(max=58.0±25.0.
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.
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.
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.
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.
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...
Energy Technology Data Exchange (ETDEWEB)
Oh, Sun Ryung; Park, Hyun Sun [POSTECH, Pohang (Korea, Republic of); Kim, Moo Hwan [KAERI, Daejeon (Korea, Republic of)
2016-05-15
The sodium-cooled fast reactor (SFR) is one of generation IV type reactors and has been extensively researched since 1950s. A strong advantage of the SFR is its liquid sodium coolant which is well-known for its superior thermal properties. However, in terms of possible pipe leakage or rupture, a liquid sodium coolant possesses a critical issue due to its high chemical reactivity which leads to fire or explosion. Due to its safety concerns, dispersion of nanoparticles in liquid sodium has been proposed to reduce the chemical reactivity of sodium. In case of sodium based titanium nanofluid (NaTiNF), the chemical reactivity suppression effect when interacting with water has been proved both experimentally and theoretically [1,2]. Suppression of chemical reactivity is critical without much loss of high heat transfer characteristic of sodium. As there is no research conducted for applying 3-omega sensor in liquid metal as well as high temperature liquid, the sensor development is performed for using in NaTiNF as well as effective thermal conductivity model validation. Based on the acquired effective thermal conductivity of NaTiNF, existing effective thermal conductivity models are evaluated. Thermal conductivity measurement is performed for liquid sodium based titanium nanofluid (NaTiNF) through 3-Omega method. The experiment is conducted at three temperature points of 120, 150, and 180 .deg. C for both pure liquid sodium and NaTiNF. By using 3- omega sensor, thermal conductivity measurement of liquid metal can be more conveniently conducted in labscale. Also, its possibility to measure the thermal conductivity of high temperature liquid metal with metallic nanoparticles being dispersed is shown. Unlike other water or oil-based nanofluids, NaTiNF exhibits reduction of thermal conductivity compare with liquid sodium. Various nanofluid models are plotted, and it is concluded that the MSBM which considers interfacial resistance and Brownian motion can be used in predicting
International Nuclear Information System (INIS)
Oh, Sun Ryung; Park, Hyun Sun; Kim, Moo Hwan
2016-01-01
The sodium-cooled fast reactor (SFR) is one of generation IV type reactors and has been extensively researched since 1950s. A strong advantage of the SFR is its liquid sodium coolant which is well-known for its superior thermal properties. However, in terms of possible pipe leakage or rupture, a liquid sodium coolant possesses a critical issue due to its high chemical reactivity which leads to fire or explosion. Due to its safety concerns, dispersion of nanoparticles in liquid sodium has been proposed to reduce the chemical reactivity of sodium. In case of sodium based titanium nanofluid (NaTiNF), the chemical reactivity suppression effect when interacting with water has been proved both experimentally and theoretically [1,2]. Suppression of chemical reactivity is critical without much loss of high heat transfer characteristic of sodium. As there is no research conducted for applying 3-omega sensor in liquid metal as well as high temperature liquid, the sensor development is performed for using in NaTiNF as well as effective thermal conductivity model validation. Based on the acquired effective thermal conductivity of NaTiNF, existing effective thermal conductivity models are evaluated. Thermal conductivity measurement is performed for liquid sodium based titanium nanofluid (NaTiNF) through 3-Omega method. The experiment is conducted at three temperature points of 120, 150, and 180 .deg. C for both pure liquid sodium and NaTiNF. By using 3- omega sensor, thermal conductivity measurement of liquid metal can be more conveniently conducted in labscale. Also, its possibility to measure the thermal conductivity of high temperature liquid metal with metallic nanoparticles being dispersed is shown. Unlike other water or oil-based nanofluids, NaTiNF exhibits reduction of thermal conductivity compare with liquid sodium. Various nanofluid models are plotted, and it is concluded that the MSBM which considers interfacial resistance and Brownian motion can be used in predicting
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
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
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.
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...
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.
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.
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
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...
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.
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...
PMU Placement Based on Heuristic Methods, when Solving the Problem of EPS State Estimation
I. N. Kolosok; E. S. Korkina; A. M. Glazunova
2014-01-01
Creation of satellite communication systems gave rise to a new generation of measurement equipment â€“ Phasor Measurement Unit (PMU). Integrated into the measurement system WAMS, the PMU sensors provide a real picture of state of energy power system (EPS). The issues of PMU placement when solving the problem of EPS state estimation (SE) are discussed in many papers. PMU placement is a complex combinatorial problem, and there is not any analytical function to optimize its variables. Therefore,...
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.
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.
DYNAMIC PARAMETER ESTIMATION BASED ON MINIMUM CROSS-ENTROPY METHOD FOR COMBINING INFORMATION SOURCES
Czech Academy of Sciences Publication Activity Database
Sečkárová, Vladimíra
2015-01-01
Roč. 24, č. 5 (2015), s. 181-188 ISSN 0204-9805. [XVI-th International Summer Conference on Probability and Statistics (ISCPS-2014). Pomorie, 21.6.-29.6.2014] R&D Projects: GA ČR GA13-13502S Grant - others:GA UK(CZ) SVV 260225/2015 Institutional support: RVO:67985556 Keywords : minimum cross- entropy principle * Kullback-Leibler divergence * dynamic diffusion estimation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2015/AS/seckarova-0445817.pdf
ÖZERDEM, Mehmet Siraç; ACAR, Emrullah
2011-01-01
Crop diseases can affect yield and/or quality of the harvested commodity. This can influence profitability and raise the risks of farming. When the diseases are estimated early, the yield will increase by taking measures thanks to farmers. The rust disease is one of the most major crop diseases that affect crop yield. Rust disease can be defined as a fungus; it makes the crops weak by blocking food to the roots and leaves. It is named “rust” disease, since the spots on the leaves look like gr...
Estimating the direction of innovative change based on theory an mixed methods
Geurts, Petrus A.T.M.; Roosendaal, Hans E.
2001-01-01
In predicting the direction of innovative changethe question arises of the valid measurement ofyet unknown variables. We developed and applied aresearch method that combines qualitativeand quantitative elements in one interview formatand an analysis tool suitable for these data. Animportant
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.
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
[A study of biomechanical method for urine test based on color difference estimation].
Wang, Chunhong; Zhou, Yue; Zhao, Hongxia; Zhou, Fengkun
2008-02-01
The biochemical analysis of urine is an important inspection and diagnosis method in hospitals. The conventional method of urine analysis covers mainly colorimetric visual appraisement and automation detection, in which the colorimetric visual appraisement technique has been superseded basically, and the automation detection method is adopted in hospital; moreover, the price of urine biochemical analyzer on market is around twenty thousand RMB yuan (Y), which is hard to enter into ordinary families. It is known that computer vision system is not subject to the physiological and psychological influence of person, its appraisement standard is objective and steady. Therefore, according to the color theory, we have established a computer vision system, which can carry through collection, management, display, and appraisement of color difference between the color of standard threshold value and the color of urine test paper after reaction with urine liquid, and then the level of an illness can be judged accurately. In this paper, we introduce the Urine Test Biochemical Analysis method, which is new and can be popularized in families. Experimental result shows that this test method is easy-to-use and cost-effective. It can realize the monitoring of a whole course and can find extensive applications.
An adaptive segment method for smoothing lidar signal based on noise estimation
Wang, Yuzhao; Luo, Pingping
2014-10-01
An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.
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.
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.
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.
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.
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
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
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
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
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)
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)
A laparoscopy-based method for BRDF estimation from in vivo human liver.
Nunes, A L P; Maciel, A; Cavazzola, L T; Walter, M
2017-01-01
While improved visual realism is known to enhance training effectiveness in virtual surgery simulators, the advances on realistic rendering for these simulators is slower than similar simulations for man-made scenes. One of the main reasons for this is that in vivo data is hard to gather and process. In this paper, we propose the analysis of videolaparoscopy data to compute the Bidirectional Reflectance Distribution Function (BRDF) of living organs as an input to physically based rendering algorithms. From the interplay between light and organic matter recorded in video images, we propose the definition of a process capable of establishing the BRDF for inside-the-body organic surfaces. We present a case study around the liver with patient-specific rendering under global illumination. Results show that despite the limited range of motion allowed within the body, the computed BRDF presents a high-coverage of the sampled regions and produces plausible renderings. Copyright © 2016 Elsevier B.V. All rights reserved.
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.)
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
Nonparametric methods for volatility density estimation
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
Boundary methods for mode estimation
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).
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.
Directory of Open Access Journals (Sweden)
Andrew E. Suyker
2013-11-01
Full Text Available Remote sensing techniques that provide synoptic and repetitive observations over large geographic areas have become increasingly important in studying the role of agriculture in global carbon cycles. However, it is still challenging to model crop yields based on remotely sensed data due to the variation in radiation use efficiency (RUE across crop types and the effects of spatial heterogeneity. In this paper, we propose a production efficiency model-based method to estimate corn and soybean yields with MODerate Resolution Imaging Spectroradiometer (MODIS data by explicitly handling the following two issues: (1 field-measured RUE values for corn and soybean are applied to relatively pure pixels instead of the biome-wide RUE value prescribed in the MODIS vegetation productivity product (MOD17; and (2 contributions to productivity from vegetation other than crops in mixed pixels are deducted at the level of MODIS resolution. Our estimated yields statistically correlate with the national survey data for rainfed counties in the Midwestern US with low errors for both corn (R2 = 0.77; RMSE = 0.89 MT/ha and soybeans (R2 = 0.66; RMSE = 0.38 MT/ha. Because the proposed algorithm does not require any retrospective analysis that constructs empirical relationships between the reported yields and remotely sensed data, it could monitor crop yields over large areas.
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
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
Directory of Open Access Journals (Sweden)
Corrado Dimauro
2010-01-01
Full Text Available Two methods of SNPs pre-selection based on single marker regression for the estimation of genomic breeding values (G-EBVs were compared using simulated data provided by the XII QTL-MAS workshop: i Bonferroni correction of the significance threshold and ii Permutation test to obtain the reference distribution of the null hypothesis and identify significant markers at P<0.01 and P<0.001 significance thresholds. From the set of markers significant at P<0.001, random subsets of 50% and 25% markers were extracted, to evaluate the effect of further reducing the number of significant SNPs on G-EBV predictions. The Bonferroni correction method allowed the identification of 595 significant SNPs that gave the best G-EBV accuracies in prediction generations (82.80%. The permutation methods gave slightly lower G-EBV accuracies even if a larger number of SNPs resulted significant (2,053 and 1,352 for 0.01 and 0.001 significance thresholds, respectively. Interestingly, halving or dividing by four the number of SNPs significant at P<0.001 resulted in an only slightly decrease of G-EBV accuracies. The genetic structure of the simulated population with few QTL carrying large effects, might have favoured the Bonferroni method.
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.
Directory of Open Access Journals (Sweden)
Binnendijk Erika
2012-10-01
Full Text Available Abstract Background Most healthcare spending in developing countries is private out-of-pocket. One explanation for low penetration of health insurance is that poorer individuals doubt their ability to enforce insurance contracts. Community-based health insurance schemes (CBHI are a solution, but launching CBHI requires obtaining accurate local data on morbidity, healthcare utilization and other details to inform package design and pricing. We developed the “Illness Mapping” method (IM for data collection (faster and cheaper than household surveys. Methods IM is a modification of two non-interactive consensus group methods (Delphi and Nominal Group Technique to operate as interactive methods. We elicited estimates from “Experts” in the target community on morbidity and healthcare utilization. Interaction between facilitator and experts became essential to bridge literacy constraints and to reach consensus. The study was conducted in Gaya District, Bihar (India during April-June 2010. The intervention included the IM and a household survey (HHS. IM included 18 women’s and 17 men’s groups. The HHS was conducted in 50 villages with1,000 randomly selected households (6,656 individuals. Results We found good agreement between the two methods on overall prevalence of illness (IM: 25.9% ±3.6; HHS: 31.4% and on prevalence of acute (IM: 76.9%; HHS: 69.2% and chronic illnesses (IM: 20.1%; HHS: 16.6%. We also found good agreement on incidence of deliveries (IM: 3.9% ±0.4; HHS: 3.9%, and on hospital deliveries (IM: 61.0%. ± 5.4; HHS: 51.4%. For hospitalizations, we obtained a lower estimate from the IM (1.1% than from the HHS (2.6%. The IM required less time and less person-power than a household survey, which translate into reduced costs. Conclusions We have shown that our Illness Mapping method can be carried out at lower financial and human cost for sourcing essential local data, at acceptably accurate levels. In view of the good fit of
Binnendijk, Erika; Gautham, Meenakshi; Koren, Ruth; Dror, David M
2012-10-09
Most healthcare spending in developing countries is private out-of-pocket. One explanation for low penetration of health insurance is that poorer individuals doubt their ability to enforce insurance contracts. Community-based health insurance schemes (CBHI) are a solution, but launching CBHI requires obtaining accurate local data on morbidity, healthcare utilization and other details to inform package design and pricing. We developed the "Illness Mapping" method (IM) for data collection (faster and cheaper than household surveys). IM is a modification of two non-interactive consensus group methods (Delphi and Nominal Group Technique) to operate as interactive methods. We elicited estimates from "Experts" in the target community on morbidity and healthcare utilization. Interaction between facilitator and experts became essential to bridge literacy constraints and to reach consensus.The study was conducted in Gaya District, Bihar (India) during April-June 2010. The intervention included the IM and a household survey (HHS). IM included 18 women's and 17 men's groups. The HHS was conducted in 50 villages with1,000 randomly selected households (6,656 individuals). We found good agreement between the two methods on overall prevalence of illness (IM: 25.9% ±3.6; HHS: 31.4%) and on prevalence of acute (IM: 76.9%; HHS: 69.2%) and chronic illnesses (IM: 20.1%; HHS: 16.6%). We also found good agreement on incidence of deliveries (IM: 3.9% ±0.4; HHS: 3.9%), and on hospital deliveries (IM: 61.0%. ± 5.4; HHS: 51.4%). For hospitalizations, we obtained a lower estimate from the IM (1.1%) than from the HHS (2.6%). The IM required less time and less person-power than a household survey, which translate into reduced costs. We have shown that our Illness Mapping method can be carried out at lower financial and human cost for sourcing essential local data, at acceptably accurate levels. In view of the good fit of results obtained, we assume that the method could work elsewhere
Wu, Man Li C.; Schubert, Siegfried; Lin, Ching I.; Stajner, Ivanka; Einaudi, Franco (Technical Monitor)
2000-01-01
A method is developed for validating model-based estimates of atmospheric moisture and ground temperature using satellite data. The approach relates errors in estimates of clear-sky longwave fluxes at the top of the Earth-atmosphere system to errors in geophysical parameters. The fluxes include clear-sky outgoing longwave radiation (CLR) and radiative flux in the window region between 8 and 12 microns (RadWn). The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data, and multiple global four-dimensional data assimilation (4-DDA) products. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic clear-sky longwave fluxes from two different 4-DDA data sets. Simple linear regression is used to relate the clear-sky longwave flux discrepancies to discrepancies in ground temperature ((delta)T(sub g)) and broad-layer integrated atmospheric precipitable water ((delta)pw). The slopes of the regression lines define sensitivity parameters which can be exploited to help interpret mismatches between satellite observations and model-based estimates of clear-sky longwave fluxes. For illustration we analyze the discrepancies in the clear-sky longwave fluxes between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS2) and a recent operational version of the European Centre for Medium-Range Weather Forecasts data assimilation system. The analysis of the synthetic clear-sky flux data shows that simple linear regression employing (delta)T(sub g)) and broad layer (delta)pw provides a good approximation to the full radiative transfer calculations, typically explaining more thin 90% of the 6 hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters, Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for
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
Order statistics & inference estimation methods
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
Energy Technology Data Exchange (ETDEWEB)
Loefgren, Martin (Kemakta Konsult AB, Stockholm (Sweden)); Vecernik, Petr; Havlova, Vaclava (Waste Disposal Dept., Nuclear Research Institute Rez plc. (Czech Republic))
2009-11-15
factors and generic surface conductivities, and fairly good agreement was obtained. Part 1 suffered from methodology problems, which ultimately lead to poor reproducibility and accuracy. Here a single sample was in sequence saturated with the 0.001, 0.03, 0.5, 0.1 and 1.0 M NaCl electrolytes. The aim was to see if the apparent formation factor increasingly overestimates the formation factor with decreasing electrical conductivity of the pore water. Notwithstanding the experimental problems and errors, it was shown that this is clearly the case. For the electrolyte 0.001 M NaCl, and for this particular sample, the apparent formation factor overestimates the formation factor by at least one order of magnitude. The measured apparent formation factors were compared with modelled apparent formation factors, where input data were the sample's measured formation factor and surface conductivity, and fairly good agreement was obtained. The formation factors obtained by the TEM method were comparable with those obtained in the previous through diffusion experiments on the same samples. Especially for the Forsmark samples of part 2, the TEM results agreed with the through diffusion results, indicating that anion exclusion is not a major issue. From comparison of the TEM formation factors, obtained with anionic tracer iodide, and estimated formation factors based on the resistivity methods, it is indicated that anion exclusion should not reduce the effective diffusivity by more than a few factors
International Nuclear Information System (INIS)
Loefgren, Martin; Vecernik, Petr; Havlova, Vaclava
2009-11-01
factors and generic surface conductivities, and fairly good agreement was obtained. Part 1 suffered from methodology problems, which ultimately lead to poor reproducibility and accuracy. Here a single sample was in sequence saturated with the 0.001, 0.03, 0.5, 0.1 and 1.0 M NaCl electrolytes. The aim was to see if the apparent formation factor increasingly overestimates the formation factor with decreasing electrical conductivity of the pore water. Notwithstanding the experimental problems and errors, it was shown that this is clearly the case. For the electrolyte 0.001 M NaCl, and for this particular sample, the apparent formation factor overestimates the formation factor by at least one order of magnitude. The measured apparent formation factors were compared with modelled apparent formation factors, where input data were the sample's measured formation factor and surface conductivity, and fairly good agreement was obtained. The formation factors obtained by the TEM method were comparable with those obtained in the previous through diffusion experiments on the same samples. Especially for the Forsmark samples of part 2, the TEM results agreed with the through diffusion results, indicating that anion exclusion is not a major issue. From comparison of the TEM formation factors, obtained with anionic tracer iodide, and estimated formation factors based on the resistivity methods, it is indicated that anion exclusion should not reduce the effective diffusivity by more than a few factors
Random Decrement Based FRF Estimation
DEFF Research Database (Denmark)
Brincker, Rune; Asmussen, J. C.
to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods...... that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation...
