Robust position estimation of a mobile vehicle
International Nuclear Information System (INIS)
Conan, V.
1994-01-01
The ability to estimate the position of a mobile vehicle is a key task for navigation over large distances in complex indoor environments such as nuclear power plants. Schematics of the plants are available, but they are incomplete, as real settings contain many objects, such as pipes, cables or furniture, that mask part of the model. The position estimation method described in this paper matches 3-D data with a simple schematic of a plant. It is basically independent of odometer information and viewpoint, robust to noisy data and spurious points and largely insensitive to occlusions. The method is based on a hypothesis/verification paradigm and its complexity is polynomial; it runs in O(m 4 n 4 ), where m represents the number of model patches and n the number of scene patches. Heuristics are presented to speed up the algorithm. Results on real 3-D data show good behaviour even when the scene is very occluded. (authors). 16 refs., 3 figs., 1 tab
Robust 3D Position Estimation in Wide and Unconstrained Indoor Environments
Directory of Open Access Journals (Sweden)
Annette Mossel
2015-12-01
Full Text Available In this paper, a system for 3D position estimation in wide, unconstrained indoor environments is presented that employs infrared optical outside-in tracking of rigid-body targets with a stereo camera rig. To overcome limitations of state-of-the-art optical tracking systems, a pipeline for robust target identification and 3D point reconstruction has been investigated that enables camera calibration and tracking in environments with poor illumination, static and moving ambient light sources, occlusions and harsh conditions, such as fog. For evaluation, the system has been successfully applied in three different wide and unconstrained indoor environments, (1 user tracking for virtual and augmented reality applications, (2 handheld target tracking for tunneling and (3 machine guidance for mining. The results of each use case are discussed to embed the presented approach into a larger technological and application context. The experimental results demonstrate the system’s capabilities to track targets up to 100 m. Comparing the proposed approach to prior art in optical tracking in terms of range coverage and accuracy, it significantly extends the available tracking range, while only requiring two cameras and providing a relative 3D point accuracy with sub-centimeter deviation up to 30 m and low-centimeter deviation up to 100 m.
Qualitative Robustness in Estimation
Directory of Open Access Journals (Sweden)
Mohammed Nasser
2012-07-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.
Robust Optical Flow Estimation
Directory of Open Access Journals (Sweden)
Javier Sánchez Pérez
2013-10-01
Full Text Available n this work, we describe an implementation of the variational method proposed by Brox etal. in 2004, which yields accurate optical flows with low running times. It has several benefitswith respect to the method of Horn and Schunck: it is more robust to the presence of outliers,produces piecewise-smooth flow fields and can cope with constant brightness changes. Thismethod relies on the brightness and gradient constancy assumptions, using the information ofthe image intensities and the image gradients to find correspondences. It also generalizes theuse of continuous L1 functionals, which help mitigate the effect of outliers and create a TotalVariation (TV regularization. Additionally, it introduces a simple temporal regularizationscheme that enforces a continuous temporal coherence of the flow fields.
Robust Wave Resource Estimation
DEFF Research Database (Denmark)
Lavelle, John; Kofoed, Jens Peter
2013-01-01
density estimates of the PDF as a function both of Hm0 and Tp, and Hm0 and T0;2, together with the mean wave power per unit crest length, Pw, as a function of Hm0 and T0;2. The wave elevation parameters, from which the wave parameters are calculated, are filtered to correct or remove spurious data....... An overview is given of the methods used to do this, and a method for identifying outliers of the wave elevation data, based on the joint distribution of wave elevations and accelerations, is presented. The limitations of using a JONSWAP spectrum to model the measured wave spectra as a function of Hm0 and T0......;2 or Hm0 and Tp for the Hanstholm site data are demonstrated. As an alternative, the non-parametric loess method, which does not rely on any assumptions about the shape of the wave elevation spectra, is used to accurately estimate Pw as a function of Hm0 and T0;2....
Robust estimation and hypothesis testing
Tiku, Moti L
2004-01-01
In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomali...
Robust Position Control of Electro-mechanical Systems
Rong Mei; Mou Chen
2013-01-01
In this work, the robust position control scheme is proposed for the electro-mechanical system using the disturbance observer and backstepping control method. To the external unknown load of the electro-mechanical system, the nonlinear disturbance observer is given to estimate the external unknown load. Combining the output of the developed nonlinear disturbance observer with backstepping technology, the robust position control scheme is proposed for the electro-mechanical system. The stabili...
Robust AIC with High Breakdown Scale Estimate
Directory of Open Access Journals (Sweden)
Shokrya Saleh
2014-01-01
Full Text Available Akaike Information Criterion (AIC based on least squares (LS regression minimizes the sum of the squared residuals; LS is sensitive to outlier observations. Alternative criterion, which is less sensitive to outlying observation, has been proposed; examples are robust AIC (RAIC, robust Mallows Cp (RCp, and robust Bayesian information criterion (RBIC. In this paper, we propose a robust AIC by replacing the scale estimate with a high breakdown point estimate of scale. The robustness of the proposed methods is studied through its influence function. We show that, the proposed robust AIC is effective in selecting accurate models in the presence of outliers and high leverage points, through simulated and real data examples.
Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold
Directory of Open Access Journals (Sweden)
Xiaoqiang Hua
2018-03-01
Full Text Available This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD matrices. The means associated with information divergences are derived and used as the estimators. Without resorting to the complete knowledge of the probability distribution of the sample data, the geometry of the Riemannian manifold of HPD matrices is considered in mean estimators. Moreover, the robustness of mean estimators is analyzed using the influence function. Simulation results indicate the robustness and superiority of an adaptive normalized matched filter with our proposed estimators compared with the existing alternatives.
Robust motion estimation using connected operators
Salembier Clairon, Philippe Jean; Sanson, H
1997-01-01
This paper discusses the use of connected operators for robust motion estimation The proposed strategy involves a motion estimation step extracting the dominant motion and a ltering step relying on connected operators that remove objects that do not fol low the dominant motion. These two steps are iterated in order to obtain an accurate motion estimation and a precise de nition of the objects fol lowing this motion This strategy can be applied on the entire frame or on individual connected c...
Robust estimation for ordinary differential equation models.
Cao, J; Wang, L; Xu, J
2011-12-01
Applied scientists often like to use ordinary differential equations (ODEs) to model complex dynamic processes that arise in biology, engineering, medicine, and many other areas. It is interesting but challenging to estimate ODE parameters from noisy data, especially when the data have some outliers. We propose a robust method to address this problem. The dynamic process is represented with a nonparametric function, which is a linear combination of basis functions. The nonparametric function is estimated by a robust penalized smoothing method. The penalty term is defined with the parametric ODE model, which controls the roughness of the nonparametric function and maintains the fidelity of the nonparametric function to the ODE model. The basis coefficients and ODE parameters are estimated in two nested levels of optimization. The coefficient estimates are treated as an implicit function of ODE parameters, which enables one to derive the analytic gradients for optimization using the implicit function theorem. Simulation studies show that the robust method gives satisfactory estimates for the ODE parameters from noisy data with outliers. The robust method is demonstrated by estimating a predator-prey ODE model from real ecological data. © 2011, The International Biometric Society.
Robust power spectral estimation for EEG data.
Melman, Tamar; Victor, Jonathan D
2016-08-01
Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.
Robust Solar Position Sensor for Tracking Systems
DEFF Research Database (Denmark)
Ritchie, Ewen; Argeseanu, Alin; Leban, Krisztina Monika
2009-01-01
The paper proposes a new solar position sensor used in tracking system control. The main advantages of the new solution are the robustness and the economical aspect. Positioning accuracy of the tracking system that uses the new sensor is better than 1°. The new sensor uses the ancient principle...... of the solar clock. The sensitive elements are eight ordinary photo-resistors. It is important to note that all the sensors are not selected simultaneously. It is not necessary for sensor operating characteristics to be quasi-identical because the sensor principle is based on extreme operating duty measurement...... (bright or dark). In addition, the proposed solar sensor significantly simplifies the operation of the tracking control device....
Robust bearing estimation for 3-component stations
International Nuclear Information System (INIS)
CLAASSEN, JOHN P.
2000-01-01
A robust bearing estimation process for 3-component stations has been developed and explored. The method, called SEEC for Search, Estimate, Evaluate and Correct, intelligently exploits the inherent information in the arrival at every step of the process to achieve near-optimal results. In particular the approach uses a consistent framework to define the optimal time-frequency windows on which to make estimates, to make the bearing estimates themselves, to construct metrics helpful in choosing the better estimates or admitting that the bearing is immeasurable, and finally to apply bias corrections when calibration information is available to yield a single final estimate. The algorithm was applied to a small but challenging set of events in a seismically active region. It demonstrated remarkable utility by providing better estimates and insights than previously available. Various monitoring implications are noted from these findings
Robust median estimator in logisitc regression
Czech Academy of Sciences Publication Activity Database
Hobza, T.; Pardo, L.; Vajda, Igor
2008-01-01
Roč. 138, č. 12 (2008), s. 3822-3840 ISSN 0378-3758 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica (ES) MPO FI - IM3/136; GA MŠk(CZ) MTM 2006-06872 Institutional research plan: CEZ:AV0Z10750506 Keywords : Logistic regression * Median * Robustness * Consistency and asymptotic normality * Morgenthaler * Bianco and Yohai * Croux and Hasellbroeck Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.679, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/vajda-robust%20median%20estimator%20in%20logistic%20regression.pdf
Heteroscedasticity resistant robust covariance matrix estimator
Czech Academy of Sciences Publication Activity Database
Víšek, Jan Ámos
2010-01-01
Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf
Neuromorphic Configurable Architecture for Robust Motion Estimation
Directory of Open Access Journals (Sweden)
Guillermo Botella
2008-01-01
Full Text Available The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM. This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.
Robust Optical Richness Estimation with Reduced Scatter
Energy Technology Data Exchange (ETDEWEB)
Rykoff, E.S.; /LBL, Berkeley; Koester, B.P.; /Chicago U. /Chicago U., KICP; Rozo, E.; /Chicago U. /Chicago U., KICP; Annis, J.; /Fermilab; Evrard, A.E.; /Michigan U. /Michigan U., MCTP; Hansen, S.M.; /Lick Observ.; Hao, J.; /Fermilab; Johnston, D.E.; /Fermilab; McKay, T.A.; /Michigan U. /Michigan U., MCTP; Wechsler, R.H.; /KIPAC, Menlo Park /SLAC
2012-06-07
Reducing the scatter between cluster mass and optical richness is a key goal for cluster cosmology from photometric catalogs. We consider various modifications to the red-sequence matched filter richness estimator of Rozo et al. (2009b), and evaluate their impact on the scatter in X-ray luminosity at fixed richness. Most significantly, we find that deeper luminosity cuts can reduce the recovered scatter, finding that {sigma}{sub ln L{sub X}|{lambda}} = 0.63 {+-} 0.02 for clusters with M{sub 500c} {approx}> 1.6 x 10{sup 14} h{sub 70}{sup -1} M{sub {circle_dot}}. The corresponding scatter in mass at fixed richness is {sigma}{sub ln M|{lambda}} {approx} 0.2-0.3 depending on the richness, comparable to that for total X-ray luminosity. We find that including blue galaxies in the richness estimate increases the scatter, as does weighting galaxies by their optical luminosity. We further demonstrate that our richness estimator is very robust. Specifically, the filter employed when estimating richness can be calibrated directly from the data, without requiring a-priori calibrations of the red-sequence. We also demonstrate that the recovered richness is robust to up to 50% uncertainties in the galaxy background, as well as to the choice of photometric filter employed, so long as the filters span the 4000 {angstrom} break of red-sequence galaxies. Consequently, our richness estimator can be used to compare richness estimates of different clusters, even if they do not share the same photometric data. Appendix A includes 'easy-bake' instructions for implementing our optimal richness estimator, and we are releasing an implementation of the code that works with SDSS data, as well as an augmented maxBCG catalog with the {lambda} richness measured for each cluster.
Robust Pitch Estimation Using an Optimal Filter on Frequency Estimates
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
of such signals from unconstrained frequency estimates (UFEs). A minimum variance distortionless response (MVDR) method is proposed as an optimal solution to minimize the variance of UFEs considering the constraint of integer harmonics. The MVDR filter is designed based on noise statistics making it robust...
Adaptive robust Kalman filtering for precise point positioning
International Nuclear Information System (INIS)
Guo, Fei; Zhang, Xiaohong
2014-01-01
The optimality of precise point postioning (PPP) solution using a Kalman filter is closely connected to the quality of the a priori information about the process noise and the updated mesurement noise, which are sometimes difficult to obtain. Also, the estimation enviroment in the case of dynamic or kinematic applications is not always fixed but is subject to change. To overcome these problems, an adaptive robust Kalman filtering algorithm, the main feature of which introduces an equivalent covariance matrix to resist the unexpected outliers and an adaptive factor to balance the contribution of observational information and predicted information from the system dynamic model, is applied for PPP processing. The basic models of PPP including the observation model, dynamic model and stochastic model are provided first. Then an adaptive robust Kalmam filter is developed for PPP. Compared with the conventional robust estimator, only the observation with largest standardized residual will be operated by the IGG III function in each iteration to avoid reducing the contribution of the normal observations or even filter divergence. Finally, tests carried out in both static and kinematic modes have confirmed that the adaptive robust Kalman filter outperforms the classic Kalman filter by turning either the equivalent variance matrix or the adaptive factor or both of them. This becomes evident when analyzing the positioning errors in flight tests at the turns due to the target maneuvering and unknown process/measurement noises. (paper)
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
a comparative study of some robust ridge and liu estimators
African Journals Online (AJOL)
Dr A.B.Ahmed
estimation techniques such as Ridge and Liu Estimators are preferable to Ordinary Least Square. On the other hand, when outliers exist in the data, robust estimators like M, MM, LTS and S. Estimators, are preferred. To handle these two problems jointly, the study combines the Ridge and Liu Estimators with Robust.
Robust estimation of seismic coda shape
Nikkilä, Mikko; Polishchuk, Valentin; Krasnoshchekov, Dmitry
2014-04-01
We present a new method for estimation of seismic coda shape. It falls into the same class of methods as non-parametric shape reconstruction with the use of neural network techniques where data are split into a training and validation data sets. We particularly pursue the well-known problem of image reconstruction formulated in this case as shape isolation in the presence of a broadly defined noise. This combined approach is enabled by the intrinsic feature of seismogram which can be divided objectively into a pre-signal seismic noise with lack of the target shape, and the remainder that contains scattered waveforms compounding the coda shape. In short, we separately apply shape restoration procedure to pre-signal seismic noise and the event record, which provides successful delineation of the coda shape in the form of a smooth almost non-oscillating function of time. The new algorithm uses a recently developed generalization of classical computational-geometry tool of α-shape. The generalization essentially yields robust shape estimation by ignoring locally a number of points treated as extreme values, noise or non-relevant data. Our algorithm is conceptually simple and enables the desired or pre-determined level of shape detail, constrainable by an arbitrary data fit criteria. The proposed tool for coda shape delineation provides an alternative to moving averaging and/or other smoothing techniques frequently used for this purpose. The new algorithm is illustrated with an application to the problem of estimating the coda duration after a local event. The obtained relation coefficient between coda duration and epicentral distance is consistent with the earlier findings in the region of interest.
Introduction to Robust Estimation and Hypothesis Testing
Wilcox, Rand R
2012-01-01
This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations.Introduction to R
Second order statistics of bilinear forms of robust scatter estimators
Kammoun, Abla
2015-08-12
This paper lies in the lineage of recent works studying the asymptotic behaviour of robust-scatter estimators in the case where the number of observations and the dimension of the population covariance matrix grow at infinity with the same pace. In particular, we analyze the fluctuations of bilinear forms of the robust shrinkage estimator of covariance matrix. We show that this result can be leveraged in order to improve the design of robust detection methods. As an example, we provide an improved generalized likelihood ratio based detector which combines robustness to impulsive observations and optimality across the shrinkage parameter, the optimality being considered for the false alarm regulation.
Robust hydraulic position controller by a fuzzy state controller
International Nuclear Information System (INIS)
Zhao, T.; Van der Wal, A.J.
1994-01-01
In nuclear industry, one of the most important design considerations of controllers is their robustness. Robustness in this context is defined as the ability of a system to be controlled in a stable way over a wide range of system parameters. Generally the systems to be controlled are linearized, and stability is subsequently proven for this idealized system. By combining classical control theory and fuzzy set theory, a new kind of state controller is proposed and successfully applied to a hydraulic position servo with excellent robustness against variation of system parameters
Second order statistics of bilinear forms of robust scatter estimators
Kammoun, Abla; Couillet, Romain; Pascal, Fré dé ric
2015-01-01
. In particular, we analyze the fluctuations of bilinear forms of the robust shrinkage estimator of covariance matrix. We show that this result can be leveraged in order to improve the design of robust detection methods. As an example, we provide an improved
A comparative study of some robust ridge and liu estimators ...
African Journals Online (AJOL)
In multiple linear regression analysis, multicollinearity and outliers are two main problems. When multicollinearity exists, biased estimation techniques such as Ridge and Liu Estimators are preferable to Ordinary Least Square. On the other hand, when outliers exist in the data, robust estimators like M, MM, LTS and S ...
Robust Parameter and Signal Estimation in Induction Motors
DEFF Research Database (Denmark)
Børsting, H.
This thesis deals with theories and methods for robust parameter and signal estimation in induction motors. The project originates in industrial interests concerning sensor-less control of electrical drives. During the work, some general problems concerning estimation of signals and parameters...... in nonlinear systems, have been exposed. The main objectives of this project are: - analysis and application of theories and methods for robust estimation of parameters in a model structure, obtained from knowledge of the physics of the induction motor. - analysis and application of theories and methods...... for robust estimation of the rotor speed and driving torque of the induction motor based only on measurements of stator voltages and currents. Only contimuous-time models have been used, which means that physical related signals and parameters are estimated directly and not indirectly by some discrete...
Geomagnetic matching navigation algorithm based on robust estimation
Xie, Weinan; Huang, Liping; Qu, Zhenshen; Wang, Zhenhuan
2017-08-01
The outliers in the geomagnetic survey data seriously affect the precision of the geomagnetic matching navigation and badly disrupt its reliability. A novel algorithm which can eliminate the outliers influence is investigated in this paper. First, the weight function is designed and its principle of the robust estimation is introduced. By combining the relation equation between the matching trajectory and the reference trajectory with the Taylor series expansion for geomagnetic information, a mathematical expression of the longitude, latitude and heading errors is acquired. The robust target function is obtained by the weight function and the mathematical expression. Then the geomagnetic matching problem is converted to the solutions of nonlinear equations. Finally, Newton iteration is applied to implement the novel algorithm. Simulation results show that the matching error of the novel algorithm is decreased to 7.75% compared to the conventional mean square difference (MSD) algorithm, and is decreased to 18.39% to the conventional iterative contour matching algorithm when the outlier is 40nT. Meanwhile, the position error of the novel algorithm is 0.017° while the other two algorithms fail to match when the outlier is 400nT.
On robust parameter estimation in brain-computer interfacing
Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert
2017-12-01
Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.
Evaluation of Robust Estimators Applied to Fluorescence Assays
Directory of Open Access Journals (Sweden)
U. Ruotsalainen
2007-12-01
Full Text Available We evaluated standard robust methods in the estimation of fluorescence signal in novel assays used for determining the biomolecule concentrations. The objective was to obtain an accurate and reliable estimate using as few observations as possible by decreasing the influence of outliers. We assumed the true signals to have Gaussian distribution, while no assumptions about the outliers were made. The experimental results showed that arithmetic mean performs poorly even with the modest deviations. Further, the robust methods, especially the M-estimators, performed extremely well. The results proved that the use of robust methods is advantageous in the estimation problems where noise and deviations are significant, such as in biological and medical applications.
Robust estimation of track parameters in wire chambers
International Nuclear Information System (INIS)
Bogdanova, N.B.; Bourilkov, D.T.
1988-01-01
The aim of this paper is to compare numerically the possibilities of the least square fit (LSF) and robust methods for modelled and real track data to determine the linear regression parameters of charged particles in wire chambers. It is shown, that Tukey robust estimate is superior to more standard (versions of LSF) methods. The efficiency of the method is illustrated by tables and figures for some important physical characteristics
EnTracked: Energy-Efficient Robust Position Tracking for Mobile Devices
DEFF Research Database (Denmark)
Kjærgaard, Mikkel Baun; Jensen, Jakob Langdal; Godsk, Torben
2009-01-01
conditions and mobility, schedules position updates to both minimize energy consumption and optimize robustness. The realized system tracks pedestrian targets equipped with GPS-enabled devices. The system is configurable to realize different trade-offs between energy consumption and robustness. We provide...... of the mobile device. Furthermore, tracking has to robustly deliver position updates when faced with changing conditions such as delays due to positioning and communication, and changing positioning accuracy. This work proposes EnTracked --- a system that, based on the estimation and prediction of system...... extensive experimental results by profiling how devices consume power, by emulation on collected data and by validation in several real-world deployments. Results from this profiling show how a device consumes power while tracking its position. Results from the emulation indicate that the system can...
On the robustness of two-stage estimators
Zhelonkin, Mikhail
2012-04-01
The aim of this note is to provide a general framework for the analysis of the robustness properties of a broad class of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a general two-stage M-estimator, and provide their interpretations. We illustrate our results in the case of the two-stage maximum likelihood estimator and the two-stage least squares estimator. © 2011.
Doubly Robust Estimation of Optimal Dynamic Treatment Regimes
DEFF Research Database (Denmark)
Barrett, Jessica K; Henderson, Robin; Rosthøj, Susanne
2014-01-01
We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret-regression appro......We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret......-regression approach of Almirall et al. (in Biometrics 66:131-139, 2010) and Henderson et al. (in Biometrics 66:1192-1201, 2010) and demonstrate that it is equivalent to a reduced form of Robins' efficient g-estimation procedure (Robins, in Proceedings of the Second Symposium on Biostatistics. Springer, New York, pp....... 189-326, 2004). Simulation studies suggest that while the regret-regression approach is most efficient when there is no model misspecification, in the presence of misspecification the efficient g-estimation procedure is more robust. The g-estimation method can be difficult to apply in complex...
Robust estimation of the noise variance from background MR data
Sijbers, J.; Den Dekker, A.J.; Poot, D.; Bos, R.; Verhoye, M.; Van Camp, N.; Van der Linden, A.
2006-01-01
In the literature, many methods are available for estimation of the variance of the noise in magnetic resonance (MR) images. A commonly used method, based on the maximum of the background mode of the histogram, is revisited and a new, robust, and easy to use method is presented based on maximum
Robust cylinder pressure estimation in heavy-duty diesel engines
Kulah, S.; Forrai, A.; Rentmeester, F.; Donkers, T.; Willems, F.P.T.
2017-01-01
The robustness of a new single-cylinder pressure sensor concept is experimentally demonstrated on a six-cylinder heavy-duty diesel engine. Using a single-cylinder pressure sensor and a crank angle sensor, this single-cylinder pressure sensor concept estimates the in-cylinder pressure traces in the
On the robust nonparametric regression estimation for a functional regressor
Azzedine , Nadjia; Laksaci , Ali; Ould-Saïd , Elias
2009-01-01
On the robust nonparametric regression estimation for a functional regressor correspondance: Corresponding author. (Ould-Said, Elias) (Azzedine, Nadjia) (Laksaci, Ali) (Ould-Said, Elias) Departement de Mathematiques--> , Univ. Djillali Liabes--> , BP 89--> , 22000 Sidi Bel Abbes--> - ALGERIA (Azzedine, Nadjia) Departement de Mathema...
Robust efficient estimation of heart rate pulse from video
Xu, Shuchang; Sun, Lingyun; Rohde, Gustavo Kunde
2014-01-01
We describe a simple but robust algorithm for estimating the heart rate pulse from video sequences containing human skin in real time. Based on a model of light interaction with human skin, we define the change of blood concentration due to arterial pulsation as a pixel quotient in log space, and successfully use the derived signal for computing the pulse heart rate. Various experiments with different cameras, different illumination condition, and different skin locations were conducted to demonstrate the effectiveness and robustness of the proposed algorithm. Examples computed with normal illumination show the algorithm is comparable with pulse oximeter devices both in accuracy and sensitivity. PMID:24761294
Robust Visual Tracking Using the Bidirectional Scale Estimation
Directory of Open Access Journals (Sweden)
An Zhiyong
2017-01-01
Full Text Available Object tracking with robust scale estimation is a challenging task in computer vision. This paper presents a novel tracking algorithm that learns the translation and scale filters with a complementary scheme. The translation filter is constructed using the ridge regression and multidimensional features. A robust scale filter is constructed by the bidirectional scale estimation, including the forward scale and backward scale. Firstly, we learn the scale filter using the forward tracking information. Then the forward scale and backward scale can be estimated using the respective scale filter. Secondly, a conservative strategy is adopted to compromise the forward and backward scales. Finally, the scale filter is updated based on the final scale estimation. It is effective to update scale filter since the stable scale estimation can improve the performance of scale filter. To reveal the effectiveness of our tracker, experiments are performed on 32 sequences with significant scale variation and on the benchmark dataset with 50 challenging videos. Our results show that the proposed tracker outperforms several state-of-the-art trackers in terms of robustness and accuracy.
A robust bayesian estimate of the concordance correlation coefficient.
Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir
2015-01-01
A need for assessment of agreement arises in many situations including statistical biomarker qualification or assay or method validation. Concordance correlation coefficient (CCC) is one of the most popular scaled indices reported in evaluation of agreement. Robust methods for CCC estimation currently present an important statistical challenge. Here, we propose a novel Bayesian method of robust estimation of CCC based on multivariate Student's t-distribution and compare it with its alternatives. Furthermore, we extend the method to practically relevant settings, enabling incorporation of confounding covariates and replications. The superiority of the new approach is demonstrated using simulation as well as real datasets from biomarker application in electroencephalography (EEG). This biomarker is relevant in neuroscience for development of treatments for insomnia.
Robust position control of induction motor using fuzzy logic control
International Nuclear Information System (INIS)
Kim, Sei Chan; Kim, Duk Hun; Yang, Seung Ho; Won, Chung Yuen
1993-01-01
In recent years, fuzzy logic or fuzzy set theory has reveived attention of a number of researchers in the area of power electronics and motion control. The paper describes a vector-controlled induction motor position servo drive where fuzzy control is used to get robustness against parameter variation and load torque disturbance effects. Both coarse and fine control with the help of look-up rule tables are used to improve transient response and system settling time. The performance characteristics are then compared with those of proportional-integral(PI) control. The simulation results clearly indicate the superiority of fuzzy control with larger number of rules. The fuzzy controller was implemented with a 16-bit microprocessor and tested in laboratory on a 3-hp IGBT inverter induction motor drive system. The test results verify the simulation performance. (Author)
Robust linear discriminant analysis with distance based estimators
Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina
2017-11-01
Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.
Robust Backlash Estimation for Industrial Drive-Train Systems—Theory and Validation
DEFF Research Database (Denmark)
Papageorgiou, Dimitrios; Blanke, Mogens; Niemann, Hans Henrik
2018-01-01
Backlash compensation is used in modern machinetool controls to ensure high-accuracy positioning. When wear of a machine causes deadzone width to increase, high-accuracy control may be maintained if the deadzone is accurately estimated. Deadzone estimation is also an important parameter to indica......-of-the-art Siemens equipment. The experiments validate the theory and show that expected performance and robustness to parameter uncertainties are both achieved....
Robust estimation of adaptive tensors of curvature by tensor voting.
Tong, Wai-Shun; Tang, Chi-Keung
2005-03-01
Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.
Robust estimation of the correlation matrix of longitudinal data
Maadooliat, Mehdi
2011-09-23
We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of the form Σ=DLL⊤D where D is a diagonal matrix proportional to the square roots of the diagonal entries of Σ and L is a unit lower-triangular matrix determining solely the correlation matrix. The first robustness is with respect to model misspecification for the innovation variances in D, and the second is robustness to outliers in the data. The latter is handled using heavy-tailed multivariate t-distributions with unknown degrees of freedom. We develop a Fisher scoring algorithm for computing the maximum likelihood estimator of the parameters when the nonredundant and unconstrained entries of (L,D) are modeled parsimoniously using covariates. We compare our results with those based on the modified Cholesky decomposition of the form LD2L⊤ using simulations and a real dataset. © 2011 Springer Science+Business Media, LLC.
A robust methodology for modal parameters estimation applied to SHM
Cardoso, Rharã; Cury, Alexandre; Barbosa, Flávio
2017-10-01
The subject of structural health monitoring is drawing more and more attention over the last years. Many vibration-based techniques aiming at detecting small structural changes or even damage have been developed or enhanced through successive researches. Lately, several studies have focused on the use of raw dynamic data to assess information about structural condition. Despite this trend and much skepticism, many methods still rely on the use of modal parameters as fundamental data for damage detection. Therefore, it is of utmost importance that modal identification procedures are performed with a sufficient level of precision and automation. To fulfill these requirements, this paper presents a novel automated time-domain methodology to identify modal parameters based on a two-step clustering analysis. The first step consists in clustering modes estimates from parametric models of different orders, usually presented in stabilization diagrams. In an automated manner, the first clustering analysis indicates which estimates correspond to physical modes. To circumvent the detection of spurious modes or the loss of physical ones, a second clustering step is then performed. The second step consists in the data mining of information gathered from the first step. To attest the robustness and efficiency of the proposed methodology, numerically generated signals as well as experimental data obtained from a simply supported beam tested in laboratory and from a railway bridge are utilized. The results appeared to be more robust and accurate comparing to those obtained from methods based on one-step clustering analysis.
Robust regularized least-squares beamforming approach to signal estimation
Suliman, Mohamed Abdalla Elhag
2017-05-12
In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold. Firstly, the process requires the inversion of the usually ill-conditioned covariance matrix of the received signals. Secondly, the steering vector pertaining to the direction of arrival of the signal of interest is not known precisely. To tackle these two challenges, the standard capon beamformer is manipulated to a form where the beamformer output is obtained as a scaled version of the inner product of two vectors. The two vectors are linearly related to the steering vector and the received signal snapshot, respectively. The linear operator, in both cases, is the square root of the covariance matrix. A regularized least-squares (RLS) approach is proposed to estimate these two vectors and to provide robustness without exploiting prior information. Simulation results show that the RLS beamformer using the proposed regularization algorithm outperforms state-of-the-art beamforming algorithms, as well as another RLS beamformers using a standard regularization approaches.
Robust Solvers for Symmetric Positive Definite Operators and Weighted Poincaré Inequalities
Efendiev, Yalchin; Galvis, Juan; Lazarov, Raytcho; Willems, Joerg
2012-01-01
An abstract setting for robustly preconditioning symmetric positive definite (SPD) operators is presented. The term "robust" refers to the property of the condition numbers of the preconditioned systems being independent of mesh parameters
Histogram equalization with Bayesian estimation for noise robust speech recognition.
Suh, Youngjoo; Kim, Hoirin
2018-02-01
The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.
Robust w-Estimators for Cryo-EM Class Means
Huang, Chenxi; Tagare, Hemant D.
2016-01-01
A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the “class mean”, improves the signal-to-noise ratio in single particle reconstruction (SPR). The averaging step is often compromised because of outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods is done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a “w-estimator” of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions (CTFs) is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers. PMID:26841397
Robust head pose estimation via supervised manifold learning.
Wang, Chao; Song, Xubo
2014-05-01
Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations. Copyright © 2014 Elsevier Ltd. All rights reserved.
Influence of binary mask estimation errors on robust speaker identification
DEFF Research Database (Denmark)
May, Tobias
2017-01-01
Missing-data strategies have been developed to improve the noise-robustness of automatic speech recognition systems in adverse acoustic conditions. This is achieved by classifying time-frequency (T-F) units into reliable and unreliable components, as indicated by a so-called binary mask. Different...... approaches have been proposed to handle unreliable feature components, each with distinct advantages. The direct masking (DM) approach attenuates unreliable T-F units in the spectral domain, which allows the extraction of conventionally used mel-frequency cepstral coefficients (MFCCs). Instead of attenuating....... Since each of these approaches utilizes the knowledge about reliable and unreliable feature components in a different way, they will respond differently to estimation errors in the binary mask. The goal of this study was to identify the most effective strategy to exploit knowledge about reliable...
Fast and Robust Nanocellulose Width Estimation Using Turbidimetry.
Shimizu, Michiko; Saito, Tsuguyuki; Nishiyama, Yoshiharu; Iwamoto, Shinichiro; Yano, Hiroyuki; Isogai, Akira; Endo, Takashi
2016-10-01
The dimensions of nanocelluloses are important factors in controlling their material properties. The present study reports a fast and robust method for estimating the widths of individual nanocellulose particles based on the turbidities of their water dispersions. Seven types of nanocellulose, including short and rigid cellulose nanocrystals and long and flexible cellulose nanofibers, are prepared via different processes. Their widths are calculated from the respective turbidity plots of their water dispersions, based on the theory of light scattering by thin and long particles. The turbidity-derived widths of the seven nanocelluloses range from 2 to 10 nm, and show good correlations with the thicknesses of nanocellulose particles spread on flat mica surfaces determined using atomic force microscopy. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Estimating nonrigid motion from inconsistent intensity with robust shape features
International Nuclear Information System (INIS)
Liu, Wenyang; Ruan, Dan
2013-01-01
Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided
Robust combined position and formation control for marine surface craft
DEFF Research Database (Denmark)
Ihle, Ivar-Andre F.; Jouffroy, Jerome; Fossen, Thor I.
We consider the robustness properties of a formation control system for marine surface vessels. Intervessel constraint functions are stabilized to achieve the desired formation configuration. We show that the formation dynamics is Input-to-State Stable (ISS) to both environmental perturbations th...
Detector Position Estimation for PET Scanners.
Pierce, Larry; Miyaoka, Robert; Lewellen, Tom; Alessio, Adam; Kinahan, Paul
2012-06-11
Physical positioning of scintillation crystal detector blocks in Positron Emission Tomography (PET) scanners is not always exact. We test a proof of concept methodology for the determination of the six degrees of freedom for detector block positioning errors by utilizing a rotating point source over stepped axial intervals. To test our method, we created computer simulations of seven Micro Crystal Element Scanner (MiCES) PET systems with randomized positioning errors. The computer simulations show that our positioning algorithm can estimate the positions of the block detectors to an average of one-seventh of the crystal pitch tangentially, and one-third of the crystal pitch axially. Virtual acquisitions of a point source grid and a distributed phantom show that our algorithm improves both the quantitative and qualitative accuracy of the reconstructed objects. We believe this estimation algorithm is a practical and accurate method for determining the spatial positions of scintillation detector blocks.
Detector position estimation for PET scanners
International Nuclear Information System (INIS)
Pierce, Larry; Miyaoka, Robert; Lewellen, Tom; Alessio, Adam; Kinahan, Paul
2012-01-01
Physical positioning of scintillation crystal detector blocks in Positron Emission Tomography (PET) scanners is not always exact. We test a proof of concept methodology for the determination of the six degrees of freedom for detector block positioning errors by utilizing a rotating point source over stepped axial intervals. To test our method, we created computer simulations of seven Micro Crystal Element Scanner (MiCES) PET systems with randomized positioning errors. The computer simulations show that our positioning algorithm can estimate the positions of the block detectors to an average of one-seventh of the crystal pitch tangentially, and one-third of the crystal pitch axially. Virtual acquisitions of a point source grid and a distributed phantom show that our algorithm improves both the quantitative and qualitative accuracy of the reconstructed objects. We believe this estimation algorithm is a practical and accurate method for determining the spatial positions of scintillation detector blocks.
Robust estimation of event-related potentials via particle filter.
Fukami, Tadanori; Watanabe, Jun; Ishikawa, Fumito
2016-03-01
In clinical examinations and brain-computer interface (BCI) research, a short electroencephalogram (EEG) measurement time is ideal. The use of event-related potentials (ERPs) relies on both estimation accuracy and processing time. We tested a particle filter that uses a large number of particles to construct a probability distribution. We constructed a simple model for recording EEG comprising three components: ERPs approximated via a trend model, background waves constructed via an autoregressive model, and noise. We evaluated the performance of the particle filter based on mean squared error (MSE), P300 peak amplitude, and latency. We then compared our filter with the Kalman filter and a conventional simple averaging method. To confirm the efficacy of the filter, we used it to estimate ERP elicited by a P300 BCI speller. A 400-particle filter produced the best MSE. We found that the merit of the filter increased when the original waveform already had a low signal-to-noise ratio (SNR) (i.e., the power ratio between ERP and background EEG). We calculated the amount of averaging necessary after applying a particle filter that produced a result equivalent to that associated with conventional averaging, and determined that the particle filter yielded a maximum 42.8% reduction in measurement time. The particle filter performed better than both the Kalman filter and conventional averaging for a low SNR in terms of both MSE and P300 peak amplitude and latency. For EEG data produced by the P300 speller, we were able to use our filter to obtain ERP waveforms that were stable compared with averages produced by a conventional averaging method, irrespective of the amount of averaging. We confirmed that particle filters are efficacious in reducing the measurement time required during simulations with a low SNR. Additionally, particle filters can perform robust ERP estimation for EEG data produced via a P300 speller. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Positive polynomials and robust stabilization with fixed-order controllers
Czech Academy of Sciences Publication Activity Database
Henrion, Didier; Šebek, M.; Kučera, V.
2003-01-01
Roč. 48, č. 7 (2003), s. 1178-1186 ISSN 0018-9286 R&D Projects: GA ČR GA102/02/0709; GA MŠk ME 496 Institutional research plan: CEZ:AV0Z1075907 Keywords : fixed-order control lers * linear matrix inequality * polynomials, robust control Subject RIV: BC - Control Systems Theory Impact factor: 1.896, year: 2003
Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang
2018-05-08
When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.
Pernet, Cyril R.; Wilcox, Rand; Rousselet, Guillaume A.
2012-01-01
Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand. PMID:23335907
Pernet, Cyril R; Wilcox, Rand; Rousselet, Guillaume A
2012-01-01
Pearson's correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab((R)) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.
Directory of Open Access Journals (Sweden)
Zhanshan Wang
2014-01-01
Full Text Available The control of a high performance alternative current (AC motor drive under sensorless operation needs the accurate estimation of rotor position. In this paper, one method of accurately estimating rotor position by using both motor complex number model based position estimation and position estimation error suppression proportion integral (PI controller is proposed for the sensorless control of the surface permanent magnet synchronous motor (SPMSM. In order to guarantee the accuracy of rotor position estimation in the flux-weakening region, one scheme of identifying the permanent magnet flux of SPMSM by extended Kalman filter (EKF is also proposed, which formed the effective combination method to realize the sensorless control of SPMSM with high accuracy. The simulation results demonstrated the validity and feasibility of the proposed position/speed estimation system.
Experimental estimation of snare detectability for robust threat monitoring.
O'Kelly, Hannah J; Rowcliffe, J Marcus; Durant, Sarah; Milner-Gulland, E J
2018-02-01
Hunting with wire snares is rife within many tropical forest systems, and constitutes one of the severest threats to a wide range of vertebrate taxa. As for all threats, reliable monitoring of snaring levels is critical for assessing the relative effectiveness of management interventions. However, snares pose a particular challenge in terms of tracking spatial or temporal trends in their prevalence because they are extremely difficult to detect, and are typically spread across large, inaccessible areas. As with cryptic animal targets, any approach used to monitor snaring levels must address the issue of imperfect detection, but no standard method exists to do so. We carried out a field experiment in Keo Seima Wildlife Reserve in eastern Cambodia with the following objectives: (1) To estimate the detection probably of wire snares within a tropical forest context, and to investigate how detectability might be affected by habitat type, snare type, or observer. (2) To trial two sets of sampling protocols feasible to implement in a range of challenging field conditions. (3) To conduct a preliminary assessment of two potential analytical approaches to dealing with the resulting snare encounter data. We found that although different observers had no discernible effect on detection probability, detectability did vary between habitat type and snare type. We contend that simple repeated counts carried out at multiple sites and analyzed using binomial mixture models could represent a practical yet robust solution to the problem of monitoring snaring levels both inside and outside of protected areas. This experiment represents an important first step in developing improved methods of threat monitoring, and such methods are greatly needed in southeast Asia, as well as in as many other regions.
Position estimation of transceivers in communication networks
Kent, Claudia A [Pleasanton, CA; Dowla, Farid [Castro Valley, CA
2008-06-03
This invention provides a system and method using wireless communication interfaces coupled with statistical processing of time-of-flight data to locate by position estimation unknown wireless receivers. Such an invention can be applied in sensor network applications, such as environmental monitoring of water in the soil or chemicals in the air where the position of the network nodes is deemed critical. Moreover, the present invention can be arranged to operate in areas where a Global Positioning System (GPS) is not available, such as inside buildings, caves, and tunnels.
Robust regularized least-squares beamforming approach to signal estimation
Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Al-Naffouri, Tareq Y.
2017-01-01
In this paper, we address the problem of robust adaptive beamforming of signals received by a linear array. The challenge associated with the beamforming problem is twofold. Firstly, the process requires the inversion of the usually ill
A Robust Incomplete Factorization Preconditioner for Positive Definite Matrices
Czech Academy of Sciences Publication Activity Database
Benzi, M.; Tůma, Miroslav
2003-01-01
Roč. 10, - (2003), s. 385-400 ISSN 1070-5325 R&D Projects: GA AV ČR IAA2030801; GA AV ČR IAA1030103 Institutional research plan: AV0Z1030915 Keywords : sparse linear systems * positive definite matrices * preconditioned conjugate gradient s * incomplete factorization * A-orthogonalization * SAINV Subject RIV: BA - General Mathematics Impact factor: 1.042, year: 2003
Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization
Casas, R.; Marco, A.; Guerrero, J. J.; Falcó, J.
2006-12-01
Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS) errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.). In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS), even when nearly half the measures suffered from NLOS or other coarse errors.
Weak Properties and Robustness of t-Hill Estimators
Czech Academy of Sciences Publication Activity Database
Jordanova, P.; Fabián, Zdeněk; Hermann, P.; Střelec, L.; Rivera, A.; Girard, S.; Torres, S.; Stehlík, M.
2016-01-01
Roč. 19, č. 4 (2016), s. 591-626 ISSN 1386-1999 Institutional support: RVO:67985807 Keywords : asymptotic properties of estimators * point estimation * t-Hill estimator * t-lgHill estimator Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.679, year: 2016
DEFF Research Database (Denmark)
Ni, Ronggang; Xu, Dianguo; Blaabjerg, Frede
2017-01-01
relationship with the magnetic field distortion. Position estimation errors caused by higher order harmonic inductances and voltage harmonics generated by the SVPWM are also discussed. Both simulations and experiments are carried out based on a commercial PMSM to verify the superiority of the proposed method......Rotor position estimated with high-frequency (HF) voltage injection methods can be distorted by voltage errors due to inverter nonlinearities, motor resistance, and rotational voltage drops, etc. This paper proposes an improved HF square-wave voltage injection algorithm, which is robust to voltage...... errors without any compensations meanwhile has less fluctuation in the position estimation error. The average position estimation error is investigated based on the analysis of phase harmonic inductances, and deduced in the form of the phase shift of the second-order harmonic inductances to derive its...
Robust Parametric Fault Estimation in a Hopper System
DEFF Research Database (Denmark)
Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal
2012-01-01
The ability of diagnosis of the possible faults is a necessity for satellite launch vehicles during their mission. In this paper, a structural analysis method is employed to divide the complex propulsion system into simpler subsystems for fault diagnosis filter design. A robust fault diagnosis me...
On the robustness of two-stage estimators
Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio
2012-01-01
The aim of this note is to provide a general framework for the analysis of the robustness properties of a broad class of two-stage models. We derive the influence function, the change-of-variance function, and the asymptotic variance of a general
Robust Hinfinity position control synthesis of an electro-hydraulic servo system.
Milić, Vladimir; Situm, Zeljko; Essert, Mario
2010-10-01
This paper focuses on the use of the techniques based on linear matrix inequalities for robust H(infinity) position control synthesis of an electro-hydraulic servo system. A nonlinear dynamic model of the hydraulic cylindrical actuator with a proportional valve has been developed. For the purpose of the feedback control an uncertain linearized mathematical model of the system has been derived. The structured (parametric) perturbations in the electro-hydraulic coefficients are taken into account. H(infinity) controller extended with an integral action is proposed. To estimate internal states of the electro-hydraulic servo system an observer is designed. Developed control algorithms have been tested experimentally in the laboratory model of an electro-hydraulic servo system. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
A Robust High-Accuracy Ultrasound Indoor Positioning System Based on a Wireless Sensor Network.
