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Sample records for filter fitted tracks

  1. Kalman Filter Track Fits and Track Breakpoint Analysis

    Astier, Pierre; Cousins, R D; Letessier-Selvon, A A; Popov, B A; Vinogradova, T G; Astier, Pierre; Cardini, Alessandro; Cousins, Robert D.; Letessier-Selvon, Antoine; Popov, Boris A.; Vinogradova, Tatiana

    2000-01-01

    We give an overview of track fitting using the Kalman filter method in the NOMAD detector at CERN, and emphasize how the wealth of by-product information can be used to analyze track breakpoints (discontinuities in track parameters caused by scattering, decay, etc.). After reviewing how this information has been previously exploited by others, we describe extensions which add power to breakpoint detection and characterization. We show how complete fits to the entire track, with breakpoint parameters added, can be easily obtained from the information from unbroken fits. Tests inspired by the Fisher F-test can then be used to judge breakpoints. Signed quantities (such as change in momentum at the breakpoint) can supplement unsigned quantities such as the various chisquares. We illustrate the method with electrons from real data, and with Monte Carlo simulations of pion decays.

  2. Parallel Kalman filter track fit based on vector classes

    Kisel, Ivan [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH (Germany); Kretz, Matthias [Kirchhoff-Institut fuer Physik, Ruprecht-Karls Universitaet, Heidelberg (Germany); Kulakov, Igor [Goethe-Universitaet, Frankfurt am Main (Germany); National Taras Shevchenko University, Kyiv (Ukraine)

    2010-07-01

    Modern high energy physics experiments have to process terabytes of input data produced in particle collisions. The core of the data reconstruction in high energy physics is the Kalman filter. Therefore, developing the fast Kalman filter algorithm, which uses maximum available power of modern processors, is important, in particular for initial selection of events interesting for the new physics. One of processors features, which can speed up the algorithm, is a SIMD instruction set, which allows to pack several data items in one register and operate on all of them in one go, thus achieving more operations per clock cycle. Therefore a flexible and useful interface, which uses the SIMD instruction set on different CPU and GPU processors architectures, has been realized as a vector classes library. The Kalman filter based track fitting algorithm has been implemented with use of the vector classes. Fitting quality tests show good results with the residuals equal to 49 {mu}m and 44 {mu}m for x and y track parameters and relative momentum resolution of 0.7%. The fitting time of 0.053 {mu}s per track has been achieved on Intel Xeon X5550 with 8 cores at 2.6 GHz by using in addition Intel Threading Building Blocks.

  3. Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

    Yun Wang

    2016-01-01

    Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

  4. Simultaneous pattern recognition and track fitting by the Kalman filtering method

    Billoir, P.

    1990-01-01

    A progressive pattern recognition algorithm based on the Kalman filtering method has been tested. The algorithm starts from a small track segment or from a fitted track of a neighbouring detector, then extends the candidate tracks by adding measured points one by one. The fitted parameters and weight matrix of the candidate track are updated when adding a point, and give an increasing precision on prediction of the next point. Thus, pattern recognition and track fitting can be accomplished simultaneously. The method has been implemented and tested for track reconstruction for the vertex detector of the ZEUS experiment at DESY. Detailed procedures of the method and its performance are presented. Its flexibility is described as well. (orig.)

  5. LHCb: Alignment of the LHCb Detector with Kalman Filter Fitted Tracks

    Amoraal, J; Hulsbergen, W; Needham, M; Nicolas, L; Pozzi, S; Raven, G; Vecchi, S

    2009-01-01

    We report on an implementation of a global chisquare algorithm for the simultaneous alignment of all tracking systems in the LHCb detector. Our algorithm uses hit residuals from the standard LHCb track fit which is based on a Kalman filter. The algorithm is implemented in the LHCb reconstruction framework and exploits the fact that all sensitive detector elements have the same geometry interface. A vertex constraint is implemented by fitting tracks to a common point and propagating the change in track parameters to the hit residuals. To remove unconstrained or poorly constrained degrees of freedom (so-called weak modes) the average movements of (subsets of) alignable detector elements can be fixed with Lagrange constraints. Alternatively, weak modes can be removed with a cutoff in the eigenvalue spectrum of the second derivative of the chisquare. As for all LHCb reconstruction and analysis software the configuration of the algorithm is done in python and gives detailed control over the selection of alignable ...

  6. Treatment of non-Gaussian tails of multiple Coulomb scattering in track fitting with a Gaussian-sum filter

    Strandlie, A.; Wroldsen, J.

    2006-01-01

    If any of the probability densities involved in track fitting deviate from the Gaussian assumption, it is plausible that a non-linear estimator which better takes the actual shape of the distribution into account can do better. One such non-linear estimator is the Gaussian-sum filter, which is adequate if the distributions under consideration can be approximated by Gaussian mixtures. The main purpose of this paper is to present a Gaussian-sum filter for track fitting, based on a two-component approximation of the distribution of angular deflections due to multiple scattering. In a simulation study within a linear track model the Gaussian-sum filter is shown to be a competitive alternative to the Kalman filter. Scenarios at various momenta and with various maximum number of components in the Gaussian-sum filter are considered. Particularly at low momenta the Gaussian-sum filter yields a better estimate of the uncertainties than the Kalman filter, and it is also slightly more precise than the latter

  7. Robust track fitting in the Belle II inner tracking detector

    Nadler, Moritz; Frühwirth, Rudolf

    2012-01-01

    Track fitting in the new inner tracker of the Belle II experiment uses the GENFIT package. In the latter both a standard Kalman filter and a robust extension, the deterministic annealing filter (DAF), are implemented. This contribution presents the results of a simulation experiment which examines the performance of the DAF in the inner tracker, in terms of outlier detection ability and of the impact of different kinds of background on the quality of the fitted tracks.

  8. Particle Filter Tracking without Dynamics

    Jaime Ortegon-Aguilar

    2007-01-01

    Full Text Available People tracking is an interesting topic in computer vision. It has applications in industrial areas such as surveillance or human-machine interaction. Particle Filters is a common algorithm for people tracking; challenging situations occur when the target's motion is poorly modelled or with unexpected motions. In this paper, an alternative to address people tracking is presented. The proposed algorithm is based in particle filters, but instead of using a dynamical model, it uses background subtraction to predict future locations of particles. The algorithm is able to track people in omnidirectional sequences with a low frame rate (one or two frames per second. Our approach can tackle unexpected discontinuities and changes in the direction of the motion. The main goal of the paper is to track people from laboratories, but it has applications in surveillance, mainly in controlled environments.

  9. Tracking speckle displacement by double Kalman filtering

    Donghui Li; Li Guo

    2006-01-01

    @@ A tracking technique using two sequentially-connected Kalman filter for tracking laser speckle displacement is presented. One Kalman filter tracks temporal speckle displacement, while another Kalman filter tracks spatial speckle displacement. The temporal Kalman filter provides a prior for the spatial Kalman filter, and the spatial Kalman filter provides measurements for the temporal Kalman filter. The contribution of a prior to estimations of the spatial Kalman filter is analyzed. An optical analysis system was set up to verify the double-Kalman-filter tracker's ability of tracking laser speckle's constant displacement.

  10. Kalman Filter Tracking on Parallel Architectures

    Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

    2016-01-01

    Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. In order to achieve the theoretical performance gains of these processors, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High-Luminosity Large Hadron Collider (HL-LHC), for example, this will be by far the dominant problem. The need for greater parallelism has driven investigations of very different track finding techniques such as Cellular Automata or Hough Transforms. The most common track finding techniques in use today, however, are those based on a Kalman filter approach. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. They are known to provide high physics performance, are robust, and are in use today at the LHC. Given the utility of the Kalman filter in track finding, we have begun to port these algorithms to parallel architectures, namely Intel Xeon and Xeon Phi. We report here on our progress towards an end-to-end track reconstruction algorithm fully exploiting vectorization and parallelization techniques in a simplified experimental environment

  11. Recent advances in the GENFIT track fitting package

    Bicker, Karl A. [CERN, Geneva (Switzerland); Hoeppner, Christian; Ketzer, Bernhard; Neubert, Sebastian; Paul, Stephan; Rauch, Johannes [Technische Universitaet Muenchen, Munich (Germany)

    2012-07-01

    The GENFIT software package provides a framework for track fitting. Due to the modular and generic structure, it is usable with arbitrary detector and field geometries. GENFIT is used in several collaborations (e.g. Belle II, COMPASS, FOPI, PANDA). GENFIT provides hit classes for common detector types and their information is used by GENFIT in their native coordinate system. Hits are collected in tracks, as are track representations. The track representation handles the extrapolation of the track through matter and fields. Multiple track representations can be fitted simultaneously. GENFIT has recently been equipped with several new features. Besides adding Smoothing, the standard Kalman fit algorithm has been extended by a Deterministic Annealing Filter (DAF), which can tag noise hits. An interface to the RAVE vertexing package has equipped GENFIT with the capability for vertex reconstruction and fitting. Results from simulation and real data are presented.

  12. Exploration and extension of an improved Riemann track fitting algorithm

    Strandlie, A.; Frühwirth, R.

    2017-09-01

    Recently, a new Riemann track fit which operates on translated and scaled measurements has been proposed. This study shows that the new Riemann fit is virtually as precise as popular approaches such as the Kalman filter or an iterative non-linear track fitting procedure, and significantly more precise than other, non-iterative circular track fitting approaches over a large range of measurement uncertainties. The fit is then extended in two directions: first, the measurements are allowed to lie on plane sensors of arbitrary orientation; second, the full error propagation from the measurements to the estimated circle parameters is computed. The covariance matrix of the estimated track parameters can therefore be computed without recourse to asymptotic properties, and is consequently valid for any number of observation. It does, however, assume normally distributed measurement errors. The calculations are validated on a simulated track sample and show excellent agreement with the theoretical expectations.

  13. Bayesian target tracking based on particle filter

    2005-01-01

    For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

  14. GENFIT - a generic track-fitting toolkit

    Rauch, Johannes [Technische Universitaet Muenchen (Germany); Schlueter, Tobias [Ludwig-Maximilians-Universitaet Muenchen (Germany)

    2014-07-01

    GENFIT is an experiment-independent track-fitting toolkit, which combines fitting algorithms, track representations, and measurement geometries into a modular framework. We report on a significantly improved version of GENFIT, based on experience gained in the Belle II, PANDA, and FOPI experiments. Improvements concern the implementation of additional track-fitting algorithms, enhanced implementations of Kalman fitters, enhanced visualization capabilities, and additional implementations of measurement types suited for various kinds of tracking detectors. The data model has been revised, allowing for efficient track merging, smoothing, residual calculation and alignment.

  15. Particle filtering for passive fathometer tracking.

    Michalopoulou, Zoi-Heleni; Yardim, Caglar; Gerstoft, Peter

    2012-01-01

    Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model particle filter with an uncertain number of reflectors. Results are compared to a classical particle filter where the number of reflectors is considered to be known. Reflector tracking is demonstrated for both conventional and adaptive processing applied to the drifting array data from the Boundary 2003 experiment. The layering information is successfully tracked by the multiple model particle filter even for noisy fathometer outputs. © 2012 Acoustical Society of America.

  16. Passive target tracking using marginalized particle filter

    2007-01-01

    A marginalized particle filtering(MPF)approach is proposed for target tracking under the background of passive measurement.Essentially,the MPF is a combination of particle filtering technique and Kalman filter.By making full use of marginalization,the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter,and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter.Simulation studies are performed on an illustrative example,and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation.Real data test results also validate the effectiveness of the presented method.

  17. A Novel Generic Framework for Track Fitting in Complex Detector Systems

    Höppner, C.; Neubert, S.; Ketzer, B.; Paul, S.

    2009-01-01

    This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices th...

  18. Electron microscope studies on nuclear track filters

    Roell, I.; Siegmon, W.

    1982-01-01

    Nuclear track filters became more and more important in various fields of application. The filtration process can be described by a set of suitable parameters. For some applications it may be necessary to know the structure of the surface and the pores themselves. In most cases the etching process yields surfaces and pore geometries that are quite different from ideal planes and cylinders. In the presented work the production of different filter types will be described. The resulting surfaces and pore structures have been investigated by means of a scanning electron microscope. (author)

  19. Track fitting and resolution with digital detectors

    Duerdoth, I.

    1982-01-01

    The analysis of data from detectors which give digitised measurements, such as MWPCs, is considered. These measurements are necessarily correlated and it is shown that the uncertainty in the combination of N measurements may fall faster than the canonical 1/√N. A new method of track fitting is described which exploits the digital aspects and which takes the correlations into account. It divides the parameter space into cells and the centroid of a cell is taken as the best estimate. The method is shown to have some advantages over the standard least-squares analysis. If the least-squares method is used for digital detectors the goodness-of-fit may not be a reliable estimate of the accuracy. The cell method is particularly suitable for implementation on microcomputers which lack floating point and divide facilities. (orig.)

  20. Particle Filtering Applied to Musical Tempo Tracking

    Macleod Malcolm D

    2004-01-01

    Full Text Available This paper explores the use of particle filters for beat tracking in musical audio examples. The aim is to estimate the time-varying tempo process and to find the time locations of beats, as defined by human perception. Two alternative algorithms are presented, one which performs Rao-Blackwellisation to produce an almost deterministic formulation while the second is a formulation which models tempo as a Brownian motion process. The algorithms have been tested on a large and varied database of examples and results are comparable with the current state of the art. The deterministic algorithm gives the better performance of the two algorithms.