Random Decrement Based FRF Estimation
DEFF Research Database (Denmark)
Brincker, Rune; Asmussen, J. C.
1997-01-01
to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods...... that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation...
Unrecorded Alcohol Consumption: Quantitative Methods of Estimation
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.
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.
Directory of Open Access Journals (Sweden)
Zeeshan Ali Siddiqui
2016-01-01
Full Text Available Component-based software system (CBSS development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.
International Nuclear Information System (INIS)
Arab, M.N.; Ayaz, M.
2004-01-01
The performance of transmission line insulator is greatly affected by dust, fumes from industrial areas and saline deposit near the coast. Such pollutants in the presence of moisture form a coating on the surface of the insulator, which in turn allows the passage of leakage current. This leakage builds up to a point where flashover develops. The flashover is often followed by permanent failure of insulation resulting in prolong outages. With the increase in system voltage owing to the greater demand of electrical energy over the past few decades, the importance of flashover due to pollution has received special attention. The objective of the present work was to study the performance of overhead line insulators in the presence of contaminants such as induced salts. A detailed review of the literature and the mechanisms of insulator flashover due to the pollution are presented. Experimental investigations on the behavior of overhead line insulators under industrial salt contamination are carried out. A special fog chamber was designed in which the contamination testing of insulators was carried out. Flashover behavior under various degrees of contamination of insulators with the most common industrial fume components such as Nitrate and Sulphate compounds was studied. Substituting the normal distribution parameter in the probability distribution function based on maximum likelihood develops a statistical method. The method gives a high accuracy in the estimation of the 50% flashover voltage, which is then used to evaluate the critical flashover index at various contamination levels. The critical flashover index is a valuable parameter in insulation design for numerous applications. (author)
Ames, D. P.; Osorio-Murillo, C.; Over, M. W.; Rubin, Y.
2012-12-01
The Method of Anchored Distributions (MAD) is an inverse modeling technique that is well-suited for estimation of spatially varying parameter fields using limited observations and Bayesian methods. This presentation will discuss the design, development, and testing of a free software implementation of the MAD technique using the open source DotSpatial geographic information system (GIS) framework, R statistical software, and the MODFLOW groundwater model. This new tool, dubbed MAD-GIS, is built using a modular architecture that supports the integration of external analytical tools and models for key computational processes including a forward model (e.g. MODFLOW, HYDRUS) and geostatistical analysis (e.g. R, GSLIB). The GIS-based graphical user interface provides a relatively simple way for new users of the technique to prepare the spatial domain, to identify observation and anchor points, to perform the MAD analysis using a selected forward model, and to view results. MAD-GIS uses the Managed Extensibility Framework (MEF) provided by the Microsoft .NET programming platform to support integration of different modeling and analytical tools at run-time through a custom "driver." Each driver establishes a connection with external programs through a programming interface, which provides the elements for communicating with core MAD software. This presentation gives an example of adapting the MODFLOW to serve as the external forward model in MAD-GIS for inferring the distribution functions of key MODFLOW parameters. Additional drivers for other models are being developed and it is expected that the open source nature of the project will engender the development of additional model drivers by 3rd party scientists.
Comparison of methods for estimating premorbid intelligence
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 ...
Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M
2018-06-01
Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
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.
Dose estimation by biological methods
International Nuclear Information System (INIS)
Guerrero C, C.; David C, L.; Serment G, J.; Brena V, M.
1997-01-01
The human being is exposed to strong artificial radiation sources, mainly of two forms: the first is referred to the occupationally exposed personnel (POE) and the second, to the persons that require radiological treatment. A third form less common is by accidents. In all these conditions it is very important to estimate the absorbed dose. The classical biological dosimetry is based in the dicentric analysis. The present work is part of researches to the process to validate the In situ Fluorescent hybridation (FISH) technique which allows to analyse the aberrations on the chromosomes. (Author)
alhilman, Judi
2017-12-01
In the production line process of the printing office, the reliability of the printing machine plays a very important role, if the machine fail it can disrupt production target so that the company will suffer huge financial loss. One method to calculate the financial loss cause by machine failure is use the Cost of Unreliability(COUR) method. COUR method works based on down time machine and costs associated with unreliability data. Based on the calculation of COUR method, so the sum of cost due to unreliability printing machine during active repair time and downtime is 1003,747.00.
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.
Bayesian estimation methods in metrology
International Nuclear Information System (INIS)
Cox, M.G.; Forbes, A.B.; Harris, P.M.
2004-01-01
In metrology -- the science of measurement -- a measurement result must be accompanied by a statement of its associated uncertainty. The degree of validity of a measurement result is determined by the validity of the uncertainty statement. In recognition of the importance of uncertainty evaluation, the International Standardization Organization in 1995 published the Guide to the Expression of Uncertainty in Measurement and the Guide has been widely adopted. The validity of uncertainty statements is tested in interlaboratory comparisons in which an artefact is measured by a number of laboratories and their measurement results compared. Since the introduction of the Mutual Recognition Arrangement, key comparisons are being undertaken to determine the degree of equivalence of laboratories for particular measurement tasks. In this paper, we discuss the possible development of the Guide to reflect Bayesian approaches and the evaluation of key comparison data using Bayesian estimation methods
International Nuclear Information System (INIS)
Alavi, Seyed Arash; Ahmadian, Ali; Aliakbar-Golkar, Masoud
2015-01-01
Highlights: • Energy management is necessary in the active distribution network to reduce operation costs. • Uncertainty modeling is essential in energy management studies in active distribution networks. • Point estimate method is a suitable method for uncertainty modeling due to its lower computation time and acceptable accuracy. • In the absence of Probability Distribution Function (PDF) robust optimization has a good ability for uncertainty modeling. - Abstract: Uncertainty can be defined as the probability of difference between the forecasted value and the real value. As this probability is small, the operation cost of the power system will be less. This purpose necessitates modeling of system random variables (such as the output power of renewable resources and the load demand) with appropriate and practicable methods. In this paper, an adequate procedure is proposed in order to do an optimal energy management on a typical micro-grid with regard to the relevant uncertainties. The point estimate method is applied for modeling the wind power and solar power uncertainties, and robust optimization technique is utilized to model load demand uncertainty. Finally, a comparison is done between deterministic and probabilistic management in different scenarios and their results are analyzed and evaluated
Guo, Shiyi; Mai, Ying; Zhao, Hongying; Gao, Pengqi
2013-05-01
The airborne video streams of small-UAVs are commonly plagued with distractive jittery and shaking motions, disorienting rotations, noisy and distorted images and other unwanted movements. These problems collectively make it very difficult for observers to obtain useful information from the video. Due to the small payload of small-UAVs, it is a priority to improve the image quality by means of electronic image stabilization. But when small-UAV makes a turn, affected by the flight characteristics of it, the video is easy to become oblique. This brings a lot of difficulties to electronic image stabilization technology. Homography model performed well in the oblique image motion estimation, while bringing great challenges to intentional motion estimation. Therefore, in this paper, we focus on solve the problem of the video stabilized when small-UAVs banking and turning. We attend to the small-UAVs fly along with an arc of a fixed turning radius. For this reason, after a series of experimental analysis on the flight characteristics and the path how small-UAVs turned, we presented a new method to estimate the intentional motion in which the path of the frame center was used to fit the video moving track. Meanwhile, the image sequences dynamic mosaic was done to make up for the limited field of view. At last, the proposed algorithm was carried out and validated by actual airborne videos. The results show that the proposed method is effective to stabilize the oblique video of small-UAVs.
Liu, Kaizhan; Ye, Yunming; Li, Xutao; Li, Yan
2018-04-01
In recent years Convolutional Neural Network (CNN) has been widely used in computer vision field and makes great progress in lots of contents like object detection and classification. Even so, combining Convolutional Neural Network, which means making multiple CNN frameworks working synchronously and sharing their output information, could figure out useful message that each of them cannot provide singly. Here we introduce a method to real-time estimate speed of object by combining two CNN: YOLOv2 and FlowNet. In every frame, YOLOv2 provides object size; object location and object type while FlowNet providing the optical flow of whole image. On one hand, object size and object location help to select out the object part of optical flow image thus calculating out the average optical flow of every object. On the other hand, object type and object size help to figure out the relationship between optical flow and true speed by means of optics theory and priori knowledge. Therefore, with these two key information, speed of object can be estimated. This method manages to estimate multiple objects at real-time speed by only using a normal camera even in moving status, whose error is acceptable in most application fields like manless driving or robot vision.
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.
Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch
2015-06-01
Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.
Directory of Open Access Journals (Sweden)
Jianping Qian
Full Text Available ABSTRACT: Apple yield estimation using a smartphone with image processing technology offers advantages such as low cost, quick access and simple operation. This article proposes distribution framework consisting of the acquisition of fruit tree images, yield prediction in smarphone client, data processing and model calculation in server client for estimating the potential fruit yield. An image processing method was designed including the core steps of image segmentation with R/B value combined with V value and circle-fitting using curvature analysis. This method enabled four parameters to be obtained, namely, total identified pixel area (TP, fitting circle amount (FC, average radius of the fitting circle (RC and small polygon pixel area (SP. A individual tree yield estimation model on an ANN (Artificial Neural Network was developed with three layers, four input parameters, 14 hidden neurons, and one output parameter. The system was used on an experimental Fuji apple (Malus domestica Borkh. cv. Red Fuji orchard. Twenty-six tree samples were selected from a total of 80 trees according to the multiples of the number three for the establishment model, whereby 21 groups of data were trained and 5 groups o data were validated. The R2 value for the training datasets was 0.996 and the relative root mean squared error (RRMSE value 0.063. The RRMSE value for the validation dataset was 0.284 Furthermore, a yield map with 80 apple trees was generated, and the space distribution o the yield was identified. It provided appreciable decision support for site-specific management.
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.
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
System and method for traffic signal timing estimation
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.
System and method for traffic signal timing estimation
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.
Directory of Open Access Journals (Sweden)
N. D. Tiannikova
2014-01-01
Full Text Available G.D. Kartashov has developed a technique to determine the rapid testing results scaling functions to the normal mode. Its feature is preliminary tests of products of one sample including tests using the alternating modes. Standard procedure of preliminary tests (researches is as follows: n groups of products with m elements in each start being tested in normal mode and, after a failure of one of products in the group, the remained products are tested in accelerated mode. In addition to tests in alternating mode, tests in constantly normal mode are conducted as well. The acceleration factor of rapid tests for this type of products, identical to any lots is determined using such testing results of products from the same lot. A drawback of this technique is that tests are to be conducted in alternating mode till the failure of all products. That is not always is possible. To avoid this shortcoming, the Renyi criterion is offered. It allows us to determine scaling functions using the right-censored data thus giving the opportunity to stop testing prior to all failures of products.In this work a statistical modeling of the acceleration factor estimation owing to Renyi statistics minimization is implemented by the Monte-Carlo method. Results of modeling show that the acceleration factor estimation obtained through Renyi statistics minimization is conceivable for rather large n . But for small sample volumes some systematic bias of acceleration factor estimation, which decreases with growth n is observed for both distributions (exponential and Veybull's distributions. Therefore the paper also presents calculation results of correction factors for a case of exponential distribution and Veybull's distribution.
Cheng, Xuemin; Hao, Qun; Xie, Mengdi
2016-04-07
Video stabilization is an important technology for removing undesired motion in videos. This paper presents a comprehensive motion estimation method for electronic image stabilization techniques, integrating the speeded up robust features (SURF) algorithm, modified random sample consensus (RANSAC), and the Kalman filter, and also taking camera scaling and conventional camera translation and rotation into full consideration. Using SURF in sub-pixel space, feature points were located and then matched. The false matched points were removed by modified RANSAC. Global motion was estimated by using the feature points and modified cascading parameters, which reduced the accumulated errors in a series of frames and improved the peak signal to noise ratio (PSNR) by 8.2 dB. A specific Kalman filter model was established by considering the movement and scaling of scenes. Finally, video stabilization was achieved with filtered motion parameters using the modified adjacent frame compensation. The experimental results proved that the target images were stabilized even when the vibrating amplitudes of the video become increasingly large.
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
DEFF Research Database (Denmark)
Berg, Casper Willestofte; Nielsen, Anders; Kristensen, Kasper
2014-01-01
Indices of abundance from fishery-independent trawl surveys constitute an important source of information for many fish stock assessments. Indices are often calculated using area stratified sample means on age-disaggregated data, and finally treated in stock assessment models as independent...... observations. We evaluate a series of alternative methods for calculating indices of abundance from trawl survey data (delta-lognormal, delta-gamma, and Tweedie using Generalized Additive Models) as well as different error structures for these indices when used as input in an age-based stock assessment model...... the different indices produced. The stratified mean method is found much more imprecise than the alternatives based on GAMs, which are found to be similar. Having time-varying index variances is found to be of minor importance, whereas the independence assumption is not only violated but has significant impact...
Ma, Lin
2017-11-01
This paper develops a method for precisely determining the tension of an inclined cable with unknown boundary conditions. First, the nonlinear motion equation of an inclined cable is derived, and a numerical model of the motion of the cable is proposed using the finite difference method. The proposed numerical model includes the sag-extensibility, flexural stiffness, inclination angle and rotational stiffness at two ends of the cable. Second, the influence of the dynamic parameters of the cable on its frequencies is discussed in detail, and a method for precisely determining the tension of an inclined cable is proposed based on the derivatives of the eigenvalues of the matrices. Finally, a multiparameter identification method is developed that can simultaneously identify multiple parameters, including the rotational stiffness at two ends. This scheme is applicable to inclined cables with varying sag, varying flexural stiffness and unknown boundary conditions. Numerical examples indicate that the method provides good precision. Because the parameters of cables other than tension (e.g., the flexural stiffness and rotational stiffness at the ends) are not accurately known in practical engineering, the multiparameter identification method could further improve the accuracy of cable tension measurements.
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...
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.
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
Directory of Open Access Journals (Sweden)
W. Z. Hou
2018-04-01
Full Text Available This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.
Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.
2018-04-01
This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.
NASA Software Cost Estimation Model: An Analogy Based Estimation Model
Hihn, Jairus; Juster, Leora; Menzies, Tim; Mathew, George; Johnson, James
2015-01-01
The cost estimation of software development activities is increasingly critical for large scale integrated projects such as those at DOD and NASA especially as the software systems become larger and more complex. As an example MSL (Mars Scientific Laboratory) developed at the Jet Propulsion Laboratory launched with over 2 million lines of code making it the largest robotic spacecraft ever flown (Based on the size of the software). Software development activities are also notorious for their cost growth, with NASA flight software averaging over 50% cost growth. All across the agency, estimators and analysts are increasingly being tasked to develop reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods there is very little focus on the use of models based on analogy and clustering algorithms. In this paper we summarize our findings on effort/cost model estimation and model development based on ten years of software effort estimation research using data mining and machine learning methods to develop estimation models based on analogy and clustering. The NASA Software Cost Model performance is evaluated by comparing it to COCOMO II, linear regression, and K- nearest neighbor prediction model performance on the same data set.
Pazderin, A. V.; Sof'in, V. V.; Samoylenko, V. O.
2015-11-01
Efforts aimed at improving energy efficiency in all branches of the fuel and energy complex shall be commenced with setting up a high-tech automated system for monitoring and accounting energy resources. Malfunctions and failures in the measurement and information parts of this system may distort commercial measurements of energy resources and lead to financial risks for power supplying organizations. In addition, measurement errors may be connected with intentional distortion of measurements for reducing payment for using energy resources on the consumer's side, which leads to commercial loss of energy resource. The article presents a universal mathematical method for verifying the validity of measurement information in networks for transporting energy resources, such as electricity and heat, petroleum, gas, etc., based on the state estimation theory. The energy resource transportation network is represented by a graph the nodes of which correspond to producers and consumers, and its branches stand for transportation mains (power lines, pipelines, and heat network elements). The main idea of state estimation is connected with obtaining the calculated analogs of energy resources for all available measurements. Unlike "raw" measurements, which contain inaccuracies, the calculated flows of energy resources, called estimates, will fully satisfy the suitability condition for all state equations describing the energy resource transportation network. The state equations written in terms of calculated estimates will be already free from residuals. The difference between a measurement and its calculated analog (estimate) is called in the estimation theory an estimation remainder. The obtained large values of estimation remainders are an indicator of high errors of particular energy resource measurements. By using the presented method it is possible to improve the validity of energy resource measurements, to estimate the transportation network observability, to eliminate
Directory of Open Access Journals (Sweden)
Valentina A. Kataeva
2017-01-01
Full Text Available The purpose of research was to study the existing methods of determining the degree of cohesion of two users of social network, identifying their shortcomings and developing a new method. The research identified shortcomings of existing methods and proposed a new method for assessing the degree of cohesion of social network profiles based on open data from a social network. Under the degree of cohesion of users’ profiles is understood the probability of communication (interaction of profile owners in real life, it is calculated for two users of the social network and expressed in percent. The work of the method is demonstrated on the example of the social network “In contact”. This method includes the sequence of the following stages: the first stage is data collection about users of the social network with API and the formation of tuples of users’ profile characteristics. A tuple of characteristics of social network profiles is the data, collected for each user, stored in a structured form.The next step is the analysis of the collected information. For each characteristic of the tuple of profiles, i.e. the possible element of interaction of users in the social network, the coefficient of cohesion by the characteristic is calculated. In addition, for each feature, its informativeness is calculated, i.e. how important is this or that feature in this social network. At the final stage, the results are generated, using the formula for the probability of communication between two users, derived during the investigation. Obtained as a result of the application of the method, the probability of communication between two users can be used to optimize the activities of the operative-search services and special bodies.In addition, the received degree of cohesion of two users can be interpreted as the probability of a channel of information leakage between them. The role of the user of the method can be any private or state organization that cares
Painter, Colin C.; Heimann, David C.; Lanning-Rush, Jennifer L.