Qi, Jun; Liu, Guo-Ping
2017-11-06
This paper describes the development and implementation of a robust high-accuracy ultrasonic indoor positioning system (UIPS). The UIPS consists of several wireless ultrasonic beacons in the indoor environment. Each of them has a fixed and known position coordinate and can collect all the transmissions from the target node or emit ultrasonic signals. Every wireless sensor network (WSN) node has two communication modules: one is WiFi, that transmits the data to the server, and the other is the radio frequency (RF) module, which is only used for time synchronization between different nodes, with accuracy up to 1 μ s. The distance between the beacon and the target node is calculated by measuring the time-of-flight (TOF) for the ultrasonic signal, and then the position of the target is computed by some distances and the coordinate of the beacons. TOF estimation is the most important technique in the UIPS. A new time domain method to extract the envelope of the ultrasonic signals is presented in order to estimate the TOF. This method, with the envelope detection filter, estimates the value with the sampled values on both sides based on the least squares method (LSM). The simulation results show that the method can achieve envelope detection with a good filtering effect by means of the LSM. The highest precision and variance can reach 0.61 mm and 0.23 mm, respectively, in pseudo-range measurements with UIPS. A maximum location error of 10.2 mm is achieved in the positioning experiments for a moving robot, when UIPS works on the line-of-sight (LOS) signal.
A Robust High-Accuracy Ultrasound Indoor Positioning System Based on a Wireless Sensor Network
Directory of Open Access Journals (Sweden)
Jun Qi
2017-11-01
Full Text Available This paper describes the development and implementation of a robust high-accuracy ultrasonic indoor positioning system (UIPS. The UIPS consists of several wireless ultrasonic beacons in the indoor environment. Each of them has a fixed and known position coordinate and can collect all the transmissions from the target node or emit ultrasonic signals. Every wireless sensor network (WSN node has two communication modules: one is WiFi, that transmits the data to the server, and the other is the radio frequency (RF module, which is only used for time synchronization between different nodes, with accuracy up to 1 μs. The distance between the beacon and the target node is calculated by measuring the time-of-flight (TOF for the ultrasonic signal, and then the position of the target is computed by some distances and the coordinate of the beacons. TOF estimation is the most important technique in the UIPS. A new time domain method to extract the envelope of the ultrasonic signals is presented in order to estimate the TOF. This method, with the envelope detection filter, estimates the value with the sampled values on both sides based on the least squares method (LSM. The simulation results show that the method can achieve envelope detection with a good filtering effect by means of the LSM. The highest precision and variance can reach 0.61 mm and 0.23 mm, respectively, in pseudo-range measurements with UIPS. A maximum location error of 10.2 mm is achieved in the positioning experiments for a moving robot, when UIPS works on the line-of-sight (LOS signal.
DEFF Research Database (Denmark)
2017-01-01
‘Robust – Reflections on Resilient Architecture’, is a scientific publication following the conference of the same name in November of 2017. Researches and PhD-Fellows, associated with the Masters programme: Cultural Heritage, Transformation and Restoration (Transformation), at The Royal Danish...
Sturm, J.-E.; de Haan, J.
2005-01-01
Two important problems exist in cross-country growth studies: outliers and model uncertainty. Employing Sala-i-Martin's (1997a,b) data set, we first use robust estimation and analyze to what extent outliers influence OLS regressions. We then use both OLS and robust estimation techniques in applying
Robust Estimation and Forecasting of the Capital Asset Pricing Model
G. Bian (Guorui); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)
2013-01-01
textabstractIn this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more
Robust Estimation and Forecasting of the Capital Asset Pricing Model
G. Bian (Guorui); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)
2010-01-01
textabstractIn this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more
A Robust Threshold for Iterative Channel Estimation in OFDM Systems
Directory of Open Access Journals (Sweden)
A. Kalaycioglu
2010-04-01
Full Text Available A novel threshold computation method for pilot symbol assisted iterative channel estimation in OFDM systems is considered. As the bits are transmitted in packets, the proposed technique is based on calculating a particular threshold for each data packet in order to select the reliable decoder output symbols to improve the channel estimation performance. Iteratively, additional pilot symbols are established according to the threshold and the channel is re-estimated with the new pilots inserted to the known channel estimation pilot set. The proposed threshold calculation method for selecting additional pilots performs better than non-iterative channel estimation, no threshold and fixed threshold techniques in poor HF channel simulations.
On Improving the Energy Efficiency and Robustness of Position Tracking for Mobile Devices
DEFF Research Database (Denmark)
Kjærgaard, Mikkel Baun
An important feature of a modern mobile device is that it can position itself and support remote position tracking. To be useful, such position tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device. Furthermore, tracking has to robustly deliver...... of different mobile devices....
Reducing Inventory System Costs by Using Robust Demand Estimators
Raymond A. Jacobs; Harvey M. Wagner
1989-01-01
Applications of inventory theory typically use historical data to estimate demand distribution parameters. Imprecise knowledge of the demand distribution adds to the usual replenishment costs associated with stochastic demands. Only limited research has been directed at the problem of choosing cost effective statistical procedures for estimating these parameters. Available theoretical findings on estimating the demand parameters for (s, S) inventory replenishment policies are limited by their...
A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera.
Ci, Wenyan; Huang, Yingping
2016-10-17
Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.
Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said
2014-09-01
In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.
National South African HIV prevalence estimates robust despite ...
African Journals Online (AJOL)
Approximately 18% of all people living with HIV in 2013 were estimated to live in South Africa (SA),[1] which ... 1 Research Department of Infection and Population Health, Institute for Global Health, University College London, UK.
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.
Robust Estimation of Productivity Changes in Japanese Shinkin Banks
Directory of Open Access Journals (Sweden)
Jianzhong DAI
2014-05-01
Full Text Available This paper estimates productivity changes in Japanese shinkin banks during the fiscal years 2001 to 2008 using the Malmquist index as the measure of productivity change. Data envelopment analysis (DEA is used to estimate the index. We also apply a smoothed bootstrapping approach to set up confidence intervals for estimates and study their statistical characteristics. By analyzing estimated scores, we identify trends in productivity changes in Japanese shinkin banks during the study period and investigate the sources of these trends. We find that in the latter half of the study period, productivity has significantly declined, primarily because of deterioration in technical efficiency, but scale efficiency has been significantly improved. Grouping the total sample according to the levels of competition reveals more details of productivity changes in shinkin banks.
Robust-BD Estimation and Inference for General Partially Linear Models
Directory of Open Access Journals (Sweden)
Chunming Zhang
2017-11-01
Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.
ROBUST ALGORITHMS OF PARAMETRIC ESTIMATION IN SOME STABILIZATION PROBLEMS
Directory of Open Access Journals (Sweden)
A.A. Vedyakov
2016-07-01
Full Text Available Subject of Research.The tasks of dynamic systems provision in the stable state by means of ensuring of trite solution stability for various dynamic systems in the education regime with the aid of their parameters tuning are considered. Method. The problems are solved by application of ideology of the robust finitely convergent algorithms creation. Main Results. The concepts of parametric algorithmization of stability and steady asymptotic stability are introduced and the results are presented on synthesis of coarsed gradient algorithms solving the proposed tasks for finite number of iterations with the purpose of the posed problems decision. Practical Relevance. The article results may be called for decision of practical stabilization tasks in the process of various engineering constructions and devices operation.
Robust stability and ℋ ∞ -estimation for uncertain discrete systems with state-delay
Directory of Open Access Journals (Sweden)
Mahmoud Magdi S.
2001-01-01
Full Text Available In this paper, we investigate the problems of robust stability and ℋ ∞ -estimation for a class of linear discrete-time systems with time-varying norm-bounded parameter uncertainty and unknown state-delay. We provide complete results for robust stability with prescribed performance measure and establish a version of the discrete Bounded Real Lemma. Then, we design a linear estimator such that the estimation error dynamics is robustly stable with a guaranteed ℋ ∞ -performance irrespective of the parameteric uncertainties and unknown state delays. A numerical example is worked out to illustrate the developed theory.
Computationally Efficient and Noise Robust DOA and Pitch Estimation
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2016-01-01
Many natural signals, such as voiced speech and some musical instruments, are approximately periodic over short intervals. These signals are often described in mathematics by the sum of sinusoids (harmonics) with frequencies that are proportional to the fundamental frequency, or pitch. In sensor...... a joint DOA and pitch estimator. In white Gaussian noise, we derive even more computationally efficient solutions which are designed using the narrowband power spectrum of the harmonics. Numerical results reveal the performance of the estimators in colored noise compared with the Cram\\'{e}r-Rao lower...
Robust estimators based on generalization of trimmed mean
Czech Academy of Sciences Publication Activity Database
Adam, Lukáš; Bejda, P.
(2018) ISSN 0361-0918 Institutional support: RVO:67985556 Keywords : Breakdown point * Estimators * Geometric median * Location * Trimmed mean Subject RIV: BA - General Mathematics Impact factor: 0.457, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/adam-0481224.pdf
Perception-oriented methodology for robust motion estimation design
Heinrich, A.; Vleuten, van der R.J.; Haan, de G.
2014-01-01
Optimizing a motion estimator (ME) for picture rate conversion is challenging. This is because there are many types of MEs and, within each type, many parameters, which makes subjective assessment of all the alternatives impractical. To solve this problem, we propose an automatic design methodology
Reconstruction of financial networks for robust estimation of systemic risk
International Nuclear Information System (INIS)
Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo
2012-01-01
In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks
Reconstruction of financial networks for robust estimation of systemic risk
Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo
2012-03-01
In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks.
On Improving the Energy Efficiency and Robustness of Position Tracking for Mobile Devices
DEFF Research Database (Denmark)
Kjærgaard, Mikkel Baun
2010-01-01
position updates when faced with changing conditions such as delays and changing positioning conditions. Previous work has established dynamic tracking systems, such as our EnTracked system, as a solution to address these issues. In this paper we propose a responsibility division for position tracking...... into sensor management strategies and position update protocols and combine the sensor management strategy of EnTracked with position update protocols, which enables the system to further reduce the power consumption with up to 268 mW extending the battery life with up to 36\\%. As our evaluation identify...... that classical position update protocols have robustness weaknesses we propose a method to improve their robustness. Furthermore, we analyze the dependency of tracking systems on the pedestrian movement patterns and positioning environment, and how the power savings depend on the power characteristics...
Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models
Cizek, P.; Aquaro, M.
2015-01-01
This paper extends an existing outlier-robust estimator of linear dynamic panel data models with fixed effects, which is based on the median ratio of two consecutive pairs of first-differenced data. To improve its precision and robust properties, a general procedure based on many pairwise
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 ...
Face Value: Towards Robust Estimates of Snow Leopard Densities.
Directory of Open Access Journals (Sweden)
Justine S Alexander
Full Text Available When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards Panthera uncia. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trap-days, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01 individuals per 100 km2. Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87. Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality.
A signal strength priority based position estimation for mobile platforms
Kalgikar, Bhargav; Akopian, David; Chen, Philip
2010-01-01
Global Positioning System (GPS) products help to navigate while driving, hiking, boating, and flying. GPS uses a combination of orbiting satellites to determine position coordinates. This works great in most outdoor areas, but the satellite signals are not strong enough to penetrate inside most indoor environments. As a result, a new strain of indoor positioning technologies that make use of 802.11 wireless LANs (WLAN) is beginning to appear on the market. In WLAN positioning the system either monitors propagation delays between wireless access points and wireless device users to apply trilateration techniques or it maintains the database of location-specific signal fingerprints which is used to identify the most likely match of incoming signal data with those preliminary surveyed and saved in the database. In this paper we investigate the issue of deploying WLAN positioning software on mobile platforms with typically limited computational resources. We suggest a novel received signal strength rank order based location estimation system to reduce computational loads with a robust performance. The proposed system performance is compared to conventional approaches.
Robustness of a Neural Network Model for Power Peak Factor Estimation in Protection Systems
International Nuclear Information System (INIS)
Souza, Rose Mary G.P.; Moreira, Joao M.L.
2006-01-01
This work presents results of robustness verification of artificial neural network correlations that improve the real time prediction of the power peak factor for reactor protection systems. The input variables considered in the correlation are those available in the reactor protection systems, namely, the axial power differences obtained from measured ex-core detectors, and the position of control rods. The correlations, based on radial basis function (RBF) and multilayer perceptron (MLP) neural networks, estimate the power peak factor, without faulty signals, with average errors between 0.13%, 0.19% and 0.15%, and maximum relative error of 2.35%. The robustness verification was performed for three different neural network correlations. The results show that they are robust against signal degradation, producing results with faulty signals with a maximum error of 6.90%. The average error associated to faulty signals for the MLP network is about half of that of the RBF network, and the maximum error is about 1% smaller. These results demonstrate that MLP neural network correlation is more robust than the RBF neural network correlation. The results also show that the input variables present redundant information. The axial power difference signals compensate the faulty signal for the position of a given control rod, and improves the results by about 10%. The results show that the errors in the power peak factor estimation by these neural network correlations, even in faulty conditions, are smaller than the current PWR schemes which may have uncertainties as high as 8%. Considering the maximum relative error of 2.35%, these neural network correlations would allow decreasing the power peak factor safety margin by about 5%. Such a reduction could be used for operating the reactor with a higher power level or with more flexibility. The neural network correlation has to meet requirements of high integrity software that performs safety grade actions. It is shown that the
Simultaneous Robust Fault and State Estimation for Linear Discrete-Time Uncertain Systems
Directory of Open Access Journals (Sweden)
Feten Gannouni
2017-01-01
Full Text Available We consider the problem of robust simultaneous fault and state estimation for linear uncertain discrete-time systems with unknown faults which affect both the state and the observation matrices. Using transformation of the original system, a new robust proportional integral filter (RPIF having an error variance with an optimized guaranteed upper bound for any allowed uncertainty is proposed to improve robust estimation of unknown time-varying faults and to improve robustness against uncertainties. In this study, the minimization problem of the upper bound of the estimation error variance is formulated as a convex optimization problem subject to linear matrix inequalities (LMI for all admissible uncertainties. The proportional and the integral gains are optimally chosen by solving the convex optimization problem. Simulation results are given in order to illustrate the performance of the proposed filter, in particular to solve the problem of joint fault and state estimation.
Robust control design for the plasma horizontal position control on J-TEXT Tokamak
International Nuclear Information System (INIS)
Yu, W.Z.; Chen, Z.P.; Zhuang, G.; Wang, Z.J.
2013-01-01
It is extremely important for tokamak to control the plasma position during routine discharge. However, the model of plasma in tokamak usually contains much of the uncertainty, such as structured uncertainties and unmodeled dynamics. Compared with the traditional PID control approach, robust control theory is more suitable to handle this problem. In the paper, we propose a H ∞ robust control scheme to control the horizontal position of plasma during the flat-top phase of discharge on Joint Texas Experimental Tokamak (J-TEXT) tokamak. First, the model of our plant for plasma horizontal position control is obtained from the position equilibrium equations. Then the H ∞ robust control framework is used to synthesize the controller. Based on this, an H ∞ controller is designed to minimize the regulation/tracking error. Finally, a comparison study is conducted between the optimized H ∞ robust controller and the traditional PID controller in simulations. The simulation results of the H ∞ robust controller show a significant improvement of the performance with respect to those obtained with traditional PID controller, which is currently used on our machine
Adjustment of positional geodetic networks by unconventional estimations
Directory of Open Access Journals (Sweden)
Silvia Gašincová
2010-06-01
Full Text Available The content of this paper is the adjustment of positional geodetic networks by robust estimations. The techniques (basedon the unconventional estimations of repeated least-square method which have turned out to be suitable and applicable in the practisehave been demonstrated on the example of the local geodetic network, which was founded to compose this thesis. In the thesisthe following techniques have been chosen to compare the Method of least-squares with those many published in foreign literature:M-estimation of Biweight,M-estimation of Welsch and Danish method. All presented methods are based on the repeated least-squaremethod principle with gradual changing of weight of individual measurements. In the first stage a standard least-square method wascarried out in the following steps – iterations we gradually change individual weights according to the relevant instructions/ regulation(so-called weight function. Iteration process will be stopped when no deviated measurements are found in the file of measured data.MatLab programme version 5.2 T was used to implement mathematical adjustment.
Robust k-mer frequency estimation using gapped k-mers.
Ghandi, Mahmoud; Mohammad-Noori, Morteza; Beer, Michael A
2014-08-01
Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome.
Order Tracking Based on Robust Peak Search Instantaneous Frequency Estimation
International Nuclear Information System (INIS)
Gao, Y; Guo, Y; Chi, Y L; Qin, S R
2006-01-01
Order tracking plays an important role in non-stationary vibration analysis of rotating machinery, especially to run-up or coast down. An instantaneous frequency estimation (IFE) based order tracking of rotating machinery is introduced. In which, a peak search algorithms of spectrogram of time-frequency analysis is employed to obtain IFE of vibrations. An improvement to peak search is proposed, which can avoid strong non-order components or noises disturbing to the peak search work. Compared with traditional methods of order tracking, IFE based order tracking is simplified in application and only software depended. Testing testify the validity of the method. This method is an effective supplement to traditional methods, and the application in condition monitoring and diagnosis of rotating machinery is imaginable
Robust Homography Estimation Based on Nonlinear Least Squares Optimization
Directory of Open Access Journals (Sweden)
Wei Mou
2014-01-01
Full Text Available The homography between image pairs is normally estimated by minimizing a suitable cost function given 2D keypoint correspondences. The correspondences are typically established using descriptor distance of keypoints. However, the correspondences are often incorrect due to ambiguous descriptors which can introduce errors into following homography computing step. There have been numerous attempts to filter out these erroneous correspondences, but it is unlikely to always achieve perfect matching. To deal with this problem, we propose a nonlinear least squares optimization approach to compute homography such that false matches have no or little effect on computed homography. Unlike normal homography computation algorithms, our method formulates not only the keypoints’ geometric relationship but also their descriptor similarity into cost function. Moreover, the cost function is parametrized in such a way that incorrect correspondences can be simultaneously identified while the homography is computed. Experiments show that the proposed approach can perform well even with the presence of a large number of outliers.
International Nuclear Information System (INIS)
Lee, Chang-Chun; Shih, Yan-Shin; Wu, Chih-Sheng; Tsai, Chia-Hao; Yeh, Shu-Tang; Peng, Yi-Hao; Chen, Kuang-Jung
2012-01-01
This work analyses the overall stress/strain characteristic of flexible encapsulations with organic light-emitting diode (OLED) devices. A robust methodology composed of a mechanical model of multi-thin film under bending loads and related stress simulations based on nonlinear finite element analysis (FEA) is proposed, and validated to be more reliable compared with related experimental data. With various geometrical combinations of cover plate, stacked thin films and plastic substrate, the position of the neutral axis (NA) plate, which is regarded as a key design parameter to minimize stress impact for the concerned OLED devices, is acquired using the present methodology. The results point out that both the thickness and mechanical properties of the cover plate help in determining the NA location. In addition, several concave and convex radii are applied to examine the reliable mechanical tolerance and to provide an insight into the estimated reliability of foldable OLED encapsulations. (paper)
A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera
Directory of Open Access Journals (Sweden)
Wenyan Ci
2016-10-01
Full Text Available Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera’s 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg–Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade–Lucas–Tomasi (KLT algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.
Graphical evaluation of the ridge-type robust regression estimators in mixture experiments.
Erkoc, Ali; Emiroglu, Esra; Akay, Kadri Ulas
2014-01-01
In mixture experiments, estimation of the parameters is generally based on ordinary least squares (OLS). However, in the presence of multicollinearity and outliers, OLS can result in very poor estimates. In this case, effects due to the combined outlier-multicollinearity problem can be reduced to certain extent by using alternative approaches. One of these approaches is to use biased-robust regression techniques for the estimation of parameters. In this paper, we evaluate various ridge-type robust estimators in the cases where there are multicollinearity and outliers during the analysis of mixture experiments. Also, for selection of biasing parameter, we use fraction of design space plots for evaluating the effect of the ridge-type robust estimators with respect to the scaled mean squared error of prediction. The suggested graphical approach is illustrated on Hald cement data set.
Robust estimation for partially linear models with large-dimensional covariates.
Zhu, LiPing; Li, RunZe; Cui, HengJian
2013-10-01
We are concerned with robust estimation procedures to estimate the parameters in partially linear models with large-dimensional covariates. To enhance the interpretability, we suggest implementing a noncon-cave regularization method in the robust estimation procedure to select important covariates from the linear component. We establish the consistency for both the linear and the nonlinear components when the covariate dimension diverges at the rate of [Formula: see text], where n is the sample size. We show that the robust estimate of linear component performs asymptotically as well as its oracle counterpart which assumes the baseline function and the unimportant covariates were known a priori. With a consistent estimator of the linear component, we estimate the nonparametric component by a robust local linear regression. It is proved that the robust estimate of nonlinear component performs asymptotically as well as if the linear component were known in advance. Comprehensive simulation studies are carried out and an application is presented to examine the finite-sample performance of the proposed procedures.
Robust domain decomposition preconditioners for abstract symmetric positive definite bilinear forms
Efendiev, Yalchin
2012-02-22
An abstract framework for constructing stable decompositions of the spaces corresponding to general symmetric positive definite problems into "local" subspaces and a global "coarse" space is developed. Particular applications of this abstract framework include practically important problems in porous media applications such as: the scalar elliptic (pressure) equation and the stream function formulation of its mixed form, Stokes\\' and Brinkman\\'s equations. The constant in the corresponding abstract energy estimate is shown to be robust with respect to mesh parameters as well as the contrast, which is defined as the ratio of high and low values of the conductivity (or permeability). The derived stable decomposition allows to construct additive overlapping Schwarz iterative methods with condition numbers uniformly bounded with respect to the contrast and mesh parameters. The coarse spaces are obtained by patching together the eigenfunctions corresponding to the smallest eigenvalues of certain local problems. A detailed analysis of the abstract setting is provided. The proposed decomposition builds on a method of Galvis and Efendiev [Multiscale Model. Simul. 8 (2010) 1461-1483] developed for second order scalar elliptic problems with high contrast. Applications to the finite element discretizations of the second order elliptic problem in Galerkin and mixed formulation, the Stokes equations, and Brinkman\\'s problem are presented. A number of numerical experiments for these problems in two spatial dimensions are provided. © EDP Sciences, SMAI, 2012.
Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization
Directory of Open Access Journals (Sweden)
Marco A
2006-01-01
Full Text Available Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.. In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS, even when nearly half the measures suffered from NLOS or other coarse errors.
Robust and bias-corrected estimation of the coefficient of tail dependence
DEFF Research Database (Denmark)
Dutang, C.; Goegebeur, Y.; Guillou, A.
2014-01-01
We introduce a robust and asymptotically unbiased estimator for the coefficient of tail dependence in multivariate extreme value statistics. The estimator is obtained by fitting a second order model to the data by means of the minimum density power divergence criterion. The asymptotic properties ...
Robust estimation and moment selection in dynamic fixed-effects panel data models
Cizek, Pavel; Aquaro, Michele
Considering linear dynamic panel data models with fixed effects, existing outlier–robust estimators based on the median ratio of two consecutive pairs of first-differenced data are extended to higher-order differencing. The estimation procedure is thus based on many pairwise differences and their
DEFF Research Database (Denmark)
Lu, Xiaobing; Liu, Zhigang; Song, Yang
2018-01-01
Active control of the pantograph is one of the promising measures for decreasing fluctuation in the contact force between the pantograph and the catenary. In this paper, an estimator-based multiobjective robust control strategy is proposed for an active pantograph, which consists of a state estim...
A robust background regression based score estimation algorithm for hyperspectral anomaly detection
Zhao, Rui; Du, Bo; Zhang, Liangpei; Zhang, Lefei
2016-12-01
Anomaly detection has become a hot topic in the hyperspectral image analysis and processing fields in recent years. The most important issue for hyperspectral anomaly detection is the background estimation and suppression. Unreasonable or non-robust background estimation usually leads to unsatisfactory anomaly detection results. Furthermore, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection. In order to implement robust background estimation, as well as to explore the intrinsic data structure of the hyperspectral image, we propose a robust background regression based score estimation algorithm (RBRSE) for hyperspectral anomaly detection. The Robust Background Regression (RBR) is actually a label assignment procedure which segments the hyperspectral data into a robust background dataset and a potential anomaly dataset with an intersection boundary. In the RBR, a kernel expansion technique, which explores the nonlinear structure of the hyperspectral data in a reproducing kernel Hilbert space, is utilized to formulate the data as a density feature representation. A minimum squared loss relationship is constructed between the data density feature and the corresponding assigned labels of the hyperspectral data, to formulate the foundation of the regression. Furthermore, a manifold regularization term which explores the manifold smoothness of the hyperspectral data, and a maximization term of the robust background average density, which suppresses the bias caused by the potential anomalies, are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation method is undertaken on the robust background and potential anomaly datasets, to implement the detection output. The experimental results show that RBRSE achieves superior ROC curves, AUC values, and background-anomaly separation than some of the other state-of-the-art anomaly detection methods, and is easy to implement
ESTIMATION OF GRASPING TORQUE USING ROBUST REACTION TORQUE OBSERVER FOR ROBOTIC FORCEPS
塚本, 祐介
2015-01-01
Abstract— In this paper, the estimation of the grasping torque of robotic forceps without the use of a force/torque sensor is discussed. To estimate the grasping torque when the robotic forceps driven by a rotary motor with a reduction gear grasps an object, a novel robust reaction torque observer is proposed. In the case where a conventional reaction force/torque observer is applied, the estimated torque includes not only the grasping torque, namely the reaction torque, but also t...
multiangulation position estimation performance analysis using
African Journals Online (AJOL)
HOD
multiangulation PE error is 50% lower than that of the directional rotating antenna system. Furthermore, the ... system is an example of a wireless positioning system that has ..... Table 2: PE error for some selection source locations. No. Range ...
Robust DOA Estimation of Harmonic Signals Using Constrained Filters on Phase Estimates
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
In array signal processing, distances between receivers, e.g., microphones, cause time delays depending on the direction of arrival (DOA) of a signal source. We can then estimate the DOA from the time-difference of arrival (TDOA) estimates. However, many conventional DOA estimators based on TDOA...... estimates are not optimal in colored noise. In this paper, we estimate the DOA of a harmonic signal source from multi-channel phase estimates, which relate to narrowband TDOA estimates. More specifically, we design filters to apply on phase estimates to obtain a DOA estimate with minimum variance. Using...
International Nuclear Information System (INIS)
Jin, Maolin; Chang, Pyung Hun
2009-01-01
This work presents two simple and robust techniques based on time delay estimation for the respective control and synchronization of chaos systems. First, one of these techniques is applied to the control of a chaotic Lorenz system with both matched and mismatched uncertainties. The nonlinearities in the Lorenz system is cancelled by time delay estimation and desired error dynamics is inserted. Second, the other technique is applied to the synchronization of the Lue system and the Lorenz system with uncertainties. The synchronization input consists of three elements that have transparent and clear meanings. Since time delay estimation enables a very effective and efficient cancellation of disturbances and nonlinearities, the techniques turn out to be simple and robust. Numerical simulation results show fast, accurate and robust performance of the proposed techniques, thereby demonstrating their effectiveness for the control and synchronization of Lorenz systems.
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...
Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
Chen, Yi-Hau
2009-03-01
Case-control association studies often aim to investigate the role of genes and gene-environment interactions in terms of the underlying haplotypes (i.e., the combinations of alleles at multiple genetic loci along chromosomal regions). The goal of this article is to develop robust but efficient approaches to the estimation of disease odds-ratio parameters associated with haplotypes and haplotype-environment interactions. We consider "shrinkage" estimation techniques that can adaptively relax the model assumptions of Hardy-Weinberg-Equilibrium and gene-environment independence required by recently proposed efficient "retrospective" methods. Our proposal involves first development of a novel retrospective approach to the analysis of case-control data, one that is robust to the nature of the gene-environment distribution in the underlying population. Next, it involves shrinkage of the robust retrospective estimator toward a more precise, but model-dependent, retrospective estimator using novel empirical Bayes and penalized regression techniques. Methods for variance estimation are proposed based on asymptotic theories. Simulations and two data examples illustrate both the robustness and efficiency of the proposed methods.
Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
Chen, Yi-Hau; Chatterjee, Nilanjan; Carroll, Raymond J.
2009-01-01
Case-control association studies often aim to investigate the role of genes and gene-environment interactions in terms of the underlying haplotypes (i.e., the combinations of alleles at multiple genetic loci along chromosomal regions). The goal of this article is to develop robust but efficient approaches to the estimation of disease odds-ratio parameters associated with haplotypes and haplotype-environment interactions. We consider "shrinkage" estimation techniques that can adaptively relax the model assumptions of Hardy-Weinberg-Equilibrium and gene-environment independence required by recently proposed efficient "retrospective" methods. Our proposal involves first development of a novel retrospective approach to the analysis of case-control data, one that is robust to the nature of the gene-environment distribution in the underlying population. Next, it involves shrinkage of the robust retrospective estimator toward a more precise, but model-dependent, retrospective estimator using novel empirical Bayes and penalized regression techniques. Methods for variance estimation are proposed based on asymptotic theories. Simulations and two data examples illustrate both the robustness and efficiency of the proposed methods.
A modern robust approach to remotely estimate chlorophyll in coastal and inland zones
Shanmugam, Palanisamy; He, Xianqiang; Singh, Rakesh Kumar; Varunan, Theenathayalan
2018-05-01
The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.
Estimating open population site occupancy from presence-absence data lacking the robust design.
Dail, D; Madsen, L
2013-03-01
Many animal monitoring studies seek to estimate the proportion of a study area occupied by a target population. The study area is divided into spatially distinct sites where the detected presence or absence of the population is recorded, and this is repeated in time for multiple seasons. However, when occupied sites are detected with probability p Ecology 84, 2200-2207) developed a multiseason model for estimating seasonal site occupancy (ψt ) while accounting for unknown p. Their model performs well when observations are collected according to the robust design, where multiple sampling occasions occur during each season; the repeated sampling aids in the estimation p. However, their model does not perform as well when the robust design is lacking. In this paper, we propose an alternative likelihood model that yields improved seasonal estimates of p and Ψt in the absence of the robust design. We construct the marginal likelihood of the observed data by conditioning on, and summing out, the latent number of occupied sites during each season. A simulation study shows that in cases without the robust design, the proposed model estimates p with less bias than the MacKenzie et al. model and hence improves the estimates of Ψt . We apply both models to a data set consisting of repeated presence-absence observations of American robins (Turdus migratorius) with yearly survey periods. The two models are compared to a third estimator available when the repeated counts (from the same study) are considered, with the proposed model yielding estimates of Ψt closest to estimates from the point count model. Copyright © 2013, The International Biometric Society.
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.
Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing
2018-03-07
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.
Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.
Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi
2017-12-01
We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.
Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing
2016-12-20
Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.
2013-09-01
This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.
International Nuclear Information System (INIS)
Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A
2013-01-01
This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)
Novel Position and Speed Estimator for PM Single Phase Brushless D.C. Motor Drives
DEFF Research Database (Denmark)
Lepure, Liviu I.; Andreescu, Gheorghe-Daniel; Iles, Doris
2010-01-01
A novel position and speed estimator for single phase permanent magnet brushless d.c. (PMBLDC) motor drives, based on flux integration and prior knowledge of ΨPM (θ) is proposed here and an adequate correction algorithm is adopted in order to increase the robustness to noise and to reduce...... the sensitivity to accuracy of flux linkage estimation. A speed and current close loop control is employed based on the Hall signal and the motor is controlled at different speeds in order to validate the proposed estimation algorithm with satisfying results. The position correction effect is analyzed...
Directory of Open Access Journals (Sweden)
Bangyan Zhu
2016-07-01
Full Text Available Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.
Robust experiment design for estimating myocardial β adrenergic receptor concentration using PET
International Nuclear Information System (INIS)
Salinas, Cristian; Muzic, Raymond F. Jr.; Ernsberger, Paul; Saidel, Gerald M.
2007-01-01
Myocardial β adrenergic receptor (β-AR) concentration can substantially decrease in congestive heart failure and significantly increase in chronic volume overload, such as in severe aortic valve regurgitation. Positron emission tomography (PET) with an appropriate ligand-receptor model can be used for noninvasive estimation of myocardial β-AR concentration in vivo. An optimal design of the experiment protocol, however, is needed for sufficiently precise estimates of β-AR concentration in a heterogeneous population. Standard methods of optimal design do not account for a heterogeneous population with a wide range of β-AR concentrations and other physiological parameters and consequently are inadequate. To address this, we have developed a methodology to design a robust two-injection protocol that provides reliable estimates of myocardial β-AR concentration in normal and pathologic states. A two-injection protocol of the high affinity β-AR antagonist [ 18 F]-(S)-fluorocarazolol was designed based on a computer-generated (or synthetic) population incorporating a wide range of β-AR concentrations. Timing and dosage of the ligand injections were optimally designed with minimax criterion to provide the least bad β-AR estimates for the worst case in the synthetic population. This robust experiment design for PET was applied to experiments with pigs before and after β-AR upregulation by chemical sympathectomy. Estimates of β-AR concentration were found by minimizing the difference between the model-predicted and experimental PET data. With this robust protocol, estimates of β-AR concentration showed high precision in both normal and pathologic states. The increase in β-AR concentration after sympathectomy predicted noninvasively with PET is consistent with the increase shown by in vitro assays in pig myocardium. A robust experiment protocol was designed for PET that yields reliable estimates of β-AR concentration in a population with normal and pathologic
Directory of Open Access Journals (Sweden)
Esteban Jiménez-Rodríguez
2016-12-01
Full Text Available This paper presents an estimation structure for a continuous stirred-tank reactor, which is comprised of a sliding mode observer-based estimator coupled with a high-order sliding-mode observer. The whole scheme allows the robust estimation of the state and some parameters, specifically the concentration of the reactive mass, the heat of reaction and the global coefficient of heat transfer, by measuring the temperature inside the reactor and the temperature inside the jacket. In order to verify the results, the convergence proof of the proposed structure is done, and numerical simulations are presented with noiseless and noisy measurements, suggesting the applicability of the posed approach.
Detection of heart beats in multimodal data: a robust beat-to-beat interval estimation approach.
Antink, Christoph Hoog; Brüser, Christoph; Leonhardt, Steffen
2015-08-01
The heart rate and its variability play a vital role in the continuous monitoring of patients, especially in the critical care unit. They are commonly derived automatically from the electrocardiogram as the interval between consecutive heart beat. While their identification by QRS-complexes is straightforward under ideal conditions, the exact localization can be a challenging task if the signal is severely contaminated with noise and artifacts. At the same time, other signals directly related to cardiac activity are often available. In this multi-sensor scenario, methods of multimodal sensor-fusion allow the exploitation of redundancies to increase the accuracy and robustness of beat detection.In this paper, an algorithm for the robust detection of heart beats in multimodal data is presented. Classic peak-detection is augmented by robust multi-channel, multimodal interval estimation to eliminate false detections and insert missing beats. This approach yielded a score of 90.70 and was thus ranked third place in the PhysioNet/Computing in Cardiology Challenge 2014: Robust Detection of Heart Beats in Muthmodal Data follow-up analysis.In the future, the robust beat-to-beat interval estimator may directly be used for the automated processing of multimodal patient data for applications such as diagnosis support and intelligent alarming.
Robust Solvers for Symmetric Positive Definite Operators and Weighted Poincaré Inequalities
Efendiev, Yalchin
2012-01-01
An abstract setting for robustly preconditioning symmetric positive definite (SPD) operators is presented. The term "robust" refers to the property of the condition numbers of the preconditioned systems being independent of mesh parameters and problem parameters. Important instances of such problem parameters are in particular (highly varying) coefficients. The method belongs to the class of additive Schwarz preconditioners. The paper gives an overview of the results obtained in a recent paper by the authors. It, furthermore, focuses on the importance of weighted Poincaré inequalities, whose notion is extended to general SPD operators, for the analysis of stable decompositions. To demonstrate the applicability of the abstract preconditioner the scalar elliptic equation and the stream function formulation of Brinkman\\'s equations in two spatial dimensions are considered. Several numerical examples are presented. © 2012 Springer-Verlag.
A robust rotation-invariance displacement measurement method for a micro-/nano-positioning system
Zhang, Xiang; Zhang, Xianmin; Wu, Heng; Li, Hai; Gan, Jinqiang
2018-05-01
A robust and high-precision displacement measurement method for a compliant mechanism-based micro-/nano-positioning system is proposed. The method is composed of an integer-pixel and a sub-pixel matching procedure. In the proposed algorithm (Pro-A), an improved ring projection transform (IRPT) and gradient information are used as features for approximating the coarse candidates and fine locations, respectively. Simulations are conducted and the results show that the Pro-A has the ability of rotation-invariance and strong robustness, with a theoretical accuracy of 0.01 pixel. To validate the practical performance, a series of experiments are carried out using a computer micro-vision and laser interferometer system (LIMS). The results demonstrate that both the LIMS and Pro-A can achieve high precision, while the Pro-A has better stability and adaptability.
Robust H∞ Control of Neutral System with Time-Delay for Dynamic Positioning Ships
Directory of Open Access Journals (Sweden)
Dawei Zhao
2015-01-01
Full Text Available Due to the input time-delay existing in most thrust systems of the ships, the robust H∞ controller is designed for the ship dynamic positioning (DP system with time-delay. The input delay system is turned to a neutral time-delay system by a state-derivative control law. The less conservative result is derived for the neutral system with state-derivative feedback by the delay-decomposition approach and linear matrix inequality (LMI. Finally, the numerical simulations demonstrate the asymptotic stability and robustness of the controller and verify that the designed DP controller is effective in the varying environment disturbances of wind, waves, and ocean currents.
International Nuclear Information System (INIS)
Mo, Se Hyun; Jeon, Young Pil; Park, Jong Ho; Chong, Kil To
2017-01-01
With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.
Energy Technology Data Exchange (ETDEWEB)
Mo, Se Hyun [Amotech, Seoul (Korea, Republic of); Jeon, Young Pil [Samsung Electronics Co., Ltd. Suwon (Korea, Republic of); Park, Jong Ho [Seonam Univ., Namwon (Korea, Republic of); Chong, Kil To [Chon-buk Nat' 1 Univ., Junju (Korea, Republic of)
2017-07-15
With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.
Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P
2014-06-26
To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.
Kendall, W.L.; Nichols, J.D.; Hines, J.E.
1997-01-01
Statistical inference for capture-recapture studies of open animal populations typically relies on the assumption that all emigration from the studied population is permanent. However, there are many instances in which this assumption is unlikely to be met. We define two general models for the process of temporary emigration, completely random and Markovian. We then consider effects of these two types of temporary emigration on Jolly-Seber (Seber 1982) estimators and on estimators arising from the full-likelihood approach of Kendall et al. (1995) to robust design data. Capture-recapture data arising from Pollock's (1982) robust design provide the basis for obtaining unbiased estimates of demographic parameters in the presence of temporary emigration and for estimating the probability of temporary emigration. We present a likelihood-based approach to dealing with temporary emigration that permits estimation under different models of temporary emigration and yields tests for completely random and Markovian emigration. In addition, we use the relationship between capture probability estimates based on closed and open models under completely random temporary emigration to derive three ad hoc estimators for the probability of temporary emigration, two of which should be especially useful in situations where capture probabilities are heterogeneous among individual animals. Ad hoc and full-likelihood estimators are illustrated for small mammal capture-recapture data sets. We believe that these models and estimators will be useful for testing hypotheses about the process of temporary emigration, for estimating demographic parameters in the presence of temporary emigration, and for estimating probabilities of temporary emigration. These latter estimates are frequently of ecological interest as indicators of animal movement and, in some sampling situations, as direct estimates of breeding probabilities and proportions.
Robust estimation of autoregressive processes using a mixture-based filter-bank
Czech Academy of Sciences Publication Activity Database
Šmídl, V.; Anthony, Q.; Kárný, Miroslav; Guy, Tatiana Valentine
2005-01-01
Roč. 54, č. 4 (2005), s. 315-323 ISSN 0167-6911 R&D Projects: GA AV ČR IBS1075351; GA ČR GA102/03/0049; GA ČR GP102/03/P010; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian estimation * probabilistic mixtures * recursive estimation Subject RIV: BC - Control Systems Theory Impact factor: 1.239, year: 2005 http://library.utia.cas.cz/separaty/historie/karny-robust estimation of autoregressive processes using a mixture-based filter- bank .pdf
Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean
Energy Technology Data Exchange (ETDEWEB)
Razooky, Brandon S. [Rockefeller Univ., New York, NY (United States). Lab. of Virology and Infectious Disease; Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Univ. of California, San Francisco, CA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary; Cao, Youfang [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hansen, Maike M. K. [Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Perelson, Alan S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Simpson, Michael L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary; Weinberger, Leor S. [Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Univ. of California, San Francisco, CA (United States). Dept. of Biochemistry and Biophysics; Univ. of California, San Francisco, CA (United States). QB3: California Inst. of Quantitative Biosciences; Univ. of California, San Francisco, CA (United States). Dept. of Pharmaceutical Chemistry
2017-10-18
Fundamental to biological decision-making is the ability to generate bimodal expression patterns where two alternate expression states simultaneously exist. Here in this study, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV’s fate decision between active replication and viral latency. We find that the HIV Tat protein manipulates the intrinsic toggling of HIV’s promoter, the LTR, to generate bimodal ON-OFF expression, and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit’s non-cooperative ‘non-latching’ feedback architecture is optimized to slow the promoter’s toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that non-latching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean-expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV’s decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.
Directory of Open Access Journals (Sweden)
Marion Hoehn
Full Text Available The effective population size (N(e is proportional to the loss of genetic diversity and the rate of inbreeding, and its accurate estimation is crucial for the monitoring of small populations. Here, we integrate temporal studies of the gecko Oedura reticulata, to compare genetic and demographic estimators of N(e. Because geckos have overlapping generations, our goal was to demographically estimate N(bI, the inbreeding effective number of breeders and to calculate the N(bI/N(a ratio (N(a =number of adults for four populations. Demographically estimated N(bI ranged from 1 to 65 individuals. The mean reduction in the effective number of breeders relative to census size (N(bI/N(a was 0.1 to 1.1. We identified the variance in reproductive success as the most important variable contributing to reduction of this ratio. We used four methods to estimate the genetic based inbreeding effective number of breeders N(bI(gen and the variance effective populations size N(eV(gen estimates from the genotype data. Two of these methods - a temporal moment-based (MBT and a likelihood-based approach (TM3 require at least two samples in time, while the other two were single-sample estimators - the linkage disequilibrium method with bias correction LDNe and the program ONeSAMP. The genetic based estimates were fairly similar across methods and also similar to the demographic estimates excluding those estimates, in which upper confidence interval boundaries were uninformative. For example, LDNe and ONeSAMP estimates ranged from 14-55 and 24-48 individuals, respectively. However, temporal methods suffered from a large variation in confidence intervals and concerns about the prior information. We conclude that the single-sample estimators are an acceptable short-cut to estimate N(bI for species such as geckos and will be of great importance for the monitoring of species in fragmented landscapes.
Estimation non-paramétrique robuste pour données fonctionnelles
Crambes , Christophe; Delsol , Laurent; Laksaci , Ali
2009-01-01
International audience; L'estimation robuste présente une approche alternative aux méthodes de régression classiques, par exemple lorsque les observations sont affectées par la présence de données aberrantes. Récemment, ces estimateurs robustes ont été considérés pour des modèles avec données fonctionnelles. Dans cet exposé, nous considérons un modèle de régression robuste avec une variable d'intérêt réelle et une variable explicative fonctionnelle. Nous définissons un estimateur non-paramétr...
Robust estimation for homoscedastic regression in the secondary analysis of case-control data
Wei, Jiawei
2012-12-04
Primary analysis of case-control studies focuses on the relationship between disease D and a set of covariates of interest (Y, X). A secondary application of the case-control study, which is often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated owing to the case-control sampling, where the regression of Y on X is different from what it is in the population. Previous work has assumed a parametric distribution for Y given X and derived semiparametric efficient estimation and inference without any distributional assumptions about X. We take up the issue of estimation of a regression function when Y given X follows a homoscedastic regression model, but otherwise the distribution of Y is unspecified. The semiparametric efficient approaches can be used to construct semiparametric efficient estimates, but they suffer from a lack of robustness to the assumed model for Y given X. We take an entirely different approach. We show how to estimate the regression parameters consistently even if the assumed model for Y given X is incorrect, and thus the estimates are model robust. For this we make the assumption that the disease rate is known or well estimated. The assumption can be dropped when the disease is rare, which is typically so for most case-control studies, and the estimation algorithm simplifies. Simulations and empirical examples are used to illustrate the approach.