  1. Kalman filter tracking on parallel architectures

    Cerati, G.; Elmer, P.; Krutelyov, S.; Lantz, S.; Lefebvre, M.; McDermott, K.; Riley, D.; Tadel, M.; Wittich, P.; Wurthwein, F.; Yagil, A.

    2017-10-01

    We report on the progress of our studies towards a Kalman filter track reconstruction algorithm with optimal performance on manycore architectures. The combinatorial structure of these algorithms is not immediately compatible with an efficient SIMD (or SIMT) implementation; the challenge for us is to recast the existing software so it can readily generate hundreds of shared-memory threads that exploit the underlying instruction set of modern processors. We show how the data and associated tasks can be organized in a way that is conducive to both multithreading and vectorization. We demonstrate very good performance on Intel Xeon and Xeon Phi architectures, as well as promising first results on Nvidia GPUs.

  2. Multisensor Distributed Track Fusion AlgorithmBased on Strong Tracking Filter and Feedback Integration1)

    YANGGuo-Sheng; WENCheng-Lin; TANMin

    2004-01-01

    A new multisensor distributed track fusion algorithm is put forward based on combiningthe feedback integration with the strong tracking Kalman filter. Firstly, an effective tracking gateis constructed by taking the intersection of the tracking gates formed before and after feedback.Secondly, on the basis of the constructed effective tracking gate, probabilistic data association andstrong tracking Kalman filter are combined to form the new multisensor distributed track fusionalgorithm. At last, simulation is performed on the original algorithm and the algorithm presented.

  3. Target Response Adaptation for Correlation Filter Tracking

    Bibi, Adel Aamer

    2016-09-16

    Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %-13.5% in precision and 3.2 %-13% in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). © Springer International Publishing AG 2016.

  4. Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

    Zu-Tao, Zhang; Jia-Shu, Zhang

    2010-01-01

    The unscented Kalman filter is a developed well-known method for nonlinear motion estimation and tracking. However, the standard unscented Kalman filter has the inherent drawbacks, such as numerical instability and much more time spent on calculation in practical applications. In this paper, we present a novel sampling strong tracking nonlinear unscented Kalman filter, aiming to overcome the difficulty in nonlinear eye tracking. In the above proposed filter, the simplified unscented transform sampling strategy with n + 2 sigma points leads to the computational efficiency, and suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking. Compared with the related unscented Kalman filter for eye tracking, the proposed filter has potential advantages in robustness, convergence speed, and tracking accuracy. The final experimental results show the validity of our method for eye tracking under realistic conditions. (classical areas of phenomenology)

  5. Mathematical framework for fast and rigorous track fit for the ZEUS detector

    Spiridonov, Alexander

    2008-12-15

    In this note we present a mathematical framework for a rigorous approach to a common track fit for trackers located in the inner region of the ZEUS detector. The approach makes use of the Kalman filter and offers a rigorous treatment of magnetic field inhomogeneity, multiple scattering and energy loss. We describe mathematical details of the implementation of the Kalman filter technique with a reduced amount of computations for a cylindrical drift chamber, barrel and forward silicon strip detectors and a forward straw drift chamber. Options with homogeneous and inhomogeneous field are discussed. The fitting of tracks in one ZEUS event takes about of 20ms on standard PC. (orig.)

  6. Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning

    XIAO Kun; FANG Shao-ji; PANG Yong-jie

    2007-01-01

    To improve underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.

  7. Context-Aware Correlation Filter Tracking

    Mueller, Matthias; Smith, Neil; Ghanem, Bernard

    2017-01-01

    Correlation filter (CF) based trackers have recently gained a lot of popularity due to their impressive performance on benchmark datasets, while maintaining high frame rates. A significant amount of recent research focuses on the incorporation of stronger features for a richer representation of the tracking target. However, this only helps to discriminate the target from background within a small neighborhood. In this paper, we present a framework that allows the explicit incorporation of global context within CF trackers. We reformulate the original optimization problem and provide a closed form solution for single and multi-dimensional features in the primal and dual domain. Extensive experiments demonstrate that this framework significantly improves the performance of many CF trackers with only a modest impact on frame rate.

  8. Context-Aware Correlation Filter Tracking

    Mueller, Matthias

    2017-11-09

    Correlation filter (CF) based trackers have recently gained a lot of popularity due to their impressive performance on benchmark datasets, while maintaining high frame rates. A significant amount of recent research focuses on the incorporation of stronger features for a richer representation of the tracking target. However, this only helps to discriminate the target from background within a small neighborhood. In this paper, we present a framework that allows the explicit incorporation of global context within CF trackers. We reformulate the original optimization problem and provide a closed form solution for single and multi-dimensional features in the primal and dual domain. Extensive experiments demonstrate that this framework significantly improves the performance of many CF trackers with only a modest impact on frame rate.

  9. The FitTrack Index as fitness indicator: A pilot study | van Rensburg ...

    Conclusions: These results suggest that the web-based FitTrack Index may be considered an appropriate tool to evaluate exercise capacity and cardiovascular fitness in healthy individuals following an aerobic training programme. Keywords: Aerobic fitness, Exercise ability, Recreational fitness, Cardiovascular fitness, ...

  10. Correlation Filter Learning Toward Peak Strength for Visual Tracking.

    Sui, Yao; Wang, Guanghui; Zhang, Li

    2018-04-01

    This paper presents a novel visual tracking approach to correlation filter learning toward peak strength of correlation response. Previous methods leverage all features of the target and the immediate background to learn a correlation filter. Some features, however, may be distractive to tracking, like those from occlusion and local deformation, resulting in unstable tracking performance. This paper aims at solving this issue and proposes a novel algorithm to learn the correlation filter. The proposed approach, by imposing an elastic net constraint on the filter, can adaptively eliminate those distractive features in the correlation filtering. A new peak strength metric is proposed to measure the discriminative capability of the learned correlation filter. It is demonstrated that the proposed approach effectively strengthens the peak of the correlation response, leading to more discriminative performance than previous methods. Extensive experiments on a challenging visual tracking benchmark demonstrate that the proposed tracker outperforms most state-of-the-art methods.

  11. A new three-dimensional track fit with multiple scattering

    Berger, Niklaus; Kozlinskiy, Alexandr [Physikalisches Institut, Heidelberg University, Heidelberg (Germany); Institut für Kernphysik and PRISMA cluster of excellence, Mainz University, Mainz (Germany); Kiehn, Moritz; Schöning, André [Physikalisches Institut, Heidelberg University, Heidelberg (Germany)

    2017-02-01

    Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

  12. A new three-dimensional track fit with multiple scattering

    Berger, Niklaus; Kozlinskiy, Alexandr; Kiehn, Moritz; Schöning, André

    2017-01-01

    Modern semiconductor detectors allow for charged particle tracking with ever increasing position resolution. Due to the reduction of the spatial hit uncertainties, multiple Coulomb scattering in the detector layers becomes the dominant source for tracking uncertainties. In this case long distance effects can be ignored for the momentum measurement, and the track fit can consequently be formulated as a sum of independent fits to hit triplets. In this paper we present an analytical solution for a three-dimensional triplet(s) fit in a homogeneous magnetic field based on a multiple scattering model. Track fitting of hit triplets is performed using a linearization ansatz. The momentum resolution is discussed for a typical spectrometer setup. Furthermore the track fit is compared with other track fits for two different pixel detector geometries, namely the Mu3e experiment at PSI and a typical high-energy collider experiment. For a large momentum range the triplets fit provides a significantly better performance than a single helix fit. The triplets fit is fast and can easily be parallelized, which makes it ideal for the implementation on parallel computing architectures.

  13. Traditional Tracking with Kalman Filter on Parallel Architectures

    Cerati, Giuseppe; Elmer, Peter; Lantz, Steven; MacNeill, Ian; McDermott, Kevin; Riley, Dan; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

    2015-05-01

    Power density constraints are limiting the performance improvements of modern CPUs. To address this, we have seen the introduction of lower-power, multi-core processors, but the future will be even more exciting. In order to stay within the power density limits but still obtain Moore's Law performance/price gains, it will be necessary to parallelize algorithms to exploit larger numbers of lightweight cores and specialized functions like large vector units. Example technologies today include Intel's Xeon Phi and GPGPUs. Track finding and fitting is one of the most computationally challenging problems for event reconstruction in particle physics. At the High Luminosity LHC, for example, this will be by far the dominant problem. The most common track finding techniques in use today are however those based on the Kalman Filter. Significant experience has been accumulated with these techniques on real tracking detector systems, both in the trigger and offline. We report the results of our investigations into the potential and limitations of these algorithms on the new parallel hardware.

  14. Target Response Adaptation for Correlation Filter Tracking

    Bibi, Adel Aamer; Mueller, Matthias; Ghanem, Bernard

    2016-01-01

    Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations

  15. The FitTrack Index as fitness indicator

    Dina Christina Janse van Rensburg

    d Institute for Sports Research, Faculty of Humanities, University of Pretoria, South Africa e Institute for Food ... The American College of Sports Medicine's guidelines for health/fitness .... It is important to stress that the focus of this study was not.

  16. Kalman filters for real-time magnetic island phase tracking

    Borgers, D.P.; Lauret, M.; Baar, M.R. de

    2013-01-01

    Highlights: • We propose two Kalman filters for tracking of NTMs on ASDEX Upgrade. • The Kalman filters can track NTMs in a much larger frequency range than PLLs. • The filters are tested on synthetic and experimental data from TEXTOR and TCV. • We conclude that the unscented Kalman filter can be useful for NTM control. -- Abstract: For control of neoclassical tearing modes (NTMs) and the resulting rotating magnetic islands in tokamak plasmas, the frequency and phase of the magnetic islands need to be accurately tracked in real-time. In previous experiments on TEXTOR, this was achieved using a phase-locked loop (PLL). For ASDEX Upgrade however, the desired frequency range in which the islands are to be tracked (100 Hz–10 kHz) is much larger than is possible with a PLL. In this contribution, an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are proposed for real-time frequency, phase and amplitude tracking of sinusoidal signals, based on noisy measurements. Compared to PLLs, the EKF and UKF are able to track sinusoidal signals in a much larger frequency range. The filters are applied on synthetic data and on experimental data from the TEXTOR and TCV tokamaks, from which we conclude that the UKF can be useful for real-time control of magnetic islands on ASDEX Upgrade

  17. Kalman filters for real-time magnetic island phase tracking

    Borgers, D.P. [Hybrid and Networked Systems, Department of Mechanical Engineering – Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Lauret, M., E-mail: M.Lauret@tue.nl [FOM Institute DIFFER – Dutch Institute for Fundamental Energy Research, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, Nieuwegein (Netherlands); Control Systems Technology, Department of Mechanical Engineering – Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Baar, M.R. de [FOM Institute DIFFER – Dutch Institute for Fundamental Energy Research, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, Nieuwegein (Netherlands); Control Systems Technology, Department of Mechanical Engineering – Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

    2013-11-15

    Highlights: • We propose two Kalman filters for tracking of NTMs on ASDEX Upgrade. • The Kalman filters can track NTMs in a much larger frequency range than PLLs. • The filters are tested on synthetic and experimental data from TEXTOR and TCV. • We conclude that the unscented Kalman filter can be useful for NTM control. -- Abstract: For control of neoclassical tearing modes (NTMs) and the resulting rotating magnetic islands in tokamak plasmas, the frequency and phase of the magnetic islands need to be accurately tracked in real-time. In previous experiments on TEXTOR, this was achieved using a phase-locked loop (PLL). For ASDEX Upgrade however, the desired frequency range in which the islands are to be tracked (100 Hz–10 kHz) is much larger than is possible with a PLL. In this contribution, an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) are proposed for real-time frequency, phase and amplitude tracking of sinusoidal signals, based on noisy measurements. Compared to PLLs, the EKF and UKF are able to track sinusoidal signals in a much larger frequency range. The filters are applied on synthetic data and on experimental data from the TEXTOR and TCV tokamaks, from which we conclude that the UKF can be useful for real-time control of magnetic islands on ASDEX Upgrade.

  18. A novel strong tracking finite-difference extended Kalman filter for nonlinear eye tracking

    ZHANG ZuTao; ZHANG JiaShu

    2009-01-01

    Non-Intrusive methods for eye tracking are Important for many applications of vision-based human computer interaction. However, due to the high nonlinearity of eye motion, how to ensure the robust-ness of external interference and accuracy of eye tracking poses the primary obstacle to the integration of eye movements into today's interfaces. In this paper, we present a strong tracking finite-difference extended Kalman filter algorithm, aiming to overcome the difficulty In modeling nonlinear eye tracking. In filtering calculation, strong tracking factor is introduced to modify a priori covariance matrix and im-prove the accuracy of the filter. The filter uses finite-difference method to calculate partial derivatives of nonlinear functions for eye tracking. The latest experimental results show the validity of our method for eye tracking under realistic conditions.

  19. Visual object tracking by correlation filters and online learning

    Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

    2018-06-01

    Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

  20. Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

    M. Sanjeev Arulampalam

    2004-11-01

    Full Text Available We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs. Three different (PFs are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS framework. The proposed filters are (i multiple model PF (MMPF, (ii auxiliary MMPF (AUX-MMPF, and (iii jump Markov system PF (JMS-PF. The performance of these filters is compared with that of standard interacting multiple model (IMM-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i single-sensor case, (ii multisensor case, and (iii tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.

  1. A-Track: Detecting Moving Objects in FITS images

    Atay, T.; Kaplan, M.; Kilic, Y.; Karapinar, N.

    2017-04-01

    A-Track is a fast, open-source, cross-platform pipeline for detecting moving objects (asteroids and comets) in sequential telescope images in FITS format. The moving objects are detected using a modified line detection algorithm.