2017-08-14
A study was done by the U.S. Geological Survey in cooperation with the Kansas Department of Transportation and the Federal Emergency Management Agency to develop regression models to estimate peak streamflows of annual exceedance probabilities of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent at ungaged locations in Kansas. Peak streamflow frequency statistics from selected streamgages were related to contributing drainage area and average precipitation using generalized least-squares regression analysis. The peak streamflow statistics were derived from 151 streamgages with at least 25 years of streamflow data through 2015. The developed equations can be used to predict peak streamflow magnitude and frequency within two hydrologic regions that were defined based on the effects of irrigation. The equations developed in this report are applicable to streams in Kansas that are not substantially affected by regulation, surface-water diversions, or urbanization. The equations are intended for use for streams with contributing drainage areas ranging from 0.17 to 14,901 square miles in the nonirrigation effects region and, 1.02 to 3,555 square miles in the irrigation-affected region, corresponding to the range of drainage areas of the streamgages used in the development of the regional equations.
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)
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.
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.
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
Monte Carlo-based tail exponent estimator
Barunik, Jozef; Vacha, Lukas
2010-11-01
In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations, we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce a Monte Carlo-based method of estimation for the tail exponent. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals. Finally, we demonstrate the power of our estimator on the international world stock market indices. On the two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.
Nouri, Hamideh; Glenn, Edward P.; Beecham, Simon; Chavoshi Boroujeni, Sattar; Sutton, Paul; Alaghmand, Sina; Nagler, Pamela L.; Noori, Behnaz
2016-01-01
Despite being the driest inhabited continent, Australia has one of the highest per capita water consumptions in the world. In addition, instead of having fit-for-purpose water supplies (using different qualities of water for different applications), highly treated drinking water is used for nearly all of Australia’s urban water supply needs, including landscape irrigation. The water requirement of urban landscapes, and particularly urban parklands, is of growing concern. The estimation of ET and subsequently plant water requirements in urban vegetation needs to consider the heterogeneity of plants, soils, water and climate characteristics. Accurate estimation of evapotranspiration (ET), which is the main component of a plant’s water requirement, in urban parks is highly desirable because this water maintains the health of green infrastructure and this in turn provides essential ecosystem services. This research contributes to a broader effort to establish sustainable irrigation practices within the Adelaide Parklands in Adelaide, South Australia.
Gagnon, Pieter; Margolis, Robert; Melius, Jennifer; Phillips, Caleb; Elmore, Ryan
2018-02-01
We provide a detailed estimate of the technical potential of rooftop solar photovoltaic (PV) electricity generation throughout the contiguous United States. This national estimate is based on an analysis of select US cities that combines light detection and ranging (lidar) data with a validated analytical method for determining rooftop PV suitability employing geographic information systems. We use statistical models to extend this analysis to estimate the quantity and characteristics of roofs in areas not covered by lidar data. Finally, we model PV generation for all rooftops to yield technical potential estimates. At the national level, 8.13 billion m2 of suitable roof area could host 1118 GW of PV capacity, generating 1432 TWh of electricity per year. This would equate to 38.6% of the electricity that was sold in the contiguous United States in 2013. This estimate is substantially higher than a previous estimate made by the National Renewable Energy Laboratory. The difference can be attributed to increases in PV module power density, improved estimation of building suitability, higher estimates of total number of buildings, and improvements in PV performance simulation tools that previously tended to underestimate productivity. Also notable, the nationwide percentage of buildings suitable for at least some PV deployment is high—82% for buildings smaller than 5000 ft2 and over 99% for buildings larger than that. In most states, rooftop PV could enable small, mostly residential buildings to offset the majority of average household electricity consumption. Even in some states with a relatively poor solar resource, such as those in the Northeast, the residential sector has the potential to offset around 100% of its total electricity consumption with rooftop PV.
Czech Academy of Sciences Publication Activity Database
Altman, Jan; Doležal, Jiří; Čížek, Lukáš
2016-01-01
Roč. 380, č. 11 (2016), s. 82-89 ISSN 0378-1127 R&D Projects: GA ČR(CZ) GA14-12262S; GA ČR GAP504/12/1952 Institutional support: RVO:67985939 ; RVO:60077344 Keywords : Tree age estimation * Dendrochronology * Partial cores Subject RIV: EH - Ecology, Behaviour Impact factor: 3.064, year: 2016
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.
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.
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.
International Nuclear Information System (INIS)
Mizokami, Shinya; Hotta, Akitoshi; Kudo, Yoshiro; Yonehara, Tadashi; Watada, Masayuki; Sakaba, Hiroshi
2009-01-01
Current licensing practice in Japan consists of using conservative boundary and initial conditions(BIC), assumptions and analytical codes. The safety analyses for licensing purpose are inherently deterministic. Therefore, conservative BIC and assumptions, such as single failure, must be employed for the analyses. However, using conservative analytical codes are not considered essential. The standard committee of Atomic Energy Society of Japan(AESJ) has drawn up the standard for using best estimate codes for safety analyses in 2008 after three-years of discussions reflecting domestic and international recent findings. (author)
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...
Channel Estimation in DCT-Based OFDM
Wang, Yulin; Zhang, Gengxin; Xie, Zhidong; Hu, Jing
2014-01-01
This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective multipath fading channel. Channel estimation has been proved to improve system throughput and performance by allowing for coherent demodulation. Pilot-aided methods are traditionally used to learn the channel response. Least square (LS) and mean square error estimators (MMSE) are investigated. We also study a compressed sensing (CS) based channel estimation, which takes the sparse property of wireless channel into account. Simulation results have shown that the CS based channel estimation is expected to have better performance than LS. However MMSE can achieve optimal performance because of prior knowledge of the channel statistic. PMID:24757439
Directory of Open Access Journals (Sweden)
István Makra
2015-01-01
• The concentration of virus nanoparticles can be calculated based on the two measured scattered light intensities by knowing the refractive index of the dispersing solution, of the polymer and virus nanoparticles as well as their relative sphere equivalent diameters.
Method-related estimates of sperm vitality.
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.
Energy Technology Data Exchange (ETDEWEB)
Kajl, S.; Roberge, M-A. [Quebec Univ., Ecole de technologie superieure, Montreal, PQ (Canada)
1999-02-01
A method for estimating energy requirements in buildings five to twenty-five stories in height using artificial intelligence techniques is proposed. In developing this technique, the pre-requisites specified were rapid execution, the ability to generate a wide range of results, including total energy consumption, power demands, heating and cooling consumption, and accuracy comparable to that of a detailed building energy simulation software. The method proposed encompasses (1) the creation of various databases such as classification of the parameters used in the energy simulation, modelling using the Department of Energy (DOE)-2 software and validation of the DOE-2 models; (2) application of the neural networks inclusive of teaching the neural network and validation of the neural network's learning; (3) designing an energy estimate assessment (EEA) system for residential buildings; and (4) validation of the EEA system. The system has been developed in the MATLAB software environment, specifically for the climate in the Ottawa region. For use under different climatic conditions appropriate adjustments need to be made for the heating and cooling consumption. 12 refs., tabs., figs., 2 appendices.
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
E. Binnendijk (Erica); M. Gautham (Meenakshi); R. Koren (Ruth); D.M. Dror (David)
2012-01-01
textabstractBackground: Most healthcare spending in developing countries is private out-of-pocket. One explanation for low penetration of health insurance is that poorer individuals doubt their ability to enforce insurance contracts. Community-based health insurance schemes (CBHI) are a solution,
Yadav, Nand K; Raghuvanshi, Ashish; Sharma, Gajanand; Beg, Sarwar; Katare, Om P; Nanda, Sanju
2016-03-01
The current studies entail systematic quality by design (QbD)-based development of simple, precise, cost-effective and stability-indicating high-performance liquid chromatography method for estimation of ketoprofen. Analytical target profile was defined and critical analytical attributes (CAAs) were selected. Chromatographic separation was accomplished with an isocratic, reversed-phase chromatography using C-18 column, pH 6.8, phosphate buffer-methanol (50 : 50v/v) as a mobile phase at a flow rate of 1.0 mL/min and UV detection at 258 nm. Systematic optimization of chromatographic method was performed using central composite design by evaluating theoretical plates and peak tailing as the CAAs. The method was validated as per International Conference on Harmonization guidelines with parameters such as high sensitivity, specificity of the method with linearity ranging between 0.05 and 250 µg/mL, detection limit of 0.025 µg/mL and quantification limit of 0.05 µg/mL. Precision was demonstrated using relative standard deviation of 1.21%. Stress degradation studies performed using acid, base, peroxide, thermal and photolytic methods helped in identifying the degradation products in the proniosome delivery systems. The results successfully demonstrated the utility of QbD for optimizing the chromatographic conditions for developing highly sensitive liquid chromatographic method for ketoprofen. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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
Sando, Roy; Sando, Steven K.; McCarthy, Peter M.; Dutton, DeAnn M.
2016-04-05
The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Natural Resources and Conservation, completed a study to update methods for estimating peak-flow frequencies at ungaged sites in Montana based on peak-flow data at streamflow-gaging stations through water year 2011. The methods allow estimation of peak-flow frequencies (that is, peak-flow magnitudes, in cubic feet per second, associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites. The annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.Regional regression analysis is a primary focus of Chapter F of this Scientific Investigations Report, and regression equations for estimating peak-flow frequencies at ungaged sites in eight hydrologic regions in Montana are presented. The regression equations are based on analysis of peak-flow frequencies and basin characteristics at 537 streamflow-gaging stations in or near Montana and were developed using generalized least squares regression or weighted least squares regression.All of the data used in calculating basin characteristics that were included as explanatory variables in the regression equations were developed for and are available through the USGS StreamStats application (http://water.usgs.gov/osw/streamstats/) for Montana. StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report chapter can be conveniently solved using the Montana StreamStats application.Selected results from
Konrad, Paul Markus
2014-01-01
All across Europe, a drama of historical proportions is unfolding as the debt crisis continues to rock the worldwide financial landscape. Whilst insecurity rises, the general public, policy makers, scientists and academics are searching high and low for independent and objective analyses that may help to assess this unusual situation. For more than a century, rating agencies had developed methods and standards to evaluate and analyze companies, projects or even sovereign countries. However, due to their dated internal processes, the independence of these rating agencies is being questioned, ra
Lai, Ting-Yu; Chen, Hsiao-I; Shih, Cho-Chiang; Kuo, Li-Chieh; Hsu, Hsiu-Yun; Huang, Chih-Chung
2016-01-01
Information about tendon displacement is important for allowing clinicians to not only quantify preoperative tendon injuries but also to identify any adhesive scaring between tendon and adjacent tissue. The Fisher-Tippett (FT) similarity measure has recently been shown to be more accurate than the Laplacian sum of absolute differences (SAD) and Gaussian sum of squared differences (SSD) similarity measures for tracking tendon displacement in ultrasound B-mode images. However, all of these similarity measures can easily be influenced by the quality of the ultrasound image, particularly its signal-to-noise ratio. Ultrasound images of injured hands are unfortunately often of poor quality due to the presence of adhesive scars. The present study investigated a novel Kalman-filter scheme for overcoming this problem. Three state-of-the-art tracking methods (FT, SAD, and SSD) were used to track the displacements of phantom and cadaver tendons, while FT was used to track human tendons. These three tracking methods were combined individually with the proposed Kalman-filter (K1) scheme and another Kalman-filter scheme used in a previous study to optimize the displacement trajectories of the phantom and cadaver tendons. The motion of the human extensor digitorum communis tendon was measured in the present study using the FT-K1 scheme. The experimental results indicated that SSD exhibited better accuracy in the phantom experiments, whereas FT exhibited better performance for tracking real tendon motion in the cadaver experiments. All three tracking methods were influenced by the signal-to-noise ratio of the images. On the other hand, the K1 scheme was able to optimize the tracking trajectory of displacement in all experiments, even from a location with a poor image quality. The human experimental data indicated that the normal tendons were displaced more than the injured tendons, and that the motion ability of the injured tendon was restored after appropriate rehabilitation
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
A method of estimating log weights.
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...
Gallivanone, F.; Interlenghi, M.; Canervari, C.; Castiglioni, I.
2016-01-01
18F-Fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET) is a standard functional diagnostic technique to in vivo image cancer. Different quantitative paramters can be extracted from PET images and used as in vivo cancer biomarkers. Between PET biomarkers Metabolic Tumor Volume (MTV) has gained an important role in particular considering the development of patient-personalized radiotherapy treatment for non-homogeneous dose delivery. Different imaging processing methods have been developed to define MTV. The different proposed PET segmentation strategies were validated in ideal condition (e.g. in spherical objects with uniform radioactivity concentration), while the majority of cancer lesions doesn't fulfill these requirements. In this context, this work has a twofold objective: 1) to implement and optimize a fully automatic, threshold-based segmentation method for the estimation of MTV, feasible in clinical practice 2) to develop a strategy to obtain anthropomorphic phantoms, including non-spherical and non-uniform objects, miming realistic oncological patient conditions. The developed PET segmentation algorithm combines an automatic threshold-based algorithm for the definition of MTV and a k-means clustering algorithm for the estimation of the background. The method is based on parameters always available in clinical studies and was calibrated using NEMA IQ Phantom. Validation of the method was performed both in ideal (e.g. in spherical objects with uniform radioactivity concentration) and non-ideal (e.g. in non-spherical objects with a non-uniform radioactivity concentration) conditions. The strategy to obtain a phantom with synthetic realistic lesions (e.g. with irregular shape and a non-homogeneous uptake) consisted into the combined use of standard anthropomorphic phantoms commercially and irregular molds generated using 3D printer technology and filled with a radioactive chromatic alginate. The proposed segmentation algorithm was feasible in a
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
Nieuwenhout, F; van den Borg, N.; van Sark, W.G.J.H.M.; Turkenburg, W.C.
In order to evaluate the performance of solar home systems (SHS), data on local insolation is a prerequisite. We present the outline of a new method to estimate insolation if direct measurements are unavailable. This method comprises estimation of daily irradiation by correlating photovoltaic
New methods of testing nonlinear hypothesis using iterative NLLS estimator
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.
Erdmann, Włodzimierz S; Kowalczyk, Radosław
2015-01-02
There are several methods for obtaining location of the centre of mass of the whole body. They are based on cadaver data, using volume and density of body parts, using radiation and image techniques. Some researchers treated the trunk as a one part only, while others divided the trunk into few parts. In addition some researchers divided the trunk with planes perpendicular to the longitudinal trunk's axis, although the best approach is to obtain trunk parts as anatomical and functional elements. This procedure was used by Dempster and Erdmann. The latter elaborated personalized estimating of inertial quantities of the trunk, while Clauser et al. gave similar approach for extremities. The aim of the investigation was to merge both indirect methods in order to obtain accurate location of the centre of mass of the whole body. As a reference location a direct method based on reaction board procedure, i.e. with a body lying on a board supported on a scale was used. The location of the centre of mass using Clauser's and Erdmann's method appeared almost identical with the location obtained with a direct method. This approach can be used for several situations, especially for people of different morphology, for the bent trunk, and for asymmetrical movements. Copyright © 2014 Elsevier Ltd. All rights reserved.
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.
View Estimation Based on Value System
Takahashi, Yasutake; Shimada, Kouki; Asada, Minoru
Estimation of a caregiver's view is one of the most important capabilities for a child to understand the behavior demonstrated by the caregiver, that is, to infer the intention of behavior and/or to learn the observed behavior efficiently. We hypothesize that the child develops this ability in the same way as behavior learning motivated by an intrinsic reward, that is, he/she updates the model of the estimated view of his/her own during the behavior imitated from the observation of the behavior demonstrated by the caregiver based on minimizing the estimation error of the reward during the behavior. From this view, this paper shows a method for acquiring such a capability based on a value system from which values can be obtained by reinforcement learning. The parameters of the view estimation are updated based on the temporal difference error (hereafter TD error: estimation error of the state value), analogous to the way such that the parameters of the state value of the behavior are updated based on the TD error. Experiments with simple humanoid robots show the validity of the method, and the developmental process parallel to young children's estimation of its own view during the imitation of the observed behavior of the caregiver is discussed.
Antti T. Kaartinen; Jeremy S. Fried; Paul A. Dunham
2002-01-01
Three Landsat TM-based GIS layers were evaluated as alternatives to conventional, photointerpretation-based stratification of FIA field plots. Estimates for timberland area, timber volume, and volume of down wood were calculated for California's North Coast Survey Unit of 2.5 million hectares. The estimates were compared on the basis of standard errors,...
Kaliszan, Michał
2013-09-01
This paper presents a verification of the thermodynamic model allowing an estimation of the time of death (TOD) by calculating the post mortem interval (PMI) based on a single eyeball temperature measurement at the death scene. The study was performed on 30 cases with known PMI, ranging from 1h 35min to 5h 15min, using pin probes connected to a high precision electronic thermometer (Dostmann-electronic). The measured eye temperatures ranged from 20.2 to 33.1°C. Rectal temperature was measured at the same time and ranged from 32.8 to 37.4°C. Ambient temperatures which ranged from -1 to 24°C, environmental conditions (still air to light wind) and the amount of hair on the head were also recorded every time. PMI was calculated using a formula based on Newton's law of cooling, previously derived and successfully tested in comprehensive studies on pigs and a few human cases. Thanks to both the significantly faster post mortem decrease of eye temperature and a residual or nonexistent plateau effect in the eye, as well as practically no influence of body mass, TOD in the human death cases could be estimated with good accuracy. The highest TOD estimation error during the post mortem intervals up to around 5h was 1h 16min, 1h 14min and 1h 03min, respectively in three cases among 30, while for the remaining 27 cases it was not more than 47min. The mean error for all 30 cases was ±31min. All that indicates that the proposed method is of quite good precision in the early post mortem period, with an accuracy of ±1h for a 95% confidence interval. On the basis of the presented method, TOD can be also calculated at the death scene with the use of a proposed portable electronic device (TOD-meter). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
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...