Robust estimation for homoscedastic regression in the secondary analysis of case-control data
Wei, Jiawei; Carroll, Raymond J.; Mü ller, Ursula U.; Keilegom, Ingrid Van; Chatterjee, Nilanjan
2012-01-01
Primary analysis of case-control studies focuses on the relationship between disease D and a set of covariates of interest (Y, X). A secondary application of the case-control study, which is often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated owing to the case-control sampling, where the regression of Y on X is different from what it is in the population. Previous work has assumed a parametric distribution for Y given X and derived semiparametric efficient estimation and inference without any distributional assumptions about X. We take up the issue of estimation of a regression function when Y given X follows a homoscedastic regression model, but otherwise the distribution of Y is unspecified. The semiparametric efficient approaches can be used to construct semiparametric efficient estimates, but they suffer from a lack of robustness to the assumed model for Y given X. We take an entirely different approach. We show how to estimate the regression parameters consistently even if the assumed model for Y given X is incorrect, and thus the estimates are model robust. For this we make the assumption that the disease rate is known or well estimated. The assumption can be dropped when the disease is rare, which is typically so for most case-control studies, and the estimation algorithm simplifies. Simulations and empirical examples are used to illustrate the approach.
Efficient estimation of the robustness region of biological models with oscillatory behavior.
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Mochamad Apri
Full Text Available Robustness is an essential feature of biological systems, and any mathematical model that describes such a system should reflect this feature. Especially, persistence of oscillatory behavior is an important issue. A benchmark model for this phenomenon is the Laub-Loomis model, a nonlinear model for cAMP oscillations in Dictyostelium discoideum. This model captures the most important features of biomolecular networks oscillating at constant frequencies. Nevertheless, the robustness of its oscillatory behavior is not yet fully understood. Given a system that exhibits oscillating behavior for some set of parameters, the central question of robustness is how far the parameters may be changed, such that the qualitative behavior does not change. The determination of such a "robustness region" in parameter space is an intricate task. If the number of parameters is high, it may be also time consuming. In the literature, several methods are proposed that partially tackle this problem. For example, some methods only detect particular bifurcations, or only find a relatively small box-shaped estimate for an irregularly shaped robustness region. Here, we present an approach that is much more general, and is especially designed to be efficient for systems with a large number of parameters. As an illustration, we apply the method first to a well understood low-dimensional system, the Rosenzweig-MacArthur model. This is a predator-prey model featuring satiation of the predator. It has only two parameters and its bifurcation diagram is available in the literature. We find a good agreement with the existing knowledge about this model. When we apply the new method to the high dimensional Laub-Loomis model, we obtain a much larger robustness region than reported earlier in the literature. This clearly demonstrates the power of our method. From the results, we conclude that the biological system underlying is much more robust than was realized until now.
Linden, Ariel
2017-08-01
When a randomized controlled trial is not feasible, health researchers typically use observational data and rely on statistical methods to adjust for confounding when estimating treatment effects. These methods generally fall into 3 categories: (1) estimators based on a model for the outcome using conventional regression adjustment; (2) weighted estimators based on the propensity score (ie, a model for the treatment assignment); and (3) "doubly robust" (DR) estimators that model both the outcome and propensity score within the same framework. In this paper, we introduce a new DR estimator that utilizes marginal mean weighting through stratification (MMWS) as the basis for weighted adjustment. This estimator may prove more accurate than treatment effect estimators because MMWS has been shown to be more accurate than other models when the propensity score is misspecified. We therefore compare the performance of this new estimator to other commonly used treatment effects estimators. Monte Carlo simulation is used to compare the DR-MMWS estimator to regression adjustment, 2 weighted estimators based on the propensity score and 2 other DR methods. To assess performance under varied conditions, we vary the level of misspecification of the propensity score model as well as misspecify the outcome model. Overall, DR estimators generally outperform methods that model one or the other components (eg, propensity score or outcome). The DR-MMWS estimator outperforms all other estimators when both the propensity score and outcome models are misspecified and performs equally as well as other DR estimators when only the propensity score is misspecified. Health researchers should consider using DR-MMWS as the principal evaluation strategy in observational studies, as this estimator appears to outperform other estimators in its class. © 2017 John Wiley & Sons, Ltd.
A new method for robust video watermarking resistant against key estimation attacks
Mitekin, Vitaly
2015-12-01
This paper presents a new method for high-capacity robust digital video watermarking and algorithms of embedding and extraction of watermark based on this method. Proposed method uses password-based two-dimensional pseudonoise arrays for watermark embedding, making brute-force attacks aimed at steganographic key retrieval mostly impractical. Proposed algorithm for 2-dimensional "noise-like" watermarking patterns generation also allows to significantly decrease watermark collision probability ( i.e. probability of correct watermark detection and extraction using incorrect steganographic key or password).. Experimental research provided in this work also shows that simple correlation-based watermark detection procedure can be used, providing watermark robustness against lossy compression and watermark estimation attacks. At the same time, without decreasing robustness of embedded watermark, average complexity of the brute-force key retrieval attack can be increased to 1014 watermark extraction attempts (compared to 104-106 for a known robust watermarking schemes). Experimental results also shows that for lowest embedding intensity watermark preserves it's robustness against lossy compression of host video and at the same time preserves higher video quality (PSNR up to 51dB) compared to known wavelet-based and DCT-based watermarking algorithms.
Efficient and robust estimation for longitudinal mixed models for binary data
DEFF Research Database (Denmark)
Holst, René
2009-01-01
This paper proposes a longitudinal mixed model for binary data. The model extends the classical Poisson trick, in which a binomial regression is fitted by switching to a Poisson framework. A recent estimating equations method for generalized linear longitudinal mixed models, called GEEP, is used...... as a vehicle for fitting the conditional Poisson regressions, given a latent process of serial correlated Tweedie variables. The regression parameters are estimated using a quasi-score method, whereas the dispersion and correlation parameters are estimated by use of bias-corrected Pearson-type estimating...... equations, using second moments only. Random effects are predicted by BLUPs. The method provides a computationally efficient and robust approach to the estimation of longitudinal clustered binary data and accommodates linear and non-linear models. A simulation study is used for validation and finally...
DEFF Research Database (Denmark)
Jensen, Anders Vestergaard; Barfod, Michael Bruhn; Leleur, Steen
2011-01-01
described is based on the fact that when using MCA as a decision-support tool, questions often arise about the weighting (or prioritising) of the included criteria. This part of the MCA is seen as the most subjective part and could give reasons for discussion among the decision makers or stakeholders......Abstract This paper discusses the concept of using rank variation concerning the stakeholder prioritising of importance criteria for exploring the sensitivity of criteria weights in multi-criteria analysis (MCA). Thereby the robustness of the MCA-based decision support can be tested. The analysis....... Furthermore, the relative weights can make a large difference in the resulting assessment of alternatives (Hobbs and Meier 2000). Therefore it is highly relevant to introduce a procedure for estimating the importance of criteria weights. This paper proposes a methodology for estimating the robustness...
DEFF Research Database (Denmark)
Jensen, Anders Vestergaard; Barfod, Michael Bruhn; Leleur, Steen
is based on the fact that when using MCA as a decision-support tool, questions often arise about the weighting (or prioritising) of the included criteria. This part of the MCA is seen as the most subjective part and could give reasons for discussion among the decision makers or stakeholders. Furthermore......This paper discusses the concept of using rank variation concerning the stake-holder prioritising of importance criteria for exploring the sensitivity of criteria weights in multi-criteria analysis (MCA). Thereby the robustness of the MCA-based decision support can be tested. The analysis described......, the relative weights can make a large difference in the resulting assessment of alternatives [1]. Therefore it is highly relevant to introduce a procedure for estimating the importance of criteria weights. This paper proposes a methodology for estimating the robustness of weights used in additive utility...
Robust independent modal space control of a coupled nano-positioning piezo-stage
Zhu, Wei; Yang, Fufeng; Rui, Xiaoting
2018-06-01
In order to accurately control a coupled 3-DOF nano-positioning piezo-stage, this paper designs a hybrid controller. In this controller, a hysteresis observer based on a Bouc-Wen model is established to compensate the hysteresis nonlinearity of the piezoelectric actuator first. Compared to hysteresis compensations using Preisach model and Prandt-Ishlinskii model, the compensation method using the hysteresis observer is computationally lighter. Then, based on the proposed dynamics model, by constructing the modal filter, a robust H∞ independent modal space controller is designed and utilized to decouple the piezo-stage and deal with the unmodeled dynamics, disturbance, and hysteresis compensation error. The effectiveness of the proposed controller is demonstrated experimentally. The experimental results show that the proposed controller can significantly achieve the high-precision positioning.
Robust and unobtrusive algorithm based on position independence for step detection
Qiu, KeCheng; Li, MengYang; Luo, YiHan
2018-04-01
Running is becoming one of the most popular exercises among the people, monitoring steps can help users better understand their running process and improve exercise efficiency. In this paper, we design and implement a robust and unobtrusive algorithm based on position independence for step detection under real environment. It applies Butterworth filter to suppress high frequency interference and then employs the projection based on mathematics to transform system to solve the problem of unknown position of smartphone. Finally, using sliding window to suppress the false peak. The algorithm was tested for eight participants on the Android 7.0 platform. In our experiments, the results show that the proposed algorithm can achieve desired effect in spite of device pose.
WTA estimates using the method of paired comparison: tests of robustness
Patricia A. Champ; John B. Loomis
1998-01-01
The method of paired comparison is modified to allow choices between two alternative gains so as to estimate willingness to accept (WTA) without loss aversion. The robustness of WTA values for two public goods is tested with respect to sensitivity of theWTA measure to the context of the bundle of goods used in the paired comparison exercise and to the scope (scale) of...
Rotated Walsh-Hadamard Spreading with Robust Channel Estimation for a Coded MC-CDMA System
Directory of Open Access Journals (Sweden)
Raulefs Ronald
2004-01-01
Full Text Available We investigate rotated Walsh-Hadamard spreading matrices for a broadband MC-CDMA system with robust channel estimation in the synchronous downlink. The similarities between rotated spreading and signal space diversity are outlined. In a multiuser MC-CDMA system, possible performance improvements are based on the chosen detector, the channel code, and its Hamming distance. By applying rotated spreading in comparison to a standard Walsh-Hadamard spreading code, a higher throughput can be achieved. As combining the channel code and the spreading code forms a concatenated code, the overall minimum Hamming distance of the concatenated code increases. This asymptotically results in an improvement of the bit error rate for high signal-to-noise ratio. Higher convolutional channel code rates are mostly generated by puncturing good low-rate channel codes. The overall Hamming distance decreases significantly for the punctured channel codes. Higher channel code rates are favorable for MC-CDMA, as MC-CDMA utilizes diversity more efficiently compared to pure OFDMA. The application of rotated spreading in an MC-CDMA system allows exploiting diversity even further. We demonstrate that the rotated spreading gain is still present for a robust pilot-aided channel estimator. In a well-designed system, rotated spreading extends the performance by using a maximum likelihood detector with robust channel estimation at the receiver by about 1 dB.
Tanner-Smith, Emily E.; Tipton, Elizabeth
2014-01-01
Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and SPSS (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding…
mBEEF-vdW: Robust fitting of error estimation density functionals
DEFF Research Database (Denmark)
Lundgård, Keld Troen; Wellendorff, Jess; Voss, Johannes
2016-01-01
. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012); J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014)]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function...... catalysis, including datasets that were not used for its training. Overall, we find that mBEEF-vdW has a higher general accuracy than competing popular functionals, and it is one of the best performing functionals on chemisorption systems, surface energies, lattice constants, and dispersion. We also show...
Robust subspace estimation using low-rank optimization theory and applications
Oreifej, Omar
2014-01-01
Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book,?the authors?discuss fundame
A robust methodology for kinetic model parameter estimation for biocatalytic reactions
DEFF Research Database (Denmark)
Al-Haque, Naweed; Andrade Santacoloma, Paloma de Gracia; Lima Afonso Neto, Watson
2012-01-01
lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches...... parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely...
Robust and efficient parameter estimation in dynamic models of biological systems.
Gábor, Attila; Banga, Julio R
2015-10-29
Dynamic modelling provides a systematic framework to understand function in biological systems. Parameter estimation in nonlinear dynamic models remains a very challenging inverse problem due to its nonconvexity and ill-conditioning. Associated issues like overfitting and local solutions are usually not properly addressed in the systems biology literature despite their importance. Here we present a method for robust and efficient parameter estimation which uses two main strategies to surmount the aforementioned difficulties: (i) efficient global optimization to deal with nonconvexity, and (ii) proper regularization methods to handle ill-conditioning. In the case of regularization, we present a detailed critical comparison of methods and guidelines for properly tuning them. Further, we show how regularized estimations ensure the best trade-offs between bias and variance, reducing overfitting, and allowing the incorporation of prior knowledge in a systematic way. We illustrate the performance of the presented method with seven case studies of different nature and increasing complexity, considering several scenarios of data availability, measurement noise and prior knowledge. We show how our method ensures improved estimations with faster and more stable convergence. We also show how the calibrated models are more generalizable. Finally, we give a set of simple guidelines to apply this strategy to a wide variety of calibration problems. Here we provide a parameter estimation strategy which combines efficient global optimization with a regularization scheme. This method is able to calibrate dynamic models in an efficient and robust way, effectively fighting overfitting and allowing the incorporation of prior information.
Pimperl, Alexander F; Rodriguez, Hector P; Schmittdiel, Julie A; Shortell, Stephen M
2018-06-01
To identify positive deviant (PD) physician organizations of Accountable Care Organizations (ACOs) with robust performance management systems (PMSYS). Third National Survey of Physician Organizations (NSPO3, n = 1,398). Organizational and external factors from NSPO3 were analyzed. Linear regression estimated the association of internal and contextual factors on PMSYS. Two cutpoints (75th/90th percentiles) identified PDs with the largest residuals and highest PMSYS scores. A total of 65 and 41 PDs were identified using 75th and 90th percentiles cutpoints, respectively. The 90th percentile more strongly differentiated PDs from non-PDs. Having a high proportion of vulnerable patients appears to constrain PMSYS development. Our PD identification method increases the likelihood that PD organizations selected for in-depth inquiry are high-performing organizations that exceed expectations. © Health Research and Educational Trust.
Evaluation of the robustness of estimating five components from a skin spectral image
Akaho, Rina; Hirose, Misa; Tsumura, Norimichi
2018-04-01
We evaluated the robustness of a method used to estimate five components (i.e., melanin, oxy-hemoglobin, deoxy-hemoglobin, shading, and surface reflectance) from the spectral reflectance of skin at five wavelengths against noise and a change in epidermis thickness. We also estimated the five components from recorded images of age spots and circles under the eyes using the method. We found that noise in the image must be no more 0.1% to accurately estimate the five components and that the thickness of the epidermis affects the estimation. We acquired the distribution of major causes for age spots and circles under the eyes by applying the method to recorded spectral images.
Ma, Yanyuan
2013-09-01
We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice. © 2013 American Statistical Association.
Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes
Kawewong, Aram; Tangruamsub, Sirinart; Hasegawa, Osamu
A novel Position-Invariant Robust Feature, designated as PIRF, is presented to address the problem of highly dynamic scene recognition. The PIRF is obtained by identifying existing local features (i.e. SIFT) that have a wide baseline visibility within a place (one place contains more than one sequential images). These wide-baseline visible features are then represented as a single PIRF, which is computed as an average of all descriptors associated with the PIRF. Particularly, PIRFs are robust against highly dynamical changes in scene: a single PIRF can be matched correctly against many features from many dynamical images. This paper also describes an approach to using these features for scene recognition. Recognition proceeds by matching an individual PIRF to a set of features from test images, with subsequent majority voting to identify a place with the highest matched PIRF. The PIRF system is trained and tested on 2000+ outdoor omnidirectional images and on COLD datasets. Despite its simplicity, PIRF offers a markedly better rate of recognition for dynamic outdoor scenes (ca. 90%) than the use of other features. Additionally, a robot navigation system based on PIRF (PIRF-Nav) can outperform other incremental topological mapping methods in terms of time (70% less) and memory. The number of PIRFs can be reduced further to reduce the time while retaining high accuracy, which makes it suitable for long-term recognition and localization.
Robust Non-Local TV-L1 Optical Flow Estimation with Occlusion Detection.
Zhang, Congxuan; Chen, Zhen; Wang, Mingrun; Li, Ming; Jiang, Shaofeng
2017-06-05
In this paper, we propose a robust non-local TV-L1 optical flow method with occlusion detection to address the problem of weak robustness of optical flow estimation with motion occlusion. Firstly, a TV-L1 form for flow estimation is defined using a combination of the brightness constancy and gradient constancy assumptions in the data term and by varying the weight under the Charbonnier function in the smoothing term. Secondly, to handle the potential risk of the outlier in the flow field, a general non-local term is added in the TV-L1 optical flow model to engender the typical non-local TV-L1 form. Thirdly, an occlusion detection method based on triangulation is presented to detect the occlusion regions of the sequence. The proposed non-local TV-L1 optical flow model is performed in a linearizing iterative scheme using improved median filtering and a coarse-to-fine computing strategy. The results of the complex experiment indicate that the proposed method can overcome the significant influence of non-rigid motion, motion occlusion, and large displacement motion. Results of experiments comparing the proposed method and existing state-of-the-art methods by respectively using Middlebury and MPI Sintel database test sequences show that the proposed method has higher accuracy and better robustness.
Directory of Open Access Journals (Sweden)
Suleiman M. Sharkh
2012-04-01
Full Text Available A robust extended Kalman filter (EKF is proposed as a method for estimation of the state of charge (SOC of lithium-ion batteries used in hybrid electric vehicles (HEVs. An equivalent circuit model of the battery, including its electromotive force (EMF hysteresis characteristics and polarization characteristics is used. The effect of the robust EKF gain coefficient on SOC estimation is analyzed, and an optimized gain coefficient is determined to restrain battery terminal voltage from fluctuating. Experimental and simulation results are presented. SOC estimates using the standard EKF are compared with the proposed robust EKF algorithm to demonstrate the accuracy and precision of the latter for SOC estimation.
BROJA-2PID: A Robust Estimator for Bivariate Partial Information Decomposition
Directory of Open Access Journals (Sweden)
Abdullah Makkeh
2018-04-01
Full Text Available Makkeh, Theis, and Vicente found that Cone Programming model is the most robust to compute the Bertschinger et al. partial information decomposition (BROJA PID measure. We developed a production-quality robust software that computes the BROJA PID measure based on the Cone Programming model. In this paper, we prove the important property of strong duality for the Cone Program and prove an equivalence between the Cone Program and the original Convex problem. Then, we describe in detail our software, explain how to use it, and perform some experiments comparing it to other estimators. Finally, we show that the software can be extended to compute some quantities of a trivaraite PID measure.
Robust best linear estimation for regression analysis using surrogate and instrumental variables.
Wang, C Y
2012-04-01
We investigate methods for regression analysis when covariates are measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies the classical measurement error model, but it may not have repeated measurements. In addition to the surrogate variables that are available among the subjects in the calibration sample, we assume that there is an instrumental variable (IV) that is available for all study subjects. An IV is correlated with the unobserved true exposure variable and hence can be useful in the estimation of the regression coefficients. We propose a robust best linear estimator that uses all the available data, which is the most efficient among a class of consistent estimators. The proposed estimator is shown to be consistent and asymptotically normal under very weak distributional assumptions. For Poisson or linear regression, the proposed estimator is consistent even if the measurement error from the surrogate or IV is heteroscedastic. Finite-sample performance of the proposed estimator is examined and compared with other estimators via intensive simulation studies. The proposed method and other methods are applied to a bladder cancer case-control study.
Liu, Huawei; Li, Baoqing; Yuan, Xiaobing; Zhou, Qianwei; Huang, Jingchang
2018-03-27
Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.
Modified generalized method of moments for a robust estimation of polytomous logistic model
Directory of Open Access Journals (Sweden)
Xiaoshan Wang
2014-07-01
Full Text Available The maximum likelihood estimation (MLE method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.
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.
Rock, N. M. S.
ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures
Robust Pose Estimation using the SwissRanger SR-3000 Camera
DEFF Research Database (Denmark)
Gudmundsson, Sigurjon Arni; Larsen, Rasmus; Ersbøll, Bjarne Kjær
2007-01-01
In this paper a robust method is presented to classify and estimate an objects pose from a real time range image and a low dimensional model. The model is made from a range image training set which is reduced dimensionally by a nonlinear manifold learning method named Local Linear Embedding (LLE)......). New range images are then projected to this model giving the low dimensional coordinates of the object pose in an efficient manner. The range images are acquired by a state of the art SwissRanger SR-3000 camera making the projection process work in real-time....
Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.
Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver
2018-02-15
Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R
Age Estimation Robust to Optical and Motion Blurring by Deep Residual CNN
Directory of Open Access Journals (Sweden)
Jeon Seong Kang
2018-04-01
Full Text Available Recently, real-time human age estimation based on facial images has been applied in various areas. Underneath this phenomenon lies an awareness that age estimation plays an important role in applying big data to target marketing for age groups, product demand surveys, consumer trend analysis, etc. However, in a real-world environment, various optical and motion blurring effects can occur. Such effects usually cause a problem in fully capturing facial features such as wrinkles, which are essential to age estimation, thereby degrading accuracy. Most of the previous studies on age estimation were conducted for input images almost free from blurring effect. To overcome this limitation, we propose the use of a deep ResNet-152 convolutional neural network for age estimation, which is robust to various optical and motion blurring effects of visible light camera sensors. We performed experiments with various optical and motion blurred images created from the park aging mind laboratory (PAL and craniofacial longitudinal morphological face database (MORPH databases, which are publicly available. According to the results, the proposed method exhibited better age estimation performance than the previous methods.
Predictive IP controller for robust position control of linear servo system.
Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi
2016-07-01
Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Tanner-Smith, Emily E; Tipton, Elizabeth
2014-03-01
Methodologists have recently proposed robust variance estimation as one way to handle dependent effect sizes in meta-analysis. Software macros for robust variance estimation in meta-analysis are currently available for Stata (StataCorp LP, College Station, TX, USA) and spss (IBM, Armonk, NY, USA), yet there is little guidance for authors regarding the practical application and implementation of those macros. This paper provides a brief tutorial on the implementation of the Stata and spss macros and discusses practical issues meta-analysts should consider when estimating meta-regression models with robust variance estimates. Two example databases are used in the tutorial to illustrate the use of meta-analysis with robust variance estimates. Copyright © 2013 John Wiley & Sons, Ltd.
Sehgal, Muhammad Shoaib B; Gondal, Iqbal; Dooley, Laurence S
2005-05-15
Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods. The new CMVE algorithm has been compared with existing estimation techniques including Bayesian principal component analysis imputation (BPCA), least square impute (LSImpute) and K-nearest neighbour (KNN). All these methods were rigorously tested to estimate missing values in three separate non-time series (ovarian cancer based) and one time series (yeast sporulation) dataset. Each method was quantitatively analyzed using the normalized root mean square (NRMS) error measure, covering a wide range of randomly introduced missing value probabilities from 0.01 to 0.2. Experiments were also undertaken on the yeast dataset, which comprised 1.7% actual missing values, to test the hypothesis that CMVE performed better not only for randomly occurring but also for a real distribution of missing values. The results confirmed that CMVE consistently demonstrated superior and robust estimation capability of missing values compared with other methods for both series types of data, for the same order of computational complexity. A concise theoretical framework has also been formulated to validate the improved performance of the CMVE
More recent robust methods for the estimation of mean and standard deviation of data
International Nuclear Information System (INIS)
Kanisch, G.
2003-01-01
Outliers in a data set result in biased values of mean and standard deviation. One way to improve the estimation of a mean is to apply tests to identify outliers and to exclude them from the calculations. Tests according to Grubbs or to Dixon, which are frequently used in practice, especially within laboratory intercomparisons, are not very efficient in identifying outliers. Since more than ten years now so-called robust methods are used more and more, which determine mean and standard deviation by iteration and down-weighting values far from the mean, thereby diminishing the impact of outliers. In 1989 the Analytical Methods Committee of the British Royal Chemical Society published such a robust method. Since 1993 the US Environmental Protection Agency published a more efficient and quite versatile method. Mean and standard deviation are calculated by iteration and application of a special weight function for down-weighting outlier candidates. In 2000, W. Cofino et al. published a very efficient robust method which works quite different from the others. It applies methods taken from the basics of quantum mechanics, such as ''wave functions'' associated with each laboratory mean value and matrix algebra (solving eigenvalue problems). In contrast to the other ones, this method includes the individual measurement uncertainties. (orig.)
Robust H(∞) positional control of 2-DOF robotic arm driven by electro-hydraulic servo system.
Guo, Qing; Yu, Tian; Jiang, Dan
2015-11-01
In this paper an H∞ positional feedback controller is developed to improve the robust performance under structural and parametric uncertainty disturbance in electro-hydraulic servo system (EHSS). The robust control model is described as the linear state-space equation by upper linear fractional transformation. According to the solution of H∞ sub-optimal control problem, the robust controller is designed and simplified to lower order linear model which is easily realized in EHSS. The simulation and experimental results can validate the robustness of this proposed method. The comparison result with PI control shows that the robust controller is suitable for this EHSS under the critical condition where the desired system bandwidth is higher and the external load of the hydraulic actuator is closed to its limited capability. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Clutch pressure estimation for a power-split hybrid transmission using nonlinear robust observer
Zhou, Bin; Zhang, Jianwu; Gao, Ji; Yu, Haisheng; Liu, Dong
2018-06-01
For a power-split hybrid transmission, using the brake clutch to realize the transition from electric drive mode to hybrid drive mode is an available strategy. Since the pressure information of the brake clutch is essential for the mode transition control, this research designs a nonlinear robust reduced-order observer to estimate the brake clutch pressure. Model uncertainties or disturbances are considered as additional inputs, thus the observer is designed in order that the error dynamics is input-to-state stable. The nonlinear characteristics of the system are expressed as the lookup tables in the observer. Moreover, the gain matrix of the observer is solved by two optimization procedures under the constraints of the linear matrix inequalities. The proposed observer is validated by offline simulation and online test, the results have shown that the observer achieves significant performance during the mode transition, as the estimation error is within a reasonable range, more importantly, it is asymptotically stable.
Human Age Estimation Method Robust to Camera Sensor and/or Face Movement
Directory of Open Access Journals (Sweden)
Dat Tien Nguyen
2015-08-01
Full Text Available Human age can be employed in many useful real-life applications, such as customer service systems, automatic vending machines, entertainment, etc. In order to obtain age information, image-based age estimation systems have been developed using information from the human face. However, limitations exist for current age estimation systems because of the various factors of camera motion and optical blurring, facial expressions, gender, etc. Motion blurring can usually be presented on face images by the movement of the camera sensor and/or the movement of the face during image acquisition. Therefore, the facial feature in captured images can be transformed according to the amount of motion, which causes performance degradation of age estimation systems. In this paper, the problem caused by motion blurring is addressed and its solution is proposed in order to make age estimation systems robust to the effects of motion blurring. Experiment results show that our method is more efficient for enhancing age estimation performance compared with systems that do not employ our method.
Directory of Open Access Journals (Sweden)
V. Jayaraj
2010-08-01
Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.
Directory of Open Access Journals (Sweden)
Rahmann Sven
2004-06-01
Full Text Available Abstract Background In phylogenetic analysis we face the problem that several subclade topologies are known or easily inferred and well supported by bootstrap analysis, but basal branching patterns cannot be unambiguously estimated by the usual methods (maximum parsimony (MP, neighbor-joining (NJ, or maximum likelihood (ML, nor are they well supported. We represent each subclade by a sequence profile and estimate evolutionary distances between profiles to obtain a matrix of distances between subclades. Results Our estimator of profile distances generalizes the maximum likelihood estimator of sequence distances. The basal branching pattern can be estimated by any distance-based method, such as neighbor-joining. Our method (profile neighbor-joining, PNJ then inherits the accuracy and robustness of profiles and the time efficiency of neighbor-joining. Conclusions Phylogenetic analysis of Chlorophyceae with traditional methods (MP, NJ, ML and MrBayes reveals seven well supported subclades, but the methods disagree on the basal branching pattern. The tree reconstructed by our method is better supported and can be confirmed by known morphological characters. Moreover the accuracy is significantly improved as shown by parametric bootstrap.
Estimation and robust control of microalgae culture for optimization of biological fixation of CO2
International Nuclear Information System (INIS)
Filali, R.
2012-01-01
This thesis deals with the optimization of carbon dioxide consumption by microalgae. Indeed, following several current environmental issues primarily related to large emissions of CO 2 , it is shown that microalgae represent a very promising solution for CO 2 mitigation. From this perspective, we are interested in the optimization strategy of CO 2 consumption through the development of a robust control law. The main aim is to ensure optimal operating conditions for a Chlorella vulgaris culture in an instrumented photo-bioreactor. The thesis is based on three major axes. The first one concerns growth modeling of the selected species based on a mathematical model reflecting the influence of light and total inorganic carbon concentration. For the control context, the second axis is related to biomass estimation from the real-time measurement of dissolved carbon dioxide. This step is necessary for the control part due to the lack of affordable real-time sensors for this kind of measurement. Three observers structures have been studied and compared: an extended Kalman filter, an asymptotic observer and an interval observer. The last axis deals with the implementation of a non-linear predictive control law coupled to the estimation strategy for the regulation of the cellular concentration around a value which maximizes the CO 2 consumption. Performance and robustness of this control law have been validated in simulation and experimentally on a laboratory-scale instrumented photo-bioreactor. This thesis represents a preliminary study for the optimization of CO 2 mitigation strategy by microalgae. (author)
A novel method for estimating the initial rotor position of PM motors without the position sensor
International Nuclear Information System (INIS)
Rostami, Alireza; Asaei, Behzad
2009-01-01
Permanent magnet (PM) motors have been used widely in the industrial applications. However, a need of the position sensor is a drawback of their control system. The sensorless methods using the back-EMF (electromotive force) cannot detect the rotor position at a standstill; recently, a few methods proposed to detect the initial rotor position, but they have high estimation error which reduces starting torque of the motor. Therefore, in this paper, a novel method to detect the initial rotor position of the PM motors is proposed, first, by using a space vector model, response of the stator current space vector to the saturation of the stator core is analyzed; then a novel method based on the saturation effect is presented that estimates the initial rotor position and the maximum estimation error is less than 3.8 deg. Simulation results confirm this method is effective and precise, and variation of the motor parameters does not affect its precision.
A novel method for estimating the initial rotor position of PM motors without the position sensor
Energy Technology Data Exchange (ETDEWEB)
Rostami, Alireza; Asaei, Behzad [School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran (Iran)
2009-08-15
Permanent magnet (PM) motors have been used widely in the industrial applications. However, a need of the position sensor is a drawback of their control system. The sensorless methods using the back-EMF (electromotive force) cannot detect the rotor position at a standstill; recently, a few methods proposed to detect the initial rotor position, but they have high estimation error which reduces starting torque of the motor. Therefore, in this paper, a novel method to detect the initial rotor position of the PM motors is proposed, first, by using a space vector model, response of the stator current space vector to the saturation of the stator core is analyzed; then a novel method based on the saturation effect is presented that estimates the initial rotor position and the maximum estimation error is less than 3.8. Simulation results confirm this method is effective and precise, and variation of the motor parameters does not affect its precision. (author)
National South African HIV prevalence estimates robust despite substantial test non-participation
Directory of Open Access Journals (Sweden)
Guy Harling
2017-07-01
Full Text Available Background. South African (SA national HIV seroprevalence estimates are of crucial policy relevance in the country, and for the worldwide HIV response. However, the most recent nationally representative HIV test survey in 2012 had 22% test non-participation, leaving the potential for substantial bias in current seroprevalence estimates, even after controlling for selection on observed factors. Objective. To re-estimate national HIV prevalence in SA, controlling for bias due to selection on both observed and unobserved factors in the 2012 SA National HIV Prevalence, Incidence and Behaviour Survey. Methods. We jointly estimated regression models for consent to test and HIV status in a Heckman-type bivariate probit framework. As selection variable, we used assigned interviewer identity, a variable known to predict consent but highly unlikely to be associated with interviewees’ HIV status. From these models, we estimated the HIV status of interviewed participants who did not test. Results. Of 26 710 interviewed participants who were invited to test for HIV, 21.3% of females and 24.3% of males declined. Interviewer identity was strongly correlated with consent to test for HIV; declining a test was weakly associated with HIV serostatus. Our HIV prevalence estimates were not significantly different from those using standard methods to control for bias due to selection on observed factors: 15.1% (95% confidence interval (CI 12.1 - 18.6 v. 14.5% (95% CI 12.8 - 16.3 for 15 - 49-year-old males; 23.3% (95% CI 21.7 - 25.8 v. 23.2% (95% CI 21.3 - 25.1 for 15 - 49-year-old females. Conclusion. The most recent SA HIV prevalence estimates are robust under the strongest available test for selection bias due to missing data. Our findings support the reliability of inferences drawn from such data.
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
MIDAS robust trend estimator for accurate GPS station velocities without step detection
Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien
2016-03-01
Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.
International Nuclear Information System (INIS)
Singh, Vimal
2007-01-01
The question of estimating the upper limit of -parallel B -parallel 2 , which is a key step in some recently reported global robust stability criteria for delayed neural networks, is revisited ( B denotes the delayed connection weight matrix). Recently, Cao, Huang, and Qu have given an estimate of the upper limit of -parallel B -parallel 2 . In the present paper, an alternative estimate of the upper limit of -parallel B -parallel 2 is highlighted. It is shown that the alternative estimate may yield some new global robust stability results
Parameters estimation for X-ray sources: positions
International Nuclear Information System (INIS)
Avni, Y.
1977-01-01
It is shown that the sizes of the positional error boxes for x-ray sources can be determined by using an estimation method which we have previously formulated generally and applied in spectral analyses. It is explained how this method can be used by scanning x-ray telescopes, by rotating modulation collimators, and by HEAO-A (author)
Eigenvalue estimates of positive integral operators with analytic ...
Indian Academy of Sciences (India)
Eigenvalue estimates of positive integral operators. 337 will be used to denote, respectively, the complex line integral of f along γ and the integral of f with respect to arc-length measure. In the first case we assume γ has an orientation. The notation Lp(γ ) will denote the Lp space of normalized arc length measure on γ with.
Position Estimation and Local Mapping Using Omnidirectional Images and Global Appearance Descriptors
Directory of Open Access Journals (Sweden)
Yerai Berenguer
2015-10-01
Full Text Available This work presents some methods to create local maps and to estimate the position of a mobile robot, using the global appearance of omnidirectional images. We use a robot that carries an omnidirectional vision system on it. Every omnidirectional image acquired by the robot is described only with one global appearance descriptor, based on the Radon transform. In the work presented in this paper, two different possibilities have been considered. In the first one, we assume the existence of a map previously built composed of omnidirectional images that have been captured from previously-known positions. The purpose in this case consists of estimating the nearest position of the map to the current position of the robot, making use of the visual information acquired by the robot from its current (unknown position. In the second one, we assume that we have a model of the environment composed of omnidirectional images, but with no information about the location of where the images were acquired. The purpose in this case consists of building a local map and estimating the position of the robot within this map. Both methods are tested with different databases (including virtual and real images taking into consideration the changes of the position of different objects in the environment, different lighting conditions and occlusions. The results show the effectiveness and the robustness of both methods.
Hua, Xue; Hibar, Derrek P; Ching, Christopher R K; Boyle, Christina P; Rajagopalan, Priya; Gutman, Boris A; Leow, Alex D; Toga, Arthur W; Jack, Clifford R; Harvey, Danielle; Weiner, Michael W; Thompson, Paul M
2013-02-01
Various neuroimaging measures are being evaluated for tracking Alzheimer's disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer's Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI. Copyright © 2012 Elsevier Inc. All rights reserved.
Approaches to relativistic positioning around Earth and error estimations
Puchades, Neus; Sáez, Diego
2016-01-01
In the context of relativistic positioning, the coordinates of a given user may be calculated by using suitable information broadcast by a 4-tuple of satellites. Our 4-tuples belong to the Galileo constellation. Recently, we estimated the positioning errors due to uncertainties in the satellite world lines (U-errors). A distribution of U-errors was obtained, at various times, in a set of points covering a large region surrounding Earth. Here, the positioning errors associated to the simplifying assumption that photons move in Minkowski space-time (S-errors) are estimated and compared with the U-errors. Both errors have been calculated for the same points and times to make comparisons possible. For a certain realistic modeling of the world line uncertainties, the estimated S-errors have proved to be smaller than the U-errors, which shows that the approach based on the assumption that the Earth's gravitational field produces negligible effects on photons may be used in a large region surrounding Earth. The applicability of this approach - which simplifies numerical calculations - to positioning problems, and the usefulness of our S-error maps, are pointed out. A better approach, based on the assumption that photons move in the Schwarzschild space-time governed by an idealized Earth, is also analyzed. More accurate descriptions of photon propagation involving non symmetric space-time structures are not necessary for ordinary positioning and spacecraft navigation around Earth.
Ebrahimian, Hossein; Jalayer, Fatemeh
2017-08-29
In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of seismicity forecasts play quite a crucial role in emergency decision-making and risk mitigation. Epidemic Type Aftershock Sequence (ETAS) models are frequently used for forecasting the spatio-temporal evolution of seismicity in the short-term. We propose robust forecasting of seismicity based on ETAS model, by exploiting the link between Bayesian inference and Markov Chain Monte Carlo Simulation. The methodology considers the uncertainty not only in the model parameters, conditioned on the available catalogue of events occurred before the forecasting interval, but also the uncertainty in the sequence of events that are going to happen during the forecasting interval. We demonstrate the methodology by retrospective early forecasting of seismicity associated with the 2016 Amatrice seismic sequence activities in central Italy. We provide robust spatio-temporal short-term seismicity forecasts with various time intervals in the first few days elapsed after each of the three main events within the sequence, which can predict the seismicity within plus/minus two standard deviations from the mean estimate within the few hours elapsed after the main event.
Robust Manhattan Frame Estimation From a Single RGB-D Image
Bernard Ghanem; Heilbron, Fabian Caba; Niebles, Juan Carlos; Thabet, Ali Kassem
2015-01-01
This paper proposes a new framework for estimating the Manhattan Frame (MF) of an indoor scene from a single RGB-D image. Our technique formulates this problem as the estimation of a rotation matrix that best aligns the normals of the captured scene to a canonical world axes. By introducing sparsity constraints, our method can simultaneously estimate the scene MF, the surfaces in the scene that are best aligned to one of three coordinate axes, and the outlier surfaces that do not align with any of the axes. To test our approach, we contribute a new set of annotations to determine ground truth MFs in each image of the popular NYUv2 dataset. We use this new benchmark to experimentally demonstrate that our method is more accurate, faster, more reliable and more robust than the methods used in the literature. We further motivate our technique by showing how it can be used to address the RGB-D SLAM problem in indoor scenes by incorporating it into and improving the performance of a popular RGB-D SLAM method.
Directory of Open Access Journals (Sweden)
Alsaidi M. Altaher
2012-01-01
Full Text Available Classical wavelet thresholding methods suffer from boundary problems caused by the application of the wavelet transformations to a finite signal. As a result, large bias at the edges and artificial wiggles occur when the classical boundary assumptions are not satisfied. Although polynomial wavelet regression and local polynomial wavelet regression effectively reduce the risk of this problem, the estimates from these two methods can be easily affected by the presence of correlated noise and outliers, giving inaccurate estimates. This paper introduces two robust methods in which the effects of boundary problems, outliers, and correlated noise are simultaneously taken into account. The proposed methods combine thresholding estimator with either a local polynomial model or a polynomial model using the generalized least squares method instead of the ordinary one. A primary step that involves removing the outlying observations through a statistical function is considered as well. The practical performance of the proposed methods has been evaluated through simulation experiments and real data examples. The results are strong evidence that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating the effects of outliers and correlated noise.
Robust Manhattan Frame Estimation From a Single RGB-D Image
Bernard Ghanem
2015-06-02
This paper proposes a new framework for estimating the Manhattan Frame (MF) of an indoor scene from a single RGB-D image. Our technique formulates this problem as the estimation of a rotation matrix that best aligns the normals of the captured scene to a canonical world axes. By introducing sparsity constraints, our method can simultaneously estimate the scene MF, the surfaces in the scene that are best aligned to one of three coordinate axes, and the outlier surfaces that do not align with any of the axes. To test our approach, we contribute a new set of annotations to determine ground truth MFs in each image of the popular NYUv2 dataset. We use this new benchmark to experimentally demonstrate that our method is more accurate, faster, more reliable and more robust than the methods used in the literature. We further motivate our technique by showing how it can be used to address the RGB-D SLAM problem in indoor scenes by incorporating it into and improving the performance of a popular RGB-D SLAM method.
A less field-intensive robust design for estimating demographic parameters with Mark-resight data
McClintock, B.T.; White, Gary C.
2009-01-01
The robust design has become popular among animal ecologists as a means for estimating population abundance and related demographic parameters with mark-recapture data. However, two drawbacks of traditional mark-recapture are financial cost and repeated disturbance to animals. Mark-resight methodology may in many circumstances be a less expensive and less invasive alternative to mark-recapture, but the models developed to date for these data have overwhelmingly concentrated only on the estimation of abundance. Here we introduce a mark-resight model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. The model may be implemented using standard statistical computing software, but it has also been incorporated into the freeware package Program MARK. We illustrate the use of our model with mainland New Zealand Robin (Petroica australis) data collected to ascertain whether this methodology may be a reliable alternative for monitoring endangered populations of a closely related species inhabiting the Chatham Islands. We found this method to be a viable alternative to traditional mark-recapture when cost or disturbance to species is of particular concern in long-term population monitoring programs. ?? 2009 by the Ecological Society of America.
Robust time estimation reconciles views of the antiquity of placental mammals.
Directory of Open Access Journals (Sweden)
Yasuhiro Kitazoe
2007-04-01
Full Text Available Molecular studies have reported divergence times of modern placental orders long before the Cretaceous-Tertiary boundary and far older than paleontological data. However, this discrepancy may not be real, but rather appear because of the violation of implicit assumptions in the estimation procedures, such as non-gradual change of evolutionary rate and failure to correct for convergent evolution.New procedures for divergence-time estimation robust to abrupt changes in the rate of molecular evolution are described. We used a variant of the multidimensional vector space (MVS procedure to take account of possible convergent evolution. Numerical simulations of abrupt rate change and convergent evolution showed good performance of the new procedures in contrast to current methods. Application to complete mitochondrial genomes identified marked rate accelerations and decelerations, which are not obtained with current methods. The root of placental mammals is estimated to be approximately 18 million years more recent than when assuming a log Brownian motion model. Correcting the pairwise distances for convergent evolution using MVS lowers the age of the root about another 20 million years compared to using standard maximum likelihood tree branch lengths. These two procedures combined revise the root time of placental mammals from around 122 million years ago to close to 84 million years ago. As a result, the estimated distribution of molecular divergence times is broadly consistent with quantitative analysis of the North American fossil record and traditional morphological views.By including the dual effects of abrupt rate change and directly accounting for convergent evolution at the molecular level, these estimates provide congruence between the molecular results, paleontological analyses and morphological expectations. The programs developed here are provided along with sample data that reproduce the results of this study and are especially
GNSS Positioning Performance Analysis Using PSO-RBF Estimation Model
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Jgouta Meriem
2017-06-01
Full Text Available Positioning solutions need to be more precise and available. The most frequent method used nowadays includes a GPS receiver, sometimes supported by other sensors. Generally, GPS and GNSS suffer from spreading perturbations that produce biases on pseudo-range measurements. With a view to optimize the use of the satellites received, we offer a positioning algorithm with pseudo range error modelling with the contribution of an appropriate filtering process. Extended Kalman Filter, The Rao- Blackwellized filter are among the most widely used algorithms to predict errors and to filter the high frequency noise. This paper describes a new method of estimating the pseudo-range errors based on the PSO-RBF model which achieves an optimal training criterion. This model is appropriate of its method to predict the GPS corrections for accurate positioning, it reduce the positioning errors at high velocities by more than 50% compared to the RLS or EKF methods.