  2. Adaptive filtering for hidden node detection and tracking in networks.

    Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L

    2017-07-01

    The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.

  3. Unscented Kalman filtering for articulated human tracking

    Boesen Lindbo Larsen, Anders; Hauberg, Søren; Pedersen, Kim Steenstrup

    2011-01-01

    We present an articulated tracking system working with data from a single narrow baseline stereo camera. The use of stereo data allows for some depth disambiguation, a common issue in articulated tracking, which in turn yields likelihoods that are practically unimodal. While current state...... with superior results. Tracking quality is measured by comparing with ground truth data from a marker-based motion capture system....

  4. On tempo tracking: Tempogram representation and Kalman filtering

    Cemgil, A.T.; Kappen, H.J.; Desain, P.W.M.; Honing, H.J.

    2001-01-01

    We formulate tempo tracking in a Bayesian framework where a tempo tracker is modeled as a stochastic dynamical system. The tempo is modeled as a hidden state variable of the system and is estimated by a Kalman filter. The Kalman filter operates on a Tempogram, a wavelet-like multiscale expansion of

  5. Disclosure and Fit Capability of the Filtering Facepiece Respirator.

    Lofgren, Don J

    2018-05-01

    The filtering facepiece air-purifying respirator is annually purchased in the tens of millions and widely used for worker protection from harmful airborne particulates. The workplace consumers of this safety product, i.e., employers, workers, and safety and health professionals, have assurances of its effectiveness through the respirator certification and disclosure requirements of the National Institute for Occupational Safety and Health. However, the certification of a critical performance requirement has been missing for the approved filtering facepiece respirator since 1995: fit capability. Without this certification, consumers continue to be at risk of purchasing a respirator model that may fit a small percentage of the intended users. This commentary updates and expands an earlier one by this author, addresses the consequences of poorly fitting certified models on the market and lack of disclosure, and calls for further action by National Institute for Occupational Safety and Health to meet the needs and expectations of the consumer.

  6. Optimum track fitting in the presence of multiple scattering

    Lutz, G.

    1987-06-01

    A method for track fitting is proposed which attempts to be as close as possible to the real track along the full path length. This is done by the introduction of scattering planes in which the particle is allowed to change its direction. A fit over the full track length includes the probability of direction change by scattering. Using matrix notation a fairly simple formalism for error estimation has been developed. Results of this method are compared to those of more widely used procedures for 'typical' examples of High Energy Spectrometers. (orig.)

  7. Nonlinear Principal Component Analysis Using Strong Tracking Filter

    2007-01-01

    The paper analyzes the problem of blind source separation (BSS) based on the nonlinear principal component analysis (NPCA) criterion. An adaptive strong tracking filter (STF) based algorithm was developed, which is immune to system model mismatches. Simulations demonstrate that the algorithm converges quickly and has satisfactory steady-state accuracy. The Kalman filtering algorithm and the recursive leastsquares type algorithm are shown to be special cases of the STF algorithm. Since the forgetting factor is adaptively updated by adjustment of the Kalman gain, the STF scheme provides more powerful tracking capability than the Kalman filtering algorithm and recursive least-squares algorithm.

  8. Track filter on the basis of a cellular automation

    Glazov, A.A.; Kisel', I.V.; Konotopskaya, E.V.; Ososkov, G.A.

    1991-01-01

    The filtering method for tracks in discrete detectors based on the cellular automation is described. Results of the application of this method to experimental data (the spectrometer ARES) are quite successful: threefold reduction of input information with data grouping according to their belonging to separate tracks. They lift up percentage of useful events, which simplifies and accelerates considerably their next recognition. The described cellular automation for track filtering can be successfully applied in parallel computers and also in on-line mode if hardware implementation is used. 21 refs.; 11 figs

  9. Random set particle filter for bearings-only multitarget tracking

    Vihola, Matti

    2005-05-01

    The random set approach to multitarget tracking is a theoretically sound framework that covers joint estimation of the number of targets and the state of the targets. This paper describes a particle filter implementation of the random set multitarget filter. The contribution of this paper to the random set tracking framework is the formulation of a measurement model where each sensor report is assumed to contain at most one measurement. The implemented filter was tested in synthetic bearings-only tracking scenarios containing up to two targets in the presence of false alarms and missed measurements. The estimated target state consisted of 2D position and velocity components. The filter was capable to track the targets fairly well despite of the missing measurements and the relatively high false alarm rates. In addition, the filter showed robustness against wrong parameter values of false alarm rates. The results that were obtained during the limited tests of the filter show that the random set framework has potential for challenging tracking situations. On the other hand, the computational burden of the described implementation is quite high and increases approximately linearly with respect to the expected number of targets.

  10. Robotic fish tracking method based on suboptimal interval Kalman filter

    Tong, Xiaohong; Tang, Chao

    2017-11-01

    Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

  11. A novel generic framework for track fitting in complex detector systems

    Hoeppner, C.; Neubert, S.; Ketzer, B.; Paul, S.

    2010-01-01

    This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices through the experiment are also implemented as interchangeable modules. Different track parameterizations and extrapolation routines can be used simultaneously for fitting of the same physical track. Representations of detector hits are the third modular ingredient to the framework. The hit dimensionality and orientation of planar tracking detectors are not restricted. Tracking information from detectors which do not measure the passage of particles in a fixed physical detector plane, e.g. drift chambers or TPCs, is used without any simplification. The concept is implemented in a light-weight C++ library called GENFIT, which is available as free software.

  12. A novel generic framework for track fitting in complex detector systems

    Hoeppner, C., E-mail: christian.hoeppner@cern.c [Technische Universitaet Muenchen, Physik Department, 85748 Garching (Germany); Neubert, S.; Ketzer, B.; Paul, S. [Technische Universitaet Muenchen, Physik Department, 85748 Garching (Germany)

    2010-08-21

    This paper presents a novel framework for track fitting which is usable in a wide range of experiments, independent of the specific event topology, detector setup, or magnetic field arrangement. This goal is achieved through a completely modular design. Fitting algorithms are implemented as interchangeable modules. At present, the framework contains a validated Kalman filter. Track parameterizations and the routines required to extrapolate the track parameters and their covariance matrices through the experiment are also implemented as interchangeable modules. Different track parameterizations and extrapolation routines can be used simultaneously for fitting of the same physical track. Representations of detector hits are the third modular ingredient to the framework. The hit dimensionality and orientation of planar tracking detectors are not restricted. Tracking information from detectors which do not measure the passage of particles in a fixed physical detector plane, e.g. drift chambers or TPCs, is used without any simplification. The concept is implemented in a light-weight C++ library called GENFIT, which is available as free software.

  13. PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

    Wei Leong Khong

    2014-02-01

    Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

  14. SURFACE FITTING FILTERING OF LIDAR POINT CLOUD WITH WAVEFORM INFORMATION

    S. Xing

    2017-09-01

    Full Text Available Full-waveform LiDAR is an active technology of photogrammetry and remote sensing. It provides more detailed information about objects along the path of a laser pulse than discrete-return topographic LiDAR. The point cloud and waveform information with high quality can be obtained by waveform decomposition, which could make contributions to accurate filtering. The surface fitting filtering method with waveform information is proposed to present such advantage. Firstly, discrete point cloud and waveform parameters are resolved by global convergent Levenberg Marquardt decomposition. Secondly, the ground seed points are selected, of which the abnormal ones are detected by waveform parameters and robust estimation. Thirdly, the terrain surface is fitted and the height difference threshold is determined in consideration of window size and mean square error. Finally, the points are classified gradually with the rising of window size. The filtering process is finished until window size is larger than threshold. The waveform data in urban, farmland and mountain areas from “WATER (Watershed Allied Telemetry Experimental Research” are selected for experiments. Results prove that compared with traditional method, the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.

  15. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

    Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; Masciovecchio, Mario; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

    2017-08-01

    For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

  16. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

    Cerati Giuseppe

    2017-01-01

    Full Text Available For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU, ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC, for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

  17. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

    Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U.; Riley, Daniel [Cornell U., LNS; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

    2017-01-01

    For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

  18. Some Aspects on Filter Design for Target Tracking

    Bertil Ekstrand

    2012-01-01

    Full Text Available Tracking filter design is discussed. It is argued that the basis of the present stochastic paradigm is questionable. White process noise is not adequate as a model for target manoeuvring, stochastic least-square optimality is not relevant or required in practice, the fact that requirements are necessary for design is ignored, and root mean square (RMS errors are insufficient as performance measure. It is argued that there is no process noise and that the covariance of the assumed process noise contains the design parameters. Focus is on the basic tracking filter, the Kalman filter, which is convenient for clarity and simplicity, but the arguments and conclusions are relevant in general. For design the possibility of an observer transfer function approach is pointed out. The issues can also be considered as a consequence of the fact that there is a difference between estimation and design. The - filter is used for illustration.

  19. Track filtering by robust neural network

    Baginyan, S.A.; Kisel', I.V.; Konotopskaya, E.V.; Ososkov, G.A.

    1993-01-01

    In the present paper we study the following problems of track information extraction by the artificial neural network (ANN) rotor model: providing initial ANN configuration by an algorithm general enough to be applicable for any discrete detector in- or out of a magnetic field; robustness to heavy contaminated raw data (up to 100% signal-to-noise ratio); stability to the growing event multiplicity. These problems were carried out by corresponding innovations of our model, namely: by a special one-dimensional histogramming, by multiplying weights by a specially designed robust multiplier, and by replacing the simulated annealing schedule by ANN dynamics with an optimally fixed temperature. Our approach is valid for both circular and straight (non-magnetic) tracks and tested on 2D simulated data contaminated by 100% noise points distributed uniformly. To be closer to some reality in our simulation, we keep parameters of the cylindrical spectrometer ARES. 12 refs.; 9 figs

  20. Track fitting in the opal vertex detector with stereo wires

    Shally, R; Hemingway, R J; McPherson, A C

    1987-10-01

    The geometry of the vertex chamber for the OPAL detector at LEP is reviewed and expressions for the coordinates of the hits are given in terms of the measured drift distance and z-coordinate. The tracks are fitted by a procedure based on the Lagrange multipliers method. The increase in the accuracy of the fit due to the use of the stereo wires is discussed.

  1. Track fitting in the opal vertex detector with stereo wires

    Shally, R.; Hemingway, R.J.; McPherson, A.C.

    1987-01-01

    The geometry of the vertex chamber for the OPAL detector at LEP is reviewed and expressions for the coordinates of the hits are given in terms of the measured drift distance and z-coordinate. The tracks are fitted by a procedure based on the Lagrange multipliers method. The increase in the accuracy of the fit due to the use of the stereo wires is discussed. (orig.)

  2. Track finding and fitting in the H1 Forward Track Detector

    Burke, S.; Henderson, R.C.W.; Maxfield, S.J.; Patel, G.D.; Morris, J.V.; Sankey, D.P.C.; Skillicorn, I.O.

    1995-07-01

    The tracking environment in the H1 Forward Tracker Detector, where the hit multiplicity from proton fragments is high, is parituclarly hostile. The techniques and software which have been developed for pattern recognition and Kalman fitting of charged particle tracks in this region are described in detail. (orig.)

  3. Ballistic target tracking algorithm based on improved particle filtering

    Ning, Xiao-lei; Chen, Zhan-qi; Li, Xiao-yang

    2015-10-01

    Tracking ballistic re-entry target is a typical nonlinear filtering problem. In order to track the ballistic re-entry target in the nonlinear and non-Gaussian complex environment, a novel chaos map particle filter (CMPF) is used to estimate the target state. CMPF has better performance in application to estimate the state and parameter of nonlinear and non-Gassuian system. The Monte Carlo simulation results show that, this method can effectively solve particle degeneracy and particle impoverishment problem by improving the efficiency of particle sampling to obtain the better particles to part in estimation. Meanwhile CMPF can improve the state estimation precision and convergence velocity compared with EKF, UKF and the ordinary particle filter.

  4. Fish tracking by combining motion based segmentation and particle filtering

    Bichot, E.; Mascarilla, L.; Courtellemont, P.

    2006-01-01

    In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

  5. 3D head pose estimation and tracking using particle filtering and ICP algorithm

    Ben Ghorbel, Mahdi; Baklouti, Malek; Couvet, Serge

    2010-01-01

    This paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.

  6. Nonlinear Vibration Signal Tracking of Large Offshore Bridge Stayed Cable Based on Particle Filter

    Ye Qingwei

    2015-12-01

    Full Text Available The stayed cables are key stress components of large offshore bridge. The fault detection of stayed cable is very important for safe of large offshore bridge. A particle filter model and algorithm of nonlinear vibration signal are used in this paper. Firstly, the particle filter model of stayed cable of large offshore bridge is created. Nonlinear dynamic model of the stayed-cable and beam coupling system is dispersed in temporal dimension by using the finite difference method. The discrete nonlinear vibration equations of any cable element are worked out. Secondly, a state equation of particle filter is fitted by least square algorithm from the discrete nonlinear vibration equations. So the particle filter algorithm can use the accurate state equations. Finally, the particle filter algorithm is used to filter the vibration signal of bridge stayed cable. According to the particle filter, the de-noised vibration signal can be tracked and be predicted for a short time accurately. Many experiments are done at some actual bridges. The simulation experiments and the actual experiments on the bridge stayed cables are all indicating that the particle filter algorithm in this paper has good performance and works stably.