Pflugradt, Maik; Geissdoerfer, Kai; Goernig, Matthias; Orglmeister, Reinhold
2017-01-14
Automatic detection of ectopic beats has become a thoroughly researched topic, with literature providing manifold proposals typically incorporating morphological analysis of the electrocardiogram (ECG). Although being well understood, its utilization is often neglected, especially in practical monitoring situations like online evaluation of signals acquired in wearable sensors. Continuous blood pressure estimation based on pulse wave velocity considerations is a prominent example, which depends on careful fiducial point extraction and is therefore seriously affected during periods of increased occurring extrasystoles. In the scope of this work, a novel ectopic beat discriminator with low computational complexity has been developed, which takes advantage of multimodal features derived from ECG and pulse wave relating measurements, thereby providing additional information on the underlying cardiac activity. Moreover, the blood pressure estimations' vulnerability towards ectopic beats is closely examined on records drawn from the Physionet database as well as signals recorded in a small field study conducted in a geriatric facility for the elderly. It turns out that a reliable extrasystole identification is essential to unsupervised blood pressure estimation, having a significant impact on the overall accuracy. The proposed method further convinces by its applicability to battery driven hardware systems with limited processing power and is a favorable choice when access to multimodal signal features is given anyway.
Kim, Jinhyun; Jung, Yoomi
2009-08-01
This paper analyzed alternative methods of calculating the conversion factor for nurse-midwife's delivery services in the national health insurance and estimated the optimal reimbursement level for the services. A cost accounting model and Sustainable Growth Rate (SGR) model were developed to estimate the conversion factor of Resource-Based Relative Value Scale (RBRVS) for nurse-midwife's services, depending on the scope of revenue considered in financial analysis. The data and sources from the government and the financial statements from nurse-midwife clinics were used in analysis. The cost accounting model and SGR model showed a 17.6-37.9% increase and 19.0-23.6% increase, respectively, in nurse-midwife fee for delivery services in the national health insurance. The SGR model measured an overall trend of medical expenditures rather than an individual financial status of nurse-midwife clinics, and the cost analysis properly estimated the level of reimbursement for nurse-midwife's services. Normal vaginal delivery in nurse-midwife clinics is considered cost-effective in terms of insurance financing. Upon a declining share of health expenditures on midwife clinics, designing a reimbursement strategy for midwife's services could be an opportunity as well as a challenge when it comes to efficient resource allocation.
Holmes, Lisa; Landsverk, John; Ward, Harriet; Rolls-Reutz, Jennifer; Saldana, Lisa; Wulczyn, Fred; Chamberlain, Patricia
2014-04-01
Estimating costs in child welfare services is critical as new service models are incorporated into routine practice. This paper describes a unit costing estimation system developed in England (cost calculator) together with a pilot test of its utility in the United States where unit costs are routinely available for health services but not for child welfare services. The cost calculator approach uses a unified conceptual model that focuses on eight core child welfare processes. Comparison of these core processes in England and in four counties in the United States suggests that the underlying child welfare processes generated from England were perceived as very similar by child welfare staff in California county systems with some exceptions in the review and legal processes. Overall, the adaptation of the cost calculator for use in the United States child welfare systems appears promising. The paper also compares the cost calculator approach to the workload approach widely used in the United States and concludes that there are distinct differences between the two approaches with some possible advantages to the use of the cost calculator approach, especially in the use of this method for estimating child welfare costs in relation to the incorporation of evidence-based interventions into routine practice.
Aller, D.; Hohl, R.; Mair, F.; Schiesser, H.-H.
2003-04-01
Extreme hailfall can cause massive damage to building structures. For the insurance and reinsurance industry it is essential to estimate the probable maximum hail loss of their portfolio. The probable maximum loss (PML) is usually defined with a return period of 1 in 250 years. Statistical extrapolation has a number of critical points, as historical hail loss data are usually only available from some events while insurance portfolios change over the years. At the moment, footprints are derived from historical hail damage data. These footprints (mean damage patterns) are then moved over a portfolio of interest to create scenario losses. However, damage patterns of past events are based on the specific portfolio that was damaged during that event and can be considerably different from the current spread of risks. A new method for estimating the probable maximum hail loss to a building portfolio is presented. It is shown that footprints derived from historical damages are different to footprints of hail kinetic energy calculated from radar reflectivity measurements. Based on the relationship between radar-derived hail kinetic energy and hail damage to buildings, scenario losses can be calculated. A systematic motion of the hail kinetic energy footprints over the underlying portfolio creates a loss set. It is difficult to estimate the return period of losses calculated with footprints derived from historical damages being moved around. To determine the return periods of the hail kinetic energy footprints over Switzerland, 15 years of radar measurements and 53 years of agricultural hail losses are available. Based on these data, return periods of several types of hailstorms were derived for different regions in Switzerland. The loss set is combined with the return periods of the event set to obtain an exceeding frequency curve, which can be used to derive the PML.
Directory of Open Access Journals (Sweden)
Seyed Bahram Beheshti-Aval
2015-06-01
Full Text Available Displacement Coefficient Method (DCM stipulated in the ASCE 41-06 standard is becoming the preferred method for seismic rehabilitation of buildings in many high-seismic-hazard countries. Applications of the method for non-building constructions such as bridges are beyond the scope of this standard. Thus its application to this kind of structure should be approached with care. Target displacement has reasonable accuracy for buildings with strong columns and weak beams, where there is the development of plastic hinges. Due to high stiffness and strength of the deck relative to the piers in most bridges, this mechanism does not occur, and it is necessary to evaluate the accuracy of DCM for such structures. In this research, an attempt is made to evaluate the credibility of DCM in the ASCE/SEI 41-06 standard for estimating target drifts in concrete regular bridges under strong ground motions. To apply the extension of the method to bridge structures, the definition of new correction factor CB, which should be multiplied to previous coefficients, is required. This novel coefficient can improve the accuracy of the mentioned method in accessing seismic displacement demands. The coefficient is presented for soil types A to D based on NEHRP soil classification. The validity of the modified DCM is examined for several bridges with use of nonlinear dynamic analysis. Good correlation is found between both procedures.
Methods for risk estimation in nuclear energy
Energy Technology Data Exchange (ETDEWEB)
Gauvenet, A [CEA, 75 - Paris (France)
1979-01-01
The author presents methods for estimating the different risks related to nuclear energy: immediate or delayed risks, individual or collective risks, risks of accidents and long-term risks. These methods have attained a highly valid level of elaboration and their application to other industrial or human problems is currently under way, especially in English-speaking countries.
Wong-Loya, J. A.; Santoyo, E.; Andaverde, J. A.; Quiroz-Ruiz, A.
2015-12-01
A Web-Based Computer System (RPM-WEBBSYS) has been developed for the application of the Rational Polynomial Method (RPM) to estimate static formation temperatures (SFT) of geothermal and petroleum wells. The system is also capable to reproduce the full thermal recovery processes occurred during the well completion. RPM-WEBBSYS has been programmed using advances of the information technology to perform more efficiently computations of SFT. RPM-WEBBSYS may be friendly and rapidly executed by using any computing device (e.g., personal computers and portable computing devices such as tablets or smartphones) with Internet access and a web browser. The computer system was validated using bottomhole temperature (BHT) measurements logged in a synthetic heat transfer experiment, where a good matching between predicted and true SFT was achieved. RPM-WEBBSYS was finally applied to BHT logs collected from well drilling and shut-in operations, where the typical problems of the under- and over-estimation of the SFT (exhibited by most of the existing analytical methods) were effectively corrected.
Directory of Open Access Journals (Sweden)
Yusuke Koda
2018-01-01
Full Text Available This paper discusses a measurement method of time-variant attenuation of IEEE 802.11ad wireless LAN signals in the 60 GHz band induced by human blockage. The IEEE 802.11ad access point (AP transmits frames intermittently, not continuously. Thus, to obtain the time-varying signal attenuation, it is required to estimate the duration in which the AP transmitted signals. To estimate whether the AP transmitted signals or not at each sampling point, this paper applies a simple two-state hidden Markov model. In addition, the validity of the model is tested based on Bayesian information criterion in order to prevent model overfitting and consequent invalid results. The measurement method is validated in that the distribution of the time duration in which the signal attenuates by 5 dB is consistent with the existing statistical model and the range of the measured time duration in which the signal attenuation decreases from 5 dB to 0 dB is similar to that in the previous report.
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...
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
Fault sound sources position estimation based on L array method%基于L型阵列的故障声源位置估计
Institute of Scientific and Technical Information of China (English)
刘斌; 栾忠权; 马超; 余周祥
2017-01-01
The traditional method of fault diagnosis is mainly based on the analysis of the vibration, whichhas great limitations in some special circumstances, but the method based on the sound signal from the equipment in the process can solve the problem.A new method for fault diagnosis based on L type acoustic array is presented in this paper.The DOA estimation based on two-dimensional MUSIC is used in radar, and the performance of the algorithm is studied.And with three kinds of different parameterson 2DDOA estimation, the computation is carried out.The comparison with the result of the rectangular arraysis carried out.The resultsshowthat the corresponding algorithm performance is changed while the different parameters have different values.And the method with suitable parameters could be better for the fault diagnosis of the gear drive system.%传统的故障诊断方法主要是基于接触式的振动信号分析,在某些特殊环境下该方法具有很大的局限性,而基于设备运转过程中的声音信号就可以解决该问题.提出了基于L型声阵列的位置估计方法来进行故障诊断,采取了雷达中常用的基于二维MUSIC的DOA估计,并研究了算法的估计性能情况.分别研究了在不同的阵元个数、信噪比和快拍数下的2D-DOA估计的计算机仿真结果,并和基于矩形阵列的DOA估计进行了比较.研究结果表明,在不同的参数下该算法的估计结果也会有很大的不同.所以在选择合适的参数条件下,该算法可以应用于齿轮箱的故障诊断中.
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.
Fasel, Benedikt; Spörri, Jörg; Schütz, Pascal; Lorenzetti, Silvio; Aminian, Kamiar
2017-01-01
For the purpose of gaining a deeper understanding of the relationship between external training load and health in competitive alpine skiing, an accurate and precise estimation of the athlete's kinematics is an essential methodological prerequisite. This study proposes an inertial sensor-based method to estimate the athlete's relative joint center positions and center of mass (CoM) kinematics in alpine skiing. Eleven inertial sensors were fixed to the lower and upper limbs, trunk, and head. The relative positions of the ankle, knee, hip, shoulder, elbow, and wrist joint centers, as well as the athlete's CoM kinematics were validated against a marker-based optoelectronic motion capture system during indoor carpet skiing. For all joints centers analyzed, position accuracy (mean error) was below 110 mm and precision (error standard deviation) was below 30 mm. CoM position accuracy and precision were 25.7 and 6.7 mm, respectively. Both the accuracy and precision of the system to estimate the distance between the ankle of the outside leg and CoM (measure quantifying the skier's overall vertical motion) were found to be below 11 mm. Some poorer accuracy and precision values (below 77 mm) were observed for the athlete's fore-aft position (i.e., the projection of the outer ankle-CoM vector onto the line corresponding to the projection of ski's longitudinal axis on the snow surface). In addition, the system was found to be sensitive enough to distinguish between different types of turns (wide/narrow). Thus, the method proposed in this paper may also provide a useful, pervasive way to monitor and control adverse external loading patterns that occur during regular on-snow training. Moreover, as demonstrated earlier, such an approach might have a certain potential to quantify competition time, movement repetitions and/or the accelerations acting on the different segments of the human body. However, prior to getting feasible for applications in daily training, future studies
Directory of Open Access Journals (Sweden)
Benedikt Fasel
2017-11-01
Full Text Available For the purpose of gaining a deeper understanding of the relationship between external training load and health in competitive alpine skiing, an accurate and precise estimation of the athlete's kinematics is an essential methodological prerequisite. This study proposes an inertial sensor-based method to estimate the athlete's relative joint center positions and center of mass (CoM kinematics in alpine skiing. Eleven inertial sensors were fixed to the lower and upper limbs, trunk, and head. The relative positions of the ankle, knee, hip, shoulder, elbow, and wrist joint centers, as well as the athlete's CoM kinematics were validated against a marker-based optoelectronic motion capture system during indoor carpet skiing. For all joints centers analyzed, position accuracy (mean error was below 110 mm and precision (error standard deviation was below 30 mm. CoM position accuracy and precision were 25.7 and 6.7 mm, respectively. Both the accuracy and precision of the system to estimate the distance between the ankle of the outside leg and CoM (measure quantifying the skier's overall vertical motion were found to be below 11 mm. Some poorer accuracy and precision values (below 77 mm were observed for the athlete's fore-aft position (i.e., the projection of the outer ankle-CoM vector onto the line corresponding to the projection of ski's longitudinal axis on the snow surface. In addition, the system was found to be sensitive enough to distinguish between different types of turns (wide/narrow. Thus, the method proposed in this paper may also provide a useful, pervasive way to monitor and control adverse external loading patterns that occur during regular on-snow training. Moreover, as demonstrated earlier, such an approach might have a certain potential to quantify competition time, movement repetitions and/or the accelerations acting on the different segments of the human body. However, prior to getting feasible for applications in daily training
Kimura, H.; Ito, T.; Tadokoro, K.
2017-12-01
Introduction In southwest Japan, Philippine sea plate is subducting under the overriding plate such as Amurian plate, and mega interplate earthquakes has occurred at about 100 years interval. There is no occurrence of mega interplate earthquakes in southwest Japan, although it has passed about 70 years since the last mega interplate earthquakes: 1944 and 1946 along Nankai trough, meaning that the strain has been accumulated at plate interface. Therefore, it is essential to reveal the interplate coupling more precisely for predicting or understanding the mechanism of next occurring mega interplate earthquake. Recently, seafloor geodetic observation revealed the detailed interplate coupling distribution in expected source region of Nankai trough earthquake (e.g., Yokota et al. [2016]). In this study, we estimated interplate coupling in southwest Japan, considering block motion model and using seafloor geodetic observation data as well as onland GNSS observation data, based on Markov Chain Monte Carlo (MCMC) method. Method Observed crustal deformation is assumed that sum of rigid block motion and elastic deformation due to coupling at block boundaries. We modeled this relationship as a non-linear inverse problem that the unknown parameters are Euler pole of each block and coupling at each subfault, and solved them simultaneously based on MCMC method. Input data we used in this study are 863 onland GNSS observation data and 24 seafloor GPS/A observation data. We made some block division models based on the map of active fault tracing and selected the best model based on Akaike's Information Criterion (AIC): that is consist of 12 blocks. Result We find that the interplate coupling along Nankai trough has heterogeneous spatial distribution, strong at the depth of 0 to 20km at off Tokai region, and 0 to 30km at off Shikoku region. Moreover, we find that observed crustal deformation at off Tokai region is well explained by elastic deformation due to subducting Izu Micro
International Nuclear Information System (INIS)
Ono, H.; Mototani, A.; Kawamura, S.; Abe, N.; Takeuchi, Y.
2004-01-01
The post-BT standard is a new fuel integrity standard or the Atomic Energy Society of Japan that allows temporary boiling transition condition in the evaluation for BWR anticipated operational occurrences. For application of the post-BT standard to BWR anticipated operational occurrences evaluation, it is important to identify which fuel assemblies and which axial, radial positions of fuel rods have temporarily experienced the post-BT condition and to evaluates how high the fuel cladding temperature rise was and how long the dryout duration continued. Therefore, whole bundle simulation, in which each fuel assembly is simulated independently by one thermal-hydraulic component, is considered to be an effective analytical method. In the present study, a best-estimate thermal-hydraulic code, TRACG02, has been modified to extend it predictive capability by implementing the post-BT evaluation model such as the post-BT heat transfer correlation and rewetting correlation and enlarging the number of components used for BWR plant simulation. Based on new evaluation methods, BWR core thermal-hydraulic behavior has been analyzed for typical anticipated operational occurrence conditions. The location where boiling transition occurs and the severity of fuel assembly in the case of boiling transition conditions such as fuel cladding temperature, which are important factors in determining whether the reuse of the fuel assembly can be permitted, were well predicted by the proposed evaluation method. In summary, a new evaluation method for a detailed BWR core thermal-hydraulic analysis based on the post-BT standard of the Atomic Energy Society of Japan has been developed and applied to the evaluation of the post-BT standard during the actual BWR plant anticipated operational occurrences. (author)
Unemployment estimation: Spatial point referenced methods and models
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
Efficient Methods of Estimating Switchgrass Biomass Supplies
Switchgrass (Panicum virgatum L.) is being developed as a biofuel feedstock for the United States. Efficient and accurate methods to estimate switchgrass biomass feedstock supply within a production area will be required by biorefineries. Our main objective was to determine the effectiveness of in...
Coalescent methods for estimating phylogenetic trees.
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.
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...
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.
A Method for Estimating Surveillance Video Georeferences
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Aleksandar Milosavljević
2017-07-01
Full Text Available The integration of a surveillance camera video with a three-dimensional (3D geographic information system (GIS requires the georeferencing of that video. Since a video consists of separate frames, each frame must be georeferenced. To georeference a video frame, we rely on the information about the camera view at the moment that the frame was captured. A camera view in 3D space is completely determined by the camera position, orientation, and field-of-view. Since the accurate measuring of these parameters can be extremely difficult, in this paper we propose a method for their estimation based on matching video frame coordinates of certain point features with their 3D geographic locations. To obtain these coordinates, we rely on high-resolution orthophotos and digital elevation models (DEM of the area of interest. Once an adequate number of points are matched, Levenberg–Marquardt iterative optimization is applied to find the most suitable video frame georeference, i.e., position and orientation of the camera.
Kroll, Lars Eric; Schumann, Maria; Müters, Stephan; Lampert, Thomas
2017-12-01
Nationwide health surveys can be used to estimate regional differences in health. Using traditional estimation techniques, the spatial depth for these estimates is limited due to the constrained sample size. So far - without special refreshment samples - results have only been available for larger populated federal states of Germany. An alternative is regression-based small-area estimation techniques. These models can generate smaller-scale data, but are also subject to greater statistical uncertainties because of the model assumptions. In the present article, exemplary regionalized results based on the studies "Gesundheit in Deutschland aktuell" (GEDA studies) 2009, 2010 and 2012, are compared to the self-rated health status of the respondents. The aim of the article is to analyze the range of regional estimates in order to assess the usefulness of the techniques for health reporting more adequately. The results show that the estimated prevalence is relatively stable when using different samples. Important determinants of the variation of the estimates are the achieved sample size on the district level and the type of the district (cities vs. rural regions). Overall, the present study shows that small-area modeling of prevalence is associated with additional uncertainties compared to conventional estimates, which should be taken into account when interpreting the corresponding findings.