International Nuclear Information System (INIS)
Sánchez-Oro, J.; Duarte, A.; Salcedo-Sanz, S.
2016-01-01
Highlights: • The total energy demand in Spain is estimated with a Variable Neighborhood algorithm. • Socio-economic variables are used, and one year ahead prediction horizon is considered. • Improvement of the prediction with an Extreme Learning Machine network is considered. • Experiments are carried out in real data for the case of Spain. - Abstract: Energy demand prediction is an important problem whose solution is evaluated by policy makers in order to take key decisions affecting the economy of a country. A number of previous approaches to improve the quality of this estimation have been proposed in the last decade, the majority of them applying different machine learning techniques. In this paper, the performance of a robust hybrid approach, composed of a Variable Neighborhood Search algorithm and a new class of neural network called Extreme Learning Machine, is discussed. The Variable Neighborhood Search algorithm is focused on obtaining the most relevant features among the set of initial ones, by including an exponential prediction model. While previous approaches consider that the number of macroeconomic variables used for prediction is a parameter of the algorithm (i.e., it is fixed a priori), the proposed Variable Neighborhood Search method optimizes both: the number of variables and the best ones. After this first step of feature selection, an Extreme Learning Machine network is applied to obtain the final energy demand prediction. Experiments in a real case of energy demand estimation in Spain show the excellent performance of the proposed approach. In particular, the whole method obtains an estimation of the energy demand with an error lower than 2%, even when considering the crisis years, which are a real challenge.
Fast and robust estimation of spectro-temporal receptive fields using stochastic approximations.
Meyer, Arne F; Diepenbrock, Jan-Philipp; Ohl, Frank W; Anemüller, Jörn
2015-05-15
The receptive field (RF) represents the signal preferences of sensory neurons and is the primary analysis method for understanding sensory coding. While it is essential to estimate a neuron's RF, finding numerical solutions to increasingly complex RF models can become computationally intensive, in particular for high-dimensional stimuli or when many neurons are involved. Here we propose an optimization scheme based on stochastic approximations that facilitate this task. The basic idea is to derive solutions on a random subset rather than computing the full solution on the available data set. To test this, we applied different optimization schemes based on stochastic gradient descent (SGD) to both the generalized linear model (GLM) and a recently developed classification-based RF estimation approach. Using simulated and recorded responses, we demonstrate that RF parameter optimization based on state-of-the-art SGD algorithms produces robust estimates of the spectro-temporal receptive field (STRF). Results on recordings from the auditory midbrain demonstrate that stochastic approximations preserve both predictive power and tuning properties of STRFs. A correlation of 0.93 with the STRF derived from the full solution may be obtained in less than 10% of the full solution's estimation time. We also present an on-line algorithm that allows simultaneous monitoring of STRF properties of more than 30 neurons on a single computer. The proposed approach may not only prove helpful for large-scale recordings but also provides a more comprehensive characterization of neural tuning in experiments than standard tuning curves. Copyright © 2015 Elsevier B.V. All rights reserved.
Estimating Common Pedestrian Routes through Indoor Path Networks using Position Traces
DEFF Research Database (Denmark)
Prentow, Thor Siiger; Blunck, Henrik; Grønbæk, Kaj
2014-01-01
routes between locations. These methods are sufficiently efficient to provide common routes based on real-time data from thousands of devices simultaneously. Furthermore, we show that the methods operate robustly even on basis of noisy and coarse-grained position estimates as provided by large......Abstract—Accurate information about how people commonly travel in a given large-scale building environment and which routes they take for given start and destination points is essential for applications such as indoor navigation, route prediction, and mobile work planning and logistics...
Energy Technology Data Exchange (ETDEWEB)
Bifulco, P; Cesarelli, M; Roccasalva Firenze, M; Verso, E; Sansone, M; Bracale, M [University of Naples, Federico II, Electronic Engineering Department, Bioengineering Unit, Via Claudio, 21 - 80125 Naples (Italy)
1999-12-31
The aim of this study is to develop a method to estimate the 3D positioning of an anatomic structure using the knowledge of its volume (provided by CT or MRI) combined with a single radiographic projection. This method could be applied in stereotactic surgery or in the study of 3D body joints kinematics. The knowledge of the 3D anatomical structure, available from CT (or in future MRI) is used to estimate the orientation of the projection that better match the actual 2D available projection. For this purpose it was necessary to develop an algorithm to simulate the radiographic projections. The radiographic image formation process has been simulated utilizing the geometrical characteristics of a real radiographic device and the volumetric anatomical data of the patient, obtained by 3D diagnostic CT images. The position of the patient volume respect to the radiological device is estimated comparing the actual radiographic projection with those simulated, maximising a similarity index. To assess the estimation, the 3D positioning of a segmented vertebra has been used as a test volume. The assessment has been carried out only by means of simulation. Estimation errors have been statistically evaluated. Conditions of mispositioning and noise have been also considered. The results relative to the simulation show the feasibility of the method. From the analysis of the errors emerges that the searching procedure results robust respect to the addition of white Gaussian noise. (authors) 13 fers., 4 figs., 1 tabs.
International Nuclear Information System (INIS)
Bifulco, P.; Cesarelli, M.; Roccasalva Firenze, M.; Verso, E.; Sansone, M.; Bracale, M.
1998-01-01
The aim of this study is to develop a method to estimate the 3D positioning of an anatomic structure using the knowledge of its volume (provided by CT or MRI) combined with a single radiographic projection. This method could be applied in stereotactic surgery or in the study of 3D body joints kinematics. The knowledge of the 3D anatomical structure, available from CT (or in future MRI) is used to estimate the orientation of the projection that better match the actual 2D available projection. For this purpose it was necessary to develop an algorithm to simulate the radiographic projections. The radiographic image formation process has been simulated utilizing the geometrical characteristics of a real radiographic device and the volumetric anatomical data of the patient, obtained by 3D diagnostic CT images. The position of the patient volume respect to the radiological device is estimated comparing the actual radiographic projection with those simulated, maximising a similarity index. To assess the estimation, the 3D positioning of a segmented vertebra has been used as a test volume. The assessment has been carried out only by means of simulation. Estimation errors have been statistically evaluated. Conditions of mispositioning and noise have been also considered. The results relative to the simulation show the feasibility of the method. From the analysis of the errors emerges that the searching procedure results robust respect to the addition of white Gaussian noise. (authors)
Adaptive algorithm for mobile user positioning based on environment estimation
Directory of Open Access Journals (Sweden)
Grujović Darko
2014-01-01
Full Text Available This paper analyzes the challenges to realize an infrastructure independent and a low-cost positioning method in cellular networks based on RSS (Received Signal Strength parameter, auxiliary timing parameter and environment estimation. The proposed algorithm has been evaluated using field measurements collected from GSM (Global System for Mobile Communications network, but it is technology independent and can be applied in UMTS (Universal Mobile Telecommunication Systems and LTE (Long-Term Evolution networks, also.
Directory of Open Access Journals (Sweden)
Dongming Li
2017-04-01
Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
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Xubin Ping
2016-01-01
Full Text Available For quasi-linear parameter varying (quasi-LPV systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR example is given to illustrate the effectiveness of the approach.
Smith, James F.
2017-11-01
With the goal of designing interferometers and interferometer sensors, e.g., LADARs with enhanced sensitivity, resolution, and phase estimation, states using quantum entanglement are discussed. These states include N00N states, plain M and M states (PMMSs), and linear combinations of M and M states (LCMMS). Closed form expressions for the optimal detection operators; visibility, a measure of the state's robustness to loss and noise; a resolution measure; and phase estimate error, are provided in closed form. The optimal resolution for the maximum visibility and minimum phase error are found. For the visibility, comparisons between PMMSs, LCMMS, and N00N states are provided. For the minimum phase error, comparisons between LCMMS, PMMSs, N00N states, separate photon states (SPSs), the shot noise limit (SNL), and the Heisenberg limit (HL) are provided. A representative collection of computational results illustrating the superiority of LCMMS when compared to PMMSs and N00N states is given. It is found that for a resolution 12 times the classical result LCMMS has visibility 11 times that of N00N states and 4 times that of PMMSs. For the same case, the minimum phase error for LCMMS is 10.7 times smaller than that of PMMS and 29.7 times smaller than that of N00N states.
A Robust Approach for Clock Offset Estimation in Wireless Sensor Networks
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Kim Jang-Sub
2010-01-01
Full Text Available The maximum likelihood estimators (MLEs for the clock phase offset assuming a two-way message exchange mechanism between the nodes of a wireless sensor network were recently derived assuming Gaussian and exponential network delays. However, the MLE performs poorly in the presence of non-Gaussian or nonexponential network delay distributions. Currently, there is a need to develop clock synchronization algorithms that are robust to the distribution of network delays. This paper proposes a clock offset estimator based on the composite particle filter (CPF to cope with the possible asymmetries and non-Gaussianity of the network delay distributions. Also, a variant of the CPF approach based on the bootstrap sampling (BS is shown to exhibit good performance in the presence of reduced number of observations. Computer simulations illustrate that the basic CPF and its BS-based variant present superior performance than MLE under general random network delay distributions such as asymmetric Gaussian, exponential, Gamma, Weibull as well as various mixtures.
Lin, Y; Rajan, V; Moret, B M E
2011-09-01
The rapid accumulation of whole-genome data has renewed interest in the study of genomic rearrangements. Comparative genomics, evolutionary biology, and cancer research all require models and algorithms to elucidate the mechanisms, history, and consequences of these rearrangements. However, even simple models lead to NP-hard problems, particularly in the area of phylogenetic analysis. Current approaches are limited to small collections of genomes and low-resolution data (typically a few hundred syntenic blocks). Moreover, whereas phylogenetic analyses from sequence data are deemed incomplete unless bootstrapping scores (a measure of confidence) are given for each tree edge, no equivalent to bootstrapping exists for rearrangement-based phylogenetic analysis. We describe a fast and accurate algorithm for rearrangement analysis that scales up, in both time and accuracy, to modern high-resolution genomic data. We also describe a novel approach to estimate the robustness of results-an equivalent to the bootstrapping analysis used in sequence-based phylogenetic reconstruction. We present the results of extensive testing on both simulated and real data showing that our algorithm returns very accurate results, while scaling linearly with the size of the genomes and cubically with their number. We also present extensive experimental results showing that our approach to robustness testing provides excellent estimates of confidence, which, moreover, can be tuned to trade off thresholds between false positives and false negatives. Together, these two novel approaches enable us to attack heretofore intractable problems, such as phylogenetic inference for high-resolution vertebrate genomes, as we demonstrate on a set of six vertebrate genomes with 8,380 syntenic blocks. A copy of the software is available on demand.
Directory of Open Access Journals (Sweden)
Xue Li
2015-01-01
Full Text Available State of charge (SOC is one of the most important parameters in battery management system (BMS. There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, and H∞ observer are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1 how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2 pros and cons of typical SOC estimators in their robustness and reliability; (3 guidelines for requirements on battery system identification and sensor selections.
Estimation of Initial Position Using Line Segment Matching in Maps
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Chongyang Wei
2016-06-01
Full Text Available While navigating in a typical traffic scene, with a drastic drift or sudden jump in its Global Positioning System (GPS position, the localization based on such an initial position is unable to extract precise overlapping data from the prior map in order to match the current data, thus rendering the localization as unfeasible. In this paper, we first propose a new method to estimate an initial position by matching the infrared reflectivity maps. The maps consist of a highly precise prior map, built with the offline simultaneous localization and mapping (SLAM technique, and a smooth current map, built with the integral over velocities. Considering the attributes of the maps, we first propose to exploit the stable, rich line segments to match the lidar maps. To evaluate the consistency of the candidate line pairs in both maps, we propose to adopt the local appearance, pairwise geometric attribute and structural likelihood to construct an affinity graph, as well as employ a spectral algorithm to solve the graph efficiently. The initial position is obtained according to the relationship between the vehicle's current position and matched lines. Experiments on the campus with a GPS error of dozens of metres show that our algorithm can provide an accurate initial value with average longitudinal and lateral errors being 1.68m and 1.04m, respectively.
Guerrero, César; Pedrosa, Elisabete T.; Pérez-Bejarano, Andrea; Keizer, Jan Jacob
2014-05-01
The temperature reached on soils is an important parameter needed to describe the wildfire effects. However, the methods for measure the temperature reached on burned soils have been poorly developed. Recently, the use of the near-infrared (NIR) spectroscopy has been pointed as a valuable tool for this purpose. The NIR spectrum of a soil sample contains information of the organic matter (quantity and quality), clay (quantity and quality), minerals (such as carbonates and iron oxides) and water contents. Some of these components are modified by the heat, and each temperature causes a group of changes, leaving a typical fingerprint on the NIR spectrum. This technique needs the use of a model (or calibration) where the changes in the NIR spectra are related with the temperature reached. For the development of the model, several aliquots are heated at known temperatures, and used as standards in the calibration set. This model offers the possibility to make estimations of the temperature reached on a burned sample from its NIR spectrum. However, the estimation of the temperature reached using NIR spectroscopy is due to changes in several components, and cannot be attributed to changes in a unique soil component. Thus, we can estimate the temperature reached by the interaction between temperature and the thermo-sensible soil components. In addition, we cannot expect the uniform distribution of these components, even at small scale. Consequently, the proportion of these soil components can vary spatially across the site. This variation will be present in the samples used to construct the model and also in the samples affected by the wildfire. Therefore, the strategies followed to develop robust models should be focused to manage this expected variation. In this work we compared the prediction accuracy of models constructed with different approaches. These approaches were designed to provide insights about how to distribute the efforts needed for the development of robust
A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments
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Zakir Ullah
2018-05-01
X- and Y-axis from the PF estimated position of the WMR, the lateral slip along X- and Y-axis is then used to take some corrective measures. Lateral slip information is also used to find the direction along which WMR has to move to get back along the desired trajectory. Simulation results show that our proposed LHE and RL heading estimation methods significantly improve the PF localization and tracking performance on a slippery surface in both indoor and outdoor environments. The simulation results also show that the accurate locations of WMR and desired path information are used to estimate and compensate the lateral slip.
DEFF Research Database (Denmark)
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.
2012-01-01
This paper presents a robust tracking control concept based on accurate feedforward compensation for hydraulic valve-cylinder drives. The proposed feedforward compensator is obtained utilizing a generalized description of the valve flow that takes into account any asymmetry of valves and...... constant gain type feedforward compensator, when subjected to strong perturbations in supply pressure and coulomb friction....
Silly, F.
2009-01-01
P>Processing of scanning probe microscopy (SPM) images is essential to explore nanoscale phenomena. Image processing and pattern recognition techniques are developed to improve the accuracy and consistency of nanoobject and surface characterization. We present a robust and versatile method to
Robust quasi NID current and flux control of an induction motor for position control
van Duijnhoven, M.; Blachuta, M.J.
1999-01-01
In the paper, a new control design method called Dynamic Contraction method is applied to the flux and quadrature current robust control of an induction motor operated using the field orientation principle. The resulting input-output decoupled and linearized drive is then used for time-optimal
On-field mounting position estimation of a lidar sensor
Khan, Owes; Bergelt, René; Hardt, Wolfram
2017-10-01
In order to retrieve a highly accurate view of their environment, autonomous cars are often equipped with LiDAR sensors. These sensors deliver a three dimensional point cloud in their own co-ordinate frame, where the origin is the sensor itself. However, the common co-ordinate system required by HAD (Highly Autonomous Driving) software systems has its origin at the center of the vehicle's rear axle. Thus, a transformation of the acquired point clouds to car co-ordinates is necessary, and thereby the determination of the exact mounting position of the LiDAR system in car coordinates is required. Unfortunately, directly measuring this position is a time-consuming and error-prone task. Therefore, different approaches have been suggested for its estimation which mostly require an exhaustive test-setup and are again time-consuming to prepare. When preparing a high number of LiDAR mounted test vehicles for data acquisition, most approaches fall short due to time or money constraints. In this paper we propose an approach for mounting position estimation which features an easy execution and setup, thus making it feasible for on-field calibration.
A Robust Mass Estimator for Dark Matter Subhalo Perturbations in Strong Gravitational Lenses
Energy Technology Data Exchange (ETDEWEB)
Minor, Quinn E. [Department of Science, Borough of Manhattan Community College, City University of New York, New York, NY 10007 (United States); Kaplinghat, Manoj [Department of Physics and Astronomy, University of California, Irvine CA 92697 (United States); Li, Nan [Department of Astronomy and Astrophysics, The University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States)
2017-08-20
A few dark matter substructures have recently been detected in strong gravitational lenses through their perturbations of highly magnified images. We derive a characteristic scale for lensing perturbations and show that they are significantly larger than the perturber’s Einstein radius. We show that the perturber’s projected mass enclosed within this radius, scaled by the log-slope of the host galaxy’s density profile, can be robustly inferred even if the inferred density profile and tidal radius of the perturber are biased. We demonstrate the validity of our analytic derivation using several gravitational lens simulations where the tidal radii and the inner log-slopes of the density profile of the perturbing subhalo are allowed to vary. By modeling these simulated data, we find that our mass estimator, which we call the effective subhalo lensing mass, is accurate to within about 10% or smaller in each case, whereas the inferred total subhalo mass can potentially be biased by nearly an order of magnitude. We therefore recommend that the effective subhalo lensing mass be reported in future lensing reconstructions, as this will allow for a more accurate comparison with the results of dark matter simulations.
Estimation of satellite position, clock and phase bias corrections
Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs
2018-05-01
Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.
Directory of Open Access Journals (Sweden)
Tao Jin
2015-04-01
Full Text Available With the development of modern society, the scale of the power system is rapidly increased accordingly, and the framework and mode of running of power systems are trending towards more complexity. It is nowadays much more important for the dispatchers to know exactly the state parameters of the power network through state estimation. This paper proposes a robust power system WLS state estimation method integrating a wide-area measurement system (WAMS and SCADA technology, incorporating phasor measurements and the results of the traditional state estimator in a post-processing estimator, which greatly reduces the scale of the non-linear estimation problem as well as the number of iterations and the processing time per iteration. This paper firstly analyzes the wide-area state estimation model in detail, then according to the issue that least squares does not account for bad data and outliers, the paper proposes a robust weighted least squares (WLS method that combines a robust estimation principle with least squares by equivalent weight. The performance assessment is discussed through setting up mathematical models of the distribution network. The effectiveness of the proposed method was proved to be accurate and reliable by simulations and experiments.
International Nuclear Information System (INIS)
Akahane, Yutaka; Ogawa, Kanade; Tsuji, Koichi; Aoyama, Makoto; Yamakawa, Koichi
2011-01-01
We have proposed and demonstrated a simple and robust femtosecond optical-parametric chirped-pulse amplification scheme in which an even order dispersion of an idler pulse is compensated by passing through an identical positive dispersive material used for temporal stretching a signal pulse. By compressing the idler pulses having a negatively chirp in this manner, high power sub-100 fs pulses were successfully obtained with only a transparent glass block used for the stretcher and compressor. (author)
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10.25046/aj0203154
2017-07-01
Full Text Available Mobile robots can be used to perform transportation tasks for different objects. These tasks have to be implemented carefully. Therefore, an accurate approach for object recognition and position estimation is required. This work presents a concept for identification and position estimation of multiple labware. These labware, which contain chemical and biological components, have to be manipulated and transported in life science laboratories using H20 mobile robots. The H20 robot has dual 6-DOF arms with 2-DOF grippers. Different marks are used to be attached with the labware lid for identification process. The Kinect sensor V2 is used to recognize and localize the mark of the required labware on a wide workstation. The difference of performance between the Kinect V1 and V2 is illustrated. SURF algorithm (Speeded-Up Robust Features is used to recognize the target according to its local features. Some preprocessing steps are applied to the RGB frame to enhance the image features. The effects of strong lighting condition are eliminated by using polarization and intensity filters which are attached to the Kinect camera. The position estimation step is performed by applying a mapping process form the color frame to the depth frame of Kinect. The communication procedure between the Kinect platform and other robot platforms is done using client-server model. An efficient performance with high success rate is obtained under different lighting conditions.
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Nitish Katal
2016-01-01
Full Text Available Automation of the robust control system synthesis for uncertain systems is of great practical interest. In this paper, the loop shaping step for synthesizing quantitative feedback theory (QFT based controller for a two-phase permanent magnet stepper motor (PMSM has been automated using teaching learning-based optimization (TLBO algorithm. The QFT controller design problem has been posed as an optimization problem and TLBO algorithm has been used to minimize the proposed cost function. This facilitates designing low-order fixed-structure controller, eliminates the need of manual loop shaping step on the Nichols charts, and prevents the overdesign of the controller. A performance comparison of the designed controller has been made with the classical PID tuning method of Ziegler-Nichols and QFT controller tuned using other optimization algorithms. The simulation results show that the designed QFT controller using TLBO offers robust stability, disturbance rejection, and proper reference tracking over a range of PMSM’s parametric uncertainties as compared to the classical design techniques.
Fottrell, Edward; Byass, Peter; Berhane, Yemane
2008-03-25
randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.
Directory of Open Access Journals (Sweden)
Berhane Yemane
2008-03-01
estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.
Robust domain decomposition preconditioners for abstract symmetric positive definite bilinear forms
Efendiev, Yalchin; Galvis, Juan; Lazarov, Raytcho; Willems, Joerg
2012-01-01
An abstract framework for constructing stable decompositions of the spaces corresponding to general symmetric positive definite problems into "local" subspaces and a global "coarse" space is developed. Particular applications of this abstract
Chu, Hui-May; Ette, Ene I
2005-09-02
his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.
Directory of Open Access Journals (Sweden)
Xubin Ping
2015-01-01
Full Text Available For the quasi-linear parameter varying (quasi-LPV system with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC is investigated. The estimation error set is represented by a zonotope and refreshed by the zonotopic set-membership estimation method. By properly refreshing the estimation error set online, the bounds of true state at the next sampling time can be obtained. Furthermore, the feasibility of the main optimization problem at the next sampling time can be determined at the current time. A numerical example is given to illustrate the effectiveness of the approach.
Robust Operation of Tendon-Driven Robot Fingers Using Force and Position-Based Control Laws
Abdallah, Muhammad E (Inventor); Platt, Jr., Robert J. (Inventor); Reiland, Matthew J (Inventor); Hargrave, Brian (Inventor); Diftler, Myron A (Inventor); Strawser, Philip A (Inventor); Ihrke, Chris A. (Inventor)
2013-01-01
A robotic system includes a tendon-driven finger and a control system. The system controls the finger via a force-based control law when a tension sensor is available, and via a position-based control law when a sensor is not available. Multiple tendons may each have a corresponding sensor. The system selectively injects a compliance value into the position-based control law when only some sensors are available. A control system includes a host machine and a non-transitory computer-readable medium having a control process, which is executed by the host machine to control the finger via the force- or position-based control law. A method for controlling the finger includes determining the availability of a tension sensor(s), and selectively controlling the finger, using the control system, via the force or position-based control law. The position control law allows the control system to resist disturbances while nominally maintaining the initial state of internal tendon tensions.
Directory of Open Access Journals (Sweden)
Yang Bai
2016-05-01
Full Text Available A simple differential capacitive sensor is provided in this paper to measure the absolute positions of length measuring systems. By utilizing a shield window inside the differential capacitor, the measurement range and linearity range of the sensor can reach several millimeters. What is more interesting is that this differential capacitive sensor is only sensitive to one translational degree of freedom (DOF movement, and immune to the vibration along the other two translational DOFs. In the experiment, we used a novel circuit based on an AC capacitance bridge to directly measure the differential capacitance value. The experimental result shows that this differential capacitive sensor has a sensitivity of 2 × 10−4 pF/μm with 0.08 μm resolution. The measurement range of this differential capacitive sensor is 6 mm, and the linearity error are less than 0.01% over the whole absolute position measurement range.
Robust balancing and position control of a single spherical wheeled mobile platform
Yavuz, Fırat; Yavuz, Firat; Ünel, Mustafa; Unel, Mustafa
2016-01-01
Self-balancing mobile platforms with single spherical wheel, generally called ballbots, are suitable example of underactuated systems. Balancing control of a ballbot platform, which aims to maintain the upright orientation by rejecting external disturbances, is important during station keeping or trajectory tracking. In this paper, acceleration based balancing and position control of a single spherical wheeled mobile platform that has three single-row omniwheel drive m...
Yang, Yanfu; Xiang, Qian; Zhang, Qun; Zhou, Zhongqing; Jiang, Wen; He, Qianwen; Yao, Yong
2017-09-01
We propose a joint estimation scheme for fast, accurate, and robust frequency offset (FO) estimation along with phase estimation based on modified adaptive Kalman filter (MAKF). The scheme consists of three key modules: extend Kalman filter (EKF), lock detector, and FO cycle slip recovery. The EKF module estimates time-varying phase induced by both FO and laser phase noise. The lock detector module makes decision between acquisition mode and tracking mode and consequently sets the EKF tuning parameter in an adaptive manner. The third module can detect possible cycle slip in the case of large FO and make proper correction. Based on the simulation and experimental results, the proposed MAKF has shown excellent estimation performance featuring high accuracy, fast convergence, as well as the capability of cycle slip recovery.
Variance-Constrained Robust Estimation for Discrete-Time Systems with Communication Constraints
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Baofeng Wang
2014-01-01
Full Text Available This paper is concerned with a new filtering problem in networked control systems (NCSs subject to limited communication capacity, which includes measurement quantization, random transmission delay, and packets loss. The measurements are first quantized via a logarithmic quantizer and then transmitted through a digital communication network with random delay and packet loss. The three communication constraints phenomena which can be seen as a class of uncertainties are formulated by a stochastic parameter uncertainty system. The purpose of the paper is to design a linear filter such that, for all the communication constraints, the error state of the filtering process is mean square bounded and the steady-state variance of the estimation error for each state is not more than the individual prescribed upper bound. It is shown that the desired filtering can effectively be solved if there are positive definite solutions to a couple of algebraic Riccati-like inequalities or linear matrix inequalities. Finally, an illustrative numerical example is presented to demonstrate the effectiveness and flexibility of the proposed design approach.
International Nuclear Information System (INIS)
Demirhan, Haydar; Kayhan Atilgan, Yasemin
2015-01-01
Highlights: • Precise horizontal global solar radiation estimation models are proposed for Turkey. • Genetic programming technique is used to construct the models. • Robust coplot analysis is applied to reduce the impact of outlier observations. • Better estimation and prediction properties are observed for the models. - Abstract: Renewable energy sources have been attracting more and more attention of researchers due to the diminishing and harmful nature of fossil energy sources. Because of the importance of solar energy as a renewable energy source, an accurate determination of significant covariates and their relationships with the amount of global solar radiation reaching the Earth is a critical research problem. There are numerous meteorological and terrestrial covariates that can be used in the analysis of horizontal global solar radiation. Some of these covariates are highly correlated with each other. It is possible to find a large variety of linear or non-linear models to explain the amount of horizontal global solar radiation. However, models that explain the amount of global solar radiation with the smallest set of covariates should be obtained. In this study, use of the robust coplot technique to reduce the number of covariates before going forward with advanced modelling techniques is considered. After reducing the dimensionality of model space, yearly and monthly mean daily horizontal global solar radiation estimation models for Turkey are built by using the genetic programming technique. It is observed that application of robust coplot analysis is helpful for building precise models that explain the amount of global solar radiation with the minimum number of covariates without suffering from outlier observations and the multicollinearity problem. Consequently, over a dataset of Turkey, precise yearly and monthly mean daily global solar radiation estimation models are introduced using the model spaces obtained by robust coplot technique and
Directory of Open Access Journals (Sweden)
Z. Khodadadi
2008-03-01
Full Text Available Let S be matrix of residual sum of square in linear model Y = Aβ + e where matrix e is distributed as elliptically contoured with unknown scale matrix Σ. In present work, we consider the problem of estimating Σ with respect to squared loss function, L(Σˆ , Σ = tr(ΣΣˆ −1 −I 2 . It is shown that improvement of the estimators were obtained by James, Stein [7], Dey and Srivasan [1] under the normality assumption remains robust under an elliptically contoured distribution respect to squared loss function
Belfield, Clive; Bailey, Thomas
2017-01-01
Recently, studies have adopted fixed effects modeling to identify the returns to college. This method has the advantage over ordinary least squares estimates in that unobservable, individual-level characteristics that may bias the estimated returns are differenced out. But the method requires extensive longitudinal data and involves complex…
Comparison of Classical and Robust Estimates of Threshold Auto-regression Parameters
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V. B. Goryainov
2017-01-01
Full Text Available The study object is the first-order threshold auto-regression model with a single zero-located threshold. The model describes a stochastic temporal series with discrete time by means of a piecewise linear equation consisting of two linear classical first-order autoregressive equations. One of these equations is used to calculate a running value of the temporal series. A control variable that determines the choice between these two equations is the sign of the previous value of the same series.The first-order threshold autoregressive model with a single threshold depends on two real parameters that coincide with the coefficients of the piecewise linear threshold equation. These parameters are assumed to be unknown. The paper studies an estimate of the least squares, an estimate the least modules, and the M-estimates of these parameters. The aim of the paper is a comparative study of the accuracy of these estimates for the main probabilistic distributions of the updating process of the threshold autoregressive equation. These probability distributions were normal, contaminated normal, logistic, double-exponential distributions, a Student's distribution with different number of degrees of freedom, and a Cauchy distribution.As a measure of the accuracy of each estimate, was chosen its variance to measure the scattering of the estimate around the estimated parameter. An estimate with smaller variance made from the two estimates was considered to be the best. The variance was estimated by computer simulation. To estimate the smallest modules an iterative weighted least-squares method was used and the M-estimates were done by the method of a deformable polyhedron (the Nelder-Mead method. To calculate the least squares estimate, an explicit analytic expression was used.It turned out that the estimation of least squares is best only with the normal distribution of the updating process. For the logistic distribution and the Student's distribution with the
Senkel, Luise
2016-01-01
This edited book aims at presenting current research activities in the field of robust variable-structure systems. The scope equally comprises highlighting novel methodological aspects as well as presenting the use of variable-structure techniques in industrial applications including their efficient implementation on hardware for real-time control. The target audience primarily comprises research experts in the field of control theory and nonlinear dynamics but the book may also be beneficial for graduate students.
DEFF Research Database (Denmark)
Chon, K H; Hoyer, D; Armoundas, A A
1999-01-01
In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic...... part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction...... error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate...
Positive semidefinite integrated covariance estimation, factorizations and asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
2017-01-01
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to estimate the different parameters sequentially with as many...
Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the correlation matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many...
Vrazic, Sacha
2015-08-01
Preventing car accidents by monitoring the driver's physiological parameters is of high importance. However, existing measurement methods are not robust to driver's body movements. In this paper, a system that estimates the heartbeat from the seat embedded piezoelectric sensors, and that is robust to strong body movements is presented. Multifractal q-Hurst exponents are used within a classifier to predict the most probable best sensor signal to be used in an Interactive Multi-Model Extended Kalman Filter pulsation estimation procedure. The car vibration noise is reduced using an autoregressive exogenous model to predict the noise on sensors. The performance of the proposed system was evaluated on real driving data up to 100 km/h and with slaloms at high speed. It is shown that this method improves by 36.7% the pulsation estimation under strong body movement compared to static sensor pulsation estimation and appears to provide reliable pulsation variability information for top-level analysis of drowsiness or other conditions.
Uncertainties in the Item Parameter Estimates and Robust Automated Test Assembly
Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G.
2013-01-01
Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…
Badshah, Amir; Choudhry, Aadil Jaleel; Ullah, Shan
2017-03-01
Industries are moving towards automation in order to increase productivity and ensure quality. Variety of electronic and electromagnetic systems are being employed to assist human operator in fast and accurate quality inspection of products. Majority of these systems are equipped with cameras and rely on diverse image processing algorithms. Information is lost in 2D image, therefore acquiring accurate 3D data from 2D images is an open issue. FAST, SURF and SIFT are well-known spatial domain techniques for features extraction and henceforth image registration to find correspondence between images. The efficiency of these methods is measured in terms of the number of perfect matches found. A novel fast and robust technique for stereo-image processing is proposed. It is based on non-rigid registration using modified normalized phase correlation. The proposed method registers two images in hierarchical fashion using quad-tree structure. The registration process works through global to local level resulting in robust matches even in presence of blur and noise. The computed matches can further be utilized to determine disparity and depth for industrial product inspection. The same can be used in driver assistance systems. The preliminary tests on Middlebury dataset produced satisfactory results. The execution time for a 413 x 370 stereo-pair is 500ms approximately on a low cost DSP.
International Nuclear Information System (INIS)
Li, Q; Mark, R G; Clifford, G D
2008-01-01
Physiological signals such as the electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often severely corrupted by noise, artifact and missing data, which lead to large errors in the estimation of the heart rate (HR) and ABP. A robust HR estimation method is described that compensates for these problems. The method is based upon the concept of fusing multiple signal quality indices (SQIs) and HR estimates derived from multiple electrocardiogram (ECG) leads and an invasive ABP waveform recorded from ICU patients. Physiological SQIs were obtained by analyzing the statistical characteristics of each waveform and their relationships to each other. HR estimates from the ECG and ABP are tracked with separate Kalman filters, using a modified update sequence based upon the individual SQIs. Data fusion of each HR estimate was then performed by weighting each estimate by the Kalman filters' SQI-modified innovations. This method was evaluated on over 6000 h of simultaneously acquired ECG and ABP from a 437 patient subset of ICU data by adding real ECG and realistic artificial ABP noise. The method provides an accurate HR estimate even in the presence of high levels of persistent noise and artifact, and during episodes of extreme bradycardia and tachycardia
A Robust Parametric Technique for Multipath Channel Estimation in the Uplink of a DS-CDMA System
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available The problem of estimating the multipath channel parameters of a new user entering the uplink of an asynchronous direct sequence-code division multiple access (DS-CDMA system is addressed. The problem is described via a least squares (LS cost function with a rich structure. This cost function, which is nonlinear with respect to the time delays and linear with respect to the gains of the multipath channel, is proved to be approximately decoupled in terms of the path delays. Due to this structure, an iterative procedure of 1D searches is adequate for time delays estimation. The resulting method is computationally efficient, does not require any specific pilot signal, and performs well for a small number of training symbols. Simulation results show that the proposed technique offers a better estimation accuracy compared to existing related methods, and is robust to multiple access interference.
John Loomis; Armando Gonzalez-Caban; Joseph Champ
2011-01-01
Over the past four decades teh contingent valuation method (CVM) has become a technique frequently used by economists to estimate willingness-to-pay (WTP) for improvements in environmental quality and prot3tion of natural resources. The CVM was originall applied to estmate recreation use values (Davis, 1963; Hammack and Brown, 1974)and air quality (Brookshire et al....
Robust Estimation of HDR in fMRI using H-infinity Filters
DEFF Research Database (Denmark)
Puthusserypady, Sadasivan; Jue, R.; Ratnarajah, T.
2010-01-01
Estimation and detection of the hemodynamic response (HDR) are of great importance in functional MRI (fMRI) data analysis. In this paper, we propose the use of three H-infinity adaptive filters (finite memory, exponentially weighted, and timevarying) for accurate estimation and detection of the HDR......-1487]. Performances of the proposed techniques are compared to the conventional t-test method as well as the well-known LMSs and recursive least squares algorithms. Extensive numerical simulations show that the proposed methods result in better HDR estimations and activation detections....
COMPARISON OF RECURSIVE ESTIMATION TECHNIQUES FOR POSITION TRACKING RADIOACTIVE SOURCES
International Nuclear Information System (INIS)
Muske, K.; Howse, J.
2000-01-01
This paper compares the performance of recursive state estimation techniques for tracking the physical location of a radioactive source within a room based on radiation measurements obtained from a series of detectors at fixed locations. Specifically, the extended Kalman filter, algebraic observer, and nonlinear least squares techniques are investigated. The results of this study indicate that recursive least squares estimation significantly outperforms the other techniques due to the severe model nonlinearity
A PSF-Shape-Based Beamforming Strategy for Robust 2D Motion Estimation in Ultrafast Data
Anne E. C. M. Saris; Stein Fekkes; Maartje M. Nillesen; Hendrik H. G. Hansen; Chris L. de Korte
2018-01-01
This paper presents a framework for motion estimation in ultrafast ultrasound data. It describes a novel approach for determining the sampling grid for ultrafast data based on the system’s point-spread-function (PSF). As a consequence, the cross-correlation functions (CCF) used in the speckle tracking (ST) algorithm will have circular-shaped peaks, which can be interpolated using a 2D interpolation method to estimate subsample displacements. Carotid artery wall motion and parabolic blood flow...
Jones, Reese E.; Mandadapu, Kranthi K.
2012-04-01
We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.
A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain
Directory of Open Access Journals (Sweden)
Ibn-Elhaj E
2009-01-01
Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.
A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain
Directory of Open Access Journals (Sweden)
E. M. Ismaili Aalaoui
2009-02-01
Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.
Directory of Open Access Journals (Sweden)
Ting Zhao
2015-01-01
Full Text Available Accurate and reliable state of charge (SOC estimation is a key enabling technique for large format lithium-ion battery pack due to its vital role in battery safety and effective management. This paper tries to make three contributions to existing literatures through robust algorithms. (1 Observer based SOC estimation error model is established, where the crucial parameters on SOC estimation accuracy are determined by quantitative analysis, being a basis for parameters update. (2 The estimation method for a battery pack in which the inconsistency of cells is taken into consideration is proposed, ensuring all batteries’ SOC ranging from 0 to 1, effectively avoiding the battery overcharged/overdischarged. Online estimation of the parameters is also presented in this paper. (3 The SOC estimation accuracy of the battery pack is verified using the hardware-in-loop simulation platform. The experimental results at various dynamic test conditions, temperatures, and initial SOC difference between two cells demonstrate the efficacy of the proposed method.
A positional estimation technique for an autonomous land vehicle in an unstructured environment
Talluri, Raj; Aggarwal, J. K.
1990-01-01
This paper presents a solution to the positional estimation problem of an autonomous land vehicle navigating in an unstructured mountainous terrain. A Digital Elevation Map (DEM) of the area in which the robot is to navigate is assumed to be given. It is also assumed that the robot is equipped with a camera that can be panned and tilted, and a device to measure the elevation of the robot above the ground surface. No recognizable landmarks are assumed to be present in the environment in which the robot is to navigate. The solution presented makes use of the DEM information, and structures the problem as a heuristic search in the DEM for the possible robot location. The shape and position of the horizon line in the image plane and the known camera geometry of the perspective projection are used as parameters to search the DEM. Various heuristics drawn from the geometric constraints are used to prune the search space significantly. The algorithm is made robust to errors in the imaging process by accounting for the worst care errors. The approach is tested using DEM data of areas in Colorado and Texas. The method is suitable for use in outdoor mobile robots and planetary rovers.
Robust estimation of the proportion of treatment effect explained by surrogate marker information.
Parast, Layla; McDermott, Mary M; Tian, Lu
2016-05-10
In randomized treatment studies where the primary outcome requires long follow-up of patients and/or expensive or invasive obtainment procedures, the availability of a surrogate marker that could be used to estimate the treatment effect and could potentially be observed earlier than the primary outcome would allow researchers to make conclusions regarding the treatment effect with less required follow-up time and resources. The Prentice criterion for a valid surrogate marker requires that a test for treatment effect on the surrogate marker also be a valid test for treatment effect on the primary outcome of interest. Based on this criterion, methods have been developed to define and estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker. These methods aim to identify useful statistical surrogates that capture a large proportion of the treatment effect. However, current methods to estimate this proportion usually require restrictive model assumptions that may not hold in practice and thus may lead to biased estimates of this quantity. In this paper, we propose a nonparametric procedure to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on a potential surrogate marker and extend this procedure to a setting with multiple surrogate markers. We compare our approach with previously proposed model-based approaches and propose a variance estimation procedure based on a perturbation-resampling method. Simulation studies demonstrate that the procedure performs well in finite samples and outperforms model-based procedures when the specified models are not correct. We illustrate our proposed procedure using a data set from a randomized study investigating a group-mediated cognitive behavioral intervention for peripheral artery disease participants. Copyright © 2015 John Wiley & Sons, Ltd.
Distributed estimation of sensors position in underwater wireless sensor network
Zandi, Rahman; Kamarei, Mahmoud; Amiri, Hadi
2016-05-01
In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error.
Directory of Open Access Journals (Sweden)
Mohammad Manir Hossain Mollah
Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large
Xie, Xiang-Peng; Yue, Dong; Park, Ju H
2018-02-01
The paper provides relaxed designs of fault estimation observer for nonlinear dynamical plants in the Takagi-Sugeno form. Compared with previous theoretical achievements, a modified version of fuzzy fault estimation observer is implemented with the aid of the so-called maximum-priority-based switching law. Given each activated switching status, the appropriate group of designed matrices can be provided so as to explore certain key properties of the considered plants by means of introducing a set of matrix-valued variables. Owing to the reason that more abundant information of the considered plants can be updated in due course and effectively exploited for each time instant, the conservatism of the obtained result is less than previous theoretical achievements and thus the main defect of those existing methods can be overcome to some extent in practice. Finally, comparative simulation studies on the classical nonlinear truck-trailer model are given to certify the benefits of the theoretic achievement which is obtained in our study. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
A robust estimate of the number and characteristics of persons released from prison in Australia.
Avery, Alex; Kinner, Stuart A
2015-08-01
To estimate the number and characteristics of adults released from prison in Australia. We calculated ratios, stratified by age, sex and Indigenous status, by comparing the number of persons released from prison in New South Wales (NSW), with the number in NSW prisons on 30 June of the corresponding year. These stratified ratios were applied to Australia-wide prison data to estimate the number and characteristics of persons released annually. We estimated that in 2013, 38,576 persons were released from prison in Australia - 25.3% more than the daily prison population. Young people, Indigenous people and women were over-represented among those released. We estimated that 3.69 Indigenous women aged 18-24 were released annually for each equivalent person in prison; and 2.75 non-Indigenous women aged 18-24 were released annually for each equivalent person in prison. The annual 'flow' through Australia's prisons is well in excess of the daily number, but information on those moving through prison systems is not yet publicly available. The characteristics of those released from prison differ meaningfully from those of people in prison. Routine, national reporting of prison separations is critical to informing upscaling and targeting of Throughcare services for this profoundly vulnerable population. © 2015 Public Health Association of Australia.
Korendijk, Elly J. H.; Moerbeek, Mirjam; Maas, Cora J. M.
2010-01-01
In the case of trials with nested data, the optimal allocation of units depends on the budget, the costs, and the intracluster correlation coefficient. In general, the intracluster correlation coefficient is unknown in advance and an initial guess has to be made based on published values or subject matter knowledge. This initial estimate is likely…
A PSF-shape-based beamforming strategy for robust 2D motion estimation in ultrafast data
Saris, Anne E.C.M.; Fekkes, Stein; Nillesen, Maartje; Hansen, Hendrik H.G.; de Korte, Chris L.
2018-01-01
This paper presents a framework for motion estimation in ultrafast ultrasound data. It describes a novel approach for determining the sampling grid for ultrafast data based on the system's point-spread-function (PSF). As a consequence, the cross-correlation functions (CCF) used in the speckle
Bayesian Estimation of the Logistic Positive Exponent IRT Model
Bolfarine, Heleno; Bazan, Jorge Luis
2010-01-01
A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric…
Terminal homing position estimation forAutonomous underwater vehicle docking
2017-06-01
mathematical tool to execute the computations in the MHE application . Zanon et al. also used the real-time iteration scheme with shifting since the...density estimation of simulation output, as well as electricity demand forecasts with respect to weather conditions. In all of these applications , epi...sub-optimal filter. The UKF, on the other hand, is considered an optimal filter. The UKF employs the UT, which is used in calculating the statistics
Robustness of Input features from Noisy Silhouettes in Human Pose Estimation
DEFF Research Database (Denmark)
Gong, Wenjuan; Fihl, Preben; Gonzàlez, Jordi
2014-01-01
. In this paper, we explore this problem. First, We compare performances of several image features widely used for human pose estimation and explore their performances against each other and select one with best performance. Second, iterative closest point algorithm is introduced for a new quantitative...... of silhouette samples of different noise levels and compare with the selected feature on a public dataset: Human Eva dataset....