  7. Joint Conditional Random Field Filter for Multi-Object Tracking

    Luo Ronghua

    2011-03-01

    Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

  8. Preparation of Track Etch Membrane Filters Using Polystyrene Film

    Kaewsaenee, Jerawut; Ratanatongchai, Wichian; Supaphol, Pitt; Visal-athaphand, Pinpan

    2007-08-01

    Full text: Polystyrene nuclear track etch membrane filters was prepared by exposed 13 .m thin film polystyrene with fission fragment. Nuclear latent track was enlarged to through hole on the film by etching with 80 o C 40% H 2 SO 4 with K 2 Cr 2 O 7 solution for 6-10 hour. The hole size was depend on concentration of etching solution and etching time with 1.3-3.4 .m hole diameter. The flow rate test of water was 0.79-1.56 mm cm-2 min-1 at 109.8-113.7 kPa pressure

  9. Track reconstruction for the Mu3e experiment based on a novel Multiple Scattering fit

    Kozlinskiy Alexandr

    2017-01-01

    Full Text Available The Mu3e experiment is designed to search for the lepton flavor violating decay μ+ → e+e+e−. The aim of the experiment is to reach a branching ratio sensitivity of 10−16. In a first phase the experiment will be performed at an existing beam line at the Paul-Scherrer Institute (Switzerland providing 108 muons per second, which will allow to reach a sensitivity of 2 · 10−15. The muons with a momentum of about 28 MeV/c are stopped and decay at rest on a target. The decay products (positrons and electrons with energies below 53MeV are measured by a tracking detector consisting of two double layers of 50 μm thin silicon pixel sensors. The high granularity of the pixel detector with a pixel size of 80 μm × 80 μm allows for a precise track reconstruction in the high multiplicity environment of the Mu3e experiment, reaching 100 tracks per reconstruction frame of 50 ns in the final phase of the experiment. To deal with such high rates and combinatorics, the Mu3e track reconstruction uses a novel fit algorithm that in the simplest case takes into account only the multiple scattering, which allows for a fast online tracking on a GPU based filter farm. An implementation of the 3-dimensional multiple scattering fit based on hit triplets is described. The extension of the fit that takes into account energy losses and pixel size is used for offline track reconstruction. The algorithm and performance of the offline track reconstruction based on a full Geant4 simulation of the Mu3e detector are presented.

  10. Particle filters for object tracking: enhanced algorithm and efficient implementations

    Abd El-Halym, H.A.

    2010-01-01

    Object tracking and recognition is a hot research topic. In spite of the extensive research efforts expended, the development of a robust and efficient object tracking algorithm remains unsolved due to the inherent difficulty of the tracking problem. Particle filters (PFs) were recently introduced as a powerful, post-Kalman filter, estimation tool that provides a general framework for estimation of nonlinear/ non-Gaussian dynamic systems. Particle filters were advanced for building robust object trackers capable of operation under severe conditions (small image size, noisy background, occlusions, fast object maneuvers ..etc.). The heavy computational load of the particle filter remains a major obstacle towards its wide use.In this thesis, an Excitation Particle Filter (EPF) is introduced for object tracking. A new likelihood model is proposed. It depends on multiple functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modified the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. This modification is based on re-exciting the particles if their weights fall below a memorized weight value. The proposed enhanced PF is implemented in software and evaluated. Its results are compared with a single likelihood function PF tracker, Particle Swarm Optimization (PSO) tracker, a correlation tracker, as well as, an edge tracker. The experimental results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness, and occlusion compared with other methods Efficient novel hardware architectures of the Sample Important Re sample Filter (SIRF) and the EPF are implemented. Three novel hardware architectures of the SIRF for object tracking are introduced. The first architecture is a two-step sequential PF machine, where particle generation, weight calculation and normalization are carried out in parallel during the first step followed by a sequential re

  11. Kalman Filter Based Tracking in an Video Surveillance System

    SULIMAN, C.

    2010-05-01

    Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

  12. Application of Evolution Strategies to the Design of Tracking Filters with a Large Number of Specifications

    Jesús García Herrero

    2003-07-01

    Full Text Available This paper describes the application of evolution strategies to the design of interacting multiple model (IMM tracking filters in order to fulfill a large table of performance specifications. These specifications define the desired filter performance in a thorough set of selected test scenarios, for different figures of merit and input conditions, imposing hundreds of performance goals. The design problem is stated as a numeric search in the filter parameters space to attain all specifications or at least minimize, in a compromise, the excess over some specifications as much as possible, applying global optimization techniques coming from evolutionary computation field. Besides, a new methodology is proposed to integrate specifications in a fitness function able to effectively guide the search to suitable solutions. The method has been applied to the design of an IMM tracker for a real-world civil air traffic control application: the accomplishment of specifications defined for the future European ARTAS system.

  13. Review of track-fitting methods in counter experiments

    Regler, M.; Eichinger, H.

    1981-01-01

    We review track-fitting methods recently used in high-energy physics experiments. Assuming that the problem of pattern recognition, i.e. of grouping the often ambiguous coordinate information (as frequently measured by wire chambers) together to form track candidates, has already been solved, we try to point out the way to obtain the ultimate geometrical resolution with the smallest and fastest possible program; owing to the wide variety of detectors and experimental set-ups, no universal method has been found. Some applications will serve as examples, and based on the experience gained we will try to indicate when and under which conditions a known algorithm could be used, and this might even help in designing future experiments. (orig.)

  14. Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

    Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U., Phys. Dept.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U., Phys. Dept.; Riley, Daniel [Cornell U., Phys. Dept.; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U., Phys. Dept.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

    2017-11-16

    Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Examples include the Intel Xeon Phi, GPGPUs, and similar technologies. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.

  15. Chaotic secure communication based on strong tracking filtering

    Li Xiongjie; Xu Zhengguo; Zhou Donghua

    2008-01-01

    A scheme for implementing secure communication based on chaotic maps and strong tracking filter (STF) is presented, and a modified STF algorithm with message estimation is developed for the special requirement of chaotic secure communication. At the emitter, the message symbol is modulated by chaotic mapping and is output through a nonlinear function. At the receiver, the driving signal is received and the message symbol is recovered dynamically by the STF with estimation of message symbol. Simulation results of Holmes map demonstrate that when message symbols are binary codes, STF can effectively recover the codes of the message from the noisy chaotic signals. Compared with the extended Kalman filter (EKF), STF has a lower bit error rate

  16. Further studies on the filtration of liquids using Kapton nuclear track micro filters

    Guo, S.L.; Ganz, M.; Fuest, M.; Vater, P.; Brandt, R.

    1990-01-01

    The flow rate of some liquids (water, heptane, toluene, xylene, dodecane) through Kapton nuclear track filters has been measured. The results can be interpreted with a modified Poiseuille formula. The influence of the viscosity of the liquids on their throughput through Kapton nuclear track filters has been determined. The purification of liquids with Kapton filters has been investigated. It is possible to measure the density of solid particles in deionized water by using Kapton filters. Consequently, nuclear track filters can remove solid particles from high-purity liquids. The soaking effect of some common liquid chemicals on Kapton filters has also been studied, no such soaking could be observed in most of the cases. Finally, these Kapton nuclear track filters are compared with a filter device from Hamamatsu (Japan). (orig.) [de

  17. Robust and Adaptive Block Tracking Method Based on Particle Filter

    Bin Sun

    2015-10-01

    Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

  18. Modified unscented Kalman filter using modified filter gain and variance scale factor for highly maneuvering target tracking

    Changyun Liu; Penglang Shui; Gang Wei; Song Li

    2014-01-01

    To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneu-vers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is pre-sented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter (UKF) via predicted variance Pk|k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneu-vering target compared with the standard UKF.

  19. Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

    Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

    2017-11-01

    The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

  20. UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data

    Karen Uribe-Murcia

    2018-01-01

    Full Text Available In smart cities, vehicles tracking is organized to increase safety by localizing cars using the Global Positioning System (GPS. The GPS-based system provides accurate tracking but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response (UFIR filter, which meets these needs as being more robust than the Kalman filter (KF. The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs with time-stamped data discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. Applications are given for measurement data, which are cooperatively transferred from a vehicle to a central station through several nodes with k-step-lags. Better tracking performance of the UFIR filter is shown experimentally.

  1. Modified Extended Kalman Filtering for Tracking with Insufficient and Intermittent Observations

    Pengpeng Chen

    2015-01-01

    Full Text Available This paper is concerned with the Kalman filtering problem for tracking a single target on the fixed-topology wireless sensor networks (WSNs. Both the insufficient anchor coverage and the packet dropouts have been taken into consideration in the filter design. The resulting tracking system is modeled as a multichannel nonlinear system with multiplicative noise. Noting that the channels may be correlated with each other, we use a general matrix to express the multiplicative noise. Then, a modified extended Kalman filtering algorithm is presented based on the obtained model to achieve high tracking accuracy. In particular, we evaluate the effect of various parameters on the tracking performance through simulation studies.

  2. Kalman Filter Predictor and Initialization Algorithm for PRI Tracking

    Hock, Melinda

    1998-01-01

    .... The algorithm uses a Kalman filter for prediction combined with a preprocessing routine to determine the period of the stagger sequence and to construct an uncorrupted data set for Kalman filter initialization...

  3. RSSI based indoor tracking in sensor networks using Kalman filters

    Tøgersen, Frede Aakmann; Skjøth, Flemming; Munksgaard, Lene

    2010-01-01

    We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio...

  4. FITNESS TRAINING AS PREPARATION FOR BICYCLE TRACKING TOURS

    Dragan Martinović

    2007-05-01

    Full Text Available Track, tracking“(English – a trail, to follow a trail. Tracking means hiking on marked tracks, roads and mountain paths, with the aim of being physically active surrounded by fresh air, natural beauties and cultural/historical monuments. Physical preparation (fi tness training is a very specifi c and complex process that has an active positive infl uence on the maintenance of health, on forming of good bodily posture, as well as on growth and development of physical and psycho-social values of an individual.

  5. Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

    Mónica A Silva

    Full Text Available Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km was nearly half that of LS estimates (11.6 ± 8.4 km. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

  6. Maximum Correntropy Criterion Kalman Filter for α-Jerk Tracking Model with Non-Gaussian Noise

    Bowen Hou

    2017-11-01

    Full Text Available As one of the most critical issues for target track, α -jerk model is an effective maneuver target track model. Non-Gaussian noises always exist in the track process, which usually lead to inconsistency and divergence of the track filter. A novel Kalman filter is derived and applied on α -jerk tracking model to handle non-Gaussian noise. The weighted least square solution is presented and the standard Kalman filter is deduced firstly. A novel Kalman filter with the weighted least square based on the maximum correntropy criterion is deduced. The robustness of the maximum correntropy criterion is also analyzed with the influence function and compared with the Huber-based filter, and, moreover, the kernel size of Gaussian kernel plays an important role in the filter algorithm. A new adaptive kernel method is proposed in this paper to adjust the parameter in real time. Finally, simulation results indicate the validity and the efficiency of the proposed filter. The comparison study shows that the proposed filter can significantly reduce the noise influence for α -jerk model.

  7. Track Reconstruction in the ATLAS Experiment The Deterministic Annealing Filter

    Fleischmann, S

    2006-01-01

    The reconstruction of the trajectories of charged particles is essential for experiments at the LHC. The experiments contain precise tracking systems structured in layers around the collision point which measure the positions where particle trajectories intersect those layers. The physics analysis on the other hand mainly needs the momentum and direction of the particle at the estimated creation or reaction point. It is therefore needed to determine these parameters from the initial measurements. At the LHC one has to deal with high backgrounds while even small deficits or artifacts can reduce the signal or may produce additional background after event selection. The track reconstruction does not only contain the estimation of the track parameters, but also a pattern recognition deciding which measurements belong to a track and how many particle tracks can be found. Track reconstruction at the ATLAS experiment suffers from the high event rate at the LHC resulting in a high occupancy of the tracking devices. A...

  8. INFLUENCE OF STOCHASTIC NOISE STATISTICS ON KALMAN FILTER PERFORMANCE BASED ON VIDEO TARGET TRACKING

    Chen Ken; Napolitano; Zhang Yun; Li Dong

    2010-01-01

    The system stochastic noises involved in Kalman filtering are preconditioned on being ideally white and Gaussian distributed. In this research,efforts are exerted on exploring the influence of the noise statistics on Kalman filtering from the perspective of video target tracking quality. The correlation of tracking precision to both the process and measurement noise covariance is investigated; the signal-to-noise power density ratio is defined; the contribution of predicted states and measured outputs to Kalman filter behavior is discussed; the tracking precision relative sensitivity is derived and applied in this study case. The findings are expected to pave the way for future study on how the actual noise statistics deviating from the assumed ones impacts on the Kalman filter optimality and degradation in the application of video tracking.

  9. COMPARATIVE EVALUATION OF FILTERS USED IN TRACKING AIR TARGETS

    Y. I. Strekalovskaya

    2015-01-01

    Full Text Available Using an imitation model for a flow of heterogeneous air targets the comparative assessment of the αβ, αβγ and the Kalman filters efficiency is evaluated. In the case of slightly maneuvering target the difference in filters’ efficiency is statistically insignificant; in the case of sharp maneuvering the Kalman filter is significantly more precise.