Software Estimation: Developing an Accurate, Reliable Method
2011-08-01
based and size-based estimates is able to accurately plan, launch, and execute on schedule. Bob Sinclair, NAWCWD Chris Rickets , NAWCWD Brad Hodgins...Office by Carnegie Mellon University. SMPSP and SMTSP are service marks of Carnegie Mellon University. 1. Rickets , Chris A, “A TSP Software Maintenance...Life Cycle”, CrossTalk, March, 2005. 2. Koch, Alan S, “TSP Can Be the Building blocks for CMMI”, CrossTalk, March, 2005. 3. Hodgins, Brad, Rickets
A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT
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.
Optical Method for Estimating the Chlorophyll Contents in Plant Leaves.
Pérez-Patricio, Madaín; Camas-Anzueto, Jorge Luis; Sanchez-Alegría, Avisaí; Aguilar-González, Abiel; Gutiérrez-Miceli, Federico; Escobar-Gómez, Elías; Voisin, Yvon; Rios-Rojas, Carlos; Grajales-Coutiño, Ruben
2018-02-22
This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD) meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica , Canavalia ensiforme , and Lycopersicon esculentum . Experimental results showed that-in terms of accuracy and processing speed-the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica , where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.
Optical Method for Estimating the Chlorophyll Contents in Plant Leaves
Directory of Open Access Journals (Sweden)
Madaín Pérez-Patricio
2018-02-01
Full Text Available This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance, a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica, Canavalia ensiforme, and Lycopersicon esculentum. Experimental results showed that—in terms of accuracy and processing speed—the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica, where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.
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
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)
Sallam, Hesham M; Seiffert, Erik R
2016-01-01
The Fayum Depression of Egypt has yielded fossils of hystricognathous rodents from multiple Eocene and Oligocene horizons that range in age from ∼37 to ∼30 Ma and document several phases in the early evolution of crown Hystricognathi and one of its major subclades, Phiomorpha. Here we describe two new genera and species of basal phiomorphs, Birkamys korai and Mubhammys vadumensis, based on rostra and maxillary and mandibular remains from the terminal Eocene (∼34 Ma) Fayum Locality 41 (L-41). Birkamys is the smallest known Paleogene hystricognath, has very simple molars, and, like derived Oligocene-to-Recent phiomorphs (but unlike contemporaneous and older taxa) apparently retained dP(4)∕4 late into life, with no evidence for P(4)∕4 eruption or formation. Mubhammys is very similar in dental morphology to Birkamys, and also shows no evidence for P(4)∕4 formation or eruption, but is considerably larger. Though parsimony analysis with all characters equally weighted places Birkamys and Mubhammys as sister taxa of extant Thryonomys to the exclusion of much younger relatives of that genus, all other methods (standard Bayesian inference, Bayesian "tip-dating," and parsimony analysis with scaled transitions between "fixed" and polymorphic states) place these species in more basal positions within Hystricognathi, as sister taxa of Oligocene-to-Recent phiomorphs. We also employ tip-dating as a means for estimating the ages of early hystricognath-bearing localities, many of which are not well-constrained by geological, geochronological, or biostratigraphic evidence. By simultaneously taking into account phylogeny, evolutionary rates, and uniform priors that appropriately encompass the range of possible ages for fossil localities, dating of tips in this Bayesian framework allows paleontologists to move beyond vague and assumption-laden "stage of evolution" arguments in biochronology to provide relatively rigorous age assessments of poorly-constrained faunas. This
Directory of Open Access Journals (Sweden)
Hesham M. Sallam
2016-03-01
Full Text Available The Fayum Depression of Egypt has yielded fossils of hystricognathous rodents from multiple Eocene and Oligocene horizons that range in age from ∼37 to ∼30 Ma and document several phases in the early evolution of crown Hystricognathi and one of its major subclades, Phiomorpha. Here we describe two new genera and species of basal phiomorphs, Birkamys korai and Mubhammys vadumensis, based on rostra and maxillary and mandibular remains from the terminal Eocene (∼34 Ma Fayum Locality 41 (L-41. Birkamys is the smallest known Paleogene hystricognath, has very simple molars, and, like derived Oligocene-to-Recent phiomorphs (but unlike contemporaneous and older taxa apparently retained dP4∕4 late into life, with no evidence for P4∕4 eruption or formation. Mubhammys is very similar in dental morphology to Birkamys, and also shows no evidence for P4∕4 formation or eruption, but is considerably larger. Though parsimony analysis with all characters equally weighted places Birkamys and Mubhammys as sister taxa of extant Thryonomys to the exclusion of much younger relatives of that genus, all other methods (standard Bayesian inference, Bayesian “tip-dating,” and parsimony analysis with scaled transitions between “fixed” and polymorphic states place these species in more basal positions within Hystricognathi, as sister taxa of Oligocene-to-Recent phiomorphs. We also employ tip-dating as a means for estimating the ages of early hystricognath-bearing localities, many of which are not well-constrained by geological, geochronological, or biostratigraphic evidence. By simultaneously taking into account phylogeny, evolutionary rates, and uniform priors that appropriately encompass the range of possible ages for fossil localities, dating of tips in this Bayesian framework allows paleontologists to move beyond vague and assumption-laden “stage of evolution” arguments in biochronology to provide relatively rigorous age assessments of poorly
2016-01-01
The Fayum Depression of Egypt has yielded fossils of hystricognathous rodents from multiple Eocene and Oligocene horizons that range in age from ∼37 to ∼30 Ma and document several phases in the early evolution of crown Hystricognathi and one of its major subclades, Phiomorpha. Here we describe two new genera and species of basal phiomorphs, Birkamys korai and Mubhammys vadumensis, based on rostra and maxillary and mandibular remains from the terminal Eocene (∼34 Ma) Fayum Locality 41 (L-41). Birkamys is the smallest known Paleogene hystricognath, has very simple molars, and, like derived Oligocene-to-Recent phiomorphs (but unlike contemporaneous and older taxa) apparently retained dP4∕4 late into life, with no evidence for P4∕4 eruption or formation. Mubhammys is very similar in dental morphology to Birkamys, and also shows no evidence for P4∕4 formation or eruption, but is considerably larger. Though parsimony analysis with all characters equally weighted places Birkamys and Mubhammys as sister taxa of extant Thryonomys to the exclusion of much younger relatives of that genus, all other methods (standard Bayesian inference, Bayesian “tip-dating,” and parsimony analysis with scaled transitions between “fixed” and polymorphic states) place these species in more basal positions within Hystricognathi, as sister taxa of Oligocene-to-Recent phiomorphs. We also employ tip-dating as a means for estimating the ages of early hystricognath-bearing localities, many of which are not well-constrained by geological, geochronological, or biostratigraphic evidence. By simultaneously taking into account phylogeny, evolutionary rates, and uniform priors that appropriately encompass the range of possible ages for fossil localities, dating of tips in this Bayesian framework allows paleontologists to move beyond vague and assumption-laden “stage of evolution” arguments in biochronology to provide relatively rigorous age assessments of poorly-constrained faunas
Rosecrance, Richard C.; Johnson, Lee; Soderstrom, Dominic
2016-01-01
Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.
Directory of Open Access Journals (Sweden)
Renxin Xiao
2016-03-01
Full Text Available In order to properly manage lithium-ion batteries of electric vehicles (EVs, it is essential to build the battery model and estimate the state of charge (SOC. In this paper, the fractional order forms of Thevenin and partnership for a new generation of vehicles (PNGV models are built, of which the model parameters including the fractional orders and the corresponding resistance and capacitance values are simultaneously identified based on genetic algorithm (GA. The relationships between different model parameters and SOC are established and analyzed. The calculation precisions of the fractional order model (FOM and integral order model (IOM are validated and compared under hybrid test cycles. Finally, extended Kalman filter (EKF is employed to estimate the SOC based on different models. The results prove that the FOMs can simulate the output voltage more accurately and the fractional order EKF (FOEKF can estimate the SOC more precisely under dynamic conditions.
Farhadian, Maryam; Aliabadi, Mohsen; Darvishi, Ebrahim
2015-01-01
Prediction models are used in a variety of medical domains, and they are frequently built from experience which constitutes data acquired from actual cases. This study aimed to analyze the potential of artificial neural networks and logistic regression techniques for estimation of hearing impairment among industrial workers. A total of 210 workers employed in a steel factory (in West of Iran) were selected, and their occupational exposure histories were analyzed. The hearing loss thresholds of the studied workers were determined using a calibrated audiometer. The personal noise exposures were also measured using a noise dosimeter in the workstations. Data obtained from five variables, which can influence the hearing loss, were used as input features, and the hearing loss thresholds were considered as target feature of the prediction methods. Multilayer feedforward neural networks and logistic regression were developed using MATLAB R2011a software. Based on the World Health Organization classification for the grades of hearing loss, 74.2% of the studied workers have normal hearing thresholds, 23.4% have slight hearing loss, and 2.4% have moderate hearing loss. The accuracy and kappa coefficient of the best developed neural networks for prediction of the grades of hearing loss were 88.6 and 66.30, respectively. The accuracy and kappa coefficient of the logistic regression were also 84.28 and 51.30, respectively. Neural networks could provide more accurate predictions of the hearing loss than logistic regression. The prediction method can provide reliable and comprehensible information for occupational health and medicine experts.
On the Methods for Estimating the Corneoscleral Limbus.
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.
Motion estimation using point cluster method and Kalman filter.
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
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.
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
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
Improved stove programs need robust methods to estimate carbon offsets
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 ...
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.
Information-theoretic methods for estimating of complicated probability distributions
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
Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.
2012-12-01
Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY
Empirical methods for estimating future climatic conditions
International Nuclear Information System (INIS)
Anon.
1990-01-01
Applying the empirical approach permits the derivation of estimates of the future climate that are nearly independent of conclusions based on theoretical (model) estimates. This creates an opportunity to compare these results with those derived from the model simulations of the forthcoming changes in climate, thus increasing confidence in areas of agreement and focusing research attention on areas of disagreements. The premise underlying this approach for predicting anthropogenic climate change is based on associating the conditions of the climatic optimums of the Holocene, Eemian, and Pliocene with corresponding stages of the projected increase of mean global surface air temperature. Provided that certain assumptions are fulfilled in matching the value of the increased mean temperature for a certain epoch with the model-projected change in global mean temperature in the future, the empirical approach suggests that relationships leading to the regional variations in air temperature and other meteorological elements could be deduced and interpreted based on use of empirical data describing climatic conditions for past warm epochs. Considerable care must be taken, of course, in making use of these spatial relationships, especially in accounting for possible large-scale differences that might, in some cases, result from different factors contributing to past climate changes than future changes and, in other cases, might result from the possible influences of changes in orography and geography on regional climatic conditions over time
A comparison of analysis methods to estimate contingency strength.
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.
An RSS based location estimation technique for cognitive relay networks
Qaraqe, Khalid A.; Hussain, Syed Imtiaz; Ç elebi, Hasari Burak; Abdallah, Mohamed M.; Alouini, Mohamed-Slim
2010-01-01
In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine
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.
Ogle, S. M.; DelGrosso, S.; Parton, W. J.
2017-12-01
Soil nitrous oxide emissions from agricultural management are a key source of greenhouse gas emissions in many countries due to the widespread use of nitrogen fertilizers, manure amendments from livestock production, planting legumes and other practices that affect N dynamics in soils. In the United States, soil nitrous oxide emissions have ranged from 250 to 280 Tg CO2 equivalent from 1990 to 2015, with uncertainties around 20-30 percent. A Tier 3 method has been used to estimate the emissions with the DayCent ecosystem model. While the Tier 3 approach is considerably more accurate than IPCC Tier 1 methods, there is still the possibility of biases in emission estimates if there are processes and drivers that are not represented in the modeling framework. Furthermore, a key principle of IPCC guidance is that inventory compilers estimate emissions as accurately as possible. Freeze-thaw cycles and associated hot moments of nitrous oxide emissions are one of key drivers influencing emissions in colder climates, such as the cold temperate climates of the upper Midwest and New England regions of the United States. Freeze-thaw activity interacts with management practices that are increasing N availability in the plant-soil system, leading to greater nitrous oxide emissions during transition periods from winter to spring. Given the importance of this driver, the DayCent model has been revised to incorproate freeze-thaw cycles, and the results suggests that including this driver can significantly modify the emissions estimates in cold temperate climate regions. Consequently, future methodological development to improve estimation of nitrous oxide emissions from soils would benefit from incorporating freeze-thaw cycles into the modeling framework for national territories with a cold climate.
Stoyanova, Detelina; Algee-Hewitt, Bridget F B; Slice, Dennis E
2015-11-01
The pubic symphysis is frequently used to estimate age-at-death from the adult skeleton. Assessment methods require the visual comparison of the bone morphology against age-informative characteristics that represent a series of phases. Age-at-death is then estimated from the age-range previously associated with the chosen phase. While easily executed, the "morphoscopic" process of feature-scoring and bone-to-phase-matching is known to be subjective. Studies of method and practitioner error demonstrate a need for alternative tools to quantify age-progressive change in the pubic symphysis. This article proposes a more objective, quantitative method that analyzes three-dimensional (3D) surface scans of the pubic symphysis using a thin plate spline algorithm (TPS). This algorithm models the bending of a flat plane to approximately match the surface of the bone and minimizes the bending energy required for this transformation. Known age-at-death and bending energy were used to construct a linear model to predict age from observed bending energy. This approach is tested with scans from 44 documented white male skeletons and 12 casts. The results of the surface analysis show a significant association (regression p-value = 0.0002 and coefficient of determination = 0.2270) between the minimum bending energy and age-at-death, with a root mean square error of ≈19 years. This TPS method yields estimates comparable to established methods but offers a fully integrated, objective and quantitative framework of analysis and has potential for use in archaeological and forensic casework. © 2015 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Xiangwei Guo
2016-02-01
Full Text Available An estimation of the power battery state of charge (SOC is related to the energy management, the battery cycle life and the use cost of electric vehicles. When a lithium-ion power battery is used in an electric vehicle, the SOC displays a very strong time-dependent nonlinearity under the influence of random factors, such as the working conditions and the environment. Hence, research on estimating the SOC of a power battery for an electric vehicle is of great theoretical significance and application value. In this paper, according to the dynamic response of the power battery terminal voltage during a discharging process, the second-order RC circuit is first used as the equivalent model of the power battery. Subsequently, on the basis of this model, the least squares method (LS with a forgetting factor and the adaptive unscented Kalman filter (AUKF algorithm are used jointly in the estimation of the power battery SOC. Simulation experiments show that the joint estimation algorithm proposed in this paper has higher precision and convergence of the initial value error than a single AUKF algorithm.
Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.
2002-01-01
The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.
International Nuclear Information System (INIS)
Lee, Seung Min; Kim, Man Cheol; Kim, Jong Hyun; Seong, Poong Hyun
2015-01-01
Highlights: • We analyze the relationship between Out-of-the-Loop and the loss of human operators’ situation awareness. • We propose an ostracism rate estimation method by only considering the negative effects of automation. • The ostracism rate reflects how much automation interrupts human operators to receive information. • The higher the ostracism rate is, the lower the accuracy of human operators’ SA will be. - Abstract: With the introduction of automation in various industries including the nuclear field, its side effect, referred to as the Out-of-the-Loop (OOTL) problem, has emerged as a critical issue that needs to be addressed. Many studies have been attempted to analyze and solve the OOTL problem, but this issue still needs a clear solution to provide criteria for introducing automation. Therefore, a quantitative estimation method for identifying negative effects of automation is proposed in this paper. The representative aspect of the OOTL problem in nuclear power plants (NPPs) is that human operators in automated operations are given less information than human operators in manual operations. In other words, human operators have less opportunity to obtain needed information as automation is introduced. From this point of view, the degree of difficulty in obtaining information from automated systems is defined as the Level of Ostracism (LOO). Using the LOO and information theory, we propose the ostracism rate, which is a new estimation method that expresses how much automation interrupts human operators’ situation awareness. We applied production rules to describe the human operators’ thinking processes, Bayesian inference to describe the production rules mathematically, and information theory to calculate the amount of information that human operators receive through observations. The validity of the suggested method was proven by conducting an experiment. The results show that the ostracism rate was significantly related to the accuracy
Methods to estimate breeding values in honey bees
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
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.
Simple method for quick estimation of aquifer hydrogeological parameters
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.
Method of estimation of scanning system quality
Larkin, Eugene; Kotov, Vladislav; Kotova, Natalya; Privalov, Alexander
2018-04-01
Estimation of scanner parameters is an important part in developing electronic document management system. This paper suggests considering the scanner as a system that contains two main channels: a photoelectric conversion channel and a channel for measuring spatial coordinates of objects. Although both of channels consist of the same elements, the testing of their parameters should be executed separately. The special structure of the two-dimensional reference signal is offered for this purpose. In this structure, the fields for testing various parameters of the scanner are sp atially separated. Characteristics of the scanner are associated with the loss of information when a document is digitized. The methods to test grayscale transmitting ability, resolution and aberrations level are offered.
Estimating North Dakota's Economic Base
Coon, Randal C.; Leistritz, F. Larry
2009-01-01
North Dakota’s economic base is comprised of those activities producing a product paid for by nonresidents, or products exported from the state. North Dakota’s economic base activities include agriculture, mining, manufacturing, tourism, and federal government payments for construction and to individuals. Development of the North Dakota economic base data is important because it provides the information to quantify the state’s economic growth, and it creates the final demand sectors for the N...
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...