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
Xiaodong Zhuge; Palenstijn, Willem Jan; Batenburg, Kees Joost
2016-01-01
In this paper, we present a novel iterative reconstruction algorithm for discrete tomography (DT) named total variation regularized discrete algebraic reconstruction technique (TVR-DART) with automated gray value estimation. This algorithm is more robust and automated than the original DART algorithm, and is aimed at imaging of objects consisting of only a few different material compositions, each corresponding to a different gray value in the reconstruction. By exploiting two types of prior knowledge of the scanned object simultaneously, TVR-DART solves the discrete reconstruction problem within an optimization framework inspired by compressive sensing to steer the current reconstruction toward a solution with the specified number of discrete gray values. The gray values and the thresholds are estimated as the reconstruction improves through iterations. Extensive experiments from simulated data, experimental μCT, and electron tomography data sets show that TVR-DART is capable of providing more accurate reconstruction than existing algorithms under noisy conditions from a small number of projection images and/or from a small angular range. Furthermore, the new algorithm requires less effort on parameter tuning compared with the original DART algorithm. With TVR-DART, we aim to provide the tomography society with an easy-to-use and robust algorithm for DT.
Chen, Siyuan; Epps, Julien
2014-12-01
Monitoring pupil and blink dynamics has applications in cognitive load measurement during human-machine interaction. However, accurate, efficient, and robust pupil size and blink estimation pose significant challenges to the efficacy of real-time applications due to the variability of eye images, hence to date, require manual intervention for fine tuning of parameters. In this paper, a novel self-tuning threshold method, which is applicable to any infrared-illuminated eye images without a tuning parameter, is proposed for segmenting the pupil from the background images recorded by a low cost webcam placed near the eye. A convex hull and a dual-ellipse fitting method are also proposed to select pupil boundary points and to detect the eyelid occlusion state. Experimental results on a realistic video dataset show that the measurement accuracy using the proposed methods is higher than that of widely used manually tuned parameter methods or fixed parameter methods. Importantly, it demonstrates convenience and robustness for an accurate and fast estimate of eye activity in the presence of variations due to different users, task types, load, and environments. Cognitive load measurement in human-machine interaction can benefit from this computationally efficient implementation without requiring a threshold calibration beforehand. Thus, one can envisage a mini IR camera embedded in a lightweight glasses frame, like Google Glass, for convenient applications of real-time adaptive aiding and task management in the future.
A PSF-Shape-Based Beamforming Strategy for Robust 2D Motion Estimation in Ultrafast Data
Directory of Open Access Journals (Sweden)
Anne E. C. M. Saris
2018-03-01
Full Text Available This paper presents a framework for motion estimation in ultrafast ultrasound data. It describes a novel approach for determining the sampling grid for ultrafast data based on the system’s point-spread-function (PSF. As a consequence, the cross-correlation functions (CCF used in the speckle tracking (ST algorithm will have circular-shaped peaks, which can be interpolated using a 2D interpolation method to estimate subsample displacements. Carotid artery wall motion and parabolic blood flow simulations together with rotating disk experiments using a Verasonics Vantage 256 are used for performance evaluation. Zero-degree plane wave data were acquired using an ATL L5-12 (fc = 9 MHz transducer for a range of pulse repetition frequencies (PRFs, resulting in 0–600 µm inter-frame displacements. The proposed methodology was compared to data beamformed on a conventionally spaced grid, combined with the commonly used 1D parabolic interpolation. The PSF-shape-based beamforming grid combined with 2D cubic interpolation showed the most accurate and stable performance with respect to the full range of inter-frame displacements, both for the assessment of blood flow and vessel wall dynamics. The proposed methodology can be used as a protocolled way to beamform ultrafast data and obtain accurate estimates of tissue motion.
Noise estimation of beam position monitors at RHIC
International Nuclear Information System (INIS)
Shen, X.; Bai, M.
2014-01-01
Beam position monitors (BPM) are used to record the average orbits and transverse turn-by-turn displacements of the beam centroid motion. The Relativistic Hadron Ion Collider (RHIC) has 160 BPMs for each plane in each of the Blue and Yellow rings: 72 dual-plane BPMs in the insertion regions (IR) and 176 single-plane modules in the arcs. Each BPM is able to acquire 1024 or 4096 consecutive turn-by-turn beam positions. Inevitably, there are broadband noisy signals in the turn-by-turn data due to BPM electronics as well as other sources. A detailed study of the BPM noise performance is critical for reliable optics measurement and beam dynamics analysis based on turn-by-turn data.
Robust estimates of the impact of broadcasting on match attendance in football
B Buraimo; D Forrest; R Simmons
2006-01-01
The paper employs data from 2,884 matches, of which 158 were televised, in the second tier of English football (currently known as The Football League Championship). It builds a model of the determinants of attendance that is designed to yield estimates of the proportionate changes in the size of crowds resulting from games being shown on either free-to-air or subscription based channels. The model has two innovatory features. First, it controls for the market size of home and away teams very...
Influence of TLD position on the estimate of fetal dose
International Nuclear Information System (INIS)
Majola, J.; Jamieson, T.J.
1995-11-01
This report examines the adequacy of the practice of using a single dosimeter worn at the front of the body as an estimate of the dose received by nuclear medicine technologies. In order to investigate this, a group of approximately 50 technologists at 9 different hospitals were double-badged, i.e. provided with front and back dosimeters, and the ratio of front to back dose computed. Both aggregate data and hospital-specific data are presented and accompanied by several forms of statistical analysis. Apparent trends and possible explanations are discussed. Recommendations are provided for additional studies relating to the badging of nuclear medicine technologists. (author). 125 refs., 15 tabs., 13 figs
Influence of TLD position on the estimate of fetal dose
Energy Technology Data Exchange (ETDEWEB)
Majola, J; Jamieson, T J [Science Applications International Corp., Ottawa, ON (Canada)
1995-11-01
This report examines the adequacy of the practice of using a single dosimeter worn at the front of the body as an estimate of the dose received by nuclear medicine technologies. In order to investigate this, a group of approximately 50 technologists at 9 different hospitals were double-badged, i.e. provided with front and back dosimeters, and the ratio of front to back dose computed. Both aggregate data and hospital-specific data are presented and accompanied by several forms of statistical analysis. Apparent trends and possible explanations are discussed. Recommendations are provided for additional studies relating to the badging of nuclear medicine technologists. (author). 125 refs., 15 tabs., 13 figs.
Convex relaxations of spectral sparsity for robust super-resolution and line spectrum estimation
Chi, Yuejie
2017-08-01
We consider recovering the amplitudes and locations of spikes in a point source signal from its low-pass spectrum that may suffer from missing data and arbitrary outliers. We first review and provide a unified view of several recently proposed convex relaxations that characterize and capitalize the spectral sparsity of the point source signal without discretization under the framework of atomic norms. Next we propose a new algorithm when the spikes are known a priori to be positive, motivated by applications such as neural spike sorting and fluorescence microscopy imaging. Numerical experiments are provided to demonstrate the effectiveness of the proposed approach.
Robust estimation and forecasting of the long-term seasonal component of electricity spot prices
International Nuclear Information System (INIS)
Nowotarski, Jakub; Tomczyk, Jakub; Weron, Rafał
2013-01-01
We present the results of an extensive study on estimation and forecasting of the long-term seasonal component (LTSC) of electricity spot prices. We consider a battery of over 300 models, including monthly dummies and models based on Fourier or wavelet decomposition combined with linear or exponential decay. We find that the considered wavelet-based models are significantly better in terms of forecasting spot prices up to a year ahead than the commonly used monthly dummies and sine-based models. This result questions the validity and usefulness of stochastic models of spot electricity prices built on the latter two types of LTSC models. - Highlights: • First comprehensive study on the forecasting of the long-term seasonal components • Over 300 models examined, including commonly used and new approaches • Wavelet-based models outperform sine-based and monthly dummy models. • Validity of stochastic models built on sines or monthly dummies is questionable
Robust node estimation and topology discovery for large-scale networks
Alouini, Mohamed-Slim
2017-02-23
Various examples are provided for node estimation and topology discovery for networks. In one example, a method includes receiving a packet having an identifier from a first node; adding the identifier to another transmission packet based on a comparison between the first identifier and existing identifiers associated with the other packet; adjusting a transmit probability based on the comparison; and transmitting the other packet based on a comparison between the transmit probability and a probability distribution. In another example, a system includes a network device that can adds an identifier received in a packet to a list including existing identifiers and adjust a transmit probability based on a comparison between the identifiers; and transmit another packet based on a comparison between the transmit probability and a probability distribution. In another example, a method includes determining a quantity of sensor devices based on a plurality of identifiers received in a packet.
Robust node estimation and topology discovery for large-scale networks
Alouini, Mohamed-Slim; Douik, Ahmed S.; Aly, Salah A.; Al-Naffouri, Tareq Y.
2017-01-01
Various examples are provided for node estimation and topology discovery for networks. In one example, a method includes receiving a packet having an identifier from a first node; adding the identifier to another transmission packet based on a comparison between the first identifier and existing identifiers associated with the other packet; adjusting a transmit probability based on the comparison; and transmitting the other packet based on a comparison between the transmit probability and a probability distribution. In another example, a system includes a network device that can adds an identifier received in a packet to a list including existing identifiers and adjust a transmit probability based on a comparison between the identifiers; and transmit another packet based on a comparison between the transmit probability and a probability distribution. In another example, a method includes determining a quantity of sensor devices based on a plurality of identifiers received in a packet.
Directory of Open Access Journals (Sweden)
Rebecca SAFRAN, Samuel FLAXMAN, Michael KOPP, Darren E. IRWIN, Derek BRIGGS, Matthew R. EVANS, W. Chris FUNK, David A. GRAY, Eileen A. HEBE
2012-06-01
Full Text Available Whereas a rich literature exists for estimating population genetic divergence, metrics of phenotypic trait divergence are lacking, particularly for comparing multiple traits among three or more populations. Here, we review and analyze via simulation Hedges’ g, a widely used parametric estimate of effect size. Our analyses indicate that g is sensitive to a combination of unequal trait variances and unequal sample sizes among populations and to changes in the scale of measurement. We then go on to derive and explain a new, non-parametric distance measure, “Δp”, which is calculated based upon a joint cumulative distribution function (CDF from all populations under study. More precisely, distances are measured in terms of the percentiles in this CDF at which each population’s median lies. Δp combines many desirable features of other distance metrics into a single metric; namely, compared to other metrics, p is relatively insensitive to unequal variances and sample sizes among the populations sampled. Furthermore, a key feature of Δp—and our main motivation for developing it—is that it easily accommodates simultaneous comparisons of any number of traits across any number of populations. To exemplify its utility, we employ Δp to address a question related to the role of sexual selection in speciation: are sexual signals more divergent than ecological traits in closely related taxa? Using traits of known function in closely related populations, we show that traits predictive of reproductive performance are, indeed, more divergent and more sexually dimorphic than traits related to ecological adaptation [Current Zoology 58 (3: 423-436, 2012].
A Robust Transform Estimator Based on Residual Analysis and Its Application on UAV Aerial Images
Directory of Open Access Journals (Sweden)
Guorong Cai
2018-02-01
Full Text Available Estimating the transformation between two images from the same scene is a fundamental step for image registration, image stitching and 3D reconstruction. State-of-the-art methods are mainly based on sorted residual for generating hypotheses. This scheme has acquired encouraging results in many remote sensing applications. Unfortunately, mainstream residual based methods may fail in estimating the transform between Unmanned Aerial Vehicle (UAV low altitude remote sensing images, due to the fact that UAV images always have repetitive patterns and severe viewpoint changes, which produce lower inlier rate and higher pseudo outlier rate than other tasks. We performed extensive experiments and found the main reason is that these methods compute feature pair similarity within a fixed window, making them sensitive to the size of residual window. To solve this problem, three schemes that based on the distribution of residuals are proposed, which are called Relational Window (RW, Sliding Window (SW, Reverse Residual Order (RRO, respectively. Specially, RW employs a relaxation residual window size to evaluate the highest similarity within a relaxation model length. SW fixes the number of overlap models while varying the length of window size. RRO takes the permutation of residual values into consideration to measure similarity, not only including the number of overlap structures, but also giving penalty to reverse number within the overlap structures. Experimental results conducted on our own built UAV high resolution remote sensing images show that the proposed three strategies all outperform traditional methods in the presence of severe perspective distortion due to viewpoint change.
Hua, Xue; Hibar, Derrek P.; Ching, Christopher R.K.; Boyle, Christina P.; Rajagopalan, Priya; Gutman, Boris A.; Leow, Alex D.; Toga, Arthur W.; Jack, Clifford R.; Harvey, Danielle; Weiner, Michael W.; Thompson, Paul M.
2013-01-01
Various neuroimaging measures are being evaluated for tracking Alzheimer’s disease (AD) progression in therapeutic trials, including measures of structural brain change based on repeated scanning of patients with magnetic resonance imaging (MRI). Methods to compute brain change must be robust to scan quality. Biases may arise if any scans are thrown out, as this can lead to the true changes being overestimated or underestimated. Here we analyzed the full MRI dataset from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) from the first phase of Alzheimer’s Disease Neuroimaging Initiative (ADNI-1) and assessed several sources of bias that can arise when tracking brain changes with structural brain imaging methods, as part of a pipeline for tensor-based morphometry (TBM). In all healthy subjects who completed MRI scanning at screening, 6, 12, and 24 months, brain atrophy was essentially linear with no detectable bias in longitudinal measures. In power analyses for clinical trials based on these change measures, only 39 AD patients and 95 mild cognitive impairment (MCI) subjects were needed for a 24-month trial to detect a 25% reduction in the average rate of change using a two-sided test (α=0.05, power=80%). Further sample size reductions were achieved by stratifying the data into Apolipoprotein E (ApoE) ε4 carriers versus non-carriers. We show how selective data exclusion affects sample size estimates, motivating an objective comparison of different analysis techniques based on statistical power and robustness. TBM is an unbiased, robust, high-throughput imaging surrogate marker for large, multi-site neuroimaging studies and clinical trials of AD and MCI. PMID:23153970
De Filippis, G.; Noël, J. P.; Kerschen, G.; Soria, L.; Stephan, C.
2017-09-01
The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 constitutes one in a series of recent attempts toward developing a realistic, first-generation framework applicable to complex structures. If this method showed promising capabilities when applied to academic structures, it is still confronted with a number of limitations which needs to be addressed. In particular, the removal of nonphysical poles in the identified nonlinear models is a distinct challenge. In the present paper, it is proposed as a first contribution to operate directly on the identified state-space matrices to carry out spurious pole removal. A modal-space decomposition of the state and output matrices is examined to discriminate genuine from numerical poles, prior to estimating the extended input and feedthrough matrices. The final state-space model thus contains physical information only and naturally leads to nonlinear coefficients free of spurious variations. Besides spurious variations due to nonphysical poles, vibration modes lying outside the frequency band of interest may also produce drifts of the nonlinear coefficients. The second contribution of the paper is to include residual terms, accounting for the existence of these modes. The proposed improved FNSI methodology is validated numerically and experimentally using a full-scale structure, the Morane-Saulnier Paris aircraft.
Directory of Open Access Journals (Sweden)
Adytia Darmawan
2016-12-01
Full Text Available Position estimation using WIMU (Wireless Inertial Measurement Unit is one of emerging technology in the field of indoor positioning systems. WIMU can detect movement and does not depend on GPS signals. The position is then estimated using a modified ZUPT (Zero Velocity Update method that was using Filter Magnitude Acceleration (FMA, Variance Magnitude Acceleration (VMA and Angular Rate (AR estimation. Performance of this method was justified on a six-legged robot navigation system. Experimental result shows that the combination of VMA-AR gives the best position estimation.
Estimation of Subdaily Polar Motion with the Global Positioning System During the Spoch '92 Campaign
Ibanez-Meier, R.; Freedman, A. P.; Herring, T. A.; Gross, R. S.; Lichten, S. M.; Lindqwister, U. J.
1994-01-01
Data collected over six days from a worldwide Global Positioning System (GPS) tracking network during the Epoch '92 campaign are used to estimate variations of the Earth's pole position every 30 minutes.
Pannullo, Francesca; Lee, Duncan; Waclawski, Eugene; Leyland, Alastair H
2016-08-01
The long-term impact of air pollution on human health can be estimated from small-area ecological studies in which the health outcome is regressed against air pollution concentrations and other covariates, such as socio-economic deprivation. Socio-economic deprivation is multi-factorial and difficult to measure, and includes aspects of income, education, and housing as well as others. However, these variables are potentially highly correlated, meaning one can either create an overall deprivation index, or use the individual characteristics, which can result in a variety of pollution-health effects. Other aspects of model choice may affect the pollution-health estimate, such as the estimation of pollution, and spatial autocorrelation model. Therefore, we propose a Bayesian model averaging approach to combine the results from multiple statistical models to produce a more robust representation of the overall pollution-health effect. We investigate the relationship between nitrogen dioxide concentrations and cardio-respiratory mortality in West Central Scotland between 2006 and 2012. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Ren, Shangjie [Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin (China); Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States); Hara, Wendy; Wang, Lei; Buyyounouski, Mark K.; Le, Quynh-Thu; Xing, Lei [Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States); Li, Ruijiang, E-mail: rli2@stanford.edu [Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California (United States)
2017-03-15
Purpose: To develop a reliable method to estimate electron density based on anatomic magnetic resonance imaging (MRI) of the brain. Methods and Materials: We proposed a unifying multi-atlas approach for electron density estimation based on standard T1- and T2-weighted MRI. First, a composite atlas was constructed through a voxelwise matching process using multiple atlases, with the goal of mitigating effects of inherent anatomic variations between patients. Next we computed for each voxel 2 kinds of conditional probabilities: (1) electron density given its image intensity on T1- and T2-weighted MR images; and (2) electron density given its spatial location in a reference anatomy, obtained by deformable image registration. These were combined into a unifying posterior probability density function using the Bayesian formalism, which provided the optimal estimates for electron density. We evaluated the method on 10 patients using leave-one-patient-out cross-validation. Receiver operating characteristic analyses for detecting different tissue types were performed. Results: The proposed method significantly reduced the errors in electron density estimation, with a mean absolute Hounsfield unit error of 119, compared with 140 and 144 (P<.0001) using conventional T1-weighted intensity and geometry-based approaches, respectively. For detection of bony anatomy, the proposed method achieved an 89% area under the curve, 86% sensitivity, 88% specificity, and 90% accuracy, which improved upon intensity and geometry-based approaches (area under the curve: 79% and 80%, respectively). Conclusion: The proposed multi-atlas approach provides robust electron density estimation and bone detection based on anatomic MRI. If validated on a larger population, our work could enable the use of MRI as a primary modality for radiation treatment planning.
Zhou, Yatong; Han, Chunying; Chi, Yue
2018-06-01
In a simultaneous source survey, no limitation is required for the shot scheduling of nearby sources and thus a huge acquisition efficiency can be obtained but at the same time making the recorded seismic data contaminated by strong blending interference. In this paper, we propose a multi-dip seislet frame based sparse inversion algorithm to iteratively separate simultaneous sources. We overcome two inherent drawbacks of traditional seislet transform. For the multi-dip problem, we propose to apply a multi-dip seislet frame thresholding strategy instead of the traditional seislet transform for deblending simultaneous-source data that contains multiple dips, e.g., containing multiple reflections. The multi-dip seislet frame strategy solves the conflicting dip problem that degrades the performance of the traditional seislet transform. For the noise issue, we propose to use a robust dip estimation algorithm that is based on velocity-slope transformation. Instead of calculating the local slope directly using the plane-wave destruction (PWD) based method, we first apply NMO-based velocity analysis and obtain NMO velocities for multi-dip components that correspond to multiples of different orders, then a fairly accurate slope estimation can be obtained using the velocity-slope conversion equation. An iterative deblending framework is given and validated through a comprehensive analysis over both numerical synthetic and field data examples.
Directory of Open Access Journals (Sweden)
Holly C Smith
Full Text Available As delphinid populations become increasingly exposed to human activities we rely on our capacity to produce accurate abundance estimates upon which to base management decisions. This study applied mark-recapture methods following the Robust Design to estimate abundance, demographic parameters, and temporary emigration rates of an Indo-Pacific bottlenose dolphin (Tursiops aduncus population off Bunbury, Western Australia. Boat-based photo-identification surveys were conducted year-round over three consecutive years along pre-determined transect lines to create a consistent sampling effort throughout the study period and area. The best fitting capture-recapture model showed a population with a seasonal Markovian temporary emigration with time varying survival and capture probabilities. Abundance estimates were seasonally dependent with consistently lower numbers obtained during winter and higher during summer and autumn across the three-year study period. Specifically, abundance estimates for all adults and juveniles (combined varied from a low of 63 (95% CI 59 to 73 in winter of 2007 to a high of 139 (95% CI 134 to148 in autumn of 2009. Temporary emigration rates (γ' for animals absent in the previous period ranged from 0.34 to 0.97 (mean = 0.54; ±SE 0.11 with a peak during spring. Temporary emigration rates for animals present during the previous period (γ'' were lower, ranging from 0.00 to 0.29, with a mean of 0.16 (± SE 0.04. This model yielded a mean apparent survival estimate for juveniles and adults (combined of 0.95 (± SE 0.02 and a capture probability from 0.07 to 0.51 with a mean of 0.30 (± SE 0.04. This study demonstrates the importance of incorporating temporary emigration to accurately estimate abundance of coastal delphinids. Temporary emigration rates were high in this study, despite the large area surveyed, indicating the challenges of sampling highly mobile animals which range over large spatial areas.
Robust Maximum Association Estimators
A. Alfons (Andreas); C. Croux (Christophe); P. Filzmoser (Peter)
2017-01-01
textabstractThe maximum association between two multivariate variables X and Y is defined as the maximal value that a bivariate association measure between one-dimensional projections αX and αY can attain. Taking the Pearson correlation as projection index results in the first canonical correlation
Methods for robustness programming
Olieman, N.J.
2008-01-01
Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition
Girinoto, Sadik, Kusman; Indahwati
2017-03-01
The National Socio-Economic Survey samples are designed to produce estimates of parameters of planned domains (provinces and districts). The estimation of unplanned domains (sub-districts and villages) has its limitation to obtain reliable direct estimates. One of the possible solutions to overcome this problem is employing small area estimation techniques. The popular choice of small area estimation is based on linear mixed models. However, such models need strong distributional assumptions and do not easy allow for outlier-robust estimation. As an alternative approach for this purpose, M-quantile regression approach to small area estimation based on modeling specific M-quantile coefficients of conditional distribution of study variable given auxiliary covariates. It obtained outlier-robust estimation from influence function of M-estimator type and also no need strong distributional assumptions. In this paper, the aim of study is to estimate the poverty indicator at sub-district level in Bogor District-West Java using M-quantile models for small area estimation. Using data taken from National Socioeconomic Survey and Villages Potential Statistics, the results provide a detailed description of pattern of incidence and intensity of poverty within Bogor district. We also compare the results with direct estimates. The results showed the framework may be preferable when direct estimate having no incidence of poverty at all in the small area.
Letcher, Benjamin H.; Schueller, Paul; Bassar, Ronald D.; Nislow, Keith H.; Coombs, Jason A.; Sakrejda, Krzysztof; Morrissey, Michael; Sigourney, Douglas B.; Whiteley, Andrew R.; O'Donnell, Matthew J.; Dubreuil, Todd L.
2015-01-01
Modelling the effects of environmental change on populations is a key challenge for ecologists, particularly as the pace of change increases. Currently, modelling efforts are limited by difficulties in establishing robust relationships between environmental drivers and population responses.We developed an integrated capture–recapture state-space model to estimate the effects of two key environmental drivers (stream flow and temperature) on demographic rates (body growth, movement and survival) using a long-term (11 years), high-resolution (individually tagged, sampled seasonally) data set of brook trout (Salvelinus fontinalis) from four sites in a stream network. Our integrated model provides an effective context within which to estimate environmental driver effects because it takes full advantage of data by estimating (latent) state values for missing observations, because it propagates uncertainty among model components and because it accounts for the major demographic rates and interactions that contribute to annual survival.We found that stream flow and temperature had strong effects on brook trout demography. Some effects, such as reduction in survival associated with low stream flow and high temperature during the summer season, were consistent across sites and age classes, suggesting that they may serve as robust indicators of vulnerability to environmental change. Other survival effects varied across ages, sites and seasons, indicating that flow and temperature may not be the primary drivers of survival in those cases. Flow and temperature also affected body growth rates; these responses were consistent across sites but differed dramatically between age classes and seasons. Finally, we found that tributary and mainstem sites responded differently to variation in flow and temperature.Annual survival (combination of survival and body growth across seasons) was insensitive to body growth and was most sensitive to flow (positive) and temperature (negative
Hubble, Michael W; Richards, Michael E; Wilfong, Denise A
2008-01-01
To estimate the cost-effectiveness of continuous positive airway pressure (CPAP) in managing prehospital acute pulmonary edema in an urban EMS system. Using estimates from published reports on prehospital and emergency department CPAP, a cost-effectiveness model of implementing CPAP in a typical urban EMS system was derived from the societal perspective as well as the perspective of the implementing EMS system. To assess the robustness of the model, a series of univariate and multivariate sensitivity analyses was performed on the input variables. The cost of consumables, equipment, and training yielded a total cost of $89 per CPAP application. The theoretical system would be expected to use CPAP 4 times per 1000 EMS patients and is expected to save 0.75 additional lives per 1000 EMS patients at a cost of $490 per life saved. CPAP is also expected to result in approximately one less intubation per 6 CPAP applications and reduce hospitalization costs by $4075 per year for each CPAP application. Through sensitivity analyses the model was verified to be robust across a wide range of input variable assumptions. Previous studies have demonstrated the clinical effectiveness of CPAP in the management of acute pulmonary edema. Through a theoretical analysis which modeled the costs and clinical benefits of implementing CPAP in an urban EMS system, prehospital CPAP appears to be a cost-effective treatment.
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...
Mazidi, Hesam; Nehorai, Arye; Lew, Matthew D.
2018-02-01
In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.
Directory of Open Access Journals (Sweden)
David P Piñero
2015-01-01
Full Text Available Purpose: To evaluate the predictability of the refractive correction achieved with a positional accommodating intraocular lenses (IOL and to develop a potential optimization of it by minimizing the error associated with the keratometric estimation of the corneal power and by developing a predictive formula for the effective lens position (ELP. Materials and Methods: Clinical data from 25 eyes of 14 patients (age range, 52-77 years and undergoing cataract surgery with implantation of the accommodating IOL Crystalens HD (Bausch and Lomb were retrospectively reviewed. In all cases, the calculation of an adjusted IOL power (P IOLadj based on Gaussian optics considering the residual refractive error was done using a variable keratometric index value (n kadj for corneal power estimation with and without using an estimation algorithm for ELP obtained by multiple regression analysis (ELP adj . P IOLadj was compared to the real IOL power implanted (P IOLReal , calculated with the SRK-T formula and also to the values estimated by the Haigis, HofferQ, and Holladay I formulas. Results: No statistically significant differences were found between P IOLReal and P IOLadj when ELP adj was used (P = 0.10, with a range of agreement between calculations of 1.23 D. In contrast, P IOLReal was significantly higher when compared to P IOLadj without using ELP adj and also compared to the values estimated by the other formulas. Conclusions: Predictable refractive outcomes can be obtained with the accommodating IOL Crystalens HD using a variable keratometric index for corneal power estimation and by estimating ELP with an algorithm dependent on anatomical factors and age.
Energy Technology Data Exchange (ETDEWEB)
Zhou, Ping; Lv, Youbin; Wang, Hong; Chai, Tianyou
2017-09-01
Optimal operation of a practical blast furnace (BF) ironmaking process depends largely on a good measurement of molten iron quality (MIQ) indices. However, measuring the MIQ online is not feasible using the available techniques. In this paper, a novel data-driven robust modeling is proposed for online estimation of MIQ using improved random vector functional-link networks (RVFLNs). Since the output weights of traditional RVFLNs are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with outliers. This affects the modeling accuracy of RVFLNs. To solve this problem, a Cauchy distribution weighted M-estimation based robust RFVLNs is proposed. Since the weights of different outlier data are properly determined by the Cauchy distribution, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Moreover, given that the BF is a complex nonlinear system with numerous coupling variables, the data-driven canonical correlation analysis is employed to identify the most influential components from multitudinous factors that affect the MIQ indices to reduce the model dimension. Finally, experiments using industrial data and comparative studies have demonstrated that the obtained model produces a better modeling and estimating accuracy and stronger robustness than other modeling methods.
time of arrival 3-d position estimation using minimum ads-b receiver ...
African Journals Online (AJOL)
HOD
The location from which a signal is transmitted can be estimated using the time it takes to be detected at a receiver. The difference between transmission time and the detection time is known as time of arrival (TOA). In this work, an algorithm for 3-dimensional (3-D) position estimation (PE) of an emitter using the minimum ...
Estimation in the positive stable shared frailty Cox proportional hazards model
DEFF Research Database (Denmark)
Martinussen, Torben; Pipper, Christian Bressen
2005-01-01
model in situations where the correlated survival data show a decreasing association with time. In this paper, we devise a likelihood based estimation procedure for the positive stable shared frailty Cox model, which is expected to obtain high efficiency. The proposed estimator is provided with large...
Directory of Open Access Journals (Sweden)
Zhi-An Deng
2016-05-01
Full Text Available This paper proposes a novel heading estimation approach for indoor pedestrian navigation using the built-in inertial sensors on a smartphone. Unlike previous approaches constraining the carrying position of a smartphone on the user’s body, our approach gives the user a larger freedom by implementing automatic recognition of the device carrying position and subsequent selection of an optimal strategy for heading estimation. We firstly predetermine the motion state by a decision tree using an accelerometer and a barometer. Then, to enable accurate and computational lightweight carrying position recognition, we combine a position classifier with a novel position transition detection algorithm, which may also be used to avoid the confusion between position transition and user turn during pedestrian walking. For a device placed in the trouser pockets or held in a swinging hand, the heading estimation is achieved by deploying a principal component analysis (PCA-based approach. For a device held in the hand or against the ear during a phone call, user heading is directly estimated by adding the yaw angle of the device to the related heading offset. Experimental results show that our approach can automatically detect carrying positions with high accuracy, and outperforms previous heading estimation approaches in terms of accuracy and applicability.
Brand market positions estimation and defining the strategic targets of its development
S.M. Makhnusha
2010-01-01
In this article the author generalizes the concept of brand characteristics which influenceits profitability and market positions. An approach to brand market positions estimation anddefining the strategic targets of its development is proposed.Keywords: brand, brand expansion, brand extension, brand value, brand power, brandrelevance, brand awareness.
Sub-spatial resolution position estimation for optical fibre sensing applications
DEFF Research Database (Denmark)
Zibar, Darko; Werzinger, Stefan; Schmauss, Bernhard
2017-01-01
Methods from machine learning community are employed for estimating the position of fibre Bragg gratings in an array. Using the conventional methods for position estimation, based on inverse discrete Fourier transform (IDFT), it is required that two-point spatial resolution is less than gratings...... of reflection coefficients and the positions is performed. From the practical point of view, we can demonstrate the reduction of the interrogator's bandwidth by factor of 2. The technique is demonstrated for incoherent optical frequency domain reflectometry (IOFDR). However, the approach is applicable to any...
Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.
Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu
2015-08-01
This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm.
Van Uffelen, Lora J; Nosal, Eva-Marie; Howe, Bruce M; Carter, Glenn S; Worcester, Peter F; Dzieciuch, Matthew A; Heaney, Kevin D; Campbell, Richard L; Cross, Patrick S
2013-10-01
Four acoustic Seagliders were deployed in the Philippine Sea November 2010 to April 2011 in the vicinity of an acoustic tomography array. The gliders recorded over 2000 broadband transmissions at ranges up to 700 km from moored acoustic sources as they transited between mooring sites. The precision of glider positioning at the time of acoustic reception is important to resolve the fundamental ambiguity between position and sound speed. The Seagliders utilized GPS at the surface and a kinematic model below for positioning. The gliders were typically underwater for about 6.4 h, diving to depths of 1000 m and traveling on average 3.6 km during a dive. Measured acoustic arrival peaks were unambiguously associated with predicted ray arrivals. Statistics of travel-time offsets between received arrivals and acoustic predictions were used to estimate range uncertainty. Range (travel time) uncertainty between the source and the glider position from the kinematic model is estimated to be 639 m (426 ms) rms. Least-squares solutions for glider position estimated from acoustically derived ranges from 5 sources differed by 914 m rms from modeled positions, with estimated uncertainty of 106 m rms in horizontal position. Error analysis included 70 ms rms of uncertainty due to oceanic sound-speed variability.
Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems
Directory of Open Access Journals (Sweden)
Omar Waleed Abdulwahhab
2017-01-01
Full Text Available Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA and received signal strength (RSS are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The results show that the neural network has good performance compared with two other analytical methods which are average positioning method and optimal positioning method.
Directory of Open Access Journals (Sweden)
Yeun-Sub Byun
2015-11-01
Full Text Available The real-time recognition of absolute (or relative position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test.
Two methods to estimate the position resolution for straw chambers with strip readout
International Nuclear Information System (INIS)
Golutvin, I.A.; Movchan, S.A.; Peshekhonov, V.D.; Preda, T.
1992-01-01
The centroid and charge-ratio methods are presented to estimate the position resolution of the straw chambers with strip readout. For the straw chambers of 10 mm in diameter, the highest position resolution was obtained for a strip pitch of 5 mm. With the centroid method and perpendicular X-ray beam, the position resolution was ≅120 μm, for the signal-to-noise ratio of 60-65. The charge-ratio method has demonstrated ≅10% better position resolution at the edges of the strip. 6 refs.; 5 figs
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 Mathematical Model to Estimate the Position of Mobile Robot by Sensing Caster Wheel Motion
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Amarendra Jnana H.
2018-01-01
Full Text Available This paper describes the position estimation of mobile robot by sensing caster wheel motion. A mathematical model is developed to determine the position of mobile robot by sensing the angular velocity and heading angle of the caster wheel. Using the established equations, simulations were carried out using MATLAB version 8.6 to observe and verify the position coordinates of mobile robot and in turn obtain its trajectory. The simulation results show that the angular velocity of caster wheel and heading angle calculated from the sensor output readings with the help of inverse kinematics equations matches well with that of actual values given as input for simulation. Simulation result of tracking rectangular trajectory implies that the path traced by the mobile robot can also be determined from the sensor output readings. This concept can be implemented on a real mobile robot for estimation of its position.
DEFF Research Database (Denmark)
Jakobsen, Jakob; Jensen, Anna B. O.; Nielsen, Allan Aasbjerg
2015-01-01
non-line-of-sight satellites. The signal reflections are implemented using the extended geometric path length of the signal path caused by reflections from the surrounding buildings. Based on real GPS satellite positions, simulated Galileo satellite positions, models of atmospheric effect...... on the satellite signals, designs of representative environments e.g. urban and rural scenarios, and a method to simulate reflection of satellite signals within the environment we are able to estimate the position accuracy given several prerequisites as described in the paper. The result is a modelling...... of the signal path from satellite to receiver, the satellite availability, the extended pseudoranges caused by signal reflection, and an estimate of the position accuracy based on a least squares adjustment of the extended pseudoranges. The paper describes the models and algorithms used and a verification test...
3D position estimation using an artificial neural network for a continuous scintillator PET detector
International Nuclear Information System (INIS)
Wang, Y; Zhu, W; Cheng, X; Li, D
2013-01-01
Continuous crystal based PET detectors have features of simple design, low cost, good energy resolution and high detection efficiency. Through single-end readout of scintillation light, direct three-dimensional (3D) position estimation could be another advantage that the continuous crystal detector would have. In this paper, we propose to use artificial neural networks to simultaneously estimate the plane coordinate and DOI coordinate of incident γ photons with detected scintillation light. Using our experimental setup with an ‘8 + 8’ simplified signal readout scheme, the training data of perpendicular irradiation on the front surface and one side surface are obtained, and the plane (x, y) networks and DOI networks are trained and evaluated. The test results show that the artificial neural network for DOI estimation is as effective as for plane estimation. The performance of both estimators is presented by resolution and bias. Without bias correction, the resolution of the plane estimator is on average better than 2 mm and that of the DOI estimator is about 2 mm over the whole area of the detector. With bias correction, the resolution at the edge area for plane estimation or at the end of the block away from the readout PMT for DOI estimation becomes worse, as we expect. The comprehensive performance of the 3D positioning by a neural network is accessed by the experimental test data of oblique irradiations. To show the combined effect of the 3D positioning over the whole area of the detector, the 2D flood images of oblique irradiation are presented with and without bias correction. (paper)
Directory of Open Access Journals (Sweden)
Yanjuan Geng
2017-01-01
Full Text Available Previous studies have showed that arm position variations would significantly degrade the classification performance of myoelectric pattern-recognition-based prosthetic control, and the cascade classifier (CC and multiposition classifier (MPC have been proposed to minimize such degradation in offline scenarios. However, it remains unknown whether these proposed approaches could also perform well in the clinical use of a multifunctional prosthesis control. In this study, the online effect of arm position variation on motion identification was evaluated by using a motion-test environment (MTE developed to mimic the real-time control of myoelectric prostheses. The performance of different classifier configurations in reducing the impact of arm position variation was investigated using four real-time metrics based on dataset obtained from transradial amputees. The results of this study showed that, compared to the commonly used motion classification method, the CC and MPC configurations improved the real-time performance across seven classes of movements in five different arm positions (8.7% and 12.7% increments of motion completion rate, resp.. The results also indicated that high offline classification accuracy might not ensure good real-time performance under variable arm positions, which necessitated the investigation of the real-time control performance to gain proper insight on the clinical implementation of EMG-pattern-recognition-based controllers for limb amputees.
Computers, coders, and voters: Comparing automated methods for estimating party positions
DEFF Research Database (Denmark)
Hjorth, F.; Klemmensen, R.; Hobolt, S.
2015-01-01
Assigning political actors positions in ideological space is a task of key importance to political scientists. In this paper we compare estimates obtained using the automated Wordscores and Wordfish techniques, along with estimates from voters and the Comparative Manifesto Project (CMP), against...... texts and a more ideologically charged vocabulary in order to produce estimates comparable to Wordscores. The paper contributes to the literature on automated content analysis by providing a comprehensive test of convergent validation, in terms of both number of cases analyzed and number of validation...
Markov Jump Linear Systems-Based Position Estimation for Lower Limb Exoskeletons
Directory of Open Access Journals (Sweden)
Samuel L. Nogueira
2014-01-01
Full Text Available In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF to improve the performance of inertial measurement units (IMUs based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank are not taken into account in other link position estimation (e.g., the foot. In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties.
Training data representation in a neural based robot position estimation system
International Nuclear Information System (INIS)
Taraglio, S.; Di Fonzo, F.; Burrascano, P.
1997-03-01
The vision subsystem of an autonomous vehicle is studies. It is based on a multi layer perceptron that uses TV images to estimate the position of the vehicle. A comparative study of the effects of output data representation and input data processing is presented and discussed
Fuzzy path tracking and position estimation of autonomous vehicles using differential GPS
Rodríguez Castaño, Ángel; Heredia Benot, José Guillermo; Ollero Baturone, Aníbal
2000-01-01
This paper presents an autonomous vehicle position estimation system based on GPS, that uses a fuzzy sensor fusion technique. A fuzzy path tracking algorithm is also proposed. Both systems have been implemented in the ROMEO-4R vehicle developed at the University of Seville.
An extended set-value observer for position estimation using single range measurements
DEFF Research Database (Denmark)
Marcal, Jose; Jouffroy, Jerome; Fossen, Thor I.
the observability of the system is briefly discussed and an extended set-valued observer is presented, with some discussion about the effect of the measurements noise on the final solution. This observer estimates bounds in the errors assuming that the exogenous signals are bounded, providing a safe region......The ability of estimating the position of an underwater vehicle from single range measurements is important in applications where one transducer marks an important geographical point, when there is a limitation in the size or cost of the vehicle, or when there is a failure in a system...... of transponders. The knowledge of the bearing of the vehicle and the range measurements from a single location can provide a solution which is sensitive to the trajectory that the vehicle is following, since there is no complete constraint on the position estimate with a single beacon. In this paper...
Granato, Gregory E.
2006-01-01
The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The KTRLine software was developed by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, for use in stochastic data modeling with local, regional, and national hydrologic data sets to develop planning-level estimates of potential effects of highway runoff on the quality of receiving waters. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. The Kendall-Theil robust line is a median line and, therefore, may underestimate total mass, volume, or loads unless the error component or a bias correction factor is incorporated into the estimate. Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. These statistics, however, may be used to formulate estimates of mass, volume, or total loads. The program is used to read a two- or three-column tab-delimited input file with variable names in the first row and
Hidden marker position estimation during sit-to-stand with walker.
Yoon, Sang Ho; Jun, Hong Gul; Dan, Byung Ju; Jo, Byeong Rim; Min, Byung Hoon
2012-01-01
Motion capture analysis of sit-to-stand task with assistive device is hard to achieve due to obstruction on reflective makers. Previously developed robotic system, Smart Mobile Walker, is used as an assistive device to perform motion capture analysis in sit-to-stand task. All lower limb markers except hip markers are invisible through whole session. The link-segment and regression method is applied to estimate the marker position during sit-to-stand. Applying a new method, the lost marker positions are restored and the biomechanical evaluation of the sit-to-stand movement with a Smart Mobile Walker could be carried out. The accuracy of the marker position estimation is verified with normal sit-to-stand data from more than 30 clinical trials. Moreover, further research on improving the link segment and regression method is addressed.
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.
Lima, José; Pereira, Ana I.; Costa, Paulo; Pinto, Andry; Costa, Pedro
2017-07-01
This paper describes an optimization procedure for a robot with 12 degrees of freedom avoiding the inverse kinematics problem, which is a hard task for this type of robot manipulator. This robot can be used to pick and place tasks in complex designs. Combining an accurate and fast direct kinematics model with optimization strategies, it is possible to achieve the joints angles for a desired end-effector position and orientation. The optimization methods stretched simulated annealing algorithm and genetic algorithm were used. The solutions found were validated using data originated by a real and by a simulated robot formed by 12 servomotors with a gripper.
Directory of Open Access Journals (Sweden)
M. Gianfreda
2012-01-01
Full Text Available We discuss conditions giving rise to stationary position-momentum correlations among quantum states in the Fock and coherent basis associated with the natural invariant for the one-dimensional time-dependent quadratic Hamiltonian operators such as the Kanai-Caldirola Hamiltonian. We also discuss some basic features such as quantum decoherence of the wave functions resulting from the corresponding quantum dynamics of these systems that exhibit no timedependence in their quantum correlations. In particular, steady statistical momentum averages are seen over well-defined time intervals in the evolution of a linear superposition of the basis states of modified exponentially damped mass systems.
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.; Kovács, B.
2014-01-01
Roč. 52, č. 6 (2014), s. 2957-2976 ISSN 0036-1429 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : streamline diffusion finite element method * solving convection-dominated elliptic problems * convergence is robust Subject RIV: BA - General Mathematics Impact factor: 1.788, year: 2014 http://epubs.siam.org/doi/abs/10.1137/130940268
Directory of Open Access Journals (Sweden)
Sadreyev Ruslan I
2004-08-01
Full Text Available Abstract Background Profile-based analysis of multiple sequence alignments (MSA allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1 MSA position and a set of predicted residue frequencies, and (2 between two MSA positions. These problems are important for (i evaluation and optimization of methods predicting residue occurrence at protein positions; (ii detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii detection of sites that determine functional or structural specificity in two related families. Results For problems (1 and (2, we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance. Conclusion The proposed computational method is of significant potential value for the analysis of protein families.