  10. Hierarchical Threshold Adaptive for Point Cloud Filter Algorithm of Moving Surface Fitting

    ZHU Xiaoxiao

    2018-02-01

    Full Text Available In order to improve the accuracy,efficiency and adaptability of point cloud filtering algorithm,a hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting was proposed.Firstly,the noisy points are removed by using a statistic histogram method.Secondly,the grid index is established by grid segmentation,and the surface equation is set up through the lowest point among the neighborhood grids.The real height and fit are calculated.The difference between the elevation and the threshold can be determined.Finally,in order to improve the filtering accuracy,hierarchical filtering is used to change the grid size and automatically set the neighborhood size and threshold until the filtering result reaches the accuracy requirement.The test data provided by the International Photogrammetry and Remote Sensing Society (ISPRS is used to verify the algorithm.The first and second error and the total error are 7.33%,10.64% and 6.34% respectively.The algorithm is compared with the eight classical filtering algorithms published by ISPRS.The experiment results show that the method has well-adapted and it has high accurate filtering result.

  11. Dual linear structured support vector machine tracking method via scale correlation filter

    Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

    2018-01-01

    Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

  12. The ATLAS Fast Tracker Processing Units - track finding and fitting

    AUTHOR|(INSPIRE)INSPIRE-00384270; The ATLAS collaboration; Alison, John; Ancu, Lucian Stefan; Andreani, Alessandro; Annovi, Alberto; Beccherle, Roberto; Beretta, Matteo; Biesuz, Nicolo Vladi; Bogdan, Mircea Arghir; Bryant, Patrick; Calabro, Domenico; Citraro, Saverio; Crescioli, Francesco; Dell'Orso, Mauro; Donati, Simone; Gentsos, Christos; Giannetti, Paola; Gkaitatzis, Stamatios; Gramling, Johanna; Greco, Virginia; Horyn, Lesya Anna; Iovene, Alessandro; Kalaitzidis, Panagiotis; Kim, Young-Kee; Kimura, Naoki; Kordas, Kostantinos; Kubota, Takashi; Lanza, Agostino; Liberali, Valentino; Luciano, Pierluigi; Magnin, Betty; Sakellariou, Andreas; Sampsonidis, Dimitrios; Saxon, James; Shojaii, Seyed Ruhollah; Sotiropoulou, Calliope Louisa; Stabile, Alberto; Swiatlowski, Maximilian; Volpi, Guido; Zou, Rui; Shochet, Mel

    2016-01-01

    The Fast Tracker is a hardware upgrade to the ATLAS trigger and data-acquisition system, with the goal of providing global track reconstruction by the start of the High Level Trigger starts. The Fast Tracker can process incoming data from the whole inner detector at full first level trigger rate, up to 100 kHz, using custom electronic boards. At the core of the system is a Processing Unit installed in a VMEbus crate, formed by two sets of boards: the Associative Memory Board and a powerful rear transition module called the Auxiliary card, while the second set is the Second Stage board. The associative memories perform the pattern matching looking for correlations within the incoming data, compatible with track candidates at coarse resolution. The pattern matching task is performed using custom application specific integrated circuits, called associative memory chips. The auxiliary card prepares the input and reject bad track candidates obtained from from the Associative Memory Board using the full precision a...

  13. Using Gaussian Process Annealing Particle Filter for 3D Human Tracking

    Michael Rudzsky

    2008-01-01

    Full Text Available We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian process annealing particle filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker's stability and robustness. Comparing with a regular annealed particle filter-based tracker, we show that our algorithm can track better for low frame rate videos. We also show that our algorithm is capable of recovering after a temporal target loss.

  14. Tracking of multiple objects with time-adjustable composite correlation filters

    Ruchay, Alexey; Kober, Vitaly; Chernoskulov, Ilya

    2017-09-01

    An algorithm for tracking of multiple objects in video based on time-adjustable adaptive composite correlation filtering is proposed. For each frame a bank of composite correlation filters are designed in such a manner to provide invariance to pose, occlusion, clutter, and illumination changes. The filters are synthesized with the help of an iterative algorithm, which optimizes the discrimination capability for each object. The filters are adapted to the objects changes online using information from the current and past scene frames. Results obtained with the proposed algorithm using real-life scenes are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing.

  15. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

    Anthony Hoak

    2017-03-01

    Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  16. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

    Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

    2017-03-03

    We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  17. Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor.

    Wu, Hao; Chen, Shuxin; Yang, Binfeng; Chen, Kun

    2016-05-09

    The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers' misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors.

  18. Estimation of three-dimensional radar tracking using modified extended kalman filter

    Aditya, Prima; Apriliani, Erna; Khusnul Arif, Didik; Baihaqi, Komar

    2018-03-01

    Kalman filter is an estimation method by combining data and mathematical models then developed be extended Kalman filter to handle nonlinear systems. Three-dimensional radar tracking is one of example of nonlinear system. In this paper developed a modification method of extended Kalman filter from the direct decline of the three-dimensional radar tracking case. The development of this filter algorithm can solve the three-dimensional radar measurements in the case proposed in this case the target measured by radar with distance r, azimuth angle θ, and the elevation angle ϕ. Artificial covariance and mean adjusted directly on the three-dimensional radar system. Simulations result show that the proposed formulation is effective in the calculation of nonlinear measurement compared with extended Kalman filter with the value error at 0.77% until 1.15%.

  19. An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.

    Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

    2017-11-18

    Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio

  20. The research of radar target tracking observed information linear filter method

    Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

    2018-05-01

    Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

  1. Multi-parameter studies of environmental aerosols with cascade track filters

    Ensinger, W.; Guo, S.-L.; Vater, P.; Brandt, R.

    2005-01-01

    Aerosols in the air in a factory processing nuclear reactor fuel material were collected by using cascade Kapton track filters with outer pore sizes of 12.8, 4.0 and 1.0μm consecutively and a conventional filter of glass fiber being behind to collect all aerosol particles left-over. The volume of air passed through the filters was measured by a flow meter. The weight of aerosol particles on each filter was obtained by the weight difference of the filter before and after collection of aerosol particles. α-activity on each filter was measured with a methane gas flow proportional counter. The sizes and elemental compositions of aerosol particles on the filters were analyzed by using a scanning electron microscope and an electron microprobe. Special attention was given to uranium aerosol particles. The median sizes of uranium aerosol particles were obtained being 1.97, 1.33 and 0.72μm on the first, second and third filter, respectively. The median size of all the uranium aerosol particles on the three track filters was 1.25μm

  2. An Improved Strong Tracking Cubature Kalman Filter for GPS/INS Integrated Navigation Systems.

    Feng, Kaiqiang; Li, Jie; Zhang, Xi; Zhang, Xiaoming; Shen, Chong; Cao, Huiliang; Yang, Yanyu; Liu, Jun

    2018-06-12

    The cubature Kalman filter (CKF) is widely used in the application of GPS/INS integrated navigation systems. However, its performance may decline in accuracy and even diverge in the presence of process uncertainties. To solve the problem, a new algorithm named improved strong tracking seventh-degree spherical simplex-radial cubature Kalman filter (IST-7thSSRCKF) is proposed in this paper. In the proposed algorithm, the effect of process uncertainty is mitigated by using the improved strong tracking Kalman filter technique, in which the hypothesis testing method is adopted to identify the process uncertainty and the prior state estimate covariance in the CKF is further modified online according to the change in vehicle dynamics. In addition, a new seventh-degree spherical simplex-radial rule is employed to further improve the estimation accuracy of the strong tracking cubature Kalman filter. In this way, the proposed comprehensive algorithm integrates the advantage of 7thSSRCKF’s high accuracy and strong tracking filter’s strong robustness against process uncertainties. The GPS/INS integrated navigation problem with significant dynamic model errors is utilized to validate the performance of proposed IST-7thSSRCKF. Results demonstrate that the improved strong tracking cubature Kalman filter can achieve higher accuracy than the existing CKF and ST-CKF, and is more robust for the GPS/INS integrated navigation system.

  3. Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

    Hamza Benzerrouk

    2018-03-01

    Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

  4. Learning based particle filtering object tracking for visible-light systems.

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  5. Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

    Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

    2017-11-01

    Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

  6. Monitors Track Vital Signs for Fitness and Safety

    2012-01-01

    Have you ever felt nauseous reading a book in the back seat of a car? Or woken from a deep sleep feeling disoriented, unsure which way is up? Momentary mixups like these happen when the sensory systems that track the body's orientation in space become confused. (In the case of the backseat bookworm, the conflict arises when the reader s inner ear, part of the body s vestibular system, senses the car s motion while her eyes are fixed on the stationary pages of the book.) Conditions like motion sickness are common on Earth, but they also present a significant challenge to astronauts in space. Human sensory systems use the pull of gravity to help determine orientation. In the microgravity environment onboard the International Space Station, for example, the body experiences a period of confusion before it adapts to the new circumstances. (In space, even the body s proprioceptive system, which tells the brain where the arms and legs are oriented without the need for visual confirmation, goes haywire, meaning astronauts sometimes lose track of where their limbs are when they are not moving them.) This Space Adaptation Syndrome affects a majority of astronauts, even experienced ones, causing everything from mild disorientation to nausea to severe vomiting. "It can be quite debilitating," says William Toscano, a research scientist in NASA s Ames Research Center Psychophysiology Laboratory, part of the Center s Human Systems Integration Division. "When this happens, as you can imagine, work proficiency declines considerably." Since astronauts cannot afford to be distracted or incapacitated during critical missions, NASA has explored various means for preventing and countering motion sickness in space, including a range of drug treatments. Many effective motion sickness drugs, however, cause undesirable side effects, such as drowsiness. Toscano and his NASA colleague, Patricia Cowings, have developed a different approach: Utilizing biofeedback training methods, the pair can

  7. TREC2002 Web, Novelty and Filtering Track Experiments Using PIRCS

    Kwok, K. L; Deng, P; Dinstl, N; Chan, M

    2006-01-01

    .... The Web track has two tasks: distillation and named-page retrieval. Distillation is a new utility concept for ranking documents, and needs new design on the output document ranked list after an ad-hoc retrieval from the web (.gov) collection...

  8. Kalman filters for real-time magnetic island phase tracking

    Borgers, D. P.; Lauret, M.; M.R. de Baar,

    2013-01-01

    For control of neoclassical tearing modes (NTMs) and the resulting rotating magnetic islands in tokamak plasmas, the frequency and phase of the magnetic islands need to be accurately tracked in real-time. In previous experiments on TEXTOR, this was achieved using a phase-locked loop (PLL). For ASDEX

  9. A hand tracking algorithm with particle filter and improved GVF snake model

    Sun, Yi-qi; Wu, Ai-guo; Dong, Na; Shao, Yi-zhe

    2017-07-01

    To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion.

  10. Signal Tracking Beyond the Time Resolution of an Atomic Sensor by Kalman Filtering

    Jiménez-Martínez, Ricardo; Kołodyński, Jan; Troullinou, Charikleia; Lucivero, Vito Giovanni; Kong, Jia; Mitchell, Morgan W.

    2018-01-01

    We study causal waveform estimation (tracking) of time-varying signals in a paradigmatic atomic sensor, an alkali vapor monitored by Faraday rotation probing. We use Kalman filtering, which optimally tracks known linear Gaussian stochastic processes, to estimate stochastic input signals that we generate by optical pumping. Comparing the known input to the estimates, we confirm the accuracy of the atomic statistical model and the reliability of the Kalman filter, allowing recovery of waveform details far briefer than the sensor's intrinsic time resolution. With proper filter choice, we obtain similar benefits when tracking partially known and non-Gaussian signal processes, as are found in most practical sensing applications. The method evades the trade-off between sensitivity and time resolution in coherent sensing.

  11. Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

    LI Shuo; TAO Ran

    2006-01-01

    We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

  12. Gaussian mixture probability hypothesis density filter for multipath multitarget tracking in over-the-horizon radar

    Qin, Yong; Ma, Hong; Chen, Jinfeng; Cheng, Li

    2015-12-01

    Conventional multitarget tracking systems presume that each target can produce at most one measurement per scan. Due to the multiple ionospheric propagation paths in over-the-horizon radar (OTHR), this assumption is not valid. To solve this problem, this paper proposes a novel tracking algorithm based on the theory of finite set statistics (FISST) called the multipath probability hypothesis density (MP-PHD) filter in cluttered environments. First, the FISST is used to derive the update equation, and then Gaussian mixture (GM) is introduced to derive the closed-form solution of the MP-PHD filter. Moreover, the extended Kalman filter (EKF) is presented to deal with the nonlinear problem of the measurement model in OTHR. Eventually, the simulation results are provided to demonstrate the effectiveness of the proposed filter.

  13. Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

    Jing Liu

    2012-01-01

    Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

  14. Joint polarization tracking and channel equalization based on radius-directed linear Kalman filter

    Zhang, Qun; Yang, Yanfu; Zhong, Kangping; Liu, Jie; Wu, Xiong; Yao, Yong

    2018-01-01

    We propose a joint polarization tracking and channel equalization scheme based on radius-directed linear Kalman filter (RD-LKF) by introducing the butterfly finite-impulse-response (FIR) filter in our previously proposed RD-LKF method. Along with the fast polarization tracking, it can also simultaneously compensate the inter-symbol interference (ISI) effects including residual chromatic dispersion and polarization mode dispersion. Compared with the conventional radius-directed equalizer (RDE) algorithm, it is demonstrated experimentally that three times faster convergence speed, one order of magnitude better tracking capability, and better BER performance is obtained in polarization division multiplexing 16 quadrature amplitude modulation system. Besides, the influences of the algorithm parameters on the convergence and the tracking performance are investigated by numerical simulation.