International Nuclear Information System (INIS)
Wilson, Brandon M; Smith, Barton L
2013-01-01
Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)
Energy Technology Data Exchange (ETDEWEB)
Bai, Yuxiang; Wang, Jinpeng; Bashari, Mohanad; Hu, Xiuting [The State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122 (China); Feng, Tao [School of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418 (China); Xu, Xueming [The State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122 (China); Jin, Zhengyu, E-mail: jinlab2008@yahoo.com [The State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122 (China); Tian, Yaoqi, E-mail: yqtian@jiangnan.edu.cn [The State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122 (China)
2012-08-10
Highlights: Black-Right-Pointing-Pointer We develop a TGA method for the measurement of the stoichiometric ratio. Black-Right-Pointing-Pointer A series of formulas are deduced to calculate the stoichiometric ratio. Black-Right-Pointing-Pointer Four {alpha}-CD-based inclusion complexes were successfully prepared. Black-Right-Pointing-Pointer The developed method is applicable. - Abstract: An approach mainly based on thermogravimetric analysis (TGA) was developed to evaluate the stoichiometric ratio (SR, guest to host) of the guest-{alpha}-cyclodextrin (Guest-{alpha}-CD) inclusion complexes (4-cresol-{alpha}-CD, benzyl alcohol-{alpha}-CD, ferrocene-{alpha}-CD and decanoic acid-{alpha}-CD). The present data obtained from Fourier transform-infrared (FT-IR) spectroscopy showed that all the {alpha}-CD-based inclusion complexes were successfully prepared in a solid-state form. The stoichiometric ratios of {alpha}-CD to the relative guests (4-cresol, benzyl alcohol, ferrocene and decanoic acid) determined by the developed method were 1:1, 1:2, 2:1 and 1:2, respectively. These SR data were well demonstrated by the previously reported X-ray diffraction (XRD) method and the NMR confirmatory experiments, except the SR of decanoic acid with a larger size and longer chain was not consistent. It is, therefore, suggested that the TGA-based method is applicable to follow the stoichiometric ratio of the polycrystalline {alpha}-CD-based inclusion complexes with smaller and shorter chain guests.
International Nuclear Information System (INIS)
Bai, Yuxiang; Wang, Jinpeng; Bashari, Mohanad; Hu, Xiuting; Feng, Tao; Xu, Xueming; Jin, Zhengyu; Tian, Yaoqi
2012-01-01
Highlights: ► We develop a TGA method for the measurement of the stoichiometric ratio. ► A series of formulas are deduced to calculate the stoichiometric ratio. ► Four α-CD-based inclusion complexes were successfully prepared. ► The developed method is applicable. - Abstract: An approach mainly based on thermogravimetric analysis (TGA) was developed to evaluate the stoichiometric ratio (SR, guest to host) of the guest–α-cyclodextrin (Guest-α-CD) inclusion complexes (4-cresol-α-CD, benzyl alcohol-α-CD, ferrocene-α-CD and decanoic acid-α-CD). The present data obtained from Fourier transform-infrared (FT-IR) spectroscopy showed that all the α-CD-based inclusion complexes were successfully prepared in a solid-state form. The stoichiometric ratios of α-CD to the relative guests (4-cresol, benzyl alcohol, ferrocene and decanoic acid) determined by the developed method were 1:1, 1:2, 2:1 and 1:2, respectively. These SR data were well demonstrated by the previously reported X-ray diffraction (XRD) method and the NMR confirmatory experiments, except the SR of decanoic acid with a larger size and longer chain was not consistent. It is, therefore, suggested that the TGA-based method is applicable to follow the stoichiometric ratio of the polycrystalline α-CD-based inclusion complexes with smaller and shorter chain guests.
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.
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...
International Nuclear Information System (INIS)
Zakharov, L.N.; Markovskij, D.V.; Frank-Kamenetskij, A.D.; Shatalov, G.E.
1978-01-01
The program for shaping neutron microconstants for calculations by means of the Monte-Carlo method, oriented on the detailed consideration of processes in the quick region. The initial information is files of the estimated datea within the UKNDL formate. The method combines the group approach to representation of the process probability and anisotropy of the elastic scattering with the individual description of the secondary neutron spectra of non-elastic processes. The NEDAM program is written in the FORTRAN language for BESM-6 computer and has the following characteristics: the initial file length of the evaluated data is 20000 words, the multigroup constant file length equals 8000 words, the MARK massive length equals 1000 words. The calculation time of a single variant equals 1-2 min
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
Optimal difference-based estimation for partially linear models
Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun
2017-01-01
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
Optimal difference-based estimation for partially linear models
Zhou, Yuejin
2017-12-16
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
ESTIMATION OF STATURE BASED ON FOOT LENGTH
Directory of Open Access Journals (Sweden)
Vidyullatha Shetty
2015-01-01
Full Text Available BACKGROUND : Stature is the height of the person in the upright posture. It is an important measure of physical identity. Estimation of body height from its segments or dismember parts has important considerations for identifications of living or dead human body or remains recovered from disasters or other similar conditions. OBJECTIVE : Stature is an important indicator for identification. There are numerous means to establish stature and their significance lies in the simplicity of measurement, applicability and accuracy in prediction. Our aim of the study was to review the relationship between foot length and body height. METHODS : The present study reviews various prospective studies which were done to estimate the stature. All the measurements were taken by using standard measuring devices and standard anthropometric techniques. RESULTS : This review shows there is a correlation between stature and foot dimensions it is found to be positive and statistically highly significant. Prediction of stature was found to be most accurate by multiple regression analysis. CONCLUSIONS : Stature and gender estimation can be done by using foot measurements and stud y will help in medico - legal cases in establishing identity of an individual and this would be useful for Anatomists and Anthropologists to calculate stature based on foot length
van der Ham, Wim; Klein, Michel; Tabatabaei, Seyed Amin; Thilakarathne, Dilhan; Treur, Jan
Smart thermostats can play an important role in achieving more economic energy usage in domestic situations. This paper focuses on the energy used for natural gas-based heating, and monitoring of gas usages versus indoor and outdoor temperatures over time. Two methods are presented that enable the
Internal Dosimetry Intake Estimation using Bayesian Methods
International Nuclear Information System (INIS)
Miller, G.; Inkret, W.C.; Martz, H.F.
1999-01-01
New methods for the inverse problem of internal dosimetry are proposed based on evaluating expectations of the Bayesian posterior probability distribution of intake amounts, given bioassay measurements. These expectation integrals are normally of very high dimension and hence impractical to use. However, the expectations can be algebraically transformed into a sum of terms representing different numbers of intakes, with a Poisson distribution of the number of intakes. This sum often rapidly converges, when the average number of intakes for a population is small. A simplified algorithm using data unfolding is described (UF code). (author)
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.)
Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods
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.
Schneider, Ulrike; Kleindienst, Julia
2016-09-01
Providing informal care can be both a burden and a source of satisfaction. To understand the welfare effect on caregivers, we need an estimate of the 'shadow value' of informal care, an imputed value for the non-market activity. We use data from the 2006-2007 Survey of Health Ageing and Retirement in Europe which offers the needed details on 29,471 individuals in Austria, Belgium, the Czech Republic, Denmark, France, Germany, Italy, the Netherlands, Poland, Spain, Sweden and Switzerland. Of these, 9768 are unpaid non-co-resident caregivers. To estimate net costs, we follow the subjective well-being valuation method, modelling respondents' life satisfaction as a product of informal care provision, income and personal characteristics, then expressing the relation between satisfaction and care as a monetary amount. We estimate a positive net effect of providing mode rate amounts of informal care, equivalent to €93 for an hour of care/week provided by a caregiver at the median income. The net effect appears to turn negative for greater high care burdens (over 30 hours/week). Interestingly, the effects of differences in care situation are at least an order of magnitude larger. We find that carers providing personal care are significantly more satisfied than those primarily giving help with housework, a difference equivalent to €811 a year at the median income. The article makes two unique contributions to knowledge. The first is its quantifying a net benefit to moderately time-intensive out-of-home caregivers. The second is its clear demonstration of the importance of heterogeneity of care burden on different subgroups. Care-giving context and specific activities matter greatly, pointing to the need for further work on targeting interventions at those caregivers most in need of them. © 2015 John Wiley & Sons Ltd.
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.
Li, Jing; Wang, Min-Yan; Zhang, Jian; He, Wan-Qing; Nie, Lei; Shao, Xia
2013-12-01
VOCs emission from petrochemical storage tanks is one of the important emission sources in the petrochemical industry. In order to find out the VOCs emission amount of petrochemical storage tanks, Tanks 4.0.9d model is utilized to calculate the VOCs emission from different kinds of storage tanks. VOCs emissions from a horizontal tank, a vertical fixed roof tank, an internal floating roof tank and an external floating roof tank were calculated as an example. The consideration of the site meteorological information, the sealing information, the tank content information and unit conversion by using Tanks 4.0.9d model in China was also discussed. Tanks 4.0.9d model can be used to estimate VOCs emissions from petrochemical storage tanks in China as a simple and highly accurate method.
Directory of Open Access Journals (Sweden)
Hongxing Liu
2013-01-01
Full Text Available As an important component of urban vegetation, street trees play an important role in maintenance of environmental quality, aesthetic beauty of urban landscape, and social service for inhabitants. Acquiring accurate and up-to-date inventory information for street trees is required for urban horticultural planning, and municipal urban forest management. This paper presents a new Voxel-based Marked Neighborhood Searching (VMNS method for efficiently identifying street trees and deriving their morphological parameters from Mobile Laser Scanning (MLS point cloud data. The VMNS method consists of six technical components: voxelization, calculating values of voxels, searching and marking neighborhoods, extracting potential trees, deriving morphological parameters, and eliminating pole-like objects other than trees. The method is validated and evaluated through two case studies. The evaluation results show that the completeness and correctness of our method for street tree detection are over 98%. The derived morphological parameters, including tree height, crown diameter, diameter at breast height (DBH, and crown base height (CBH, are in a good agreement with the field measurements. Our method provides an effective tool for extracting various morphological parameters for individual street trees from MLS point cloud data.
Directory of Open Access Journals (Sweden)
Jorge Yunta
2018-02-01
Full Text Available Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire’s loss of grip and estimations of the lateral friction coefficient.
Yunta, Jorge; Garcia-Pozuelo, Daniel; Diaz, Vicente; Olatunbosun, Oluremi
2018-02-06
Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire's loss of grip and estimations of the lateral friction coefficient.
A new DOD and DOA estimation method for MIMO radar
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.
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.
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.)
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.
International Nuclear Information System (INIS)
Hou Jieli
1999-01-01
Based on the computing principle given in ICRP-30, a method had been given by the author for fast estimating internal dose from an intake of mixed fission products after nuclear accident. Following the ICRP-66 Human respiratory tract model published in 1994, the method was reconstructed. The doses of 1 Bq intake of mixed fission products (its AMAD = 1 μm, decay rate coefficient n = 0.2∼2.0) during the period of 1∼15 d after an accident were calculated. It is lower slightly based on ICRP 1994 respiratory tract model than that based on ICRP-30 model
Directory of Open Access Journals (Sweden)
Michal Vondra
2009-01-01
Full Text Available The application of methods based on measurements of photosynthesis efficiency is now more and more popular and used not only for the evaluation of the efficiency of herbicides but also for the estimation of their phytotoxicity to the cultivated crop. These methods enable to determine also differences in the sensitivity of cultivars and/or hybrids to individual herbicides. The advantage of these methods consists above all in the speed and accuracy of measuring.In a field experiment, the sensitivity of several selected grain maize hybrids (EDENSTAR, NK AROBASE, NK LUGAN, LG 33.30 and NK THERMO to the herbicide CALLISTO 480 SC + ATPLUS 463 was tested for a period of three years. The sensitivity to a registered dose of 0.25 l . ha−1 + 0.5 % was measured by means of the apparatus PS1 meter, which could measure the reflected radiation. Measurements of sensitivity of hybrids were performed on the 2nd, 3rd, 4th, 5th and 8th day after the application of the tested herbicide, i.e. in the growing stage of the 3rd–5th leaf. Plant material was harvested using a small-plot combine harvester SAMPO 2010. Samples were weighed and converted to the yield with 15 % of moisture in grain DM.The obtained three-year results did not demonstrate differences in sensitivity of tested hybrids to the registered dose of the herbicide CALLISTO 480 SC + ATPLUS 463 (i.e. 0.25 l . ha−1 + 0,5 %. Recorded results indicated that for the majority of tested hybrids the most critical were the 4th and the 5th day after the application; on these days the average PS1 values were the highest at all. In years 2005 and 2007, none of the tested hybrids exceeded the limit value 15 (which indicated a certain decrease in the efficiency of photosynthesis. Although in 2006 three of tested hybrids showed a certain decrease in photosynthetic activity (i.e. EDENSTAR and NK AROBASE on the 3rd day and NK LUGAN on the 2nd–4th day after the application, no visual symptoms
Hydrological model uncertainty due to spatial evapotranspiration estimation methods
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.
Bayesian methods to estimate urban growth potential
Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.
2017-01-01
Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.
The MIRD method of estimating absorbed dose
International Nuclear Information System (INIS)
Weber, D.A.
1991-01-01
The estimate of absorbed radiation dose from internal emitters provides the information required to assess the radiation risk associated with the administration of radiopharmaceuticals for medical applications. The MIRD (Medical Internal Radiation Dose) system of dose calculation provides a systematic approach to combining the biologic distribution data and clearance data of radiopharmaceuticals and the physical properties of radionuclides to obtain dose estimates. This tutorial presents a review of the MIRD schema, the derivation of the equations used to calculate absorbed dose, and shows how the MIRD schema can be applied to estimate dose from radiopharmaceuticals used in nuclear medicine
Psychological methods of subjective risk estimates
International Nuclear Information System (INIS)
Zimolong, B.
1980-01-01
Reactions to situations involving risks can be divided into the following parts/ perception of danger, subjective estimates of the risk and risk taking with respect to action. Several investigations have compared subjective estimates of the risk with an objective measure of that risk. In general there was a mis-match between subjective and objective measures of risk, especially, objective risk involved in routine activities is most commonly underestimated. This implies, for accident prevention, that attempts must be made to induce accurate subjective risk estimates by technical and behavioural measures. (orig.) [de
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.
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....
Statistical inference based on latent ability estimates
Hoijtink, H.J.A.; Boomsma, A.
The quality of approximations to first and second order moments (e.g., statistics like means, variances, regression coefficients) based on latent ability estimates is being discussed. The ability estimates are obtained using either the Rasch, oi the two-parameter logistic model. Straightforward use
PERFORMANCE ANALYSIS OF METHODS FOR ESTIMATING ...
African Journals Online (AJOL)
2014-12-31
Dec 31, 2014 ... speed is the most significant parameter of the wind energy. ... wind-powered generators and applied to estimate potential power output at various ...... Wind and Solar Power Systems, U.S. Merchant Marine Academy Kings.
Estimation methods for special nuclear materials holdup
International Nuclear Information System (INIS)
Pillay, K.K.S.; Picard, R.R.
1984-01-01
The potential value of statistical models for the estimation of residual inventories of special nuclear materials was examined using holdup data from processing facilities and through controlled experiments. Although the measurement of hidden inventories of special nuclear materials in large facilities is a challenging task, reliable estimates of these inventories can be developed through a combination of good measurements and the use of statistical models. 7 references, 5 figures
Statistical methods of estimating mining costs
Long, K.R.
2011-01-01
Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.
Seasonal adjustment methods and real time trend-cycle estimation
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...
Dual ant colony operational modal analysis parameter estimation method
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.
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.
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.
Solar radiation estimation based on the insolation
International Nuclear Information System (INIS)
Assis, F.N. de; Steinmetz, S.; Martins, S.R.; Mendez, M.E.G.
1998-01-01
A series of daily global solar radiation data measured by an Eppley pyranometer was used to test PEREIRA and VILLA NOVA’s (1997) model to estimate the potential of radiation based on the instantaneous values measured at solar noon. The model also allows to estimate the parameters of PRESCOTT’s equation (1940) assuming a = 0,29 cosj. The results demonstrated the model’s validity for the studied conditions. Simultaneously, the hypothesis of generalizing the use of the radiation estimative formulas based on insolation, and using K = Ko (0,29 cosj + 0,50 n/N), was analysed and confirmed [pt
Particle filter based MAP state estimation: A comparison
Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha
2009-01-01
MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi
Observer-Based Human Knee Stiffness Estimation.
Misgeld, Berno J E; Luken, Markus; Riener, Robert; Leonhardt, Steffen
2017-05-01
We consider the problem of stiffness estimation for the human knee joint during motion in the sagittal plane. The new stiffness estimator uses a nonlinear reduced-order biomechanical model and a body sensor network (BSN). The developed model is based on a two-dimensional knee kinematics approach to calculate the angle-dependent lever arms and the torques of the muscle-tendon-complex. To minimize errors in the knee stiffness estimation procedure that result from model uncertainties, a nonlinear observer is developed. The observer uses the electromyogram (EMG) of involved muscles as input signals and the segmental orientation as the output signal to correct the observer-internal states. Because of dominating model nonlinearities and nonsmoothness of the corresponding nonlinear functions, an unscented Kalman filter is designed to compute and update the observer feedback (Kalman) gain matrix. The observer-based stiffness estimation algorithm is subsequently evaluated in simulations and in a test bench, specifically designed to provide robotic movement support for the human knee joint. In silico and experimental validation underline the good performance of the knee stiffness estimation even in the cases of a knee stiffening due to antagonistic coactivation. We have shown the principle function of an observer-based approach to knee stiffness estimation that employs EMG signals and segmental orientation provided by our own IPANEMA BSN. The presented approach makes realtime, model-based estimation of knee stiffness with minimal instrumentation possible.
Tong, X. X.; Hu, B.; Xu, W. S.; Liu, J. G.; Zhang, P. C.
2017-12-01
In this paper, Three Gorges Reservoir Area (TGRA) was chosen to be the study area, the export coefficients of different land-use type were calculated through the observation experiments and literature consultation, and then the load of non-point source (NPS) nitrogen and phosphorus of different pollution sources such as farmland pollution sources, decentralized livestock and poultry breeding pollution sources and domestic pollution sources were estimated. The results show as follows: the pollution load of dry land is the main source of farmland pollution. The order of total nitrogen load of different pollution sources from high to low is livestock breeding pollution, domestic pollution, land use pollution, while the order of phosphorus load of different pollution sources from high to low is land use pollution, livestock breeding pollution, domestic pollution, Therefore, reasonable farmland management, effective control methods of dry land fertilization and sewage discharge of livestock breeding are the keys to the prevention and control of NPS nitrogen and phosphorus in TGRA.
Methods to estimate irrigated reference crop evapotranspiration - a review.
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.
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
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....
Influence function method for fast estimation of BWR core performance
International Nuclear Information System (INIS)
Rahnema, F.; Martin, C.L.; Parkos, G.R.; Williams, R.D.
1993-01-01
The model, which is based on the influence function method, provides rapid estimate of important quantities such as margins to fuel operating limits, the effective multiplication factor, nodal power and void and bundle flow distributions as well as the traversing in-core probe (TIP) and local power range monitor (LPRM) readings. The fast model has been incorporated into GE's three-dimensional core monitoring system (3D Monicore). In addition to its predicative capability, the model adapts to LPRM readings in the monitoring mode. Comparisons have shown that the agreement between the results of the fast method and those of the standard 3D Monicore is within a few percent. (orig.)