The First Result of Relative Positioning and Velocity Estimation Based on CAPS
Zhao, Jiaojiao; Ge, Jian; Wang, Liang; Wang, Ningbo; Zhou, Kai; Yuan, Hong
2018-01-01
The Chinese Area Positioning System (CAPS) is a new positioning system developed by the Chinese Academy of Sciences based on the communication satellites in geosynchronous orbit. The CAPS has been regarded as a pilot system to test the new technology for the design, construction and update of the BeiDou Navigation Satellite System (BDS). The system structure of CAPS, including the space, ground control station and user segments, is almost like the traditional Global Navigation Satellite Systems (GNSSs), but with the clock on the ground, the navigation signal in C waveband, and different principles of operation. The major difference is that the CAPS navigation signal is first generated at the ground control station, before being transmitted to the satellite in orbit and finally forwarded by the communication satellite transponder to the user. This design moves the clock from the satellite in orbit to the ground. The clock error can therefore be easily controlled and mitigated to improve the positioning accuracy. This paper will present the performance of CAPS-based relative positioning and velocity estimation as assessed in Beijing, China. The numerical results show that, (1) the accuracies of relative positioning, using only code measurements, are 1.25 and 1.8 m in the horizontal and vertical components, respectively; (2) meanwhile, they are about 2.83 and 3.15 cm in static mode and 6.31 and 10.78 cm in kinematic mode, respectively, when using the carrier-phase measurements with ambiguities fixed; and (3) the accuracy of the velocity estimation is about 0.04 and 0.11 m/s in static and kinematic modes, respectively. These results indicate the potential application of CAPS for high-precision positioning and velocity estimation and the availability of a new navigation mode based on communication satellites. PMID:29757204
Directory of Open Access Journals (Sweden)
Luis Payá
Full Text Available Along the past years, mobile robots have proliferated both in domestic and in industrial environments to solve some tasks such as cleaning, assistance, or material transportation. One of their advantages is the ability to operate in wide areas without the necessity of introducing changes into the existing infrastructure. Thanks to the sensors they may be equipped with and their processing systems, mobile robots constitute a versatile alternative to solve a wide range of applications. When designing the control system of a mobile robot so that it carries out a task autonomously in an unknown environment, it is expected to take decisions about its localization in the environment and about the trajectory that it has to follow in order to arrive to the target points. More concisely, the robot has to find a relatively good solution to two crucial problems: building a model of the environment, and estimating the position of the robot within this model. In this work, we propose a framework to solve these problems using only visual information. The mobile robot is equipped with a catadioptric vision sensor that provides omnidirectional images from the environment. First, the robot goes along the trajectories to include in the model and uses the visual information captured to build this model. After that, the robot is able to estimate its position and orientation with respect to the trajectory. Among the possible approaches to solve these problems, global appearance techniques are used in this work. They have emerged recently as a robust and efficient alternative compared to landmark extraction techniques. A global description method based on Radon Transform is used to design mapping and localization algorithms and a set of images captured by a mobile robot in a real environment, under realistic operation conditions, is used to test the performance of these algorithms.
Galante, Joseph M.; Van Eepoel, John; D'Souza, Chris; Patrick, Bryan
2016-01-01
The Raven ISS Hosted Payload will feature several pose measurement sensors on a pan/tilt gimbal which will be used to autonomously track resupply vehicles as they approach and depart the International Space Station. This paper discusses the derivation of a Relative Navigation Filter (RNF) to fuse measurements from the different pose measurement sensors to produce relative position and attitude estimates. The RNF relies on relative translation and orientation kinematics and careful pose sensor modeling to eliminate dependence on orbital position information and associated orbital dynamics models. The filter state is augmented with sensor biases to provide a mechanism for the filter to estimate and mitigate the offset between the measurements from different pose sensors
Initial rotor position estimation and sliding preventing for elevators with surface-mounted PMSMs
Liu, Feng; Shen, Anwen; Tang, Qipeng; Xu, Jinbang
2016-03-01
Improved methods of initial rotor position estimation and sliding prevention are presented in this paper for elevators with surface-mounted permanent magnet synchronous machines (SPMSMs). In contrast to most of the existing literature, in this paper, estimation errors caused by stator resistance and dead time are analysed in detail. The improved estimation method can reduce the errors greatly without dead-time compensations and knowledge of motor parameters. Besides, an observer-based feedforward compensation of load torque is introduced to elevator applications to prevent sliding during the starting process. Since the torque observer is widely used in other motor applications, we focus on the impact caused by the change in inertia. Finally, a series of experiments are performed on a testing system with two 13.4 kW SPMSMs and drivers to illustrate the effectiveness and improvement of the method.
Extended Kalman Filter Channel Estimation for Line-of-Sight Detection in WCDMA Mobile Positioning
Directory of Open Access Journals (Sweden)
Abdelmonaem Lakhzouri
2003-12-01
Full Text Available In mobile positioning, it is very important to estimate correctly the delay between the transmitter and the receiver. When the receiver is in line-of-sight (LOS condition with the transmitter, the computation of the mobile position in two dimensions becomes straightforward. In this paper, the problem of LOS detection in WCDMA for mobile positioning is considered, together with joint estimation of the delays and channel coefficients. These are very challenging topics in multipath fading channels because LOS component is not always present, and when it is present, it might be severely affected by interfering paths spaced at less than one chip distance (closely spaced paths. The extended Kalman filter (EKF is used to estimate jointly the delays and complex channel coefficients. The decision whether the LOS component is present or not is based on statistical tests to determine the distribution of the channel coefficient corresponding to the first path. The statistical test-based techniques are practical, simple, and of low computation complexity, which is suitable for WCDMA receivers. These techniques can provide an accurate decision whether LOS component is present or not.
Estimation Methods of the Point Spread Function Axial Position: A Comparative Computational Study
Directory of Open Access Journals (Sweden)
Javier Eduardo Diaz Zamboni
2017-01-01
Full Text Available The precise knowledge of the point spread function is central for any imaging system characterization. In fluorescence microscopy, point spread function (PSF determination has become a common and obligatory task for each new experimental device, mainly due to its strong dependence on acquisition conditions. During the last decade, algorithms have been developed for the precise calculation of the PSF, which fit model parameters that describe image formation on the microscope to experimental data. In order to contribute to this subject, a comparative study of three parameter estimation methods is reported, namely: I-divergence minimization (MIDIV, maximum likelihood (ML and non-linear least square (LSQR. They were applied to the estimation of the point source position on the optical axis, using a physical model. Methods’ performance was evaluated under different conditions and noise levels using synthetic images and considering success percentage, iteration number, computation time, accuracy and precision. The main results showed that the axial position estimation requires a high SNR to achieve an acceptable success level and higher still to be close to the estimation error lower bound. ML achieved a higher success percentage at lower SNR compared to MIDIV and LSQR with an intrinsic noise source. Only the ML and MIDIV methods achieved the error lower bound, but only with data belonging to the optical axis and high SNR. Extrinsic noise sources worsened the success percentage, but no difference was found between noise sources for the same method for all methods studied.
Methodology in robust and nonparametric statistics
Jurecková, Jana; Picek, Jan
2012-01-01
Introduction and SynopsisIntroductionSynopsisPreliminariesIntroductionInference in Linear ModelsRobustness ConceptsRobust and Minimax Estimation of LocationClippings from Probability and Asymptotic TheoryProblemsRobust Estimation of Location and RegressionIntroductionM-EstimatorsL-EstimatorsR-EstimatorsMinimum Distance and Pitman EstimatorsDifferentiable Statistical FunctionsProblemsAsymptotic Representations for L-Estimators
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.
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard
The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...
A study on the position estimation and recovery of a small-sized mobile robot
International Nuclear Information System (INIS)
Kim, Jae Hwan
1994-02-01
Position estimation capability of an autonomous mobile robot is important for a correct path tracking as well as for a complete navigation in a given environment. This paper describes the system with which the robot can estimate the current position and orientation without perceiving its any outer environments or processing vision image which requires much computational load. The designed system is new and simple. It detects wheel slippage, the main cause of navigational error, and makes it possible to recover from its strayed position. The designed system is composed of an encoder on a non-driven castor, an encoded compass disc as an absolute reference frame, two laser-diodes units with photosensors, and some pertinent data processing hardware and software. An encoded compass disc has two-track codes along its outer perimeter, which give the information on the amount of rotation as well as the direction of rotation in case when slip occurs, and gives the information on the exact turning angles to a mobile robot. The experimental results show that the designed system detects wheel slippage and recovers the robot from its strayed position very well
High-precision position estimation in PET using artificial neural networks
Energy Technology Data Exchange (ETDEWEB)
Mateo, F. [Digital Systems Design Group (DSD), Instituto de las Tecnologias de la Informacion y de las Comunicaciones Avanzadas (ITACA), Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain)], E-mail: fermaji@upvnet.upv.es; Aliaga, R.J.; Ferrando, N.; Martinez, J.D.; Herrero, V.; Lerche, Ch.W.; Colom, R.J.; Monzo, J.M.; Sebastia, A.; Gadea, R. [Digital Systems Design Group (DSD), Instituto de las Tecnologias de la Informacion y de las Comunicaciones Avanzadas (ITACA), Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain)
2009-06-01
Traditionally, the most popular technique to predict the impact position of gamma photons on a PET detector has been Anger's logic. However, it introduces nonlinearities that compress the light distribution, reducing the useful field of view and the spatial resolution, especially at the edges of the scintillator crystal. In this work, we make use of neural networks to address a bias-corrected position estimation from real stimulus obtained from a 2D PET system setup. The preprocessing and data acquisition were performed by separate custom boards, especially designed for this application. The results show that neural networks yield a more uniform field of view while improving the systematic error and the spatial resolution. Therefore, they stand as a better performing and readily available alternative to classic positioning methods.
High-precision position estimation in PET using artificial neural networks
International Nuclear Information System (INIS)
Mateo, F.; Aliaga, R.J.; Ferrando, N.; Martinez, J.D.; Herrero, V.; Lerche, Ch.W.; Colom, R.J.; Monzo, J.M.; Sebastia, A.; Gadea, R.
2009-01-01
Traditionally, the most popular technique to predict the impact position of gamma photons on a PET detector has been Anger's logic. However, it introduces nonlinearities that compress the light distribution, reducing the useful field of view and the spatial resolution, especially at the edges of the scintillator crystal. In this work, we make use of neural networks to address a bias-corrected position estimation from real stimulus obtained from a 2D PET system setup. The preprocessing and data acquisition were performed by separate custom boards, especially designed for this application. The results show that neural networks yield a more uniform field of view while improving the systematic error and the spatial resolution. Therefore, they stand as a better performing and readily available alternative to classic positioning methods.
Performance estimation of control rod position indicator due to aging of magnet
International Nuclear Information System (INIS)
Yu, Je Yong; Kim, Ji Ho; Huh, Hyung; Choi, Myoung Hwan; Sohn, Dong Seong
2009-01-01
The Control Element Drive Mechanism (CEDM) for the integral reactor is designed to raise and lower the control rod in steps of 2mm in order to satisfy the design features of the integral reactor which are the soluble boron free operation and the use of a nuclear heating for the reactor start-up. The actual position of the control rod could be achieved to sense the magnet connected to the control rod by the position indicator around the upper pressure housing of CEDM. It is sufficient that the actual position information of control rod at 20mm interval from the position indicator is used for the core safety analysis. As the magnet moves upward along the position indicator assembly from the bottom to the top in the upper pressure housing, the output voltage increases linearly step-wise at 0.2VDC increments. Between every step there are transient areas which occur by a contact closing of three reed switches which is the 2-3-2 contact closing sequence. In this paper the output voltage signal corresponding to the position of control rod was estimated on the 2-1-2 contact closing sequence due to the aging of the magnet.
International Nuclear Information System (INIS)
Silva, E C C M; Vliet, K J van
2006-01-01
The atomic force microscope is used increasingly to investigate the mechanical properties of materials via sample displacement under an applied force. However, both the extent of forces attainable and the accuracy of those forces measurements are significantly limited by the optical lever configuration that is commonly used to infer nanoscale deflection of the cantilever. We present a robust and general approach to characterize and compensate for the nonlinearity of the position-sensitive optical device via data processing, requiring no modification of existing instrumentation. We demonstrate that application of this approach reduced the maximum systematic error on the gradient of a force-displacement response from 50% to 5%, and doubled the calibrated force application range. Finally, we outline an experimental protocol that optimizes the use of the quasi-linear range of the most commonly available optical feedback configurations and also accounts for the residual systematic error, allowing the user to benefit from the full detection range of these indirect force sensors
Directory of Open Access Journals (Sweden)
O. Jakubov
2013-09-01
Full Text Available Common techniques for position-velocity-time estimation in satellite navigation, iterative least squares and the extended Kalman filter, involve matrix operations. The matrix inversion and inclusion of a matrix library pose requirements on a computational power and operating platform of the navigation processor. In this paper, we introduce a novel distributed algorithm suitable for implementation in simple parallel processing units each for a tracked satellite. Such a unit performs only scalar sum, subtraction, multiplication, and division. The algorithm can be efficiently implemented in hardware logic. Given the fast position-velocity-time estimator, frequent estimates can foster dynamic performance of a vector tracking receiver. The algorithm has been designed from a factor graph representing the extended Kalman filter by splitting vector nodes into scalar ones resulting in a cyclic graph with few iterations needed. Monte Carlo simulations have been conducted to investigate convergence and accuracy. Simulation case studies for a vector tracking architecture and experimental measurements with a real-time software receiver developed at CTU in Prague were conducted. The algorithm offers compromises in stability, accuracy, and complexity depending on the number of iterations. In scenarios with a large number of tracked satellites, it can outperform the traditional methods at low complexity.
DEFF Research Database (Denmark)
Pertl, Michael; Douglass, Philip James; Heussen, Kai
2018-01-01
network approach for voltage estimation in active distribution grids by means of measured data from two feeders of a real low voltage distribution grid. The approach enables a real-time voltage estimation at locations in the distribution grid, where otherwise only non-real-time measurements are available......The installation of measurements in distribution grids enables the development of data driven methods for the power system. However, these methods have to be validated in order to understand the limitations and capabilities for their use. This paper presents a systematic validation of a neural...
A Study on the Estimation of the Scale Factor for Precise Point Positioning
Erdogan, Bahattin; Kayacik, Orhan
2017-04-01
Precise Point Positioning (PPP) technique is one of the most important subject in Geomatic Engineering. PPP technique needs only one GNSS receiver and users have preferred it instead of traditional relative positioning technique for several applications. Scientific software has been used for PPP solutions and the software may underestimate the formal errors of the estimated coordinates. The formal errors have major effects on statistical interpretation. Variance-Covariance (VCV) matrix derived from GNSS processing software plays important role for deformation analysis and scientists sometimes need to scale VCV matrix. In this study, 10 continuously operating reference stations have been considered for 11 days dated 2014. All points have been analyzed by Gipsy-OASIS v6.4 scientific software. The solutions were derived for different session durations as 2, 4, 6, 8, 12 and 24 hours to obtain repeatability of the coordinates and analyses were carried out in order to estimate scale factor for Gipsy-OASIS v6.4 PPP results. According to the first results scale factors slightly increase depending on the raises in respect of session duration. Keywords: Precise Point Positioning, Gipsy-OASIS v6.4, Variance-Covariance Matrix, Scale Factor
J Olive, David
2017-01-01
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...
International Nuclear Information System (INIS)
Morio, Jerome
2011-01-01
Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.
Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J
2017-10-10
Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.
Directory of Open Access Journals (Sweden)
Eusebio Eduardo Hernández Martinez
2013-01-01
Full Text Available In robotics, solving the direct kinematics problem (DKP for parallel robots is very often more difficult and time consuming than for their serial counterparts. The problem is stated as follows: given the joint variables, the Cartesian variables should be computed, namely the pose of the mobile platform. Most of the time, the DKP requires solving a non-linear system of equations. In addition, given that the system could be non-convex, Newton or Quasi-Newton (Dogleg based solvers get trapped on local minima. The capacity of such kinds of solvers to find an adequate solution strongly depends on the starting point. A well-known problem is the selection of such a starting point, which requires a priori information about the neighbouring region of the solution. In order to circumvent this issue, this article proposes an efficient method to select and to generate the starting point based on probabilistic learning. Experiments and discussion are presented to show the method performance. The method successfully avoids getting trapped on local minima without the need for human intervention, which increases its robustness when compared with a single Dogleg approach. This proposal can be extended to other structures, to any non-linear system of equations, and of course, to non-linear optimization problems.
May, Peter; Garrido, Melissa M; Cassel, J Brian; Morrison, R Sean; Normand, Charles
2016-10-01
To evaluate the sensitivity of treatment effect estimates when length of stay (LOS) is used to control for unobserved heterogeneity when estimating treatment effect on cost of hospital admission with observational data. We used data from a prospective cohort study on the impact of palliative care consultation teams (PCCTs) on direct cost of hospital care. Adult patients with an advanced cancer diagnosis admitted to five large medical and cancer centers in the United States between 2007 and 2011 were eligible for this study. Costs were modeled using generalized linear models with a gamma distribution and a log link. We compared variability in estimates of PCCT impact on hospitalization costs when LOS was used as a covariate, as a sample parameter, and as an outcome denominator. We used propensity scores to account for patient characteristics associated with both PCCT use and total direct hospitalization costs. We analyzed data from hospital cost databases, medical records, and questionnaires. Our propensity score weighted sample included 969 patients who were discharged alive. In analyses of hospitalization costs, treatment effect estimates are highly sensitive to methods that control for LOS, complicating interpretation. Both the magnitude and significance of results varied widely with the method of controlling for LOS. When we incorporated intervention timing into our analyses, results were robust to LOS-controls. Treatment effect estimates using LOS-controls are not only suboptimal in terms of reliability (given concerns over endogeneity and bias) and usefulness (given the need to validate the cost-effectiveness of an intervention using overall resource use for a sample defined at baseline) but also in terms of robustness (results depend on the approach taken, and there is little evidence to guide this choice). To derive results that minimize endogeneity concerns and maximize external validity, investigators should match and analyze treatment and comparison arms
Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira
2015-12-18
An approach that is commonly used for calculating the retention time of a compound in GC departs from the thermodynamic properties ΔH, ΔS and ΔCp of phase change (from mobile to stationary). Such properties can be estimated by using experimental retention time data, which results in a non-linear regression problem for non-isothermal temperature programs. As shown in this work, the surface of the objective function (approximation error criterion) on the basis of thermodynamic parameters can be divided into three clearly defined regions, and solely in one of them there is a possibility for the global optimum to be found. The main contribution of this study was the development of an algorithm that distinguishes the different regions of the error surface and its use in the robust initialization of the estimation of parameters ΔH, ΔS and ΔCp. Copyright © 2015 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Madsen Per
2007-07-01
Full Text Available Abstract In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.
Sullivan, Benjamin W; Smith, W Kolby; Townsend, Alan R; Nasto, Megan K; Reed, Sasha C; Chazdon, Robin L; Cleveland, Cory C
2014-06-03
Biological nitrogen fixation (BNF) is the largest natural source of exogenous nitrogen (N) to unmanaged ecosystems and also the primary baseline against which anthropogenic changes to the N cycle are measured. Rates of BNF in tropical rainforest are thought to be among the highest on Earth, but they are notoriously difficult to quantify and are based on little empirical data. We adapted a sampling strategy from community ecology to generate spatial estimates of symbiotic and free-living BNF in secondary and primary forest sites that span a typical range of tropical forest legume abundance. Although total BNF was higher in secondary than primary forest, overall rates were roughly five times lower than previous estimates for the tropical forest biome. We found strong correlations between symbiotic BNF and legume abundance, but we also show that spatially free-living BNF often exceeds symbiotic inputs. Our results suggest that BNF in tropical forest has been overestimated, and our data are consistent with a recent top-down estimate of global BNF that implied but did not measure low tropical BNF rates. Finally, comparing tropical BNF within the historical area of tropical rainforest with current anthropogenic N inputs indicates that humans have already at least doubled reactive N inputs to the tropical forest biome, a far greater change than previously thought. Because N inputs are increasing faster in the tropics than anywhere on Earth, both the proportion and the effects of human N enrichment are likely to grow in the future.
Sullivan, Benjamin W.; Smith, William K.; Townsend, Alan R.; Nasto, Megan K.; Reed, Sasha C.; Chazdon, Robin L.; Cleveland, Cory C.
2014-01-01
Biological nitrogen fixation (BNF) is the largest natural source of exogenous nitrogen (N) to unmanaged ecosystems and also the primary baseline against which anthropogenic changes to the N cycle are measured. Rates of BNF in tropical rainforest are thought to be among the highest on Earth, but they are notoriously difficult to quantify and are based on little empirical data. We adapted a sampling strategy from community ecology to generate spatial estimates of symbiotic and free-living BNF in secondary and primary forest sites that span a typical range of tropical forest legume abundance. Although total BNF was higher in secondary than primary forest, overall rates were roughly five times lower than previous estimates for the tropical forest biome. We found strong correlations between symbiotic BNF and legume abundance, but we also show that spatially free-living BNF often exceeds symbiotic inputs. Our results suggest that BNF in tropical forest has been overestimated, and our data are consistent with a recent top-down estimate of global BNF that implied but did not measure low tropical BNF rates. Finally, comparing tropical BNF within the historical area of tropical rainforest with current anthropogenic N inputs indicates that humans have already at least doubled reactive N inputs to the tropical forest biome, a far greater change than previously thought. Because N inputs are increasing faster in the tropics than anywhere on Earth, both the proportion and the effects of human N enrichment are likely to grow in the future.
LENUS (Irish Health Repository)
Dooley, Ian
2012-02-01
PURPOSE: To evaluate the validity of a keratometry (K)-independent method of estimating effective lens position (ELP) before phacoemulsification cataract surgery. SETTING: Institute of Eye Surgery, Whitfield Clinic, Waterford, Ireland. DESIGN: Evaluation of diagnostic test or technology. METHODS: The anterior chamber diameter and corneal height in eyes scheduled for cataract surgery were measured with a rotating Scheimpflug camera. Corneal height and anterior chamber diameter were used to estimate the ELP in a K-independent method (using the SRK\\/T [ELP(rs)] and Holladay 1 [ELP(rh)] formulas). RESULTS: The mean ELP was calculated using the traditional (mean ELP(s) 5.59 mm +\\/- 0.52 mm [SD]; mean ELP(h) 5.63 +\\/- 0.42 mm) and K-independent (mean ELP(rs) 5.55 +\\/- 0.42 mm; mean ELP(rh) +\\/- SD 5.60 +\\/- 0.36 mm) methods. Agreement between ELP(s) and ELP(rs) and between ELP(h) and ELP(rh) were represented by Bland-Altman plots, with mean differences (+\\/- 1.96 SD) of 0.06 +\\/- 0.65 mm (range -0.59 to +0.71 mm; P=.08) in association with ELP(rs) and -0.04 +\\/- 0.39 mm (range -0.43 to +0.35 mm; P=.08) in association with ELP(rh). The mean absolute error for ELP(s) versus ELP(rs) estimation and for ELP(h) versus ELP(rh) estimation was 0.242 +\\/- 0.222 mm (range 0.001 to 1.272 mm) and 0.152 +\\/- 0.137 mm (range 0.001 to 0.814 mm), respectively. CONCLUSION: This study confirms that the K-independent ELP estimation method is comparable to traditional K-dependent methods and may be useful in post-refractive surgery patients.
DEFF Research Database (Denmark)
Wu, Xuan; Huang, Shoudao; Liu, Xiao
2017-01-01
This paper presents a new initial rotor position estimation method for an interior permanent magnet synchronous motor. The proposed method includes two steps: firstly, the minimum voltage vectors are injected to estimate the rotor position. Secondly, in order to identify the magnet polarity...
A Simple Interface for 3D Position Estimation of a Mobile Robot with Single Camera.
Chao, Chun-Tang; Chung, Ming-Hsuan; Chiou, Juing-Shian; Wang, Chi-Jo
2016-03-25
In recent years, there has been an increase in the number of mobile robots controlled by a smart phone or tablet. This paper proposes a visual control interface for a mobile robot with a single camera to easily control the robot actions and estimate the 3D position of a target. In this proposal, the mobile robot employed an Arduino Yun as the core processor and was remote-controlled by a tablet with an Android operating system. In addition, the robot was fitted with a three-axis robotic arm for grasping. Both the real-time control signal and video transmission are transmitted via Wi-Fi. We show that with a properly calibrated camera and the proposed prototype procedures, the users can click on a desired position or object on the touchscreen and estimate its 3D coordinates in the real world by simple analytic geometry instead of a complicated algorithm. The results of the measurement verification demonstrates that this approach has great potential for mobile robots.
Method of detecting fuel failure in FBR type reactor and method of estimating fuel failure position
International Nuclear Information System (INIS)
Sonoda, Yukio; Tamaoki, Tetsuo
1989-01-01
Noise components in a normal state contained in detection signals from delayed neutron monitors disposed to a coolant inlet, etc. of an intermediate heat exchanger are forecast by self-recurring model and eliminated, and resultant detection signals are monitored thereby detecting fuel failure high sensitivity. Subsequently, the reactor is controlled to a low power operation state and a new self-recurring model to the detection signals from the delayed neutron monitors are prepared. Then, noise components in this state are removed and control rods near the delayed neutron monitors are extracted in a short stroke successively to examine the change of response of the delayed neutron monitors. Accordingly, the failed position for each of the fuels can be estimated at a level of one fuel assembly or a level of several assemblies containing the above-mentioned fuel assembly. Since the fuel failure can be detected at a high sensitivity and the position can be estimated, diffusion of abnormality can be prevented and plant shutdown for fuel exchange can be minimized. (I.S.)
A Simple Interface for 3D Position Estimation of a Mobile Robot with Single Camera
Directory of Open Access Journals (Sweden)
Chun-Tang Chao
2016-03-01
Full Text Available In recent years, there has been an increase in the number of mobile robots controlled by a smart phone or tablet. This paper proposes a visual control interface for a mobile robot with a single camera to easily control the robot actions and estimate the 3D position of a target. In this proposal, the mobile robot employed an Arduino Yun as the core processor and was remote-controlled by a tablet with an Android operating system. In addition, the robot was fitted with a three-axis robotic arm for grasping. Both the real-time control signal and video transmission are transmitted via Wi-Fi. We show that with a properly calibrated camera and the proposed prototype procedures, the users can click on a desired position or object on the touchscreen and estimate its 3D coordinates in the real world by simple analytic geometry instead of a complicated algorithm. The results of the measurement verification demonstrates that this approach has great potential for mobile robots.
Boada, Beatriz L.; Boada, Maria Jesus L.; Vargas-Melendez, Leandro; Diaz, Vicente
2018-01-01
Nowadays, one of the main objectives in road transport is to decrease the number of accident victims. Rollover accidents caused nearly 33% of all deaths from passenger vehicle crashes. Roll Stability Control (RSC) systems prevent vehicles from untripped rollover accidents. The lateral load transfer is the main parameter which is taken into account in the RSC systems. This parameter is related to the roll angle, which can be directly measured from a dual-antenna GPS. Nevertheless, this is a costly technique. For this reason, roll angle has to be estimated. In this paper, a novel observer based on H∞ filtering in combination with a neural network (NN) for the vehicle roll angle estimation is proposed. The design of this observer is based on four main criteria: to use a simplified vehicle model, to use signals of sensors which are installed onboard in current vehicles, to consider the inaccuracy in the system model and to attenuate the effect of the external disturbances. Experimental results show the effectiveness of the proposed observer.
Plate Motion and Crustal Deformation Estimated with Geodetic Data from the Global Positioning System
Argus, Donald F.; Heflin, Michael B.
1995-01-01
We use geodetic data taken over four years with the Global Positioning System (GPS) to estimate: (1) motion between six major plates and (2) motion relative to these plates of ten sites in plate boundary zones. The degree of consistency between geodetic velocities and rigid plates requires the (one-dimensional) standard errors in horizontal velocities to be approx. 2 mm/yr. Each of the 15 angular velocities describing motion between plate pairs that we estimate with GPS differs insignificantly from the corresponding angular velocity in global plate motion model NUVEL-1A, which averages motion over the past 3 m.y. The motion of the Pacific plate relative to both the Eurasian and North American plates is observed to be faster than predicted by NUVEL-1A, supporting the inference from Very Long B ase- line Interferometry (VLBI) that motion of the Pacific plate has speed up over the past few m.y. The Eurasia-North America pole of rotation is estimated to be north of NUVEL-1A, consistent with the independent hypothesis that the pole has recently migrated northward across northeast Asia to near the Lena River delta. Victoria, which lies above the main thrust at the Cascadia subduction zone, moves relative to the interior of the overriding plate at 30% of the velocity of the subducting plate, reinforcing the conclusion that the thrust there is locked beneath the continental shelf and slope.
Empirical methods for controlling false positives and estimating confidence in ChIP-Seq peaks
Directory of Open Access Journals (Sweden)
Courdy Samir J
2008-12-01
Full Text Available Abstract Background High throughput signature sequencing holds many promises, one of which is the ready identification of in vivo transcription factor binding sites, histone modifications, changes in chromatin structure and patterns of DNA methylation across entire genomes. In these experiments, chromatin immunoprecipitation is used to enrich for particular DNA sequences of interest and signature sequencing is used to map the regions to the genome (ChIP-Seq. Elucidation of these sites of DNA-protein binding/modification are proving instrumental in reconstructing networks of gene regulation and chromatin remodelling that direct development, response to cellular perturbation, and neoplastic transformation. Results Here we present a package of algorithms and software that makes use of control input data to reduce false positives and estimate confidence in ChIP-Seq peaks. Several different methods were compared using two simulated spike-in datasets. Use of control input data and a normalized difference score were found to more than double the recovery of ChIP-Seq peaks at a 5% false discovery rate (FDR. Moreover, both a binomial p-value/q-value and an empirical FDR were found to predict the true FDR within 2–3 fold and are more reliable estimators of confidence than a global Poisson p-value. These methods were then used to reanalyze Johnson et al.'s neuron-restrictive silencer factor (NRSF ChIP-Seq data without relying on extensive qPCR validated NRSF sites and the presence of NRSF binding motifs for setting thresholds. Conclusion The methods developed and tested here show considerable promise for reducing false positives and estimating confidence in ChIP-Seq data without any prior knowledge of the chIP target. They are part of a larger open source package freely available from http://useq.sourceforge.net/.
Directory of Open Access Journals (Sweden)
Richard Moore
2015-12-01
Full Text Available The p53 tumor suppressor protein plays a critical role in cellular stress and cancer prevention. A number of post-transcriptional regulators, termed microRNAs, are closely connected with the p53-mediated cellular networks. While the molecular interactions among p53 and microRNAs have emerged, a systems-level understanding of the regulatory mechanism and the role of microRNAs-forming feedback loops with the p53 core remains elusive. Here we have identified from literature that there exist three classes of microRNA-mediated feedback loops revolving around p53, all with the nature of positive feedback coincidentally. To explore the relationship between the cellular performance of p53 with the microRNA feedback pathways, we developed a mathematical model of the core p53-MDM2 module coupled with three microRNA-mediated positive feedback loops involving miR-192, miR-34a, and miR-29a. Simulations and bifurcation analysis in relationship to extrinsic noise reproduce the oscillatory behavior of p53 under DNA damage in single cells, and notably show that specific microRNA abrogation can disrupt the wild-type cellular phenotype when the ubiquitous cell-to-cell variability is taken into account. To assess these in silico results we conducted microRNA-perturbation experiments in MCF7 breast cancer cells. Time-lapse microscopy of cell-population behavior in response to DNA double-strand breaks, together with image classification of single-cell phenotypes across a population, confirmed that the cellular p53 oscillations are compromised after miR-192 perturbations, matching well with the model predictions. Our study via modeling in combination with quantitative experiments provides new evidence on the role of microRNA-mediated positive feedback loops in conferring robustness to the system performance of stress-induced response of p53.
Multiview face detection based on position estimation over multicamera surveillance system
Huang, Ching-chun; Chou, Jay; Shiu, Jia-Hou; Wang, Sheng-Jyh
2012-02-01
In this paper, we propose a multi-view face detection system that locates head positions and indicates the direction of each face in 3-D space over a multi-camera surveillance system. To locate 3-D head positions, conventional methods relied on face detection in 2-D images and projected the face regions back to 3-D space for correspondence. However, the inevitable false face detection and rejection usually degrades the system performance. Instead, our system searches for the heads and face directions over the 3-D space using a sliding cube. Each searched 3-D cube is projected onto the 2-D camera views to determine the existence and direction of human faces. Moreover, a pre-process to estimate the locations of candidate targets is illustrated to speed-up the searching process over the 3-D space. In summary, our proposed method can efficiently fuse multi-camera information and suppress the ambiguity caused by detection errors. Our evaluation shows that the proposed approach can efficiently indicate the head position and face direction on real video sequences even under serious occlusion.
Directory of Open Access Journals (Sweden)
Orlando N. Grillo
2011-03-01
Full Text Available Missing data is a common problem in paleontology. It makes it difficult to reconstruct extinct taxa accurately and restrains the inclusion of some taxa on comparative and biomechanical studies. Particularly, estimating the position of vertebrae on incomplete series is often non-empirical and does not allow precise estimation of missing parts. In this work we present a method for calculating the position of preserved middle sequences of caudal vertebrae in the saurischian dinosaur Staurikosaurus pricei, based on the length and height of preserved anterior and posterior caudal vertebral centra. Regression equations were used to estimate these dimensions for middle vertebrae and, consequently, to assess the position of the preserved middle sequences. It also allowed estimating these dimensions for non-preserved vertebrae. Results indicate that the preserved caudal vertebrae of Staurikosaurus may correspond to positions 1-3, 5, 7, 14-19/15-20, 24-25/25-26, and 29-47, and that at least 25 vertebrae had transverse processes. Total length of the tail was estimated in 134 cm and total body length was 220-225 cm.Dados lacunares são um problema comum na paleontologia. Eles dificultam a reconstrução acurada de táxons extintos e limitam a inclusão de alguns táxons em estudos comparativose biomecânicos. Particularmente, estimar a posição de vértebras em séries incompletas tem sido feito com base em métodos não empíricos que não permitem estimar corretamente as partes ausentes. Neste trabalho apresentamos uma metodologia que permite estimar a posição de sequências médias preservadas de vértebras caudais no dinossauro saurísquio Staurikosaurus pricei, com base no comprimento e altura dos centros das vértebras anteriores e posteriores preservadas. Equações de regressão foram usadas para estimar essas dimensões para as vértebras médias e, consequentemente, para posicionar as sequências médias preservadas e para estimar o tamanho das
Guarnieri, A.; Milan, N.; Pirotti, F.; Vettore, A.
2011-12-01
In the automotive sector, especially in these last decade, a growing number of investigations have taken into account electronic systems to check and correct the behavior of drivers, increasing road safety. The possibility to identify with high accuracy the vehicle position in a mapping reference frame for driving directions and best-route analysis is also another topic which attracts lot of interest from the research and development sector. To reach the objective of accurate vehicle positioning and integrate response events, it is necessary to estimate time by time the position, orientation and velocity of the system. To this aim low cost GPS and MEMS (sensors can be used. In comparison to a four wheel vehicle, the dynamics of a two wheel vehicle (e.g. a scooter) feature a higher level of complexity. Indeed more degrees of freedom must be taken into account to describe the motion of the latter. For example a scooter can twist sideways, thus generating a roll angle. A slight pitch angle has to be considered as well, since wheel suspensions have a higher degree of motion with respect to four wheel vehicles. In this paper we present a method for the accurate reconstruction of the trajectory of a motorcycle ("Vespa" scooter), which can be used as alternative to the "classical" approach based on the integration of GPS and INS sensors. Position and orientation of the scooter are derived from MEMS data and images acquired by on-board digital camera. A Bayesian filter provides the means for integrating the data from MEMS-based orientation sensor and the GPS receiver.
Robust Self Tuning Controllers
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
1985-01-01
The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay.......The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...
Influence Function and Robust Variant of Kernel Canonical Correlation Analysis
Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping
2017-01-01
Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. In addition, while the influence function (IF) of an estimator can characterize its robustness, asymptotic ...
International Nuclear Information System (INIS)
Lee, Jung Uk; Sun, Ju Young; Won, Mooncheol
2013-01-01
In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner
Energy Technology Data Exchange (ETDEWEB)
Lee, Jung Uk [Samsung Electroics, Suwon (Korea, Republic of); Sun, Ju Young; Won, Mooncheol [Chungnam Nat' l Univ., Daejeon (Korea, Republic of)
2013-12-15
In this paper, we propose a real-time algorithm for estimating the relative position of a person with respect to a robot (camera) using a monocular camera. The algorithm detects the head and shoulder regions of a person using HOG (Histogram of Oriented Gradient) feature vectors and an SVM (Support Vector Machine) classifier. The size and location of the detected area are used for calculating the relative distance and angle between the person and the camera on a robot. To increase the speed of the algorithm, we use a GPU and NVIDIA's CUDA library; the resulting algorithm speed is ∼ 15 Hz. The accuracy of the algorithm is compared with the output of a SICK laser scanner.
Hajdu, Gergely; Dékány, István; Catelan, Márcio; Grebel, Eva K.; Jurcsik, Johanna
2018-04-01
RR Lyrae variables are widely used tracers of Galactic halo structure and kinematics, but they can also serve to constrain the distribution of the old stellar population in the Galactic bulge. With the aim of improving their near-infrared photometric characterization, we investigate their near-infrared light curves, as well as the empirical relationships between their light curve and metallicities using machine learning methods. We introduce a new, robust method for the estimation of the light-curve shapes, hence the average magnitudes of RR Lyrae variables in the K S band, by utilizing the first few principal components (PCs) as basis vectors, obtained from the PC analysis of a training set of light curves. Furthermore, we use the amplitudes of these PCs to predict the light-curve shape of each star in the J-band, allowing us to precisely determine their average magnitudes (hence colors), even in cases where only one J measurement is available. Finally, we demonstrate that the K S-band light-curve parameters of RR Lyrae variables, together with the period, allow the estimation of the metallicity of individual stars with an accuracy of ∼0.2–0.25 dex, providing valuable chemical information about old stellar populations bearing RR Lyrae variables. The methods presented here can be straightforwardly adopted for other classes of variable stars, bands, or for the estimation of other physical quantities.
Energy Technology Data Exchange (ETDEWEB)
Risser, L.; Vincent, T.; Ciuciu, Ph. [NeuroSpin CEA, F-91191 Gif sur Yvette (France); Risser, L.; Vincent, T. [Laboratoire de Neuroimagerie Assistee par Ordinateur (LNAO) CEA - DSV/I2BM/NEUROSPIN (France); Risser, L. [Institut de mecanique des fluides de Toulouse (IMFT), CNRS: UMR5502 - Universite Paul Sabatier - Toulouse III - Institut National Polytechnique de Toulouse - INPT (France); Idier, J. [Institut de Recherche en Communications et en Cybernetique de Nantes (IRCCyN) CNRS - UMR6597 - Universite de Nantes - ecole Centrale de Nantes - Ecole des Mines de Nantes - Ecole Polytechnique de l' Universite de Nantes (France)
2009-07-01
In this paper, we present a first numerical scheme to estimate Partition Functions (PF) of 3D Ising fields. Our strategy is applied to the context of the joint detection-estimation of brain activity from functional Magnetic Resonance Imaging (fMRI) data, where the goal is to automatically recover activated regions and estimate region-dependent, hemodynamic filters. For any region, a specific binary Markov random field may embody spatial correlation over the hidden states of the voxels by modeling whether they are activated or not. To make this spatial regularization fully adaptive, our approach is first based upon it, classical path-sampling method to approximate a small subset of reference PFs corresponding to pre-specified regions. Then, file proposed extrapolation method allows its to approximate the PFs associated with the Ising fields defined over the remaining brain regions. In comparison with preexisting approaches, our method is robust; to topological inhomogeneities in the definition of the reference regions. As a result, it strongly alleviates the computational burden and makes spatially adaptive regularization of whole brain fMRI datasets feasible. (authors)
Position estimation and driving of an autonomous vehicle by monocular vision
Hanan, Jay C.; Kayathi, Pavan; Hughlett, Casey L.
2007-04-01
Automatic adaptive tracking in real-time for target recognition provided autonomous control of a scale model electric truck. The two-wheel drive truck was modified as an autonomous rover test-bed for vision based guidance and navigation. Methods were implemented to monitor tracking error and ensure a safe, accurate arrival at the intended science target. Some methods are situation independent relying only on the confidence error of the target recognition algorithm. Other methods take advantage of the scenario of combined motion and tracking to filter out anomalies. In either case, only a single calibrated camera was needed for position estimation. Results from real-time autonomous driving tests on the JPL simulated Mars yard are presented. Recognition error was often situation dependent. For the rover case, the background was in motion and may be characterized to provide visual cues on rover travel such as rate, pitch, roll, and distance to objects of interest or hazards. Objects in the scene may be used as landmarks, or waypoints, for such estimations. As objects are approached, their scale increases and their orientation may change. In addition, particularly on rough terrain, these orientation and scale changes may be unpredictable. Feature extraction combined with the neural network algorithm was successful in providing visual odometry in the simulated Mars environment.
Target Centroid Position Estimation of Phase-Path Volume Kalman Filtering
Directory of Open Access Journals (Sweden)
Fengjun Hu
2016-01-01
Full Text Available For the problem of easily losing track target when obstacles appear in intelligent robot target tracking, this paper proposes a target tracking algorithm integrating reduced dimension optimal Kalman filtering algorithm based on phase-path volume integral with Camshift algorithm. After analyzing the defects of Camshift algorithm, compare the performance with the SIFT algorithm and Mean Shift algorithm, and Kalman filtering algorithm is used for fusion optimization aiming at the defects. Then aiming at the increasing amount of calculation in integrated algorithm, reduce dimension with the phase-path volume integral instead of the Gaussian integral in Kalman algorithm and reduce the number of sampling points in the filtering process without influencing the operational precision of the original algorithm. Finally set the target centroid position from the Camshift algorithm iteration as the observation value of the improved Kalman filtering algorithm to fix predictive value; thus to make optimal estimation of target centroid position and keep the target tracking so that the robot can understand the environmental scene and react in time correctly according to the changes. The experiments show that the improved algorithm proposed in this paper shows good performance in target tracking with obstructions and reduces the computational complexity of the algorithm through the dimension reduction.
Energy Technology Data Exchange (ETDEWEB)
Lee, Taewoong; Lee, Hyounggun; Kim, Younghak; Lee, Wonho [Korea University, Seoul (Korea, Republic of)
2017-07-15
The performance of a Compton imager using a single three-dimensional position-sensitive LYSO scintillator detector was estimated using a Monte Carlo simulation. The Compton imager consisted of a single LYSO scintillator with a pixelized structure. The size of the scintillator and each pixel were 1.3 × 1.3 × 1.3 cm{sup 3} and 0.3 × 0.3 × 0.3 cm{sup 3}, respectively. The order of γ-ray interactions was determined based on the deposited energies in each detector. After the determination of the interaction sequence, various types of reconstruction algorithms such as simple back-projection, filtered back-projection, and list-mode maximum-likelihood expectation maximization (LM-MLEM) were applied and compared with each other in terms of their angular resolution and signal-tonoise ratio (SNR) for several γ-ray energies. The LM-MLEM reconstruction algorithm exhibited the best performance for Compton imaging in maintaining high angular resolution and SNR. The two sources of {sup 137}Cs (662 keV) could be distinguishable if they were more than 17 ◦ apart. The reconstructed Compton images showed the precise position and distribution of various radiation isotopes, which demonstrated the feasibility of the monitoring of nuclear materials in homeland security and radioactive waste management applications.
Multi-User Identification-Based Eye-Tracking Algorithm Using Position Estimation
Directory of Open Access Journals (Sweden)
Suk-Ju Kang
2016-12-01
Full Text Available This paper proposes a new multi-user eye-tracking algorithm using position estimation. Conventional eye-tracking algorithms are typically suitable only for a single user, and thereby cannot be used for a multi-user system. Even though they can be used to track the eyes of multiple users, their detection accuracy is low and they cannot identify multiple users individually. The proposed algorithm solves these problems and enhances the detection accuracy. Specifically, the proposed algorithm adopts a classifier to detect faces for the red, green, and blue (RGB and depth images. Then, it calculates features based on the histogram of the oriented gradient for the detected facial region to identify multiple users, and selects the template that best matches the users from a pre-determined face database. Finally, the proposed algorithm extracts the final eye positions based on anatomical proportions. Simulation results show that the proposed algorithm improved the average F1 score by up to 0.490, compared with benchmark algorithms.
Stochastic models in the DORIS position time series: estimates for IDS contribution to ITRF2014
Klos, Anna; Bogusz, Janusz; Moreaux, Guilhem
2017-11-01
This paper focuses on the investigation of the deterministic and stochastic parts of the Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) weekly time series aligned to the newest release of ITRF2014. A set of 90 stations was divided into three groups depending on when the data were collected at an individual station. To reliably describe the DORIS time series, we employed a mathematical model that included the long-term nonlinear signal, linear trend, seasonal oscillations and a stochastic part, all being estimated with maximum likelihood estimation. We proved that the values of the parameters delivered for DORIS data are strictly correlated with the time span of the observations. The quality of the most recent data has significantly improved. Not only did the seasonal amplitudes decrease over the years, but also, and most importantly, the noise level and its type changed significantly. Among several tested models, the power-law process may be chosen as the preferred one for most of the DORIS data. Moreover, the preferred noise model has changed through the years from an autoregressive process to pure power-law noise with few stations characterised by a positive spectral index. For the latest observations, the medians of the velocity errors were equal to 0.3, 0.3 and 0.4 mm/year, respectively, for the North, East and Up components. In the best cases, a velocity uncertainty of DORIS sites of 0.1 mm/year is achievable when the appropriate coloured noise model is taken into consideration.