  15. Implementation and Performance of FPGA based track fitting for the Atlas Fast TracKer

    Zou, Rui; The ATLAS collaboration

    2018-01-01

    The Fast TracKer (FTK) within the ATLAS trigger system provides global track reconstruction for all events passing the ATLAS Level 1 trigger by dividing the detector into parallel processing pipelines that implement pattern matching in custom integrated circuits and data routing, reduction, and parameter extraction in FPGAs. In this presentation we will describe the implementation of a critical component of the system which does partial track fitting using a method based on a principal component analysis at a rate of greater than 1 fit per 10 ps, system-wide, to reduce the output of the pattern matching. Firmware design, timing performance and preliminary results will be discussed.

  16. Proposed hardware architectures of particle filter for object tracking

    Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED

    2012-12-01

    In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.

  17. Tracking performance of unbalanced QPSK demodulators. I - Biphase Costas loop with passive arm filters

    Simon, M. K.; Alem, W. K.

    1978-01-01

    Unbalanced quadriphase-shift-keying (QPSK) is an attractive means for transmitting two digital data streams which in general have different average powers, data rates, and data formats. Previous analyses of the tracking performance of Costas loop demodulators of unbalanced QPSK have accounted only for the filtering effect produced by the loop's two arm filters on the equivalent additive noise perturbing the loop. When the bandwidth of these filters is selected on the basis of the order of the data rate, as is typical of optimum Costas loop design, the filtering degradations of the data modulations themselves and the cross-modulation noise produced by their multiplication in the loop often cannot be neglected. The purpose of this paper is to incorporate these additional filtering effects into the analysis. Many of the results obtained herein are in the form of closed-form expressions which can easily be evaluated numerically for design and performance prediction purposes.

  18. Frequency tracking and variable bandwidth for line noise filtering without a reference.

    Kelly, John W; Collinger, Jennifer L; Degenhart, Alan D; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

    2011-01-01

    This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.

  19. Detecting Power Voltage Dips using Tracking Filters - A Comparison against Kalman

    STANCIU, I.-R.

    2012-11-01

    Full Text Available Due of its significant economical impact, Power-Quality (PQ analysis is an important domain today. Severe voltage distortions affect the consumers and disturb their activity. They may be caused by short circuits (in this case the voltage drops significantly or by varying loads (with a smaller drop. These two types are the PQ currently issues. Monitoring these phenomena (called dips or sags require powerful techniques. Digital Signal Processing (DSP algorithms are currently employed to fulfill this task. Discrete Wavelet Transforms, (and variants, Kalman filters, and S-Transform are currently proposed by researchers to detect voltage dips. This paper introduces and examines a new tool to detect voltage dips: the so-called tracking filters. Discovered and tested during the cold war, they can estimate a parameter of interest one-step-ahead based on the previously observed values. Two filters are implemented. Their performance is assessed by comparison against the Kalman filter?s results.

  20. Carrier tracking by smoothing filter improves symbol SNR

    Pomalaza-Raez, Carlos A.; Hurd, William J.

    1986-01-01

    The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (SNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

  1. Carrier tracking by smoothing filter can improve symbol SNR

    Hurd, W. J.; Pomalaza-Raez, C. A.

    1985-01-01

    The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (CNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

  2. Ultrasound effects on the electrolytically controlled etching of nuclear track filters (NTFs)

    Chakarvarti, S.K.; Mahna, S.K.; Sud, L.V.; Singh, P.

    1990-01-01

    The mechanical stirring of the etchant creates tremendous changes in the etching properties of SSNTDs. Ultrasound stirring also produces a number of effects in liquids by giving a rapid movement to etchant. Cavitation is the most probable phenomenon caused by ultrasound and responsible for most of the effects observed in chemical reactions. Microbubbles are created in liquid medium and explosion of these microbubbles is responsible for momentarily rise in temperature. The possible effects of ultrasound on etching of particle tracks in plastic track detectors as nuclear track filters has been studied. The ultrasound effects on V t and V b have been studied in this work. (author). 5 re fs

  3. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

    2016-01-01

    , an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  4. Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation : Robustness and Accuracy Assessment

    Bourque, Alexandra E; Bedwani, Stéphane; Carrier, Jean-François; Ménard, Cynthia; Borman, Pim; Bos, Clemens; Raaymakers, Bas W; Mickevicius, Nikolai; Paulson, Eric; Tijssen, Rob H N

    PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments. METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized

  5. GM-PHD Filter Combined with Track-Estimate Association and Numerical Interpolation

    Jinguang Chen

    2015-01-01

    Full Text Available For the standard Gaussian mixture probability hypothesis density (GM-PHD filter, the number of targets can be overestimated if the clutter rate is too high or underestimated if the detection rate is too low. These problems seriously affect the accuracy of multitarget tracking for the number and the value of measurements and clutters cannot be distinguished and recognized. Therefore, we proposed an improved GM-PHD filter to tackle these problems. Firstly, a track-estimate association was implemented in the filtering process to detect and remove false-alarm targets. Secondly, a numerical interpolation technique was used to compensate the missing targets caused by low detection rate. At the end of this paper, simulation results were presented to demonstrate the proposed GM-PHD algorithm is more effective in estimating the number and state of targets than the previous ones.

  6. Adaptive Kalman Filter Applied to Vision Based Head Gesture Tracking for Playing Video Games

    Mohammadreza Asghari Oskoei

    2017-11-01

    Full Text Available This paper proposes an adaptive Kalman filter (AKF to improve the performance of a vision-based human machine interface (HMI applied to a video game. The HMI identifies head gestures and decodes them into corresponding commands. Face detection and feature tracking algorithms are used to detect optical flow produced by head gestures. Such approaches often fail due to changes in head posture, occlusion and varying illumination. The adaptive Kalman filter is applied to estimate motion information and reduce the effect of missing frames in a real-time application. Failure in head gesture tracking eventually leads to malfunctioning game control, reducing the scores achieved, so the performance of the proposed vision-based HMI is examined using a game scoring mechanism. The experimental results show that the proposed interface has a good response time, and the adaptive Kalman filter improves the game scores by ten percent.

  7. Event-triggered Kalman-consensus filter for two-target tracking sensor networks.

    Su, Housheng; Li, Zhenghao; Ye, Yanyan

    2017-11-01

    This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event-triggered protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  8. A low-complexity interacting multiple model filter for maneuvering target tracking

    Khalid, Syed Safwan

    2017-01-22

    In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

  9. A low-complexity interacting multiple model filter for maneuvering target tracking

    Khalid, Syed Safwan; Abrar, Shafayat

    2017-01-01

    In this work, we address the target tracking problem for a coordinate-decoupled Markovian jump-mean-acceleration based maneuvering mobility model. A novel low-complexity alternative to the conventional interacting multiple model (IMM) filter is proposed for this class of mobility models. The proposed tracking algorithm utilizes a bank of interacting filters where the interactions are limited to the mixing of the mean estimates, and it exploits a fixed off-line computed Kalman gain matrix for the entire filter bank. Consequently, the proposed filter does not require matrix inversions during on-line operation which significantly reduces its complexity. Simulation results show that the performance of the low-complexity proposed scheme remains comparable to that of the traditional (highly-complex) IMM filter. Furthermore, we derive analytical expressions that iteratively evaluate the transient and steady-state performance of the proposed scheme, and establish the conditions that ensure the stability of the proposed filter. The analytical findings are in close accordance with the simulated results.

  10. An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

    Raihan A. V, Dilshad; Chakravorty, Suman

    2018-03-01

    Optimal and consistent estimation of the state of space objects is pivotal to surveillance and tracking applications. However, probabilistic estimation of space objects is made difficult by the non-Gaussianity and nonlinearity associated with orbital mechanics. In this paper, we present an unscented Kalman-particle hybrid filtering framework for recursive Bayesian estimation of space objects. The hybrid filtering scheme is designed to provide accurate and consistent estimates when measurements are sparse without incurring a large computational cost. It employs an unscented Kalman filter (UKF) for estimation when measurements are available. When the target is outside the field of view (FOV) of the sensor, it updates the state probability density function (PDF) via a sequential Monte Carlo method. The hybrid filter addresses the problem of particle depletion through a suitably designed filter transition scheme. To assess the performance of the hybrid filtering approach, we consider two test cases of space objects that are assumed to undergo full three dimensional orbital motion under the effects of J 2 and atmospheric drag perturbations. It is demonstrated that the hybrid filters can furnish fast, accurate and consistent estimates outperforming standard UKF and particle filter (PF) implementations.

  11. Arbitrary-step randomly delayed robust filter with application to boost phase tracking

    Qin, Wutao; Wang, Xiaogang; Bai, Yuliang; Cui, Naigang

    2018-04-01

    The conventional filters such as extended Kalman filter, unscented Kalman filter and cubature Kalman filter assume that the measurement is available in real-time and the measurement noise is Gaussian white noise. But in practice, both two assumptions are invalid. To solve this problem, a novel algorithm is proposed by taking the following four steps. At first, the measurement model is modified by the Bernoulli random variables to describe the random delay. Then, the expression of predicted measurement and covariance are reformulated, which could get rid of the restriction that the maximum number of delay must be one or two and the assumption that probabilities of Bernoulli random variables taking the value one are equal. Next, the arbitrary-step randomly delayed high-degree cubature Kalman filter is derived based on the 5th-degree spherical-radial rule and the reformulated expressions. Finally, the arbitrary-step randomly delayed high-degree cubature Kalman filter is modified to the arbitrary-step randomly delayed high-degree cubature Huber-based filter based on the Huber technique, which is essentially an M-estimator. Therefore, the proposed filter is not only robust to the randomly delayed measurements, but robust to the glint noise. The application to the boost phase tracking example demonstrate the superiority of the proposed algorithms.

  12. Calorie counting and fitness tracking technology: Associations with eating disorder symptomatology.

    Simpson, Courtney C; Mazzeo, Suzanne E

    2017-08-01

    The use of online calorie tracking applications and activity monitors is increasing exponentially. Anecdotal reports document the potential for these trackers to trigger, maintain, or exacerbate eating disorder symptomatology. Yet, research has not examined the relation between use of these devices and eating disorder-related attitudes and behaviors. This study explored associations between the use of calorie counting and fitness tracking devices and eating disorder symptomatology. Participants (N=493) were college students who reported their use of tracking technology and completed measures of eating disorder symptomatology. Individuals who reported using calorie trackers manifested higher levels of eating concern and dietary restraint, controlling for BMI. Additionally, fitness tracking was uniquely associated with ED symptomatology after adjusting for gender and bingeing and purging behavior within the past month. Findings highlight associations between use of calorie and fitness trackers and eating disorder symptomatology. Although preliminary, overall results suggest that for some individuals, these devices might do more harm than good. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Guitarist Fingertip Tracking by Integrating a Bayesian Classifier into Particle Filters

    Chutisant Kerdvibulvech

    2008-01-01

    Full Text Available We propose a vision-based method for tracking guitar fingerings made by guitar players. We present it as a new framework for tracking colored finger markers by integrating a Bayesian classifier into particle filters. This adds the useful abilities of automatic track initialization and recovery from tracking failures in a dynamic background. Furthermore, by using the online adaptation of color probabilities, this method is able to cope with illumination changes. Augmented Reality Tag (ARTag is then utilized to calculate the projection matrix as an online process which allows the guitar to be moved while being played. Representative experimental results are also included. The method presented can be used to develop the application of human-computer interaction (HCI to guitar playing by recognizing the chord being played by a guitarist in virtual spaces. The aforementioned application would assist guitar learners by allowing them to automatically identify if they are using the correct chords required by the musical piece.

  14. An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

    Li, Jian; Wei, Xinguo; Zhang, Guangjun

    2017-08-21

    Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

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

    Bizhong Xia

    2015-11-01

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

  16. Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

    Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

    2018-01-01

    Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

  17. Kalman filter based data fusion for neutral axis tracking in wind turbine towers

    Soman, Rohan; Malinowski, Pawel; Ostachowicz, Wieslaw

    2015-01-01

    downtime, hence increasing the availability of the system. The present work is based on the use of neutral axis (NA) for SHM of the structure. The NA is tracked by data fusion of measured yaw angle and strain through the use of Extended Kalman Filter (EKF). The EKF allows accurate tracking even...... in the NA position may be used for detecting and locating the damage. The wind turbine tower has been modelled with FE software ABAQUS and validated on data from load measurements carried out on the 34m high tower of the Nordtank, NTK 500/41 wind turbine....

  18. Realization of nuclear track filters and their applications to the study of environmental aerosol samples

    Guo Shilun

    1993-01-01

    Detailed study of the behaviours of radon decay products requires the knowledge of environmental aerosols. A combination of devices and instruments have been tested to be superior in study of aerosol characteristics. Nuclear track filters and cascade track filter impactor are basic devices, which bring the functions of α -spectrometer, scanning electron microscope and electron microprobe into full play. This paper describes how to use these devices and instruments to collect aerosols, to determine aerosol radioactivity, size distribution and elemental compositions and to determine the concentration of aerosols in air as a function of aerosol sizes, which are important parameters in dominating the interactions between aerosol and radon decay products. (author). 15 refs, 7 figs

  19. Fitness

    ... gov home http://www.girlshealth.gov/ Home Fitness Fitness Want to look and feel your best? Physical ... are? Check out this info: What is physical fitness? top Physical fitness means you can do everyday ...

  20. Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

    Liu, Hua; Wu, Wen

    2017-06-13

    For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

  1. Interacting Multiple Model (IMM Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

    Hua Liu

    2017-06-01

    Full Text Available For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF. The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF, the interacting multiple model cubature Kalman filter (IMMCKF and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF.