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
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.
Estimating monthly temperature using point based interpolation techniques
Saaban, Azizan; Mah Hashim, Noridayu; Murat, Rusdi Indra Zuhdi
2013-04-01
This paper discusses the use of point based interpolation to estimate the value of temperature at an unallocated meteorology stations in Peninsular Malaysia using data of year 2010 collected from the Malaysian Meteorology Department. Two point based interpolation methods which are Inverse Distance Weighted (IDW) and Radial Basis Function (RBF) are considered. The accuracy of the methods is evaluated using Root Mean Square Error (RMSE). The results show that RBF with thin plate spline model is suitable to be used as temperature estimator for the months of January and December, while RBF with multiquadric model is suitable to estimate the temperature for the rest of the months.
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.
Directory of Open Access Journals (Sweden)
Keča Ljiljana
2011-01-01
Full Text Available Cost-effectiveness of polar cultivation was analyzed based on one of the indicators for the assessment of agriculture and forestry projects - cost-benefit (r. Poplar plantations of the clone I-214 of different rotations and on different soil types were analyzed in the area of Ravni Srem. The aim of the study was to evaluate the justification of the invested financial means in wood production in poplar plantations, based on the analysis of costs and receipts at different plantation ages, using the cost-benefit method. It was found that in all 13 analyzed compartments, the average cost-benefit ratio was 0.36. This means that the costs at the discount rate of 12% are about 2.8 times higher than the receipts. Accordingly, it can be asserted that it is economically unjustified to invest in the projected stands, but only in the case when the value of social capital accounts for 12%. Based on the analysis of sensitivity of the cost-benefit method, it was concluded that cost benefit ratio for p=8-12% was below 1 within the study range of costs and receipts changes, while for p=4-6% this ratio was above 1 in some cases of decrease in costs, i.e. increase in receipts. It was noted that the change in r depending on the change in costs, developed by the exponential function, and the change in r depending on the change in receipts developed by the linear function. Also, it was concluded that at the lower discount rates, the values of r moved towards 1, so for 8% r=0.71, and for 6% r=0.94. The value at the discount rate of 4% indicates that the project is cost-effective and that the invested € 1 makes € 1.22. This fact is especially important when poplar cultivation projects are ranked. For this reason, this method is used for the evaluation of social benefits, i.e. for economic analyses. It is almost never applied in the analysis of private investments.
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.
A method to estimate stellar ages from kinematical data
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.
A Novel Nonlinear Parameter Estimation Method of Soft Tissues
Directory of Open Access Journals (Sweden)
Qianqian Tong
2017-12-01
Full Text Available The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values. To provide highly precise data for estimating nonlinear parameters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine (WCFM_SVM. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young’s modulus and Poisson’s ratio to avoid solving complicated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg–Marquardt (LM algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM_SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.
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)
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
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
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...
Head pose estimation algorithm based on deep learning
Cao, Yuanming; Liu, Yijun
2017-05-01
Head pose estimation has been widely used in the field of artificial intelligence, pattern recognition and intelligent human-computer interaction and so on. Good head pose estimation algorithm should deal with light, noise, identity, shelter and other factors robustly, but so far how to improve the accuracy and robustness of attitude estimation remains a major challenge in the field of computer vision. A method based on deep learning for pose estimation is presented. Deep learning with a strong learning ability, it can extract high-level image features of the input image by through a series of non-linear operation, then classifying the input image using the extracted feature. Such characteristics have greater differences in pose, while they are robust of light, identity, occlusion and other factors. The proposed head pose estimation is evaluated on the CAS-PEAL data set. Experimental results show that this method is effective to improve the accuracy of pose estimation.
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.
Hexographic Method of Complex Town-Planning Terrain Estimate
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
International Nuclear Information System (INIS)
Jarry, G; De Marco, J J; Beifuss, U; Cagnon, C H; McNitt-Gray, M F
2003-01-01
The purpose of this work is to develop and test a method to estimate the relative and absolute absorbed radiation dose from axial and spiral CT scans using a Monte Carlo approach. Initial testing was done in phantoms and preliminary results were obtained from a standard mathematical anthropomorphic model (MIRD V) and voxelized patient data. To accomplish this we have modified a general purpose Monte Carlo transport code (MCNP4B) to simulate the CT x-ray source and movement, and then to calculate absorbed radiation dose in desired objects. The movement of the source in either axial or spiral modes was modelled explicitly while the CT system components were modelled using published information about x-ray spectra as well as information provided by the manufacturer. Simulations were performed for single axial scans using the head and body computed tomography dose index (CTDI) polymethylmethacrylate phantoms at both central and peripheral positions for all available beam energies and slice thicknesses. For comparison, corresponding physical measurements of CTDI in phantom were made with an ion chamber. To obtain absolute dose values, simulations and measurements were performed in air at the scanner isocentre for each beam energy. To extend the verification, the CT scanner model was applied to the MIRD V model and compared with published results using similar technical factors. After verification of the model, the generalized source was simulated and applied to voxelized models of patient anatomy. The simulated and measured absolute dose data in phantom agreed to within 2% for the head phantom and within 4% for the body phantom at 120 and 140 kVp; this extends to 8% for the head and 9% for the body phantom across all available beam energies and positions. For the head phantom, the simulated and measured absolute dose data agree to within 2% across all slice thicknesses at 120 kVp. Our results in the MIRD phantom agree within 11% of all the different organ dose values
Risk Probability Estimating Based on Clustering
DEFF Research Database (Denmark)
Chen, Yong; Jensen, Christian D.; Gray, Elizabeth
2003-01-01
of prior experiences, recommendations from a trusted entity or the reputation of the other entity. In this paper we propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models...... from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based...
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)
Thermodynamic properties of organic compounds estimation methods, principles and practice
Janz, George J
1967-01-01
Thermodynamic Properties of Organic Compounds: Estimation Methods, Principles and Practice, Revised Edition focuses on the progression of practical methods in computing the thermodynamic characteristics of organic compounds. Divided into two parts with eight chapters, the book concentrates first on the methods of estimation. Topics presented are statistical and combined thermodynamic functions; free energy change and equilibrium conversions; and estimation of thermodynamic properties. The next discussions focus on the thermodynamic properties of simple polyatomic systems by statistical the
Directory of Open Access Journals (Sweden)
Rachel Lugassi
2015-06-01
Full Text Available The main objective of the present study was to apply a slope-based spectral method to both dry and fresh pasture vegetation. Differences in eight spectral ranges were identified across the near infrared-shortwave infrared (NIR-SWIR that were indicative of changes in chemical properties. Slopes across these ranges were calculated and a partial least squares (PLS analytical model was constructed for the slopes vs. crude protein (CP and neutral detergent fiber (NDF contents. Different datasets with different numbers of fresh/dry samples were constructed to predict CP and NDF contents. When using a mixed-sample dataset with dry-to-fresh ratios of 85%:15% and 75%:25%, the correlations of CP (R2 = 0.95, in both and NDF (R2 = 0.84 and 0.82, respectively were almost as high as when using only dry samples (0.97 and 0.85, respectively. Furthermore, satisfactory correlations were obtained with a dry-to-fresh ratio of 50%:50% for CP (R2 = 0.92. The results of our study are especially encouraging because CP and NDF contents could be predicted even though some of the selected spectral regions were directly affected by atmospheric water vapor or water in the plants.
Directory of Open Access Journals (Sweden)
Nicanor R. S. Pinto
1997-10-01
detectar los casos de diabetes mellitus previamente diagnosticados y se recomienda su uso para evaluaciones o planeamiento de servicios de salud. La medición de glucemia en ayunas (M3 como método exclusivo no reportó ventajas sobre el cuestionario individual (M2. Entre los métodos combinados o múltiples, la glucemia en ayunas junto con el cuestionario individual (M4 fue eficiente en relación con M5, que incorpora la glucemia a las 2 horas después de la ingestión de una sobrecarga oral de glucosa.To aid in the search for more practical and reliable methods for use in population-based studies of diabetes mellitus, this article compares five ways of estimating prevalence rates. The analysis was performed on secondary data from a cross-sectional study of a cluster sample of the adult population in nine state capitals in Brazil. The original study was carried out from 1986 to 1988. The 21 846 participants were classified as diabetic or not diabetic by five different methods: household questionnaires administered to the entire sample population (M1; individual questionnaires administered to the selected population (M2; measurement of fasting glucose levels in capillary blood, with levels > or = 120 mg/dL as the cutoff (M3; individual questionnaire and fasting capillary blood glucose > or = 120 mg/dL (M4; and individual questionnaire plus fasting capillary blood glucose > or = 200 mg/dL and capillary glucose 2 hours after oral glucose loading > or = 200 mg/dL (M5. Agreement between the methods was determined by comparison of the rates obtained and use of the kappa coefficient. The age-adjusted prevalence rates of diabetes varied according to the method used. Values obtained with M1 were lower than those indicated by M2; M3 values were higher than M2 values, except in the age group 60-69 years; and with M5 the rates were higher than with M4, except among persons 30-39 years old. With regard to the age-adjusted rates found by the various methods, M1 detected 84% of the M2
System and method for correcting attitude estimation
Josselson, Robert H. (Inventor)
2010-01-01
A system includes an angular rate sensor disposed in a vehicle for providing angular rates of the vehicle, and an instrument disposed in the vehicle for providing line-of-sight control with respect to a line-of-sight reference. The instrument includes an integrator which is configured to integrate the angular rates of the vehicle to form non-compensated attitudes. Also included is a compensator coupled across the integrator, in a feed-forward loop, for receiving the angular rates of the vehicle and outputting compensated angular rates of the vehicle. A summer combines the non-compensated attitudes and the compensated angular rates of the to vehicle to form estimated vehicle attitudes for controlling the instrument with respect to the line-of-sight reference. The compensator is configured to provide error compensation to the instrument free-of any feedback loop that uses an error signal. The compensator may include a transfer function providing a fixed gain to the received angular rates of the vehicle. The compensator may, alternatively, include a is transfer function providing a variable gain as a function of frequency to operate on the received angular rates of the vehicle.
Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.
2013-01-01
The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.
Teletactile System Based on Mechanical Properties Estimation
Directory of Open Access Journals (Sweden)
Mauro M. Sette
2011-01-01
Full Text Available Tactile feedback is a major missing feature in minimally invasive procedures; it is an essential means of diagnosis and orientation during surgical procedures. Previous works have presented a remote palpation feedback system based on the coupling between a pressure sensor and a general haptic interface. Here a new approach is presented based on the direct estimation of the tissue mechanical properties and finally their presentation to the operator by means of a haptic interface. The approach presents different technical difficulties and some solutions are proposed: the implementation of a fast Young’s modulus estimation algorithm, the implementation of a real time finite element model, and finally the implementation of a stiffness estimation approach in order to guarantee the system’s stability. The work is concluded with an experimental evaluation of the whole system.
Control and estimation methods over communication networks
Mahmoud, Magdi S
2014-01-01
This book provides a rigorous framework in which to study problems in the analysis, stability and design of networked control systems. Four dominant sources of difficulty are considered: packet dropouts, communication bandwidth constraints, parametric uncertainty, and time delays. Past methods and results are reviewed from a contemporary perspective, present trends are examined, and future possibilities proposed. Emphasis is placed on robust and reliable design methods. New control strategies for improving the efficiency of sensor data processing and reducing associated time delay are presented. The coverage provided features: · an overall assessment of recent and current fault-tolerant control algorithms; · treatment of several issues arising at the junction of control and communications; · key concepts followed by their proofs and efficient computational methods for their implementation; and · simulation examples (including TrueTime simulations) to...
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...
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 ...
Analytical Method to Estimate the Complex Permittivity of Oil Samples
Directory of Open Access Journals (Sweden)
Lijuan Su
2018-03-01
Full Text Available In this paper, an analytical method to estimate the complex dielectric constant of liquids is presented. The method is based on the measurement of the transmission coefficient in an embedded microstrip line loaded with a complementary split ring resonator (CSRR, which is etched in the ground plane. From this response, the dielectric constant and loss tangent of the liquid under test (LUT can be extracted, provided that the CSRR is surrounded by such LUT, and the liquid level extends beyond the region where the electromagnetic fields generated by the CSRR are present. For that purpose, a liquid container acting as a pool is added to the structure. The main advantage of this method, which is validated from the measurement of the complex dielectric constant of olive and castor oil, is that reference samples for calibration are not required.
Li, Tingting; Cheng, Zhengguo; Zhang, Le
2017-01-01
Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency. PMID:29194393
Directory of Open Access Journals (Sweden)
Tingting Li
2017-12-01
Full Text Available Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency.
Directory of Open Access Journals (Sweden)
Keča Ljiljana
2011-01-01
Full Text Available Poplar plantations are a category of fixed assets in forestry, i.e. the assets with a biological character. They are related to their site, they are cultivated for a relatively long time and they have a relatively long utilization cycle, with the yield development determined by the plantation growth and age. Plantations transfer their value gradually to the obtained products during the period of their harvesting, and, by the realization of the products, the means invested in the plantation establishment are reproduced. The period of investments in poplar growing can be relatively long, and so is the period of harvesting. Therefore, it is important to determine the time of the return of the capital invested in these and similar plantations. This paper presents the analysis of commercial profitability of poplar cultivation according to the indicator for the assessment of projects in agriculture and forestry - pay back period. The application of pay back period (PBP calculation can affect greatly the reliability of predicting the degree of economic effectiveness of investments, and also the potential risks for the investor in his decisions on the investments in poplar cultivation. The analysis of poplar clone I-214 plantations was carried out in the area of Ravni Srem, under different rotations and soil types. Based on the analysis of costs and receipts in different plantation ages, and using the method of pay back period, the objective of the study was to evaluate the possible pay back period of invested capital in wood production in poplar plantations. PBP is practically unacceptable by the investor under the discount rate of 6%. The most favorable situation is in the youngest stands, using the discount rate of 2%. The situation regarding the pay back period in the over-aged stands is utterly unfavorable, so the credit cannot be repaid under any conditions. This fact supports the idea that the production cycle length should be shortened.
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)
Directory of Open Access Journals (Sweden)
Taimoor Zahid
2016-09-01
Full Text Available Battery energy storage management for electric vehicles (EV and hybrid EV is the most critical and enabling technology since the dawn of electric vehicle commercialization. A battery system is a complex electrochemical phenomenon whose performance degrades with age and the existence of varying material design. Moreover, it is very tedious and computationally very complex to monitor and control the internal state of a battery’s electrochemical systems. For Thevenin battery model we established a state-space model which had the advantage of simplicity and could be easily implemented and then applied the least square method to identify the battery model parameters. However, accurate state of charge (SoC estimation of a battery, which depends not only on the battery model but also on highly accurate and efficient algorithms, is considered one of the most vital and critical issue for the energy management and power distribution control of EV. In this paper three different estimation methods, i.e., extended Kalman filter (EKF, particle filter (PF and unscented Kalman Filter (UKF, are presented to estimate the SoC of LiFePO4 batteries for an electric vehicle. Battery’s experimental data, current and voltage, are analyzed to identify the Thevenin equivalent model parameters. Using different open circuit voltages the SoC is estimated and compared with respect to the estimation accuracy and initialization error recovery. The experimental results showed that these online SoC estimation methods in combination with different open circuit voltage-state of charge (OCV-SoC curves can effectively limit the error, thus guaranteeing the accuracy and robustness.
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
Jiang, Jingyi; Comar, Alexis; Burger, Philippe; Bancal, Pierre; Weiss, Marie; Baret, Frédéric
2018-01-01
Leaf biochemical composition corresponds to traits related to the plant state and its functioning. This study puts the emphasis on the main leaf absorbers: chlorophyll a and b ([Formula: see text]), carotenoids ([Formula: see text]), water ([Formula: see text]) and dry mater ([Formula: see text]) contents. Two main approaches were used to estimate [[Formula: see text] [Formula: see text], [Formula: see text], [Formula: see text
Stress estimation in reservoirs using an integrated inverse method
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.
Methods for cost estimation in software project management
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.
Novel method for quantitative estimation of biofilms
DEFF Research Database (Denmark)
Syal, Kirtimaan
2017-01-01
Biofilm protects bacteria from stress and hostile environment. Crystal violet (CV) assay is the most popular method for biofilm determination adopted by different laboratories so far. However, biofilm layer formed at the liquid-air interphase known as pellicle is extremely sensitive to its washing...... and staining steps. Early phase biofilms are also prone to damage by the latter steps. In bacteria like mycobacteria, biofilm formation occurs largely at the liquid-air interphase which is susceptible to loss. In the proposed protocol, loss of such biofilm layer was prevented. In place of inverting...... and discarding the media which can lead to the loss of the aerobic biofilm layer in CV assay, media was removed from the formed biofilm with the help of a syringe and biofilm layer was allowed to dry. The staining and washing steps were avoided, and an organic solvent-tetrahydrofuran (THF) was deployed...
VHTRC experiment for verification test of H∞ reactivity estimation method
International Nuclear Information System (INIS)
Fujii, Yoshio; Suzuki, Katsuo; Akino, Fujiyoshi; Yamane, Tsuyoshi; Fujisaki, Shingo; Takeuchi, Motoyoshi; Ono, Toshihiko
1996-02-01
This experiment was performed at VHTRC to acquire the data for verifying the H∞ reactivity estimation method. In this report, the experimental method, the measuring circuits and data processing softwares are described in details. (author)
Carbon footprint: current methods of estimation.
Pandey, Divya; Agrawal, Madhoolika; Pandey, Jai Shanker
2011-07-01
Increasing greenhouse gaseous concentration in the atmosphere is perturbing the environment to cause grievous global warming and associated consequences. Following the rule that only measurable is manageable, mensuration of greenhouse gas intensiveness of different products, bodies, and processes is going on worldwide, expressed as their carbon footprints. The methodologies for carbon footprint calculations are still evolving and it is emerging as an important tool for greenhouse gas management. The concept of carbon footprinting has permeated and is being commercialized in all the areas of life and economy, but there is little coherence in definitions and calculations of carbon footprints among the studies. There are disagreements in the selection of gases, and the order of emissions to be covered in footprint calculations. Standards of greenhouse gas accounting are the common resources used in footprint calculations, although there is no mandatory provision of footprint verification. Carbon footprinting is intended to be a tool to guide the relevant emission cuts and verifications, its standardization at international level are therefore necessary. Present review describes the prevailing carbon footprinting methods and raises the related issues.