Directory of Open Access Journals (Sweden)
Wilmar Hernandez
2005-11-01
Full Text Available In the present paper, in order to estimate the response of both a wheel speedsensor and an accelerometer placed in a car under performance tests, robust and optimalmultivariable estimation techniques are used. In this case, the disturbances and noisescorrupting the relevant information coming from the sensorsÃ¢Â€Â™ outputs are so dangerous thattheir negative influence on the electrical systems impoverish the general performance of thecar. In short, the solution to this problem is a safety related problem that deserves our fullattention. Therefore, in order to diminish the negative effects of the disturbances and noiseson the carÃ¢Â€Â™s electrical and electromechanical systems, an optimum observer is used. Theexperimental results show a satisfactory improvement in the signal-to-noise ratio of therelevant signals and demonstrate the importance of the fusion of several intelligent sensordesign techniques when designing the intelligent sensors that todayÃ¢Â€Â™s cars need.
Numerical algorithm for rigid body position estimation using the quaternion approach
Zigic, Miodrag; Grahovac, Nenad
2017-11-01
This paper deals with rigid body attitude estimation on the basis of the data obtained from an inertial measurement unit mounted on the body. The aim of this work is to present the numerical algorithm, which can be easily applied to the wide class of problems concerning rigid body positioning, arising in aerospace and marine engineering, or in increasingly popular robotic systems and unmanned aerial vehicles. Following the considerations of kinematics of rigid bodies, the relations between accelerations of different points of the body are given. A rotation matrix is formed using the quaternion approach to avoid singularities. We present numerical procedures for determination of the absolute accelerations of the center of mass and of an arbitrary point of the body expressed in the inertial reference frame, as well as its attitude. An application of the algorithm to the example of a heavy symmetrical gyroscope is presented, where input data for the numerical procedure are obtained from the solution of differential equations of motion, instead of using sensor measurements.
Jing, Nan; Li, Chuang; Chong, Yaqin
2017-01-20
An estimation method for indirectly observable parameters for a typical low dynamic vehicle (LDV) is presented. The estimation method utilizes apparent magnitude, azimuth angle, and elevation angle to estimate the position and velocity of a typical LDV, such as a high altitude balloon (HAB). In order to validate the accuracy of the estimated parameters gained from an unscented Kalman filter, two sets of experiments are carried out to obtain the nonresolved photometric and astrometric data. In the experiments, a HAB launch is planned; models of the HAB dynamics and kinematics and observation models are built to use as time update and measurement update functions, respectively. When the HAB is launched, a ground-based optoelectronic detector is used to capture the object images, which are processed using aperture photometry technology to obtain the time-varying apparent magnitude of the HAB. Two sets of actual and estimated parameters are given to clearly indicate the parameter differences. Two sets of errors between the actual and estimated parameters are also given to show how the estimated position and velocity differ with respect to the observation time. The similar distribution curve results from the two scenarios, which agree within 3σ, verify that nonresolved photometric and astrometric data can be used to estimate the indirectly observable state parameters (position and velocity) for a typical LDV. This technique can be applied to small and dim space objects in the future.
Position and volume estimation of atmospheric nuclear detonations from video reconstruction
Schmitt, Daniel T.
Recent work in digitizing films of foundational atmospheric nuclear detonations from the 1950s provides an opportunity to perform deeper analysis on these historical tests. This work leverages multi-view geometry and computer vision techniques to provide an automated means to perform three-dimensional analysis of the blasts for several points in time. The accomplishment of this requires careful alignment of the films in time, detection of features in the images, matching of features, and multi-view reconstruction. Sub-explosion features can be detected with a 67% hit rate and 22% false alarm rate. Hotspot features can be detected with a 71.95% hit rate, 86.03% precision and a 0.015% false positive rate. Detected hotspots are matched across 57-109 degree viewpoints with 76.63% average correct matching by defining their location relative to the center of the explosion, rotating them to the alternative viewpoint, and matching them collectively. When 3D reconstruction is applied to the hotspot matching it completes an automated process that has been used to create 168 3D point clouds with 31.6 points per reconstruction with each point having an accuracy of 0.62 meters with 0.35, 0.24, and 0.34 meters of accuracy in the x-, y- and z-direction respectively. As a demonstration of using the point clouds for analysis, volumes are estimated and shown to be consistent with radius-based models and in some cases improve on the level of uncertainty in the yield calculation.
Energy Technology Data Exchange (ETDEWEB)
Aoki, Y.; Osaragi, T. (Tokyo Institute of Technology, Tokyo (Japan). Faculty of Engineering)
1991-07-30
In this study, a method for robust estimation of parameters of the space influence function model, which was possible to become unstable, was investigated by applying a principal component method. In order to carry out the robust estimation of parameters without the effect of multicollinearity, regression coefficients of principal components with small eigenvalue and with small single-correlation with dependent variables were required to forced to be zero in the estimation method by principal component. Through the case study using the real urban lattice data, the conventional method was compared with the principal component method. As a result, the latter method realized the excellent sabilization of spatial distribution patterns of estimation parameters and the simple interpretation of parameters. It also improved reliability since 95% confidence interval of the estimated value became smaller. This method was found to be effective as a basic measure to acheve the stability of parameters. 10 refs., 7 figs.
Sidler, Dominik; Schwaninger, Arthur; Riniker, Sereina
2016-10-21
In molecular dynamics (MD) simulations, free-energy differences are often calculated using free energy perturbation or thermodynamic integration (TI) methods. However, both techniques are only suited to calculate free-energy differences between two end states. Enveloping distribution sampling (EDS) presents an attractive alternative that allows to calculate multiple free-energy differences in a single simulation. In EDS, a reference state is simulated which "envelopes" the end states. The challenge of this methodology is the determination of optimal reference-state parameters to ensure equal sampling of all end states. Currently, the automatic determination of the reference-state parameters for multiple end states is an unsolved issue that limits the application of the methodology. To resolve this, we have generalised the replica-exchange EDS (RE-EDS) approach, introduced by Lee et al. [J. Chem. Theory Comput. 10, 2738 (2014)] for constant-pH MD simulations. By exchanging configurations between replicas with different reference-state parameters, the complexity of the parameter-choice problem can be substantially reduced. A new robust scheme to estimate the reference-state parameters from a short initial RE-EDS simulation with default parameters was developed, which allowed the calculation of 36 free-energy differences between nine small-molecule inhibitors of phenylethanolamine N-methyltransferase from a single simulation. The resulting free-energy differences were in excellent agreement with values obtained previously by TI and two-state EDS simulations.
Ono, Tomohiro; Nakamura, Mitsuhiro; Hirose, Yoshinori; Kitsuda, Kenji; Ono, Yuka; Ishigaki, Takashi; Hiraoka, Masahiro
2017-09-01
To estimate the lung tumor position from multiple anatomical features on four-dimensional computed tomography (4D-CT) data sets using single regression analysis (SRA) and multiple regression analysis (MRA) approach and evaluate an impact of the approach on internal target volume (ITV) for stereotactic body radiotherapy (SBRT) of the lung. Eleven consecutive lung cancer patients (12 cases) underwent 4D-CT scanning. The three-dimensional (3D) lung tumor motion exceeded 5 mm. The 3D tumor position and anatomical features, including lung volume, diaphragm, abdominal wall, and chest wall positions, were measured on 4D-CT images. The tumor position was estimated by SRA using each anatomical feature and MRA using all anatomical features. The difference between the actual and estimated tumor positions was defined as the root-mean-square error (RMSE). A standard partial regression coefficient for the MRA was evaluated. The 3D lung tumor position showed a high correlation with the lung volume (R = 0.92 ± 0.10). Additionally, ITVs derived from SRA and MRA approaches were compared with ITV derived from contouring gross tumor volumes on all 10 phases of the 4D-CT (conventional ITV). The RMSE of the SRA was within 3.7 mm in all directions. Also, the RMSE of the MRA was within 1.6 mm in all directions. The standard partial regression coefficient for the lung volume was the largest and had the most influence on the estimated tumor position. Compared with conventional ITV, average percentage decrease of ITV were 31.9% and 38.3% using SRA and MRA approaches, respectively. The estimation accuracy of lung tumor position was improved by the MRA approach, which provided smaller ITV than conventional ITV. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
Directory of Open Access Journals (Sweden)
Shanker Man Shrestha
2003-11-01
Full Text Available Super-resolution is very important for the signal processing of GPR (ground penetration radar to resolve closely buried targets. However, it is not easy to get high resolution as GPR signals are very weak and enveloped by the noise. The MUSIC (multiple signal classification algorithm, which is well known for its super-resolution capacity, has been implemented for signal and image processing of GPR. In addition, conventional spectral estimation technique, FFT (fast Fourier transform, has also been implemented for high-precision receiving signal level. In this paper, we propose CPM (combined processing method, which combines time domain response of MUSIC algorithm and conventional IFFT (inverse fast Fourier transform to obtain a super-resolution and high-precision signal level. In order to support the proposal, detailed simulation was performed analyzing SNR (signal-to-noise ratio. Moreover, a field experiment at a research field and a laboratory experiment at the University of Electro-Communications, Tokyo, were also performed for thorough investigation and supported the proposed method. All the simulation and experimental results are presented.
DEFF Research Database (Denmark)
Gorm Hansen, Birgitte
their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...
A robust standard deviation control chart
Schoonhoven, M.; Does, R.J.M.M.
2012-01-01
This article studies the robustness of Phase I estimators for the standard deviation control chart. A Phase I estimator should be efficient in the absence of contaminations and resistant to disturbances. Most of the robust estimators proposed in the literature are robust against either diffuse
Mendez Astudillo, Jorge; Lau, Lawrence; Tang, Yu-Ting; Moore, Terry
2018-02-14
As Global Navigation Satellite System (GNSS) signals travel through the troposphere, a tropospheric delay occurs due to a change in the refractive index of the medium. The Precise Point Positioning (PPP) technique can achieve centimeter/millimeter positioning accuracy with only one GNSS receiver. The Zenith Tropospheric Delay (ZTD) is estimated alongside with the position unknowns in PPP. Estimated ZTD can be very useful for meteorological applications, an example is the estimation of water vapor content in the atmosphere from the estimated ZTD. PPP is implemented with different algorithms and models in online services and software packages. In this study, a performance assessment with analysis of ZTD estimates from three PPP online services and three software packages is presented. The main contribution of this paper is to show the accuracy of ZTD estimation achievable in PPP. The analysis also provides the GNSS users and researchers the insight of the processing algorithm dependence and impact on PPP ZTD estimation. Observation data of eight whole days from a total of nine International GNSS Service (IGS) tracking stations spread in the northern hemisphere, the equatorial region and the southern hemisphere is used in this analysis. The PPP ZTD estimates are compared with the ZTD obtained from the IGS tropospheric product of the same days. The estimates of two of the three online PPP services show good agreement (<1 cm) with the IGS ZTD values at the northern and southern hemisphere stations. The results also show that the online PPP services perform better than the selected PPP software packages at all stations.
Directory of Open Access Journals (Sweden)
Jorge Mendez Astudillo
2018-02-01
Full Text Available As Global Navigation Satellite System (GNSS signals travel through the troposphere, a tropospheric delay occurs due to a change in the refractive index of the medium. The Precise Point Positioning (PPP technique can achieve centimeter/millimeter positioning accuracy with only one GNSS receiver. The Zenith Tropospheric Delay (ZTD is estimated alongside with the position unknowns in PPP. Estimated ZTD can be very useful for meteorological applications, an example is the estimation of water vapor content in the atmosphere from the estimated ZTD. PPP is implemented with different algorithms and models in online services and software packages. In this study, a performance assessment with analysis of ZTD estimates from three PPP online services and three software packages is presented. The main contribution of this paper is to show the accuracy of ZTD estimation achievable in PPP. The analysis also provides the GNSS users and researchers the insight of the processing algorithm dependence and impact on PPP ZTD estimation. Observation data of eight whole days from a total of nine International GNSS Service (IGS tracking stations spread in the northern hemisphere, the equatorial region and the southern hemisphere is used in this analysis. The PPP ZTD estimates are compared with the ZTD obtained from the IGS tropospheric product of the same days. The estimates of two of the three online PPP services show good agreement (<1 cm with the IGS ZTD values at the northern and southern hemisphere stations. The results also show that the online PPP services perform better than the selected PPP software packages at all stations.
Kim, Sooyeon; Moses, Tim
2016-01-01
The purpose of this study is to evaluate the extent to which item response theory (IRT) proficiency estimation methods are robust to the presence of aberrant responses under the "GRE"® General Test multistage adaptive testing (MST) design. To that end, a wide range of atypical response behaviors affecting as much as 10% of the test items…
Mocroft, Amanda; Kirk, Ole; Reiss, Peter; de Wit, Stephane; Sedlacek, Dalibor; Beniowski, Marek; Gatell, Jose; Phillips, Andrew N.; Ledergerber, Bruno; Lundgren, Jens D.; Losso, M.; Elias, C.; Vetter, N.; Zangerle, R.; Karpov, I.; Vassilenko, A.; Mitsura, V. M.; Suetnov, O.; Clumeck, N.; Poll, B.; Colebunders, R.; Vandekerckhove, L.; Hadziosmanovic, V.; Kostov, K.; Begovac, J.; Machala, L.; Rozsypal, H.; Sedlacek, D.; Nielsen, J.; Kronborg, G.; Benfield, T.; Larsen, M.; Gerstoft, J.; Katzenstein, T.; Hansen, A.-B. E.; Skinhøj, P.; Pedersen, C.; Oestergaard, L.; Zilmer, K.; Smidt, Jelena; Ristola, M.; Katlama, C.; Viard, J.-P.; Girard, P.-M.; Livrozet, J. M.; Vanhems, P.; Pradier, C.; Dabis, F.; Neau, D.; Rockstroh, J.
2010-01-01
Objectives: Chronic kidney disease (CKD) in HIV-positive persons might be caused by both HIV and traditional or non-HIV-related factors. Our objective was to investigate long-term exposure to specific antiretroviral drugs and CKD. Design: A cohort study including 6843 HIV-positive persons with at
Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang
2018-01-01
Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm
Maximum likelihood estimation of the position of a radiating source in a waveguide
International Nuclear Information System (INIS)
Hinich, M.J.
1979-01-01
An array of sensors is receiving radiation from a source of interest. The source and the array are in a one- or two-dimensional waveguide. The maximum-likelihood estimators of the coordinates of the source are analyzed under the assumptions that the noise field is Gaussian. The Cramer-Rao lower bound is of the order of the number of modes which define the source excitation function. The results show that the accuracy of the maximum likelihood estimator of source depth using a vertical array in a infinite horizontal waveguide (such as the ocean) is limited by the number of modes detected by the array regardless of the array size
Improved Stewart platform state estimation using inertial and actuator position measurements
MiletoviC, I.; Pool, D.M.; Stroosma, O.; van Paassen, M.M.; Chu, Q.
2017-01-01
Accurate and reliable estimation of the kinematic state of a six degrees-of-freedom Stewart platform is a problem of interest in various engineering disciplines. Particularly so in the area of flight simulation, where the Stewart platform is in widespread use for the generation of motion similar
Robust Trust in Expert Testimony
Directory of Open Access Journals (Sweden)
Christian Dahlman
2015-05-01
Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.
Nakagawa, M.; Akano, K.; Kobayashi, T.; Sekiguchi, Y.
2017-09-01
Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.
International Nuclear Information System (INIS)
Parwani, Ajit K.; Talukdar, Prabal; Subbarao, P.M.V.
2013-01-01
An inverse heat transfer problem is discussed to estimate simultaneously the unknown position and timewise varying strength of a heat source by utilizing differential evolution approach. A two dimensional enclosure with isothermal and black boundaries containing non-scattering, absorbing and emitting gray medium is considered. Both radiation and conduction heat transfer are included. No prior information is used for the functional form of timewise varying strength of heat source. The finite volume method is used to solve the radiative transfer equation and the energy equation. In this work, instead of measured data, some temperature data required in the solution of the inverse problem are taken from the solution of the direct problem. The effect of measurement errors on the accuracy of estimation is examined by introducing errors in the temperature data of the direct problem. The prediction of source strength and its position by the differential evolution (DE) algorithm is found to be quite reasonable. -- Highlights: •Simultaneous estimation of strength and position of a heat source. •A conducting and radiatively participating medium is considered. •Implementation of differential evolution algorithm for such kind of problems. •Profiles with discontinuities can be estimated accurately. •No limitation in the determination of source strength at the final time
Robust Portfolio Optimization Using Pseudodistances.
Toma, Aida; Leoni-Aubin, Samuela
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.
Energy Technology Data Exchange (ETDEWEB)
Dickerhoff, Darryl; Walker, Iain
2008-08-01
The DeltaQ test is a method of estimating the air leakage from forced air duct systems. Developed primarily for residential and small commercial applications it uses the changes in blower door test results due to forced air system operation. Previous studies established the principles behind DeltaQ testing, but raised issues of precision of the test, particularly for leaky homes on windy days. Details of the measurement technique are available in an ASTM Standard (ASTM E1554-2007). In order to ease adoption of the test method, this study answers questions regarding the uncertainty due to changing weather during the test (particularly changes in wind speed) and the applicability to low leakage systems. The first question arises because the building envelope air flows and pressures used in the DeltaQ test are influenced by weather induced pressures. Variability in wind induced pressures rather than temperature difference induced pressures dominates this effect because the wind pressures change rapidly over the time period of a test. The second question needs to answered so that DeltaQ testing can be used in programs requiring or giving credit for tight ducts (e.g., California's Building Energy Code (CEC 2005)). DeltaQ modeling biases have been previously investigated in laboratory studies where there was no weather induced changes in envelope flows and pressures. Laboratory work by Andrews (2002) and Walker et al. (2004) found biases of about 0.5% of forced air system blower flow and individual test uncertainty of about 2% of forced air system blower flow. The laboratory tests were repeated by Walker and Dickerhoff (2006 and 2008) using a new ramping technique that continuously varied envelope pressures and air flows rather than taking data at pre-selected pressure stations (as used in ASTM E1554-2003 and other previous studies). The biases and individual test uncertainties for ramping were found to be very close (less than 0.5% of air handler flow) to those
Rotor Position Estimation for Switched Reluctance Wind Generator Using Extreme Learning Machine
DEFF Research Database (Denmark)
Wang, Chao; Liu, Xiao; Chen, Zhe
2014-01-01
Switched reluctance generator (SRG) is becoming more and more attractive in wind energy applications mainly because of its high fault tolerant ability and high reliability. The position sensor is one of the vulnerable points of the SRG when exposed to harsh environments such as offshore where man...
Directory of Open Access Journals (Sweden)
M. Nakagawa
2017-09-01
Full Text Available Image-based virtual reality (VR is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.
Mansour , Salwa; Canot , Edouard; Delannay , Renaud; March , Ramiro J.; Cordero , José Agustin; Carlos Ferreri , Juan
2015-01-01
The report is basically divided into two main parts. In the first part, we introduce a numerical strategy in both 1D and 3D axisymmetric coordinate systems to estimate the thermophysical properties of the soil (volumetric heat capacity (ρC)s , thermal conductivity λs and porosity φ) of a saturated porous medium where a phase change problem (liquid/vapor) appears due to intense heating from above. Usually φ is the true porosity, however when the soil is not saturated (which should concern most...
Estimation of physical development of young sportsmen from traditional and modern positions
Directory of Open Access Journals (Sweden)
Khor'yakov V.A.
2012-12-01
Full Text Available The problem of evaluation of anthropometric status of young sportsmen is examined with the use of method of indexes and modern pictures of somatic health of man. In research young boxers took part 10-11 (n=41, 12-13 (n=48 and 14-16 years (n=39. Contradiction and ambiguousness of estimations of physical development of children and teenagers is rotined by means of traditional indexes of Erismana, Quetelet, Pin'e, sthenic and development of thorax. It is marked that an estimation of physical development of children and teenagers with the use of standard deviation of selection is not productive, because in most cases distributing of the studied signs falls short of a normal law. A concept «norm» is recommended to replace a concept «norm» as an obligatory requirement of the state to the level of somatic health of children and teenagers of different regions of country. It is marked that it is expedient to examine physical development of individuals as a structural element of bodily condition the major components of which are indexes of power and capacity of mechanisms of energy supply.
Versaevel, C; Samama, D; Jeanson, R; Lajugie, C; Dufeutrel, L; Defromont, L; Lebouteiller, V; Danel, T; Duhamel, A; Genin, M; Salleron, J; Cottencin, O
2013-09-01
For the brief systemic therapy (BST), the evaluation of the patient's position towards the care is a prerequisite to psychotherapy. Three positions of the patient are described. The "tourist's" position: the patient claims to have no problem and doesn't suffer. Someone asks him to make an appointment, sometimes with threats. The "complaint's" position: the patient claims to suffer, but attributes the responsibility of this suffering to others. These two positions are not good for beginning a therapy. The "customer's" position differs from both previous positions. The "customer" considers that he has a psychological problem which depends on him and he is motivated in the resolution of it. In theory, the "customer" is more motivated and the therapeutic alliance is better. It is for this reason that the BST estimates the position of the patient at first, to bring the patient to the "customer's" position. The objective of this study is to assess an interview which identifies the patient's position towards the care, and to validate the theoretical elaborations of the brief systemic therapy. The study concerns the follow-up of outpatients who consult a psychiatrist for the first time. The evaluation of the patients checks their position towards care using the Tourist-Complaint-Customer (TCC) inventory, how they suffer, the therapeutic alliance (scale Haq-2) and the compliance during care. The evaluation by the psychiatrists checks the suffering perceived, the motivation perceived and the diagnoses according to the DSM. The typology of these patients is made up of one half "complaint", a quarter of "tourist" and a quarter of "customer". The "customer's" position is correlated with the therapeutic alliance and the motivation perceived by the psychiatrist. The motivation perceived by the psychiatrist is correlated with the therapeutic alliance. These results correspond to the theoretical elaborations of the BST. the TCC inventory provides information on the motivation and
Czech Academy of Sciences Publication Activity Database
Pavelková, Lenka
2011-01-01
Roč. 47, č. 3 (2011), s. 370-384 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : non-linear state space model * bounded uncertainty * missing measurements * state filtering * vehicle position estimation Subject RIV: BC - Control Systems Theory Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/pavelkova-0360239.pdf
Directory of Open Access Journals (Sweden)
Abdulmalik Shehu Yaro
2017-01-01
Full Text Available Multilateration estimates aircraft position using the Time Difference Of Arrival (TDOA with a lateration algorithm. The Position Estimation (PE accuracy of the lateration algorithm depends on several factors which are the TDOA estimation error, the lateration algorithm approach, the number of deployed GRSs and the selection of the GRS reference used for the PE process. Using the minimum number of GRSs for 3D emitter PE, a technique based on the condition number calculation is proposed to select the suitable GRS reference pair for improving the accuracy of the PE using the lateration algorithm. Validation of the proposed technique was performed with the GRSs in the square and triangular GRS configuration. For the selected emitter positions, the result shows that the proposed technique can be used to select the suitable GRS reference pair for the PE process. A unity condition number is achieved for GRS pair most suitable for the PE process. Monte Carlo simulation result, in comparison with the fixed GRS reference pair lateration algorithm, shows a reduction in PE error of at least 70% for both GRS in the square and triangular configuration.
DEFF Research Database (Denmark)
Mocroft, Amanda; Kirk, Ole; Reiss, Peter
2010-01-01
with at least three serum creatinine measurements and corresponding body weight measurements from 2004 onwards. METHODS:: CKD was defined as either confirmed (two measurements >/=3 months apart) estimated glomerular filtration rate (eGFR) of 60 ml/min per 1.73 m or below for persons with baseline eGFR of above...... cumulative exposure to tenofovir [incidence rate ratio (IRR) per year 1.16, 95% CI 1.06-1.25, P ... increased rate of CKD. Consistent results were observed in wide-ranging sensitivity analyses, although of marginal statistical significance for lopinavir/r. No other antiretroviral dugs were associated with increased incidence of CKD. CONCLUSION:: In this nonrandomized large cohort, increasing exposure...
Position of cytogenetic examination of cosmonauts for the space radiation exposure estimate
Snigiryova, Galina; Novitskaya, Natalia; Fedorenko, Boris
The cytogenetic monitoring was carried out to evaluate of radiation induced stable and un-stable chromosome aberration frequency in peripheral blood lymphocytes of cosmonauts who participated in flights on Mir Orbital Station and ISS (International Space Station). In the period of 1992 -2008 chromosome aberrations in 202 blood samples from 48 cosmonauts were analyzed using the conventional method. In addition 23 blood samples from 12 cosmonauts were analyzed using FISH (fluorescence in situ hybridization) technique. Whole chromosome painting probes for chromosomes 1, 4 and 12 were used simultaneously with a pancentromeric probe. Samples taken before and after the flights were analyzed. Long-term space flights led to an increase of stable (FISH method) and unstable (conventional method) chromosome aber-ration frequencies. The frequencies of dicentrics and centric rings depend on the space flight duration and accumulated dose value. Extravehicular activity also adds to chromosome aber-ration frequency in blood lymphocytes of cosmonauts. Several years after the space flight the increased level of unstable chromosome aberrations is still apparent. The radiation load was decreased for cosmonauts after taking ISS over from MIR station. The cytogenetic results were in agreement with data of physical dosimetry. The dose interval after the first flight, estimated by the frequency of dicentrics, was 113-227 mSv for long-term flights (73 -199 days) and 53-107 mSv for short-term flights (1 -21 days). According to the frequency of FISH translocations, the average dose after the first long-term flight was 186 mSv, which is comparable with estimates made from the dicentric assay. Cytogenetic examination of cosmonauts, including analysis of dicentrics (conventional method) and translocations (FISH method) should find wider applica-tion to assessment of radiation effects associated with long-term space flights such as flights to Mars.
Forecasting exchange rates: a robust regression approach
Preminger, Arie; Franck, Raphael
2005-01-01
The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...
Teymouri, Jessica; Hullar, Timothy E; Holden, Timothy A; Chole, Richard A
2011-08-01
To determine the efficacy of clinical computed tomographic (CT) imaging to verify postoperative electrode array placement in cochlear implant (CI) patients. Nine fresh cadaver heads underwent clinical CT scanning, followed by bilateral CI insertion and postoperative clinical CT scanning. Temporal bones were removed, trimmed, and scanned using micro-CT. Specimens were then dehydrated, embedded in either methyl methacrylate or LR White resin, and sectioned with a diamond wafering saw. Histology sections were examined by 3 blinded observers to determine the position of individual electrodes relative to soft tissue structures within the cochlea. Electrodes were judged to be within the scala tympani, scala vestibuli, or in an intermediate position between scalae. The position of the array could be estimated accurately from clinical CT scans in all specimens using micro-CT and histology as a criterion standard. Verification using micro-CT yielded 97% agreement, and histologic analysis revealed 95% agreement with clinical CT results. A composite, 3-dimensional image derived from a patient's preoperative and postoperative CT images using a clinical scanner accurately estimates the position of the electrode array as determined by micro-CT imaging and histologic analyses. Information obtained using the CT method provides valuable insight into numerous variables of interest to patient performance such as surgical technique, array design, and processor programming and troubleshooting.
Larson, Kristine M.; Freymueller, Jeff
1995-01-01
Global Positioning System (GPS) measurements spanning approximately 3 years have been used to determine velocities for 7 sites on the Australian, Pacific and Antarctic plates. The site velocities agree with both plate model predictions and other space geodetic techniques. We find no evidence for internal deformation of the interior of the Australian plate. Wellington, New Zealand, located in the Australian-Pacific plate boundary zone, moves 20 +/- 5 mm/yr west-southwest relative to the Australian plate. Its velocity lies midway between the predicted velocities of the two plates. Relative Euler vectors for the Australia-Antarctica and Pacific-Antarctica plates agree within one standard deviation with the NUVEL-1A predictions.
Lerman, Gilad M; Levy, Uriel
2013-03-13
Great hopes rest on surface plasmon polaritons' (SPPs) potential to bring new functionalities and applications into various branches of optics. In this paper, we demonstrate a pin cushion structure capable of coupling light from free space into SPPs, split them based on the polarization content of the illuminating beam of light, and focus them into small spots. We also show that for a circularly or randomly polarized light, four focal spots will be generated at the center of each quarter circle comprising the pin cushion device. Furthermore, following the relation between the relative intensity of the obtained four focal spots and the relative position of the illuminating beam with respect to the structure, we propose and demonstrate the potential use of our structure as a miniaturized plasmonic version of the well-known four quadrant detector. Additional potential applications may vary from multichannel microscopy and multioptical traps to real time beam tracking systems.
Directory of Open Access Journals (Sweden)
Andreas Tuerk
2017-05-01
Full Text Available Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. "mixquare", a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq; state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.
Position of cytogenetic examination of cosmonauts for the space radiation expose estimate
Snigireva, Galina; Novitskaya, Natalia; Ivanov, Alexander
Analysis of chromosome aberrations in human peripheral blood lymphocytes is widely used for the indication and quantitative assessment of radiation. The dose, as estimated by the frequency of chromosome aberrations takes into account not only the physical impact of radiation on the human body but also its individual characteristics, such as radiation sensitivity and functional conditions during irradiation. The purpose of this study was to evaluate the influence of radiation on the chromosome aberration frequency in peripheral blood lymphocytes of the cosmonauts who participated in flights on the ISS (International Space Station). Cytogenetic examination was performed in the period 1992-2013 and included the analysis of chromosome aberrations using conventional Giemsa staining method in blood samples from 38 cosmonauts who participated in flights on the ISS. The cytogenetic examination results showed that cosmic flights lead to an increase of chromosome aberrations in the lymphocytes of cosmonauts. Compared with the pre-flight levels frequencies of dicentrics and centric rings (the radiation exposure markers) are about 4 times higher for cosmonauts after flights. The frequency of chromosome aberrations depends on the length of the flight and, correspondingly, on the accumulated dose of cosmic irradiation. Between flights, a decrease in the chromosome aberration frequency is observed, but even several years after a flight, the level of chromosome aberrations in the lymphocytes of cosmonauts remains high. Cytogenetic monitoring of cosmonauts can undoubtedly play an important role in comprehensive medical surveys of these individuals if we take into account the possible connection of higher levels of chromosomal aberrations with the risk of oncological diseases. Analysis of chromosome aberration dynamics after flights will allow the determination of individuals with an increased cancerogenese risk and provision of required treatments.
Arevalo, L.; Wu, D.; Jacobson, B.
2013-08-01
The main propose of this paper is to present a physical model of long air gap electrical discharges under positive switching impulses. The development and progression of discharges in long air gaps are attributable to two intertwined physical phenomena, namely, the leader channel and the streamer zone. Experimental studies have been used to develop empirical and physical models capable to represent the streamer zone and the leader channel. The empirical ones have led to improvements in the electrical design of high voltage apparatus and insulation distances, but they cannot take into account factors associated with fundamental physics and/or the behavior of materials. The physical models have been used to describe and understand the discharge phenomena of laboratory and lightning discharges. However, because of the complex simulations necessary to reproduce real cases, they are not in widespread use in the engineering of practical applications. Hence, the aim of the work presented here is to develop a model based on physics of the discharge capable to validate and complement the existing engineering models. The model presented here proposes a new geometrical approximation for the representation of the streamer and the calculation of the accumulated electrical charge. The model considers a variable streamer region that changes with the temporal and spatial variations of the electric field. The leader channel is modeled using the non local thermo-equilibrium equations. Furthermore, statistical delays before the inception of the first corona, and random distributions to represent the tortuous nature of the path taken by the leader channel were included based on the behavior observed in experimental tests, with the intention of ensuring the discharge behaved in a realistic manner. For comparison purposes, two different gap configurations were simulated. A reasonable agreement was found between the physical model and the experimental test results.
Moving-Target Position Estimation Using GPU-Based Particle Filter for IoT Sensing Applications
Directory of Open Access Journals (Sweden)
Seongseop Kim
2017-11-01
Full Text Available A particle filter (PF has been introduced for effective position estimation of moving targets for non-Gaussian and nonlinear systems. The time difference of arrival (TDOA method using acoustic sensor array has normally been used to for estimation by concealing the location of a moving target, especially underwater. In this paper, we propose a GPU -based acceleration of target position estimation using a PF and propose an efficient system and software architecture. The proposed graphic processing unit (GPU-based algorithm has more advantages in applying PF signal processing to a target system, which consists of large-scale Internet of Things (IoT-driven sensors because of the parallelization which is scalable. For the TDOA measurement from the acoustic sensor array, we use the generalized cross correlation phase transform (GCC-PHAT method to obtain the correlation coefficient of the signal using Fast Fourier Transform (FFT, and we try to accelerate the calculations of GCC-PHAT based TDOA measurements using FFT with GPU compute unified device architecture (CUDA. The proposed approach utilizes a parallelization method in the target position estimation algorithm using GPU-based PF processing. In addition, it could efficiently estimate sudden movement change of the target using GPU-based parallel computing which also can be used for multiple target tracking. It also provides scalability in extending the detection algorithm according to the increase of the number of sensors. Therefore, the proposed architecture can be applied in IoT sensing applications with a large number of sensors. The target estimation algorithm was verified using MATLAB and implemented using GPU CUDA. We implemented the proposed signal processing acceleration system using target GPU to analyze in terms of execution time. The execution time of the algorithm is reduced by 55% from to the CPU standalone operation in target embedded board, NVIDIA Jetson TX1. Also, to apply large
A fast position estimation method for a control rod guide tube inspection robot with a single camera
International Nuclear Information System (INIS)
Lee, Jae C.; Seop, Jun H.; Choi, Yu R.; Kim, Jae H.
2004-01-01
One of the problems in the inspection of control rod guide tubes using a mobile robot is accurate estimation of the robot's position. The problem is usually explained by the question 'Where am I?'. We can solve this question by a method called dead reckoning using odometers. But it has some inherent drawbacks such that the position error grows without bound unless an independent reference is used periodically to reduce the errors. In this paper, we presented one method to overcome this drawback by using a vision sensor. Our method is based on the classical Lucas Kanade algorithm for on image tracking. In this algorithm, an optical flow must be calculated at every image frame, thus it has intensive computing load. In order to handle large motions, it is preferable to use a large integration window. But a small integration window is more preferable to keep the details contained in the images. We used the robot's movement information obtained from the dead reckoning as an input parameter for the feature tracking algorithm in order to restrict the position of an integration window. By means of this method, we could reduce the size of an integration window without any loss of its ability to handle large motions and could avoid the trade off in the accuracy. And we could estimate the position of our robot relatively fast without on intensive computing time and the inherent drawbacks mentioned above. We studied this algorithm for applying it to the control rod guide tubes inspection robot and tried an inspection without on operator's intervention
Feasibility of using single photon counting X-ray for lung tumor position estimation based on 4D-CT
Energy Technology Data Exchange (ETDEWEB)
Aschenbrenner, Katharina P.; Hesser, Juergen W. [Heidelberg Univ., Mannheim (Germany). Dept. of Experimental Radiation Oncology; Heidelberg Univ. (Germany). IWR; Guthier, Christian V. [Heidelberg Univ., Mannheim (Germany). Dept. of Experimental Radiation Oncology; Lyatskaya, Yulia [Brigham and Women' s Center, Boston, MA (United States); Harvard Medical School, Boston, MA (United States); Boda-Heggemann, Judit; Wenz, Frederik [Heidelberg Univ., Mannheim (Germany). Dept. of Radiation Oncology
2017-10-01
In stereotactic body radiation therapy of lung tumors, reliable position estimation of the tumor is necessary in order to minimize normal tissue complication rate. While kV X-ray imaging is frequently used, continuous application during radiotherapy sessions is often not possible due to concerns about the additional dose. Thus, ultra low-dose (ULD) kV X-ray imaging based on a single photon counting detector is suggested. This paper addresses the lower limit of photons to locate the tumor reliably with an accuracy in the range of state-of-the-art methods, i.e. a few millimeters. 18 patient cases with four dimensional CT (4D-CT), which serves as a-priori information, are included in the study. ULD cone beam projections are simulated from the 4D-CTs including Poisson noise. The projections from the breathing phases which correspond to different tumor positions are compared to the ULD projection by means of Poisson log-likelihood (PML) and correlation coefficient (CC), and template matching under these metrics. The results indicate that in full thorax imaging five photons per pixel suffice for a standard deviation in tumor positions of less than half a breathing phase. Around 50 photons per pixel are needed to achieve this accuracy with the field of view restricted to the tumor region. Compared to CC, PML tends to perform better for low photon counts and shifts in patient setup. Template matching only improves the position estimation in high photon counts. The quality of the reconstruction is independent of the projection angle. The accuracy of the proposed ULD single photon counting system is in the range of a few millimeters and therefore comparable to state-of-the-art tumor tracking methods. At the same time, a reduction in photons per pixel by three to four orders of magnitude relative to commercial systems with flatpanel detectors can be achieved. This enables continuous kV image-based position estimation during all fractions since the additional dose to the
Feasibility of using single photon counting X-ray for lung tumor position estimation based on 4D-CT.
Aschenbrenner, Katharina P; Guthier, Christian V; Lyatskaya, Yulia; Boda-Heggemann, Judit; Wenz, Frederik; Hesser, Jürgen W
2017-09-01
In stereotactic body radiation therapy of lung tumors, reliable position estimation of the tumor is necessary in order to minimize normal tissue complication rate. While kV X-ray imaging is frequently used, continuous application during radiotherapy sessions is often not possible due to concerns about the additional dose. Thus, ultra low-dose (ULD) kV X-ray imaging based on a single photon counting detector is suggested. This paper addresses the lower limit of photons to locate the tumor reliably with an accuracy in the range of state-of-the-art methods, i.e. a few millimeters. 18 patient cases with four dimensional CT (4D-CT), which serves as a-priori information, are included in the study. ULD cone beam projections are simulated from the 4D-CTs including Poisson noise. The projections from the breathing phases which correspond to different tumor positions are compared to the ULD projection by means of Poisson log-likelihood (PML) and correlation coefficient (CC), and template matching under these metrics. The results indicate that in full thorax imaging five photons per pixel suffice for a standard deviation in tumor positions of less than half a breathing phase. Around 50 photons per pixel are needed to achieve this accuracy with the field of view restricted to the tumor region. Compared to CC, PML tends to perform better for low photon counts and shifts in patient setup. Template matching only improves the position estimation in high photon counts. The quality of the reconstruction is independent of the projection angle. The accuracy of the proposed ULD single photon counting system is in the range of a few millimeters and therefore comparable to state-of-the-art tumor tracking methods. At the same time, a reduction in photons per pixel by three to four orders of magnitude relative to commercial systems with flatpanel detectors can be achieved. This enables continuous kV image-based position estimation during all fractions since the additional dose to the
Feasibility of using single photon counting X-ray for lung tumor position estimation based on 4D-CT
International Nuclear Information System (INIS)
Aschenbrenner, Katharina P.; Hesser, Juergen W.; Boda-Heggemann, Judit; Wenz, Frederik
2017-01-01
In stereotactic body radiation therapy of lung tumors, reliable position estimation of the tumor is necessary in order to minimize normal tissue complication rate. While kV X-ray imaging is frequently used, continuous application during radiotherapy sessions is often not possible due to concerns about the additional dose. Thus, ultra low-dose (ULD) kV X-ray imaging based on a single photon counting detector is suggested. This paper addresses the lower limit of photons to locate the tumor reliably with an accuracy in the range of state-of-the-art methods, i.e. a few millimeters. 18 patient cases with four dimensional CT (4D-CT), which serves as a-priori information, are included in the study. ULD cone beam projections are simulated from the 4D-CTs including Poisson noise. The projections from the breathing phases which correspond to different tumor positions are compared to the ULD projection by means of Poisson log-likelihood (PML) and correlation coefficient (CC), and template matching under these metrics. The results indicate that in full thorax imaging five photons per pixel suffice for a standard deviation in tumor positions of less than half a breathing phase. Around 50 photons per pixel are needed to achieve this accuracy with the field of view restricted to the tumor region. Compared to CC, PML tends to perform better for low photon counts and shifts in patient setup. Template matching only improves the position estimation in high photon counts. The quality of the reconstruction is independent of the projection angle. The accuracy of the proposed ULD single photon counting system is in the range of a few millimeters and therefore comparable to state-of-the-art tumor tracking methods. At the same time, a reduction in photons per pixel by three to four orders of magnitude relative to commercial systems with flatpanel detectors can be achieved. This enables continuous kV image-based position estimation during all fractions since the additional dose to the
International Nuclear Information System (INIS)
Heidrich, P; Wolfersdorf, J v; Schmidt, S; Schnieder, M
2008-01-01
This paper describes a non-invasive, non-destructive, transient inverse measurement technique that allows one to determine internal heat transfer coefficients and rib positions of real gas turbine blades from outer surface temperature measurements after a sudden flow heating. The determination of internal heat transfer coefficients is important during the design process to adjust local heat transfer to spatial thermal load. The detection of rib positions is important during production to fulfill design and quality requirements. For the analysis the one-dimensional transient heat transfer problem inside of the turbine blade's wall was solved. This solution was combined with the Levenberg-Marquardt method to estimate the unknown boundary condition by an inverse technique. The method was tested with artificial data to determine uncertainties with positive results. Then experimental testing with a reference model was carried out. Based on the results, it is concluded that the presented inverse technique could be used to determine internal heat transfer coefficients and to detect rib positions of real turbine blades.
Nielsen, Jens M; Popp, Brian N; Winder, Monika
2015-07-01
Estimating trophic structures is a common approach used to retrieve information regarding energy pathways, predation, and competition in complex ecosystems. The application of amino acid (AA) compound-specific nitrogen (N) isotope analysis (CSIA) is a relatively new method used to estimate trophic position (TP) and feeding relationships in diverse organisms. Here, we conducted the first meta-analysis of δ(15)N AA values from measurements of 359 marine species covering four trophic levels, and compared TP estimates from AA-CSIA to literature values derived from food items, gut or stomach content analysis. We tested whether the AA trophic enrichment factor (TEF), or the (15)N enrichment among different individual AAs is constant across trophic levels and whether inclusion of δ(15)N values from multiple AAs improves TP estimation. For the TEF of glutamic acid relative to phenylalanine (Phe) we found an average value of 6.6‰ across all taxa, which is significantly lower than the commonly applied 7.6‰. We found that organism feeding ecology influences TEF values of several trophic AAs relative to Phe, with significantly higher TEF values for herbivores compared to omnivores and carnivores, while TEF values were also significantly lower for animals excreting urea compared to ammonium. Based on the comparison of multiple model structures using the metadata of δ(15)N AA values we show that increasing the number of AAs in principle improves precision in TP estimation. This meta-analysis clarifies the advantages and limitations of using individual δ(15)N AA values as tools in trophic ecology and provides a guideline for the future application of AA-CSIA to food web studies.
Aspects of robust linear regression
Davies, P.L.
1993-01-01
Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that $S$-estimators satisfy an exact
Robust statistical methods with R
Jureckova, Jana
2005-01-01
Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...
Hayes, M.; Herbert, G.; Ellis, G.
2017-12-01
The diets of apex predators such as sharks are expected to change in response to overfishing of their mesopredator prey, but pre-anthropogenic baselines necessary to test for such changes are lacking. Stable isotope analysis (SIA) of soft tissues is commonly used to study diets in animals based on the bioaccumulation of heavier isotopes of carbon and nitrogen with increasing trophic level. In specimens representing pre-anthropogenic baselines, however, a modified SIA approach is needed to deal with taphonomic challenges, such as loss of soft tissues or selective loss of less stable amino acids (AAs) in other sources of organic compounds (e.g., teeth or bone) which can alter bulk isotope values. These challenges can be overcome with a compound-specific isotope analysis of individual AAs (AA-CSIA), but this first requires a thorough understanding of trophic enrichment factors for individual AAs within biomineralized tissues. In this study, we compare dental and muscle proteins of individual sharks via AA-CSIA to determine how trophic position is recorded within teeth and whether that information differs from that obtained from soft tissues. If skeletal organics reliably record information about shark ecology, then archaeological and perhaps paleontological specimens can be used to investigate pre-anthropogenic ecosystems. Preliminary experiments show that the commonly used glutamic acid/phenylalanine AA pairing may not be useful for establishing trophic position from dental proteins, but that estimated trophic position determined from alternate AA pairs are comparable to those from muscle tissue within the same species.