  2. Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

    Moore, Douglas; Sawant, Amit; Ruan, Dan

    2016-01-01

    Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al

  3. Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking

    Moore, Douglas, E-mail: douglas.moore@utsouthwestern.edu; Sawant, Amit [Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Ruan, Dan [Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

    2016-01-15

    Purpose: Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. Methods: This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. [“Management of three-dimensional intrafraction motion through real-time DMLC tracking,” Med. Phys. 35, 2050–2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. Results: This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al

  4. Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

    Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

    2014-11-11

    The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

  5. Electrochemical synthesis of metallic microstructures using etched ion tracks in nuclear track filters

    Sanjeev Kumar; Shyam Kumar; Rajesh Kumar; Chakravarti, K.

    2004-01-01

    Interest in nano/microstructures results from their numerous potential applications in various areas such as materials and biomedical sciences, electronics, optics, magnetism, energy storage and electrochemistry. Materials with micro/nanoscopic dimensions not only have potential technological applications in areas such as device technology and drug delivery, but also are of fundamental interest in that the properties of a material can change in this regime of transition between the bulk and molecular scales. Electrodeposition is a versatile technique combining low processing cost with ambient conditions that can be used to prepare metallic, polymeric and semiconducting microstructures. In the present work ion track membranes of Makrofol (KG) have been used as templates for synthesis of metallic microstructures using the technique of electrodeposition. (author)

  6. Strong Tracking Filter for Nonlinear Systems with Randomly Delayed Measurements and Correlated Noises

    Hongtao Yang

    2018-01-01

    Full Text Available This paper proposes a novel strong tracking filter (STF, which is suitable for dealing with the filtering problem of nonlinear systems when the following cases occur: that is, the constructed model does not match the actual system, the measurements have the one-step random delay, and the process and measurement noises are correlated at the same epoch. Firstly, a framework of decoupling filter (DF based on equivalent model transformation is derived. Further, according to the framework of DF, a new extended Kalman filtering (EKF algorithm via using first-order linearization approximation is developed. Secondly, the computational process of the suboptimal fading factor is derived on the basis of the extended orthogonality principle (EOP. Thirdly, the ultimate form of the proposed STF is obtained by introducing the suboptimal fading factor into the above EKF algorithm. The proposed STF can automatically tune the suboptimal fading factor on the basis of the residuals between available and predicted measurements and further the gain matrices of the proposed STF tune online to improve the filtering performance. Finally, the effectiveness of the proposed STF has been proved through numerical simulation experiments.

  7. Particle Filter with Integrated Voice Activity Detection for Acoustic Source Tracking

    Anders M. Johansson

    2007-01-01

    Full Text Available In noisy and reverberant environments, the problem of acoustic source localisation and tracking (ASLT using an array of microphones presents a number of challenging difficulties. One of the main issues when considering real-world situations involving human speakers is the temporally discontinuous nature of speech signals: the presence of silence gaps in the speech can easily misguide the tracking algorithm, even in practical environments with low to moderate noise and reverberation levels. A natural extension of currently available sound source tracking algorithms is the integration of a voice activity detection (VAD scheme. We describe a new ASLT algorithm based on a particle filtering (PF approach, where VAD measurements are fused within the statistical framework of the PF implementation. Tracking accuracy results for the proposed method is presented on the basis of synthetic audio samples generated with the image method, whereas performance results obtained with a real-time implementation of the algorithm, and using real audio data recorded in a reverberant room, are published elsewhere. Compared to a previously proposed PF algorithm, the experimental results demonstrate the improved robustness of the method described in this work when tracking sources emitting real-world speech signals, which typically involve significant silence gaps between utterances.

  8. Radar tracking with an interacting multiple model and probabilistic data association filter for civil aviation applications.

    Jan, Shau-Shiun; Kao, Yu-Chun

    2013-05-17

    The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC) system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM) system that is enabled by global positioning system (GPS) technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF), is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF), is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods.

  9. Radar Tracking with an Interacting Multiple Model and Probabilistic Data Association Filter for Civil Aviation Applications

    Shau-Shiun Jan

    2013-05-01

    Full Text Available The current trend of the civil aviation technology is to modernize the legacy air traffic control (ATC system that is mainly supported by many ground based navigation aids to be the new air traffic management (ATM system that is enabled by global positioning system (GPS technology. Due to the low receiving power of GPS signal, it is a major concern to aviation authorities that the operation of the ATM system might experience service interruption when the GPS signal is jammed by either intentional or unintentional radio-frequency interference. To maintain the normal operation of the ATM system during the period of GPS outage, the use of the current radar system is proposed in this paper. However, the tracking performance of the current radar system could not meet the required performance of the ATM system, and an enhanced tracking algorithm, the interacting multiple model and probabilistic data association filter (IMMPDAF, is therefore developed to support the navigation and surveillance services of the ATM system. The conventional radar tracking algorithm, the nearest neighbor Kalman filter (NNKF, is used as the baseline to evaluate the proposed radar tracking algorithm, and the real flight data is used to validate the IMMPDAF algorithm. As shown in the results, the proposed IMMPDAF algorithm could enhance the tracking performance of the current aviation radar system and meets the required performance of the new ATM system. Thus, the current radar system with the IMMPDAF algorithm could be used as an alternative system to continue aviation navigation and surveillance services of the ATM system during GPS outage periods.

  10. Model-based extended quaternion Kalman filter to inertial orientation tracking of arbitrary kinematic chains.

    Szczęsna, Agnieszka; Pruszowski, Przemysław

    2016-01-01

    Inertial orientation tracking is still an area of active research, especially in the context of out-door, real-time, human motion capture. Existing systems either propose loosely coupled tracking approaches where each segment is considered independently, taking the resulting drawbacks into account, or tightly coupled solutions that are limited to a fixed chain with few segments. Such solutions have no flexibility to change the skeleton structure, are dedicated to a specific set of joints, and have high computational complexity. This paper describes the proposal of a new model-based extended quaternion Kalman filter that allows for estimation of orientation based on outputs from the inertial measurements unit sensors. The filter considers interdependencies resulting from the construction of the kinematic chain so that the orientation estimation is more accurate. The proposed solution is a universal filter that does not predetermine the degree of freedom at the connections between segments of the model. To validation the motion of 3-segments single link pendulum captured by optical motion capture system is used. The next step in the research will be to use this method for inertial motion capture with a human skeleton model.

  11. Performance enhancement for a GPS vector-tracking loop utilizing an adaptive iterated extended Kalman filter.

    Chen, Xiyuan; Wang, Xiying; Xu, Yuan

    2014-12-09

    This paper deals with the problem of state estimation for the vector-tracking loop of a software-defined Global Positioning System (GPS) receiver. For a nonlinear system that has the model error and white Gaussian noise, a noise statistics estimator is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) named adaptive iterated Kalman filter (AIEKF) is proposed. A vector-tracking GPS receiver utilizing AIEKF is implemented to evaluate the performance of the proposed method. Through road tests, it is shown that the proposed method has an obvious accuracy advantage over the IEKF and Adaptive Extended Kalman filter (AEKF) in position determination. The results show that the proposed method is effective to reduce the root-mean-square error (RMSE) of position (including longitude, latitude and altitude). Comparing with EKF, the position RMSE values of AIEKF are reduced by about 45.1%, 40.9% and 54.6% in the east, north and up directions, respectively. Comparing with IEKF, the position RMSE values of AIEKF are reduced by about 25.7%, 19.3% and 35.7% in the east, north and up directions, respectively. Compared with AEKF, the position RMSE values of AIEKF are reduced by about 21.6%, 15.5% and 30.7% in the east, north and up directions, respectively.

  12. Sky-Hook Control and Kalman Filtering in Nonlinear Model of Tracked Vehicle Suspension System

    Jurkiewicz Andrzej

    2017-09-01

    Full Text Available The essence of the undertaken topic is application of the continuous sky-hook control strategy and the Extended Kalman Filter as the state observer in the 2S1 tracked vehicle suspension system. The half-car model of this suspension system consists of seven logarithmic spiral springs and two magnetorheological dampers which has been described by the Bingham model. The applied continuous sky-hook control strategy considers nonlinear stiffness characteristic of the logarithmic spiral springs. The control is determined on estimates generated by the Extended Kalman Filter. Improve of ride comfort is verified by comparing simulation results, under the same driving conditions, of controlled and passive vehicle suspension systems.

  13. Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

    Yazhe Tang

    2015-01-01

    Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

  14. Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar

    Fei Cai

    2014-01-01

    Full Text Available A particle filter based track-before-detect (PF-TBD algorithm is proposed for the monopulse high pulse repetition frequency (PRF pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied.

  15. Tracking single dynamic MEG dipole sources using the projected Extended Kalman Filter.

    Yao, Yuchen; Swindlehurst, A Lee

    2011-01-01

    This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

  16. Human tracking in thermal images using adaptive particle filters with online random forest learning

    Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

    2013-11-01

    This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

  17. Tracking of BMI, fatness and cardiorespiratory fitness from adolescence to middle adulthood: the Zagreb Growth and Development Longitudinal Study.

    Sorić, Maroje; Jembrek Gostović, Mirjana; Gostović, Mladen; Hočevar, Marija; Mišigoj-Duraković, Marjeta

    2014-01-01

    Effective intervention strategies aiming to improve cardiorespiratory fitness and to decrease body fatness are needed. However, long-term stability of these traits is not well understood. To assess long-term tracking of cardiorespiratory fitness and body fatness from late adolescence to middle adulthood. The sample consisted of 50 participants (31 boys) from the Zagreb Growth and Development Longitudinal Study who were followed up in adulthood (median age = 43). Fatness was evaluated through BMI and skin-folds, while cardiorespiratory fitness was assessed using a cardiopulmonary exercise test. Inter-age partial correlation coefficients were calculated to evaluate tracking. Body mass index and skin-folds showed moderate tracking from age 15 years to middle adulthood (partial r = 0.55, p < 0.001 and partial r = 0.52, p < 0.001, respectively), while tracking of subcutaneous fat distribution was somewhat lower (partial r = 0.38, p < 0.01). At the same time, the observed tracking of peak oxygen uptake was low-to-moderate (partial r = 0.30, p = 0.03), while ventilatory aerobic and anaerobic thresholds did not show significant tracking. The results of this study indicate that preventive efforts aiming to increase cardiorespiratory fitness should include all adolescents, irrespective of their cardiorespiratory fitness status. Conversely, strategies aiming at obesity prevention should focus on high-risk groups of adolescents.

  18. A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer.

    Ligorio, Gabriele; Sabatini, Angelo M

    2015-08-01

    Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in this study. A significant accuracy improvement was achieved over state-of-the-art approaches, due to a filter design that better matched the basic optimality assumptions of Kalman filtering. Human motion tracking is the main application field of the proposed method. Accurately discriminating the two components present in the triaxial accelerometer signal is well suited for studying both the rotational and the linear body kinematics.

  19. Electron Energy Resolution of the ATLAS TILECAL Modules with Fit Filter Method (July 2002 test beam)

    Kulchitskii, Yu A; Vinogradov, V B

    2006-01-01

    The constructed ATLAS detector at the LHC will have the great physics discovery potential, in particular in the detection of a heavy Higgs boson. Calorimeters will play a crucial role in it. It is necessary to have confidence that the calorimeters will perform as expected. With the aim of understanding of performance of the ATLAS Tile hadronic calorimeter to electrons 12\\% of modules have been exposed in electron beams with various energies by three possible ways: cell-scan at $\\theta =20^o$ at the centers of the front face cells, $\\eta$-scan and tilerow scan at $\\theta = 90^o$ for the module side cells. We have extracted the electron energy resolutions of the $EBM-$ (ANL-44), $EBM+$ (IFA-42) and $BM$ (JINR-55) Modules of the ATLAS Tile Calorimeter at energies E = 10, 20, 50, 100 and 180 GeV and $\\theta = 20^o$ and $90^o $ and $\\eta$ scan from the July 2002 testbeam run data using the fit filter method of the PMT signal reconstruction. We have determined the statistical and constant terms for the electron ene...

  20. Energy awareness for supercapacitors using Kalman filter state-of-charge tracking

    Nadeau, Andrew; Hassanalieragh, Moeen; Sharma, Gaurav; Soyata, Tolga

    2015-11-01

    Among energy buffering alternatives, supercapacitors can provide unmatched efficiency and durability. Additionally, the direct relation between a supercapacitor's terminal voltage and stored energy can improve energy awareness. However, a simple capacitive approximation cannot adequately represent the stored energy in a supercapacitor. It is shown that the three branch equivalent circuit model provides more accurate energy awareness. This equivalent circuit uses three capacitances and associated resistances to represent the supercapacitor's internal SOC (state-of-charge). However, the SOC cannot be determined from one observation of the terminal voltage, and must be tracked over time using inexact measurements. We present: 1) a Kalman filtering solution for tracking the SOC; 2) an on-line system identification procedure to efficiently estimate the equivalent circuit's parameters; and 3) experimental validation of both parameter estimation and SOC tracking for 5 F, 10 F, 50 F, and 350 F supercapacitors. Validation is done within the operating range of a solar powered application and the associated power variability due to energy harvesting. The proposed techniques are benchmarked against the simple capacitive model and prior parameter estimation techniques, and provide a 67% reduction in root-mean-square error for predicting usable buffered energy.