THE METHODS FOR ESTIMATING REGIONAL PROFESSIONAL MOBILE RADIO MARKET POTENTIAL
Directory of Open Access Journals (Sweden)
Y.À. Korobeynikov
2008-12-01
Full Text Available The paper represents the author’s methods of estimating regional professional mobile radio market potential, that belongs to high-tech b2b markets. These methods take into consideration such market peculiarities as great range and complexity of products, technological constraints and infrastructure development for the technological systems operation. The paper gives an estimation of professional mobile radio potential in Perm region. This estimation is already used by one of the systems integrator for its strategy development.
Evaluation and reliability of bone histological age estimation methods
African Journals Online (AJOL)
Human age estimation at death plays a vital role in forensic anthropology and bioarchaeology. Researchers used morphological and histological methods to estimate human age from their skeletal remains. This paper discussed different histological methods that used human long bones and ribs to determine age ...
A new rapid method for rockfall energies and distances estimation
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
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
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.
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.
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
Methods for estimating low-flow statistics for Massachusetts streams
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
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
Optical Enhancement of Exoskeleton-Based Estimation of Glenohumeral Angles
Cortés, Camilo; Unzueta, Luis; de los Reyes-Guzmán, Ana; Ruiz, Oscar E.; Flórez, Julián
2016-01-01
In Robot-Assisted Rehabilitation (RAR) the accurate estimation of the patient limb joint angles is critical for assessing therapy efficacy. In RAR, the use of classic motion capture systems (MOCAPs) (e.g., optical and electromagnetic) to estimate the Glenohumeral (GH) joint angles is hindered by the exoskeleton body, which causes occlusions and magnetic disturbances. Moreover, the exoskeleton posture does not accurately reflect limb posture, as their kinematic models differ. To address the said limitations in posture estimation, we propose installing the cameras of an optical marker-based MOCAP in the rehabilitation exoskeleton. Then, the GH joint angles are estimated by combining the estimated marker poses and exoskeleton Forward Kinematics. Such hybrid system prevents problems related to marker occlusions, reduced camera detection volume, and imprecise joint angle estimation due to the kinematic mismatch of the patient and exoskeleton models. This paper presents the formulation, simulation, and accuracy quantification of the proposed method with simulated human movements. In addition, a sensitivity analysis of the method accuracy to marker position estimation errors, due to system calibration errors and marker drifts, has been carried out. The results show that, even with significant errors in the marker position estimation, method accuracy is adequate for RAR. PMID:27403044
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.
International Nuclear Information System (INIS)
Wei, Zhongbao; Zhao, Jiyun; Ji, Dongxu; Tseng, King Jet
2017-01-01
Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.
Estimation of creatinine in Urine sample by Jaffe's method
International Nuclear Information System (INIS)
Wankhede, Sonal; Arunkumar, Suja; Sawant, Pramilla D.; Rao, B.B.
2012-01-01
In-vitro bioassay monitoring is based on the determination of activity concentrations in biological samples excreted from the body and is most suitable for alpha and beta emitters. A truly representative bioassay sample is the one having all the voids collected during a 24-h period however, this being technically difficult, overnight urine samples collected by the workers are analyzed. These overnight urine samples are collected for 10-16 h, however in the absence of any specific information, 12 h duration is assumed and the observed results are then corrected accordingly obtain the daily excretion rate. To reduce the uncertainty due to unknown duration of sample collection, IAEA has recommended two methods viz., measurement of specific gravity and creatinine excretion rate in urine sample. Creatinine is a final metabolic product creatinine phosphate in the body and is excreted at a steady rate for people with normally functioning kidneys. It is, therefore, often used as a normalization factor for estimation of duration of sample collection. The present study reports the chemical procedure standardized and its application for the estimation of creatinine in urine samples collected from occupational workers. Chemical procedure for estimation of creatinine in bioassay samples was standardized and applied successfully for its estimation in bioassay samples collected from the workers. The creatinine excretion rate observed for these workers is lower than observed in literature. Further, work is in progress to generate a data bank of creatinine excretion rate for most of the workers and also to study the variability in creatinine coefficient for the same individual based on the analysis of samples collected for different duration
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.
Advances in Time Estimation Methods for Molecular Data.
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
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:
Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann
2016-10-01
Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches
DEFF Research Database (Denmark)
Dupont, Nana Hee; Fertner, Mette; Birkegård, Anna Camilla
2017-01-01
With the increasing occurrence of antimicrobial resistance, more attention has been directed towards surveillance of both human and veterinary antimicrobial use. Since the early 2000s, several research papers on Danish pig antimicrobial usage have been published, based on data from the Danish...
Hata, Yoshiya; Yabe, Masaaki; Kasai, Akira; Matsuzaki, Hiroshi; Takahashi, Yoshikazu; Akiyama, Mitsuyoshi
2016-12-01
An earthquake of JMA magnitude 6.5 (first event) hit Kumamoto Prefecture, Japan, at 21:26 JST, April 14, 2016. Subsequently, an earthquake of JMA magnitude 7.3 (second event) hit Kumamoto and Oita Prefectures at 01:46 JST, April 16, 2016. An out-of-service Kyushu Shinkansen train carrying no passengers traveling on elevated bridges was derailed by the first event. This was the third derailment caused by an earthquake in the history of the Japanese Shinkansen, after one caused by the 2004 Mid-Niigata Prefecture Earthquake and another triggered by the 2011 Tohoku Earthquake. To analyze the mechanism of this third derailment, it is crucial to evaluate the strong ground motion at the derailment site with high accuracy. For this study, temporary earthquake observations were first carried out at a location near the bridge site; these observations were conducted because although the JMA Kumamoto Station site and the derailment site are closely located, the ground response characteristics at these sites differ. Next, empirical site amplification and phase effects were evaluated based on the obtained observation records. Finally, seismic waveforms during the first event at the bridge site of interest were estimated based on the site-effect substitution method. The resulting estimated acceleration and velocity waveforms for the derailment site include much larger amplitudes than the waveforms recorded at the JMA Kumamoto and MLIT Kumamoto station sites. The reliability of these estimates is confirmed by the finding that the same methods reproduce strong ground motions at the MLIT Kumamoto Station site accurately. These estimated ground motions will be useful for reasonable safety assessment of anti-derailment devices on elevated railway bridges.[Figure not available: see fulltext.
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%.
A Dynamic Travel Time Estimation Model Based on Connected Vehicles
Directory of Open Access Journals (Sweden)
Daxin Tian
2015-01-01
Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.
An RSS based location estimation technique for cognitive relay networks
Qaraqe, Khalid A.
2010-11-01
In this paper, a received signal strength (RSS) based location estimation method is proposed for a cooperative wireless relay network where the relay is a cognitive radio. We propose a method for the considered cognitive relay network to determine the location of the source using the direct and the relayed signal at the destination. We derive the Cramer-Rao lower bound (CRLB) expressions separately for x and y coordinates of the location estimate. We analyze the effects of cognitive behaviour of the relay on the performance of the proposed method. We also discuss and quantify the reliability of the location estimate using the proposed technique if the source is not stationary. The overall performance of the proposed method is presented through simulations. ©2010 IEEE.
Estimation of citicoline sodium in tablets by difference spectrophotometric method
Directory of Open Access Journals (Sweden)
Sagar Suman Panda
2013-01-01
Full Text Available Aim: The present work deals with development and validation of a novel, precise, and accurate spectrophotometric method for the estimation of citicoline sodium (CTS in tablets. This spectrophotometric method is based on the principle that CTS shows two different forms that differs in the absorption spectra in basic and acidic medium. Materials and Methods: The present work was being carried out on Shimadzu 1800 Double Beam UV-visible spectrophotometer. Difference spectra were generated using 10 mm quartz cells over the range of 200-400 nm. Solvents used were 0.1 M NaOH and 0.1 M HCl. Results: The maxima and minima in the difference spectra of CTS were found to be 239 nm and 283 nm, respectively. Amplitude was calculated from the maxima and minima of spectrum. The drug follows linearity in the range of 1-50 μ/ml (R 2 = 0.999. The average % recovery from the tablet formulation was found to be 98.47%. The method was validated as per International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use: ICH Q2(R1 Validation of Analytical Procedures: Text and Methodology guidelines. Conclusion: This method is simple and inexpensive. Hence it can be applied for determination of the drug in pharmaceutical dosage forms.
DEFF Research Database (Denmark)
Asif, Ali
There is an increasing concern about excessive use of herbicides for weed control in arable lands. Usually the whole field is sprayed uniformly, while the distribution of weeds often is non-uniform. Often there are spots in a field where weed pressure is very low and has no significant effect...... on crop yield. The excessive use of spraying can potentially be reduced by spraying only those parts of the field where it has economic importance. The competition relation between weeds and crop was ana-lyzed in context of real time patch spray. A non-destructive image analysis method was developed...
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
Consumptive use of upland rice as estimated by different methods
International Nuclear Information System (INIS)
Chhabda, P.R.; Varade, S.B.
1985-01-01
The consumptive use of upland rice (Oryza sativa Linn.) grown during the wet season (kharif) as estimated by modified Penman, radiation, pan-evaporation and Hargreaves methods showed a variation from computed consumptive use estimated by the gravimetric method. The variability increased with an increase in the irrigation interval, and decreased with an increase in the level of N applied. The average variability was less in pan-evaporation method, which could reliably be used for estimating water requirement of upland rice if percolation losses are considered
Dahm, T.; Heimann, S.; Isken, M.; Vasyura-Bathke, H.; Kühn, D.; Sudhaus, H.; Kriegerowski, M.; Daout, S.; Steinberg, A.; Cesca, S.
2017-12-01
Seismic source and moment tensor waveform inversion is often ill-posed or non-unique if station coverage is poor or signals are weak. Therefore, the interpretation of moment tensors can become difficult, if not the full model space is explored, including all its trade-offs and uncertainties. This is especially true for non-double couple components of weak or shallow earthquakes, as for instance found in volcanic, geothermal or mining environments.We developed a bootstrap-based probabilistic optimization scheme (Grond), which is based on pre-calculated Greens function full waveform databases (e.g. fomosto tool, doi.org/10.5880/GFZ.2.1.2017.001). Grond is able to efficiently explore the full model space, the trade-offs and the uncertainties of source parameters. The program is highly flexible with respect to the adaption to specific problems, the design of objective functions, and the diversity of empirical datasets.It uses an integrated, robust waveform data processing based on a newly developed Python toolbox for seismology (Pyrocko, see Heimann et al., 2017, http://doi.org/10.5880/GFZ.2.1.2017.001), and allows for visual inspection of many aspects of the optimization problem. Grond has been applied to the CMT moment tensor inversion using W-phases, to nuclear explosions in Korea, to meteorite atmospheric explosions, to volcano-tectonic events during caldera collapse and to intra-plate volcanic and tectonic crustal events.Grond can be used to optimize simultaneously seismological waveforms, amplitude spectra and static displacements of geodetic data as InSAR and GPS (e.g. KITE, Isken et al., 2017, http://doi.org/10.5880/GFZ.2.1.2017.002). We present examples of Grond optimizations to demonstrate the advantage of a full exploration of source parameter uncertainties for interpretation.
Three methods for estimating a range of vehicular interactions
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.
Method of estimating investment decisions effectiveness in power engineering
International Nuclear Information System (INIS)
Kamrat, W.
1996-01-01
A new concept of determining efficient power plants investment decision-making is proposed.The results of research on capital expenditures for building and modernization of power plants are presented. The model introduced is based on the well-known Annual Cost Model which is modified by adding annual risk costs. So the formula for annual costs is: K = K f + K v + K r , where: K f are annual fixed costs, K v - annual variables costs, K r -annual risk costs. The annual risk costs can be calculated by the expression: K r = e i x K c , where e i is the investment risk factor, and K c - leveled capital investment. The risk factor was created on the basis of some elements of the taxonometric method with a high level of estimation probability. The essential problem is the selection of risk investment variables, most important of which are economic, financial, technical, social, political, legal. These variables create a multidimensional space. A so called 'ideal' model of the power plant is created taking into account capacity, type, fuel used, etc. The values of the multidimensional risk factor e i lie within limit and make it possible to rank the planned plants in series according to the estimated level of risk. This method can be used not only for risk evaluation in power engineering but also for investment efficiency studies in different industrial branches
Power system dynamic state estimation using prediction based evolutionary technique
International Nuclear Information System (INIS)
Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan
2016-01-01
In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.
Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2
Energy Technology Data Exchange (ETDEWEB)
Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.
1994-07-01
The activities that produce electric power typically range from extracting and transporting a fuel, to its conversion into electric power, and finally to the disposition of residual by-products. This chain of activities is called a fuel cycle. A fuel cycle has emissions and other effects that result in unintended consequences. When these consequences affect third parties (i.e., those other than the producers and consumers of the fuel-cycle activity) in a way that is not reflected in the price of electricity, they are termed ''hidden'' social costs or externalities. They are the economic value of environmental, health and any other impacts, that the price of electricity does not reflect. How do you estimate the externalities of fuel cycles? Our previous report describes a methodological framework for doing so--called the damage function approach. This approach consists of five steps: (1) characterize the most important fuel cycle activities and their discharges, where importance is based on the expected magnitude of their externalities, (2) estimate the changes in pollutant concentrations or other effects of those activities, by modeling the dispersion and transformation of each pollutant, (3) calculate the impacts on ecosystems, human health, and any other resources of value (such as man-made structures), (4) translate the estimates of impacts into economic terms to estimate damages and benefits, and (5) assess the extent to which these damages and benefits are externalities, not reflected in the price of electricity. Each step requires a different set of equations, models and analysis. Analysts generally believe this to be the best approach for estimating externalities, but it has hardly been used! The reason is that it requires considerable analysis and calculation, and to this point in time, the necessary equations and models have not been assembled. Equally important, the process of identifying and estimating externalities leads to a number
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.
Postprocessing MPEG based on estimated quantization parameters
DEFF Research Database (Denmark)
Forchhammer, Søren
2009-01-01
the case where the coded stream is not accessible, or from an architectural point of view not desirable to use, and instead estimate some of the MPEG stream parameters based on the decoded sequence. The I-frames are detected and the quantization parameters are estimated from the coded stream and used...... in the postprocessing. We focus on deringing and present a scheme which aims at suppressing ringing artifacts, while maintaining the sharpness of the texture. The goal is to improve the visual quality, so perceptual blur and ringing metrics are used in addition to PSNR evaluation. The performance of the new `pure......' postprocessing compares favorable to a reference postprocessing filter which has access to the quantization parameters not only for I-frames but also on P and B-frames....
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
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
Ore reserve estimation: a summary of principles and methods
International Nuclear Information System (INIS)
Marques, J.P.M.
1985-01-01
The mining industry has experienced substantial improvements with the increasing utilization of computerized and electronic devices throughout the last few years. In the ore reserve estimation field the main methods have undergone recent advances in order to improve their overall efficiency. This paper presents the three main groups of ore reserve estimation methods presently used worldwide: Conventional, Statistical and Geostatistical, and elaborates a detaited description and comparative analysis of each. The Conventional Methods are the oldest, less complex and most employed ones. The Geostatistical Methods are the most recent precise and more complex ones. The Statistical Methods are intermediate to the others in complexity, diffusion and chronological order. (D.J.M.) [pt
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
Methods for design flood estimation in South Africa | Smithers ...
African Journals Online (AJOL)
The estimation of design floods is necessary for the design of hydraulic structures and to quantify the risk of failure of the structures. Most of the methods used for design flood estimation in South Africa were developed in the late 1960s and early 1970s and are in need of updating with more than 40 years of additional data ...
Quantifying Accurate Calorie Estimation Using the "Think Aloud" Method
Holmstrup, Michael E.; Stearns-Bruening, Kay; Rozelle, Jeffrey
2013-01-01
Objective: Clients often have limited time in a nutrition education setting. An improved understanding of the strategies used to accurately estimate calories may help to identify areas of focused instruction to improve nutrition knowledge. Methods: A "Think Aloud" exercise was recorded during the estimation of calories in a standard dinner meal…
Performance of sampling methods to estimate log characteristics for wildlife.
Lisa J. Bate; Torolf R. Torgersen; Michael J. Wisdom; Edward O. Garton
2004-01-01
Accurate estimation of the characteristics of log resources, or coarse woody debris (CWD), is critical to effective management of wildlife and other forest resources. Despite the importance of logs as wildlife habitat, methods for sampling logs have traditionally focused on silvicultural and fire applications. These applications have emphasized estimates of log volume...
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.
Estimation of Anthocyanin Content of Berries by NIR Method
International Nuclear Information System (INIS)
Zsivanovits, G.; Ludneva, D.; Iliev, A.
2010-01-01
Anthocyanin contents of fruits were estimated by VIS spectrophotometer and compared with spectra measured by NIR spectrophotometer (600-1100 nm step 10 nm). The aim was to find a relationship between NIR method and traditional spectrophotometric method. The testing protocol, using NIR, is easier, faster and non-destructive. NIR spectra were prepared in pairs, reflectance and transmittance. A modular spectrocomputer, realized on the basis of a monochromator and peripherals Bentham Instruments Ltd (GB) and a photometric camera created at Canning Research Institute, were used. An important feature of this camera is the possibility offered for a simultaneous measurement of both transmittance and reflectance with geometry patterns T0/180 and R0/45. The collected spectra were analyzed by CAMO Unscrambler 9.1 software, with PCA, PLS, PCR methods. Based on the analyzed spectra quality and quantity sensitive calibrations were prepared. The results showed that the NIR method allows measuring of the total anthocyanin content in fresh berry fruits or processed products without destroying them.
Methods of multicriterion estimations in system total quality management
Directory of Open Access Journals (Sweden)
Nikolay V. Diligenskiy
2011-05-01
Full Text Available In this article the method of multicriterion comparative estimation of efficiency (Data Envelopment Analysis and possibility of its application in system of total quality management is considered.
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...
Methods for design flood estimation in South Africa
African Journals Online (AJOL)
2012-07-04
Jul 4,