Wasza, Jakob; Bauer, Sebastian; Hornegger, Joachim
2012-01-01
Over the last years, range imaging (RI) techniques have been proposed for patient positioning and respiration analysis in motion compensation. Yet, current RI based approaches for patient positioning employ rigid-body transformations, thus neglecting free-form deformations induced by respiratory motion. Furthermore, RI based respiration analysis relies on non-rigid registration techniques with run-times of several seconds. In this paper we propose a real-time framework based on RI to perform respiratory motion compensated positioning and non-rigid surface deformation estimation in a joint manner. The core of our method are pre-procedurally obtained 4-D shape priors that drive the intra-procedural alignment of the patient to the reference state, simultaneously yielding a rigid-body table transformation and a free-form deformation accounting for respiratory motion. We show that our method outperforms conventional alignment strategies by a factor of 3.0 and 2.3 in the rotation and translation accuracy, respectively. Using a GPU based implementation, we achieve run-times of 40 ms.
Directory of Open Access Journals (Sweden)
Marek Hicar
2004-01-01
Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.
Robust photometric stereo using structural light sources
Han, Tian-Qi; Cheng, Yue; Shen, Hui-Liang; Du, Xin
2014-05-01
We propose a robust photometric stereo method by using structural arrangement of light sources. In the arrangement, light sources are positioned on a planar grid and form a set of collinear combinations. The shadow pixels are detected by adaptive thresholding. The specular highlight and diffuse pixels are distinguished according to their intensity deviations of the collinear combinations, thanks to the special arrangement of light sources. The highlight detection problem is cast as a pattern classification problem and is solved using support vector machine classifiers. Considering the possible misclassification of highlight pixels, the ℓ1 regularization is further employed in normal map estimation. Experimental results on both synthetic and real-world scenes verify that the proposed method can robustly recover the surface normal maps in the case of heavy specular reflection and outperforms the state-of-the-art techniques.
2013-10-18
area of 3D point estimation of flapping- wing UASs. The benefits of designing and developing such a system is instrumental in researching various...series of successive states until a given name is reached such as: Object Animate Animal Mammal Dog Labrador Chocolate (Brown) Male Name...are many benefits to us- ing SIFT in tracking. It detects features that are invariant to image scale and rotation, and are shown to provide robust
Robust canonical correlations: A comparative study
Branco, JA; Croux, Christophe; Filzmoser, P; Oliveira, MR
2005-01-01
Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust) correlation. A second method is based on alternating robust regressions. These methods axe discussed in detail and compared with the more traditional approach to robust canonical correlation via covariance matrix estimates. A simulation study ...
Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira
2015-12-18
For this work, an analysis of parameter estimation for the retention factor in GC model was performed, considering two different criteria: sum of square error, and maximum error in absolute value; relevant statistics are described for each case. The main contribution of this work is the implementation of an initialization scheme (specialized) for the estimated parameters, which features fast convergence (low computational time) and is based on knowledge of the surface of the error criterion. In an application to a series of alkanes, specialized initialization resulted in significant reduction to the number of evaluations of the objective function (reducing computational time) in the parameter estimation. The obtained reduction happened between one and two orders of magnitude, compared with the simple random initialization. Copyright © 2015 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Ryom, Lene; Mocroft, Amanda; Kirk, Ole
2017-01-01
OBJECTIVES: The objectives of this analysis were to investigate predictors of progression, stabilization or improvement in estimated glomerular filtration rate (eGFR) after development of chronic renal impairment (CRI) in HIV-positive individuals. DESIGN: Prospective observational study. METHODS......: The Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study participants progressing to CRI defined as confirmed, at least 3 months apart, and eGFR 70 ml/min per 1.73 m or less were included in the analysis. The median of all eGFRs measured 24-36 months post-CRI was compared with the median e......GFR defining CRI, and changes were grouped into improvement (>+10 ml/min per 1.73 m), stabilization (-10 to +10 ml/min per 1.73 m) and progression (
Robust and distributed hypothesis testing
Gül, Gökhan
2017-01-01
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...
International Nuclear Information System (INIS)
Tanaka, Masao; Fujii, Tadashige; Hirayama, Jiro; Okubo, Shinichi; Sekiguchi, Morie
1990-01-01
To estimate pulmonary hypertension in patients with various heart diseases, we devised a new method using perfusion lung scintigraphy with 99m Tc-labelled macroaggregated albumin. In this method, changes in the distribution of pulmonary perfusion caused by gravitational effects, namely, changes in the total count ratios of the right lung against the left lung between right and left lateral decubitus positions (rt/lt), were assessed in 62 patients and in 10 normal subjects. The rt/lt ratios were calculated as indices of the above changes. They correlated significantly with mean pulmonary arterial pressure (mPAP) (γ=-0.62, P<0.001), pulmonary capillary wedge pressure (γ=-0.63, P<0.001) and pulmonary arteriolar resistance (γ=0.50, P<0.001) in all subjects. In 17 patients with valvular heart diseases, the ratio correlated significantly with mPAP (γ=-0.84, P<0.001). In 10 patients with various heart diseases, the U/S ratio, i.e. the index of changes in the count ratios of the upper field against the lower field for the right lung following postural change from the uprigth to the supine position, was also obtained as well as the rt/lt ratio. The latter evidenced a better correlation with mPAP (γ=-0.90, P<0.001) than the former (γ=-0.64, P<0.05). We conclude that this method is valuable as a noninvasive approach for the estimation of pulmonary hypertension. (orig.)
International Nuclear Information System (INIS)
Désert, Jean-Michel; Brown, Timothy M.; Charbonneau, David; Torres, Guillermo; Fressin, François; Ballard, Sarah; Latham, David W.; Bryson, Stephen T.; Borucki, William J.; Knutson, Heather A.; Batalha, Natalie M.; Deming, Drake; Ford, Eric B.; Fortney, Jonathan J.; Gilliland, Ronald L.; Seager, Sara
2015-01-01
NASA’s Kepler mission has provided several thousand transiting planet candidates during the 4 yr of its nominal mission, yet only a small subset of these candidates have been confirmed as true planets. Therefore, the most fundamental question about these candidates is the fraction of bona fide planets. Estimating the rate of false positives of the overall Kepler sample is necessary to derive the planet occurrence rate. We present the results from two large observational campaigns that were conducted with the Spitzer Space Telescope during the the Kepler mission. These observations are dedicated to estimating the false positive rate (FPR) among the Kepler candidates. We select a sub-sample of 51 candidates, spanning wide ranges in stellar, orbital, and planetary parameter space, and we observe their transits with Spitzer at 4.5 μm. We use these observations to measures the candidate’s transit depths and infrared magnitudes. An authentic planet produces an achromatic transit depth (neglecting the modest effect of limb darkening). Conversely a bandpass-dependent depth alerts us to the potential presence of a blending star that could be the source of the observed eclipse: a false positive scenario. For most of the candidates (85%), the transit depths measured with Kepler are consistent with the transit depths measured with Spitzer as expected for planetary objects, while we find that the most discrepant measurements are due to the presence of unresolved stars that dilute the photometry. The Spitzer constraints on their own yield FPRs between 5% and depending on the Kepler Objects of Interest. By considering the population of the Kepler field stars, and by combining follow-up observations (imaging) when available, we find that the overall FPR of our sample is low. The measured upper limit on the FPR of our sample is 8.8% at a confidence level of 3σ. This observational result, which uses the achromatic property of planetary transit signals that is not investigated
Energy Technology Data Exchange (ETDEWEB)
Désert, Jean-Michel; Brown, Timothy M. [CASA, Department of Astrophysical and Planetary Sciences, University of Colorado, 389-UCB, Boulder, CO 80309 (United States); Charbonneau, David; Torres, Guillermo; Fressin, François; Ballard, Sarah; Latham, David W. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Bryson, Stephen T.; Borucki, William J. [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Knutson, Heather A. [Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 (United States); Batalha, Natalie M. [San Jose State University, San Jose, CA 95192 (United States); Deming, Drake [Department of Astronomy, University of Maryland, College Park, MD 20742-2421 (United States); Ford, Eric B. [University of Florida, Gainesville, FL 32611 (United States); Fortney, Jonathan J. [Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States); Gilliland, Ronald L. [Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802 (United States); Seager, Sara, E-mail: desert@colorado.edu [Massachusetts Institute of Technology, Cambridge, MA 02159 (United States)
2015-05-01
NASA’s Kepler mission has provided several thousand transiting planet candidates during the 4 yr of its nominal mission, yet only a small subset of these candidates have been confirmed as true planets. Therefore, the most fundamental question about these candidates is the fraction of bona fide planets. Estimating the rate of false positives of the overall Kepler sample is necessary to derive the planet occurrence rate. We present the results from two large observational campaigns that were conducted with the Spitzer Space Telescope during the the Kepler mission. These observations are dedicated to estimating the false positive rate (FPR) among the Kepler candidates. We select a sub-sample of 51 candidates, spanning wide ranges in stellar, orbital, and planetary parameter space, and we observe their transits with Spitzer at 4.5 μm. We use these observations to measures the candidate’s transit depths and infrared magnitudes. An authentic planet produces an achromatic transit depth (neglecting the modest effect of limb darkening). Conversely a bandpass-dependent depth alerts us to the potential presence of a blending star that could be the source of the observed eclipse: a false positive scenario. For most of the candidates (85%), the transit depths measured with Kepler are consistent with the transit depths measured with Spitzer as expected for planetary objects, while we find that the most discrepant measurements are due to the presence of unresolved stars that dilute the photometry. The Spitzer constraints on their own yield FPRs between 5% and depending on the Kepler Objects of Interest. By considering the population of the Kepler field stars, and by combining follow-up observations (imaging) when available, we find that the overall FPR of our sample is low. The measured upper limit on the FPR of our sample is 8.8% at a confidence level of 3σ. This observational result, which uses the achromatic property of planetary transit signals that is not investigated
Brouard , Olivier; Delannay , Fabrice; Ricordel , Vincent; Barba , Dominique
2007-01-01
4 pages; International audience; Motion segmentation methods are effective for tracking video objects. However, objects segmentation methods based on motion need to know the global motion of the video in order to back-compensate it before computing the segmentation. In this paper, we propose a method which estimates the global motion of a High Definition (HD) video shot and then segments it using the remaining motion information. First, we develop a fast method for multi-resolution motion est...
Directory of Open Access Journals (Sweden)
Nils Ternès
2017-05-01
Full Text Available Abstract Background Thanks to the advances in genomics and targeted treatments, more and more prediction models based on biomarkers are being developed to predict potential benefit from treatments in a randomized clinical trial. Despite the methodological framework for the development and validation of prediction models in a high-dimensional setting is getting more and more established, no clear guidance exists yet on how to estimate expected survival probabilities in a penalized model with biomarker-by-treatment interactions. Methods Based on a parsimonious biomarker selection in a penalized high-dimensional Cox model (lasso or adaptive lasso, we propose a unified framework to: estimate internally the predictive accuracy metrics of the developed model (using double cross-validation; estimate the individual survival probabilities at a given timepoint; construct confidence intervals thereof (analytical or bootstrap; and visualize them graphically (pointwise or smoothed with spline. We compared these strategies through a simulation study covering scenarios with or without biomarker effects. We applied the strategies to a large randomized phase III clinical trial that evaluated the effect of adding trastuzumab to chemotherapy in 1574 early breast cancer patients, for which the expression of 462 genes was measured. Results In our simulations, penalized regression models using the adaptive lasso estimated the survival probability of new patients with low bias and standard error; bootstrapped confidence intervals had empirical coverage probability close to the nominal level across very different scenarios. The double cross-validation performed on the training data set closely mimicked the predictive accuracy of the selected models in external validation data. We also propose a useful visual representation of the expected survival probabilities using splines. In the breast cancer trial, the adaptive lasso penalty selected a prediction model with 4
Robust Portfolio Optimization Using Pseudodistances
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948
Directory of Open Access Journals (Sweden)
Byung-Keun Song
2017-10-01
Full Text Available This paper presents a new fuzzy sliding mode controller (FSMC to improve control performances in the presence of uncertainties related to model errors and external disturbance (UAD. As a first step, an adaptive control law is designed using Lyapunov stability analysis. The control law can update control parameters of the FSMC with a disturbance estimator (DE in which the closed-loop stability and finite-time convergence of tracking error are guaranteed. A solution for estimating the compensative quantity of the impact of UAD on a control system and a set of solutions are then presented in order to avoid the singular cases of the fuzzy-based function approximation, increase convergence ability, and reduce the calculating cost. Subsequently, the effectiveness of the proposed controller is verified through the investigation of vibration control performances of a semi-active vehicle suspension system featuring a magnetorheological damper (MRD. It is shown that the proposed controller can provide better control ability of vibration control with lower consumed power compared with two existing fuzzy sliding mode controllers.
Beretta, Elisa; De Momi, Elena; Camomilla, Valentina; Cereatti, Andrea; Cappozzo, Aurelio; Ferrigno, Giancarlo
2014-09-01
In computer-assisted knee surgery, the accuracy of the localization of the femur centre of rotation relative to the hip-bone (hip joint centre) is affected by the unavoidable and untracked pelvic movements because only the femoral pose is acquired during passive pivoting manoeuvres. We present a dual unscented Kalman filter algorithm that allows the estimation of the hip joint centre also using as input the position of a pelvic reference point that can be acquired with a skin marker placed on the hip, without increasing the invasiveness of the surgical procedure. A comparative assessment of the algorithm was carried out using data provided by in vitro experiments mimicking in vivo surgical conditions. Soft tissue artefacts were simulated and superimposed onto the position of a pelvic landmark. Femoral pivoting made of a sequence of star-like quasi-planar movements followed by a circumduction was performed. The dual unscented Kalman filter method proved to be less sensitive to pelvic displacements, which were shown to be larger during the manoeuvres in which the femur was more adducted. Comparable accuracy between all the analysed methods resulted for hip joint centre displacements smaller than 1 mm (error: 2.2 ± [0.2; 0.3] mm, median ± [inter-quartile range 25%; inter-quartile range 75%]) and between 1 and 6 mm (error: 4.8 ± [0.5; 0.8] mm) during planar movements. When the hip joint centre displacement exceeded 6 mm, the dual unscented Kalman filter proved to be more accurate than the other methods by 30% during multi-planar movements (error: 5.2 ± [1.2; 1] mm). © IMechE 2014.
Robust Inference with Multi-way Clustering
A. Colin Cameron; Jonah B. Gelbach; Douglas L. Miller; Doug Miller
2009-01-01
In this paper we propose a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g. Liang and Zeger (1986), Arellano (1987)) and relies on similar relatively weak distributional assumptions. Our...
Energy Technology Data Exchange (ETDEWEB)
Ozcan, Zehra [University Faculty of Medicine, Nuclear Medicine Department of Ege, Bornova, Izmir (Turkey); Anderson, Peter J.; Gordon, Isky [Great Ormond Street Hospital For Children, Department of Radiology, London (United Kingdom)
2006-06-15
The two methods recommended for estimation of differential renal function (DRF) in the renography guidelines published by the European Association of Nuclear Medicine are the area under the background-subtracted time-activity curves (AUCs) (often called the integral method) and the regression slope of the background-subtracted Rutland/Patlak plot analysis. The current study investigated the agreement/disagreement of DRF estimations obtained using these two techniques. This report also focusses on the occurrence of supranormal function of the affected kidney (defined as DRF >55%) and reviews the related technical and physiological factors. A total of 394 renographic studies in 101 children with a prenatal diagnosis of unilateral renal pelvic dilatation confirmed on postnatal studies were retrieved from optical disc and reprocessed by one author. DRF was calculated using the Rutland/Patlak plot and the AUC over the time period 40-120 s following an injection of{sup 99m}Tc-mercaptoacetyltriglycine. The difference in DRF between the methods (Rutland/Patlak minus AUC) and 95% limits of agreement were calculated. The age distribution of the difference between the methods was also analysed. For all 394 measurements the mean difference was -0.8% (range -21.0% to 16.9%, SD 3.9%). The 95% limits of agreement were -7.0% to 8.6%. Analysis of the data revealed that greater spread of DRF between the techniques was seen in studies performed at a younger age: a discrepancy of >5% DRF was significantly more common in those <1 year of age than in those >1 year old (25.3% vs 9.9%; chi-square, p<0.0005). Supranormal function was found less frequently using the Rutland/Patlak method than with the AUC method (8.4% vs 11.2%; chi-square, p<0.0005). The frequency of this diagnosis was reduced to 4.6% when both methods were required to be in agreement. (orig.)
Star, L.
2008-01-01
The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust
Klos, A.; Bogusz, J.; Moreaux, G.
2017-12-01
This research focuses on the investigation of the deterministic and stochastic parts of the DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) weekly coordinate time series from the IDS contribution to the ITRF2014A set of 90 stations was divided into three groups depending on when the data was collected at an individual station. To reliably describe the DORIS time series, we employed a mathematical model that included the long-term nonlinear signal, linear trend, seasonal oscillations (these three sum up to produce the Polynomial Trend Model) and a stochastic part, all being resolved with Maximum Likelihood Estimation (MLE). We proved that the values of the parameters delivered for DORIS data are strictly correlated with the time span of the observations, meaning that the most recent data are the most reliable ones. Not only did the seasonal amplitudes decrease over the years, but also, and most importantly, the noise level and its type changed significantly. We examined five different noise models to be applied to the stochastic part of the DORIS time series: a pure white noise (WN), a pure power-law noise (PL), a combination of white and power-law noise (WNPL), an autoregressive process of first order (AR(1)) and a Generalized Gauss Markov model (GGM). From our study it arises that the PL process may be chosen as the preferred one for most of the DORIS data. Moreover, the preferred noise model has changed through the years from AR(1) to pure PL with few stations characterized by a positive spectral index.
International Nuclear Information System (INIS)
Gogolak, C.V.
1986-11-01
The concentration of a contaminant measured in a particular medium might be distributed as a positive random variable when it is present, but it may not always be present. If there is a level below which the concentration cannot be distinguished from zero by the analytical apparatus, a sample from such a population will be censored on the left. The presence of both zeros and positive values in the censored portion of such samples complicates the problem of estimating the parameters of the underlying positive random variable and the probability of a zero observation. Using the method of maximum likelihood, it is shown that the solution to this estimation problem reduces largely to that of estimating the parameters of the distribution truncated at the point of censorship. The maximum likelihood estimate of the proportion of zero values follows directly. The derivation of the maximum likelihood estimates for a lognormal population with zeros is given in detail, and the asymptotic properties of the estimates are examined. The estimation method was used to fit several different distributions to a set of severely censored 85 Kr monitoring data from six locations at the Savannah River Plant chemical separations facilities
Directory of Open Access Journals (Sweden)
Prusik Katerina
2011-09-01
Full Text Available In the article materials of the three-year looking are utillized after the state of positive health of group of women in age 50-80 years. The method of statistical ground of adequate control indexes is shown for the estimation of bodily condition of inspected. The use of high-quality criteria is offered for the estimation of efficiency of physical exercises on the Norwegian method of walking with sticks.
Härkänen, Tommi; Kaikkonen, Risto; Virtala, Esa; Koskinen, Seppo
2014-11-06
To assess the nonresponse rates in a questionnaire survey with respect to administrative register data, and to correct the bias statistically. The Finnish Regional Health and Well-being Study (ATH) in 2010 was based on a national sample and several regional samples. Missing data analysis was based on socio-demographic register data covering the whole sample. Inverse probability weighting (IPW) and doubly robust (DR) methods were estimated using the logistic regression model, which was selected using the Bayesian information criteria. The crude, weighted and true self-reported turnout in the 2008 municipal election and prevalences of entitlements to specially reimbursed medication, and the crude and weighted body mass index (BMI) means were compared. The IPW method appeared to remove a relatively large proportion of the bias compared to the crude prevalence estimates of the turnout and the entitlements to specially reimbursed medication. Several demographic factors were shown to be associated with missing data, but few interactions were found. Our results suggest that the IPW method can improve the accuracy of results of a population survey, and the model selection provides insight into the structure of missing data. However, health-related missing data mechanisms are beyond the scope of statistical methods, which mainly rely on socio-demographic information to correct the results.
Robust Control Charts for Time Series Data
Croux, C.; Gelper, S.; Mahieu, K.
2010-01-01
This article presents a control chart for time series data, based on the one-step- ahead forecast errors of the Holt-Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain
Bundschuh, Mirco; Newman, Michael C; Zubrod, Jochen P; Seitz, Frank; Rosenfeldt, Ricki R; Schulz, Ralf
2015-03-01
We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.
Robust Models for Operator Workload Estimation
2015-03-01
piloted aircraft (RPA) simultaneously, a vast improvement in resource utilization compared to existing operations that require several operators per...into distinct cognitive channels (visual, auditory, spatial, etc.) based on our ability to multitask effectively as long as no one channel is
Energy Technology Data Exchange (ETDEWEB)
Holden, Jacob [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wood, Eric W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhu, Lei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gonder, Jeffrey D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Tian, Ye [Metropia, Inc.
2017-09-15
A data-driven technique for estimation of energy requirements for a proposed vehicle trip has been developed. Based on over 700,000 miles of driving data, the technique has been applied to generate a model that estimates trip energy requirements. The model uses a novel binning approach to categorize driving by road type, traffic conditions, and driving profile. The trip-level energy estimations can easily be aggregated to any higher-level transportation system network desired. The model has been tested and validated on the Austin, Texas, data set used to build this model. Ground-truth energy consumption for the data set was obtained from Future Automotive Systems Technology Simulator (FASTSim) vehicle simulation results. The energy estimation model has demonstrated 12.1 percent normalized total absolute error. The energy estimation from the model can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations, to reduce energy consumption. The model can also be used to determine more accurate energy consumption of regional or national transportation networks if trip origin and destinations are known. Additionally, this method allows the estimation tool to be tuned to a specific driver or vehicle type.
Robustness of Structural Systems
DEFF Research Database (Denmark)
Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.
2007-01-01
The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...
Identification of Dynamically Positioned Ships
Directory of Open Access Journals (Sweden)
Thor I. Fossen
1996-04-01
Full Text Available Todays model-based dynamic positioning (DP systems require that the ship and thruster dynamics are known with some accuracy in order to use linear quadratic optical control theory. However, it is difficult to identify the mathematical model of a dynamically posititmed (DP ship since the ship is not persistently excited under DP. In addition the ship parameter estimation problem is nonlinear and multivariable with only position and thruster state measurements available for parameter estimation. The process and measurement noise must also be modeled in order to avoid parameter drift due to environmental disturbances and sensor failure. This article discusses an off-line parallel extended Kalman filter (EKF algorithm utilizing two measurement series in parallel to estimate the parameters in the DP ship model. Full-scale experiments with a supply vessel are used to demonstrate the convergence and robustness of the proposed parameter estimator.
DEFF Research Database (Denmark)
Nakagawa, F; Delpech, V; Albert, J
2017-01-01
were undiagnosed respectively. CONCLUSION: We have shown a working example to characterize the HIV population in a European context which incorporates migrants from countries with generalized epidemics. Despite all aspects of HIV care being free and widely available to anyone in need in the UK......OBJECTIVE: Migrants account for a significant number of people living with HIV in Europe, and it is important to fully consider this population in national estimates. Using a novel approach with the UK as an example, we present key public health measures of the HIV epidemic, taking into account...... of these people, 24 600 (15 000-36 200) were estimated to be undiagnosed; this number has remained stable over the last decade. An estimated 32% of the total undiagnosed population had CD4 cell count less than 350 cells/μl in 2013. Twenty-five and 23% of black African men and women heterosexuals living with HIV...
Ronald E. McRoberts
2010-01-01
Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...
An Overview of the Adaptive Robust DFT
Directory of Open Access Journals (Sweden)
Djurović Igor
2010-01-01
Full Text Available Abstract This paper overviews basic principles and applications of the robust DFT (RDFT approach, which is used for robust processing of frequency-modulated (FM signals embedded in non-Gaussian heavy-tailed noise. In particular, we concentrate on the spectral analysis and filtering of signals corrupted by impulsive distortions using adaptive and nonadaptive robust estimators. Several adaptive estimators of location parameter are considered, and it is shown that their application is preferable with respect to non-adaptive counterparts. This fact is demonstrated by efficiency comparison of adaptive and nonadaptive RDFT methods for different noise environments.
Petersen, Andrea K; Cheung, Sau Wai; Smith, Janice L; Bi, Weimin; Ward, Patricia A; Peacock, Sandra; Braxton, Alicia; Van Den Veyver, Ignatia B; Breman, Amy M
2017-12-01
Since its debut in 2011, cell-free fetal DNA screening has undergone rapid expansion with respect to both utilization and coverage. However, conclusive data regarding the clinical validity and utility of this screening tool, both for the originally included common autosomal and sex-chromosomal aneuploidies as well as the more recently added chromosomal microdeletion syndromes, have lagged behind. Thus, there is a continued need to educate clinicians and patients about the current benefits and limitations of this screening tool to inform pre- and posttest counseling, pre/perinatal decision making, and medical risk assessment/management. The objective of this study was to determine the positive predictive value and false-positive rates for different chromosomal abnormalities identified by cell-free fetal DNA screening using a large data set of diagnostic testing results on invasive samples submitted to the laboratory for confirmatory studies. We tested 712 patient samples sent to our laboratory to confirm a cell-free fetal DNA screening result, indicating high risk for a chromosome abnormality. We compiled data from all cases in which the indication for confirmatory testing was a positive cell-free fetal DNA screen, including the common trisomies, sex chromosomal aneuploidies, microdeletion syndromes, and other large genome-wide copy number abnormalities. Testing modalities included fluorescence in situ hybridization, G-banded karyotype, and/or chromosomal microarray analysis performed on chorionic villus samples, amniotic fluid, or postnatally obtained blood samples. Positive predictive values and false-positive rates were calculated from tabulated data. The positive predictive values for trisomy 13, 18, and 21 were consistent with previous reports at 45%, 76%, and 84%, respectively. For the microdeletion syndrome regions, positive predictive values ranged from 0% for detection of Cri-du-Chat syndrome and Prader-Willi/Angelman syndrome to 14% for 1p36 deletion
DEFF Research Database (Denmark)
Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard
2011-01-01
In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...
DEFF Research Database (Denmark)
Jensen, Bente Rona; Hovgaard-Hansen, Line; Cappelen, Katrine Louise
2016-01-01
Running on a lower-body positive pressure (LBPP) treadmill allows effects of weight support on leg muscle activation to be assessed systematically, and has the potential to facilitate rehabilitation and prevent overloading. The aim was to study the effect of running with weight support on leg mus...
Faber, G.S.; Kingma, I.; van Dieen, J.H.
2010-01-01
L5/S1, hip and knee moments during manual lifting tasks are, in a laboratory environment, frequently established by bottom-up inverse dynamics, using force plates to measure ground reaction forces (GRFs) and an optoelectronic system to measure segment positions and orientations. For field
Nakagawa, Fumiyo
2017-01-28
Migrants account for a significant number of people living with HIV in Europe, and it is important to fully consider this population in national estimates. Using a novel approach with the UK as an example, we present key public health measures of the HIV epidemic, taking into account both in-country infections and infections likely to have been acquired abroad. Mathematical model calibrated to extensive data sources. An individual-based stochastic simulation model is used to calibrate to routinely collected surveillance data in the UK. Data on number of new HIV diagnoses, number of deaths, CD4 cell count at diagnosis, as well as time of arrival into the UK for migrants and the annual number of people receiving care were used. An estimated 106 400 (90% plausibility range: 88 700-124 600) people were living with HIV in the UK in 2013. Twenty-three percent of these people, 24 600 (15 000-36 200) were estimated to be undiagnosed; this number has remained stable over the last decade. An estimated 32% of the total undiagnosed population had CD4 cell count less than 350 cells/μl in 2013. Twenty-five and 23% of black African men and women heterosexuals living with HIV were undiagnosed respectively. We have shown a working example to characterize the HIV population in a European context which incorporates migrants from countries with generalized epidemics. Despite all aspects of HIV care being free and widely available to anyone in need in the UK, there is still a substantial number of people who are not yet diagnosed and thus not in care.
Doppelhofer, Gernot; Weeks, Melvyn
2011-01-01
This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...
Bishop , Matt; Elliott , Chip
2011-01-01
Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.
Robust procedures in chemometrics
DEFF Research Database (Denmark)
Kotwa, Ewelina
properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...
Directory of Open Access Journals (Sweden)
Fernando Augusto de Souza
2014-07-01
Full Text Available The aim of this research was to evaluate the influence of the number and position of nutrient levels used in dose-response trials in the estimation of the optimal-level (OL and the goodness of fit on the models: quadratic polynomial (QP, exponential (EXP, linear response plateau (LRP and quadratic response plateau (QRP. It was used data from dose-response trials realized in FCAV-Unesp Jaboticabal considering the homogeneity of variances and normal distribution. The fit of the models were evaluated considered the following statistics: adjusted coefficient of determination (R²adj, coefficient of variation (CV and the sum of the squares of deviations (SSD.It was verified in QP and EXP models that small changes on the placement and distribution of the levels caused great changes in the estimation of the OL. The LRP model was deeply influenced by the absence or presence of the level between the response and stabilization phases (change in the straight to plateau. The QRP needed more levels on the response phase and the last level on stabilization phase to estimate correctly the plateau. It was concluded that the OL and the adjust of the models are dependent on the positioning and the number of the levels and the specific characteristics of each model, but levels defined near to the true requirement and not so spaced are better to estimate the OL.
Directory of Open Access Journals (Sweden)
Edgar Talavera
2018-01-01
Full Text Available In recent years, vehicular communications systems have evolved and allowed for the improvement of adaptive cruise control (ACC systems to make them cooperative (cooperative adaptive cruise control, CACC. Conventional ACC systems use sensors on the ego-vehicle, such as radar or computer vision, to generate their behavioral decisions. However, by having vehicle-to-X (V2X onboard communications, the need to incorporate perception in the vehicle is drastically reduced. Thus, in this paper a CACC solution is proposed that only uses communications to make its decisions with the help of previous road mapping. At the same time, a method to develop these maps is presented, combining the information of a computer vision system to correct the positions obtained from the navigation system. In addition, the cut-in and cut-out maneuvers for a CACC platoon are taken into account, showing the tests of these situations in real environments with instrumented vehicles. To show the potential of the system in a larger-scale implementation, simulations of the behavior are provided under dense traffic conditions where the positive impact on the reduction of traffic congestion and fuel consumption is appreciated.
A Robust Controller Structure for Pico-Satellite Applications
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Green, Martin; Kristensen, Mads
This paper describes the development of a robust controller structure for use in pico-satellite missions. The structure relies on unknown disturbance estimation and use of robust control theory to implement a system that is robust to both unmodeled disturbances and parameter uncertainties. As one...
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
Robustness of the ATLAS pixel clustering neural network algorithm
AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration
2016-01-01
Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. The algorithms depend heavily on accurate estimation of the position of particles as they traverse the inner detector elements. An artificial neural network algorithm is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The method recovers otherwise lost tracks in dense environments where particles are separated by distances comparable to the size of the detector read-out elements. Such environments are highly relevant for LHC run 2, e.g. in searches for heavy resonances. Within the scope of run 2 track reconstruction performance and upgrades, the robustness of the neural network algorithm will be presented. The robustness has been studied by evaluating the stability of the algorithm’s performance under a range of variations in the pixel detector conditions.
Directory of Open Access Journals (Sweden)
Michael B Arndt
Full Text Available BACKGROUND: Traditional methods using microscopy for the detection of helminth infections have limited sensitivity. Polymerase chain reaction (PCR assays enhance detection of helminths, particularly low burden infections. However, differences in test performance may modify the ability to detect associations between helminth infection, risk factors, and sequelae. We compared these associations using microscopy and PCR. METHODS: This cross-sectional study was nested within a randomized clinical trial conducted at 3 sites in Kenya. We performed microscopy and real-time multiplex PCR for the stool detection and quantification of Ascaris lumbricoides, Necator americanus, Ancylostoma duodenale, Strongyloides stercoralis, and Schistosoma species. We utilized regression to evaluate associations between potential risk factors or outcomes and infection as detected by either method. RESULTS: Of 153 HIV-positive adults surveyed, 55(36.0% and 20(13.1% were positive for one or more helminth species by PCR and microscopy, respectively (p<0.001. PCR-detected infections were associated with farming (Prevalence Ratio 1.57, 95% CI: 1.02, 2.40, communal water source (PR 3.80, 95% CI: 1.01, 14.27, and no primary education (PR 1.54, 95% CI: 1.14, 2.33, whereas microscopy-detected infections were not associated with any risk factors under investigation. Microscopy-detected infections were associated with significantly lower hematocrit and hemoglobin (means of -3.56% and -0.77 g/dl and a 48% higher risk of anemia (PR 1.48, 95% CI: 1.17, 1.88 compared to uninfected. Such associations were absent for PCR-detected infections unless infection intensity was considered, Infections diagnosed with either method were associated with increased risk of eosinophilia (PCR PR 2.42, 95% CI: 1.02, 5.76; microscopy PR 2.92, 95% CI: 1.29, 6.60. CONCLUSION: Newer diagnostic methods, including PCR, improve the detection of helminth infections. This heightened sensitivity may improve the
Directory of Open Access Journals (Sweden)
Li Sun
2017-01-01
Full Text Available Exfoliation of oxide scales from high-temperature heating surfaces of power boilers threatened the safety of supercritical power generating units. According to available space model, the oxidation kinetics of two ferritic-martensitic steels are developed to predict in supercritical water at 400°C, 500°C, and 600°C. The iron diffusion coefficients in magnetite and Fe-Cr spinel are extrapolated from studies of Backhaus and Töpfer. According to Fe-Cr-O ternary phase diagram, oxygen partial pressure at the steel/Fe-Cr spinel oxide interface is determined. The oxygen partial pressure at the magnetite/supercritical water interface meets the equivalent oxygen partial pressure when system equilibrium has been attained. The relative error between calculated values and experimental values is analyzed and the reasons of error are suggested. The research results show that the results of simulation at 600°C are approximately close to experimental results. The iron diffusion coefficient is discontinuous in the duplex scale of two ferritic-martensitic steels. The simulation results of thicknesses of the oxide scale on tubes (T91 of final superheater of a 600 MW supercritical boiler are compared with field measurement data and calculation results by Adrian’s method. The calculated void positions of oxide scales are in good agreement with a cross-sectional SEM image of the oxide layers.
Robustness Beamforming Algorithms
Directory of Open Access Journals (Sweden)
Sajad Dehghani
2014-04-01
Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.
Robust inference in sample selection models
Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio
2015-01-01
The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.
Robust inference in sample selection models
Zhelonkin, Mikhail
2015-11-20
The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.
Robust statistics and geochemical data analysis
International Nuclear Information System (INIS)
Di, Z.
1987-01-01
Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures
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...
Robustness Metrics: Consolidating the multiple approaches to quantify Robustness
DEFF Research Database (Denmark)
Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.
2016-01-01
robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2008-01-01
This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...
DEFF Research Database (Denmark)
Vrouwenvelder, T.; Sørensen, John Dalsgaard
2009-01-01
After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....
Robust Approaches to Forecasting
Jennifer Castle; David Hendry; Michael P. Clements
2014-01-01
We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...
Robustness - theoretical framework
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.
2010-01-01
More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new struct...... of this fact sheet is to describe a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines....
Design principles for robust oscillatory behavior.
Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M
2015-09-01
Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.
Robust bayesian analysis of an autoregressive model with ...
African Journals Online (AJOL)
In this work, robust Bayesian analysis of the Bayesian estimation of an autoregressive model with exponential innovations is performed. Using a Bayesian robustness methodology, we show that, using a suitable generalized quadratic loss, we obtain optimal Bayesian estimators of the parameters corresponding to the ...
Mett, Tobias R; Krezdorn, Nicco; Luketina, Rosalia; Boyce, Maria K; Henseler, Helga; Ipaktchi, Ramin; Vogt, Peter M
2017-12-01
without a statistically significant impact. The intuitive determination of the NACs is a challenge for the plastic surgeon. In this study, a statistically significant deviation was seen in almost all dimensions, although the clinical relevance cannot be conclusively assessed. We found a positional relationship of the NAC to the infraclavicular groove ("Mohrenheim pit") in the vertical and 4-4.5 cm above the submammary fold. The position of the NAC can be satisfactorily determined by a combination of plastic surgical intuition, patient wishes and practical metric methods using the Mohrenheim-Estimated-Tangential-Tracking-Line (METT-Line). This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to Table of Contents or the online Instructions to Authors www.springer.com/00266 .
International Nuclear Information System (INIS)
McGee, Kiaran P.; Fein, Douglas A.; Hanlon, Alex L.; Schultheiss, Timothy E.; Fowble, Barbara L.
1997-01-01
Purpose: To determine if portal setup films are an accurate representation of a patient's position throughout the course of fractionated tangential breast irradiation. Methods and Materials: Thirteen patients undergoing external beam irradiation for T1-T2 infiltrating ductal carcinoma of the breast following excisional biopsy and axillary dissection were imaged using an on-line portal imaging device attached to a 6 MV linear accelerator. Medial and lateral tangential fields were imaged and a total of 139 fractions, 225 portal fields, and 4450 images were obtained. Interfractional and intrafractional variations for anatomical parameters including the central lung distance (CLD), central flash distance (CFD), and inferior central margin (ICM) were calculated from these images. A pooled estimate of the random error associated with a given treatment was determined by adding the interfractional and intrafractional standard deviations in quadrature. A 95% confidence level assigned a value of two standard deviations of the random error estimate. Central lung distance, CFD, and ICM distances were then measured for all portal setup films. Significant differences were defined as occurring when the simulation-setup difference was greater than the 95% confidence value. Results: Differences between setup portal and simulation films were less than their 95% confidence values in 70 instances indicating that in 90% of the time these differences are a result of random differences in daily treatment positioning. Conclusions: In 90% of cases tested, initial portal setup films are an accurate representation of a patients daily treatment setup
Sriboonchitta, Songsak; Huynh, Van-Nam
2017-01-01
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
2013-01-01
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...
Chu, Haitao; Zhou, Yijie; Cole, Stephen R.; Ibrahim, Joseph G.
2010-01-01
Summary To evaluate the probabilities of a disease state, ideally all subjects in a study should be diagnosed by a definitive diagnostic or gold standard test. However, since definitive diagnostic tests are often invasive and expensive, it is generally unethical to apply them to subjects whose screening tests are negative. In this article, we consider latent class models for screening studies with two imperfect binary diagnostic tests and a definitive categorical disease status measured only for those with at least one positive screening test. Specifically, we discuss a conditional independent and three homogeneous conditional dependent latent class models and assess the impact of misspecification of the dependence structure on the estimation of disease category probabilities using frequentist and Bayesian approaches. Interestingly, the three homogeneous dependent models can provide identical goodness-of-fit but substantively different estimates for a given study. However, the parametric form of the assumed dependence structure itself is not “testable” from the data, and thus the dependence structure modeling considered here can only be viewed as a sensitivity analysis concerning a more complicated non-identifiable model potentially involving heterogeneous dependence structure. Furthermore, we discuss Bayesian model averaging together with its limitations as an alternative way to partially address this particularly challenging problem. The methods are applied to two cancer screening studies, and simulations are conducted to evaluate the performance of these methods. In summary, further research is needed to reduce the impact of model misspecification on the estimation of disease prevalence in such settings. PMID:20191614
International Nuclear Information System (INIS)
Epstein, Ariel; Tessler, Nir; Einziger, Pinchas D.; Roberts, Matthew
2014-01-01
We present an analytical method for evaluating the first and second moments of the effective exciton spatial distribution in organic light-emitting diodes (OLED) from measured emission patterns. Specifically, the suggested algorithm estimates the emission zone mean position and width, respectively, from two distinct features of the pattern produced by interference between the emission sources and their images (induced by the reflective cathode): the angles in which interference extrema are observed, and the prominence of interference fringes. The relations between these parameters are derived rigorously for a general OLED structure, indicating that extrema angles are related to the mean position of the radiating excitons via Bragg's condition, and the spatial broadening is related to the attenuation of the image-source interference prominence due to an averaging effect. The method is applied successfully both on simulated emission patterns and on experimental data, exhibiting a very good agreement with the results obtained by numerical techniques. We investigate the method performance in detail, showing that it is capable of producing accurate estimations for a wide range of source-cathode separation distances, provided that the measured spectral interval is large enough; guidelines for achieving reliable evaluations are deduced from these results as well. As opposed to numerical fitting tools employed to perform similar tasks to date, our approximate method explicitly utilizes physical intuition and requires far less computational effort (no fitting is involved). Hence, applications that do not require highly resolved estimations, e.g., preliminary design and production-line verification, can benefit substantially from the analytical algorithm, when applicable. This introduces a novel set of efficient tools for OLED engineering, highly important in the view of the crucial role the exciton distribution plays in determining the device performance.
Energy Technology Data Exchange (ETDEWEB)
Epstein, Ariel, E-mail: ariel.epstein@utoronto.ca; Tessler, Nir, E-mail: nir@ee.technion.ac.il; Einziger, Pinchas D. [Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa 32000 (Israel); Roberts, Matthew, E-mail: mroberts@cdtltd.co.uk [Cambridge Display Technology Ltd, Building 2020, Cambourne Business Park, Cambourne, Cambridgeshire CB23 6DW (United Kingdom)
2014-06-14
We present an analytical method for evaluating the first and second moments of the effective exciton spatial distribution in organic light-emitting diodes (OLED) from measured emission patterns. Specifically, the suggested algorithm estimates the emission zone mean position and width, respectively, from two distinct features of the pattern produced by interference between the emission sources and their images (induced by the reflective cathode): the angles in which interference extrema are observed, and the prominence of interference fringes. The relations between these parameters are derived rigorously for a general OLED structure, indicating that extrema angles are related to the mean position of the radiating excitons via Bragg's condition, and the spatial broadening is related to the attenuation of the image-source interference prominence due to an averaging effect. The method is applied successfully both on simulated emission patterns and on experimental data, exhibiting a very good agreement with the results obtained by numerical techniques. We investigate the method performance in detail, showing that it is capable of producing accurate estimations for a wide range of source-cathode separation distances, provided that the measured spectral interval is large enough; guidelines for achieving reliable evaluations are deduced from these results as well. As opposed to numerical fitting tools employed to perform similar tasks to date, our approximate method explicitly utilizes physical intuition and requires far less computational effort (no fitting is involved). Hence, applications that do not require highly resolved estimations, e.g., preliminary design and production-line verification, can benefit substantially from the analytical algorithm, when applicable. This introduces a novel set of efficient tools for OLED engineering, highly important in the view of the crucial role the exciton distribution plays in determining the device performance.
DEFF Research Database (Denmark)
Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas
2014-01-01
Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...
Borghi, Giacomo; Tabacchini, Valerio; Seifert, Stefan; Schaart, Dennis R.
2015-02-01
Monolithic scintillator detectors can achieve excellent spatial resolution and coincidence resolving time. However, their practical use for positron emission tomography (PET) and other applications in the medical imaging field is still limited due to drawbacks of the different methods used to estimate the position of interaction. Common statistical methods for example require the collection of an extensive dataset of reference events with a narrow pencil beam aimed at a fine grid of reference positions. Such procedures are time consuming and not straightforwardly implemented in systems composed of many detectors. Here, we experimentally demonstrate for the first time a new calibration procedure for k-nearest neighbor ( k-NN) position estimation that utilizes reference data acquired with a fan beam. The procedure is tested on two detectors consisting of 16 mm ×16 mm ×10 mm and 16 mm ×16 mm ×20 mm monolithic, Ca-codoped LSO:Ce crystals and digital photon counter (DPC) arrays. For both detectors, the spatial resolution and the bias obtained with the new method are found to be practically the same as those obtained with the previously used method based on pencil-beam irradiation, while the calibration time is reduced by a factor of 20. Specifically, a FWHM of 1.1 mm and a FWTM of 2.7 mm were obtained using the fan-beam method with the 10 mm crystal, whereas a FWHM of 1.5 mm and a FWTM of 6 mm were achieved with the 20 mm crystal. Using a fan beam made with a 4.5 MBq 22Na point-source and a tungsten slit collimator with 0.5 mm aperture, the total measurement time needed to acquire the reference dataset was 3 hours for the thinner crystal and 2 hours for the thicker one.