  1. Fusing inertial sensor data in an extended Kalman filter for 3D camera tracking.

    Erdem, Arif Tanju; Ercan, Ali Özer

    2015-02-01

    In a setup where camera measurements are used to estimate 3D egomotion in an extended Kalman filter (EKF) framework, it is well-known that inertial sensors (i.e., accelerometers and gyroscopes) are especially useful when the camera undergoes fast motion. Inertial sensor data can be fused at the EKF with the camera measurements in either the correction stage (as measurement inputs) or the prediction stage (as control inputs). In general, only one type of inertial sensor is employed in the EKF in the literature, or when both are employed they are both fused in the same stage. In this paper, we provide an extensive performance comparison of every possible combination of fusing accelerometer and gyroscope data as control or measurement inputs using the same data set collected at different motion speeds. In particular, we compare the performances of different approaches based on 3D pose errors, in addition to camera reprojection errors commonly found in the literature, which provides further insight into the strengths and weaknesses of different approaches. We show using both simulated and real data that it is always better to fuse both sensors in the measurement stage and that in particular, accelerometer helps more with the 3D position tracking accuracy, whereas gyroscope helps more with the 3D orientation tracking accuracy. We also propose a simulated data generation method, which is beneficial for the design and validation of tracking algorithms involving both camera and inertial measurement unit measurements in general.

  2. Guidelines for the fitting of anomalous diffusion mean square displacement graphs from single particle tracking experiments.

    Eldad Kepten

    Full Text Available Single particle tracking is an essential tool in the study of complex systems and biophysics and it is commonly analyzed by the time-averaged mean square displacement (MSD of the diffusive trajectories. However, past work has shown that MSDs are susceptible to significant errors and biases, preventing the comparison and assessment of experimental studies. Here, we attempt to extract practical guidelines for the estimation of anomalous time averaged MSDs through the simulation of multiple scenarios with fractional Brownian motion as a representative of a large class of fractional ergodic processes. We extract the precision and accuracy of the fitted MSD for various anomalous exponents and measurement errors with respect to measurement length and maximum time lags. Based on the calculated precision maps, we present guidelines to improve accuracy in single particle studies. Importantly, we find that in some experimental conditions, the time averaged MSD should not be used as an estimator.

  3. Strategy for fitting source strength and reconstruction procedure in radioactive particle tracking

    Mosorov, Volodymyr

    2015-01-01

    The Radioactive Particle Tracking (RPT) technique is widely applied to study the dynamic properties of flows inside a reactor. Usually, a single radioactive particle that is neutrally buoyant with respect to the phase is used as a tracker. The particle moves inside a 3D volume of interest, and its positions are determined by an array of scintillation detectors, which count the incoming photons. The particle position coordinates are calculated by using a reconstruction procedure that solves a minimization problem between the measured counts and calibration data. Although previous studies have described the influence of specified factors on the RPT resolution and sensitivities, the question of how to choose an appropriate source strength and reconstruction procedure for the given RPT setup remains an unsolved problem. This work describes and applies the original strategy for fitting both the source strength and the sampling time interval to a specified RPT setup to guarantee a required accuracy of measurements. Additionally, the measurement accuracy of an RPT setup can be significantly increased by changing the reconstruction procedure. The results of the simulations, based on the Monte Carlo approach, have demonstrated that the proposed strategy allows for the successful implementation of the As Low As Reasonably Achievable (ALARA) principle when designing the RPT setup. The limitations and drawbacks of the proposed procedure are also presented. - Highlights: • We develop an original strategy for fitting source strength and measurement time interval in radioactive particle tracking (RPT) technique. • The proposed strategy allows successfully to implement the ALAPA (As Low As Reasonably Achievable) principle in designing of a RPT setup. • Measurement accuracy of a RPT setup can be significantly increased by improvement of the reconstruction procedure. • The algorithm can be applied to monitor the motion of the radioactive tracer in a reactor

  4. Procedure manual for the estimation of average indoor radon-daughter concentrations using the filtered alpha-track method

    George, J.L.

    1988-04-01

    One of the measurement needs of US Department of Energy (DOE) remedial action programs is the estimation of the annual-average indoor radon-daughter concentration (RDC) in structures. The filtered alpha-track method, using a 1-year exposure period, can be used to accomplish RDC estimations for the DOE remedial action programs. This manual describes the procedure used to obtain filtered alpha-track measurements to derive average RDC estimates from the measurrements. Appropriate quality-assurance and quality-control programs are also presented. The ''prompt'' alpha-track method of exposing monitors for 2 to 6 months during specific periods of the year is also briefly discussed in this manual. However, the prompt alpha-track method has been validated only for use in the Mesa County, Colorado, area. 3 refs., 3 figs

  5. Kalman Filter Based Data Fusion for Bi-Axial Neutral Axis Tracking in Wind Turbine Towers

    Soman, Rohan; Malinowski, Pawel; Schmidt Paulsen, Uwe

    2015-01-01

    demonstrates a methodology for the selection of threshold for damage detection based on qualitative data acquired from several damage scenarios of a 10 MW wind turbine. The damage indicator is the change of neutral axis (NA) which is tracked using Kalman Filter (KF). Based on the level of damage to be detected...... in the structure is reflected by a change in this feature. If this change is above a threshold the structure is said to be damaged. In most applications the determination of this threshold is based on engineering judgment and the previous experience of the operator. These practices are highly subjective...... and the probability of occurrence of false positive and false negative detections, a threshold value is selected. This threshold is then applied to strain data from the Nordtank NTK500/41 wind turbine for validation....

  6. Evaluation of an image-based tracking workflow with Kalman filtering for automatic image plane alignment in interventional MRI.

    Neumann, M; Cuvillon, L; Breton, E; de Matheli, M

    2013-01-01

    Recently, a workflow for magnetic resonance (MR) image plane alignment based on tracking in real-time MR images was introduced. The workflow is based on a tracking device composed of 2 resonant micro-coils and a passive marker, and allows for tracking of the passive marker in clinical real-time images and automatic (re-)initialization using the microcoils. As the Kalman filter has proven its benefit as an estimator and predictor, it is well suited for use in tracking applications. In this paper, a Kalman filter is integrated in the previously developed workflow in order to predict position and orientation of the tracking device. Measurement noise covariances of the Kalman filter are dynamically changed in order to take into account that, according to the image plane orientation, only a subset of the 3D pose components is available. The improved tracking performance of the Kalman extended workflow could be quantified in simulation results. Also, a first experiment in the MRI scanner was performed but without quantitative results yet.

  7. Physics-based coastal current tomographic tracking using a Kalman filter.

    Wang, Tongchen; Zhang, Ying; Yang, T C; Chen, Huifang; Xu, Wen

    2018-05-01

    Ocean acoustic tomography can be used based on measurements of two-way travel-time differences between the nodes deployed on the perimeter of the surveying area to invert/map the ocean current inside the area. Data at different times can be related using a Kalman filter, and given an ocean circulation model, one can in principle now cast and even forecast current distribution given an initial distribution and/or the travel-time difference data on the boundary. However, an ocean circulation model requires many inputs (many of them often not available) and is unpractical for estimation of the current field. A simplified form of the discretized Navier-Stokes equation is used to show that the future velocity state is just a weighted spatial average of the current state. These weights could be obtained from an ocean circulation model, but here in a data driven approach, auto-regressive methods are used to obtain the time and space dependent weights from the data. It is shown, based on simulated data, that the current field tracked using a Kalman filter (with an arbitrary initial condition) is more accurate than that estimated by the standard methods where data at different times are treated independently. Real data are also examined.

  8. Kalman filter based data fusion for neutral axis tracking in wind turbine towers

    Soman, Rohan; Malinowski, Pawel; Ostachowicz, Wieslaw; Paulsen, Uwe S.

    2015-03-01

    Wind energy is seen as one of the most promising solutions to man's ever increasing demands of a clean source of energy. In particular to reduce the cost of energy (COE) generated, there are efforts to increase the life-time of the wind turbines, to reduce maintenance costs and to ensure high availability. Maintenance costs may be lowered and the high availability and low repair costs ensured through the use of condition monitoring (CM) and structural health monitoring (SHM). SHM allows early detection of damage and allows maintenance planning. Furthermore, it can allow us to avoid unnecessary downtime, hence increasing the availability of the system. The present work is based on the use of neutral axis (NA) for SHM of the structure. The NA is tracked by data fusion of measured yaw angle and strain through the use of Extended Kalman Filter (EKF). The EKF allows accurate tracking even in the presence of changing ambient conditions. NA is defined as the line or plane in the section of the beam which does not experience any tensile or compressive forces when loaded. The NA is the property of the cross section of the tower and is independent of the applied loads and ambient conditions. Any change in the NA position may be used for detecting and locating the damage. The wind turbine tower has been modelled with FE software ABAQUS and validated on data from load measurements carried out on the 34m high tower of the Nordtank, NTK 500/41 wind turbine.

  9. Characterization of small-to-medium head-and-face dimensions for developing respirator fit test panels and evaluating fit of filtering facepiece respirators with different faceseal design

    Lin, Yi-Chun

    2017-01-01

    A respirator fit test panel (RFTP) with facial size distribution representative of intended users is essential to the evaluation of respirator fit for new models of respirators. In this study an anthropometric survey was conducted among youths representing respirator users in mid-Taiwan to characterize head-and-face dimensions key to RFTPs for application to small-to-medium facial features. The participants were fit-tested for three N95 masks of different facepiece design and the results compared to facial size distribution specified in the RFTPs of bivariate and principal component analysis design developed in this study to realize the influence of facial characteristics to respirator fit in relation to facepiece design. Nineteen dimensions were measured for 206 participants. In fit testing the qualitative fit test (QLFT) procedures prescribed by the U.S. Occupational Safety and Health Administration were adopted. As the results show, the bizygomatic breadth of the male and female participants were 90.1 and 90.8% of their counterparts reported for the U.S. youths (P < 0.001), respectively. Compared to the bivariate distribution, the PCA design better accommodated variation in facial contours among different respirator user groups or populations, with the RFTPs reported in this study and from literature consistently covering over 92% of the participants. Overall, the facial fit of filtering facepieces increased with increasing facial dimensions. The total percentages of the tests wherein the final maneuver being completed was “Moving head up-and-down”, “Talking” or “Bending over” in bivariate and PCA RFTPs were 13.3–61.9% and 22.9–52.8%, respectively. The respirators with a three-panel flat fold structured in the facepiece provided greater fit, particularly when the users moved heads. When the facial size distribution in a bivariate RFTP did not sufficiently represent petite facial size, the fit testing was inclined to overestimate the general fit

  10. Leader-Follower Tracking System for Agricultural Vehicles: Fusion of Laser and Odometry Positioning Using Extended Kalman Filter

    Zhang Lin Huan

    2015-03-01

    Full Text Available The aim of this research was to develop a safe human-driven and autonomous leader-follower tracking system for an autonomous tractor. To enable the tracking system, a laser range finder (LRF-based landmark detection system was designed to observe the relative position between a leader and a follower used in agricultural operations. The virtual follower-based formation-tracking algorithm was developed to minimize tracking errors and ensure safety. An extended Kalman filter (EKF was implemented for fusing LRF and odometry position to ensure stability of tracking in noisy farmland conditions. Simulations were conducted for tracking the leader in small and large sinusoidal curved paths. Simulated results verified high accuracy of formation tracking, stable velocity, and regulated steering angle of the follower. The tracking method confirmed the follower could follow the leader with a required formation safely and steadily in noisy conditions. The EKF helped to improve observation accuracy, velocity, and steering angle stability of the follower. As a result of the improved accuracy of observation and motion action, the tracking performance for lateral, longitudinal, and heading were also improved after the EKF was implemented in the tracking system.

  11. Determination of boron in aqueous solutions by solid state nuclear track detectors technique, using a filtered neutron beam

    Moraes, M.A.P.V. de; Pugliesi, R.; Khouri, M.T.F.C.

    1985-11-01

    The solid state nuclear track detectors technique has been used for determination of boron in aqueous solutions, using a filtered neutron beam. The particles tracks from the 10 B(n,α)Li 7 reaction were registered in the CR-39 film, chemically etched in a (30%) KOH solution 70 0 C during 90 minutes. The obtained results showed the usefulness of this technique for boron determination in the ppm range. The inferior detectable limit was 9 ppm. The combined track registration efficiency factor K has been evaluated in the solutions, for the CR-39 detector and its values is K= (4,60 - + 0,06). 10 -4 cm. (Author) [pt

  12. Estimation of error components in a multi-error linear regression model, with an application to track fitting

    Fruehwirth, R.

    1993-01-01

    We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)

  13. Tracking magma volume recovery at okmok volcano using GPS and an unscented kalman filter

    Fournier, T.; Freymueller, Jeffrey T.; Cervelli, Peter

    2009-01-01

    Changes beneath a volcano can be observed through position changes in a GPS network, but distinguishing the source of site motion is not always straightforward. The records of continuous GPS sites provide a favorable data set for tracking magma migration. Dense campaign observations usually provide a better spatial picture of the overall deformation field, at the expense of an episodic temporal record. Combining these observations provides the best of both worlds. A Kalman filter provides a means for integrating discrete and continuous measurements and for interpreting subtle signals. The unscented Kalman filter (UKF) is a nonlinear method for time-dependent observations. We demonstrate the application of this technique to deformation data by applying it to GPS data collected at Okmok volcano. Seven years of GPS observations at Okmok are analyzed using a Mogi source model and the UKF. The deformation source at Okmok is relatively stable at 2.5 km depth below sea level, located beneath the center of the caldera, which means the surface deformation is caused by changes in the strength of the source. During the 7 years of GPS observations more than 0.5 m of uplift has occurred, a majority of that during the time period January 2003 to July 2004. The total volume recovery at Okmok since the last eruption in 1997 is ??60-80%. The UKF allows us to solve simultaneously for the time-dependence of the source strength and for the location without a priori information about the source. ?? 2009 by the American Geophysical Union.

  14. Improved Particle Filter for Passive Target Tracking%改进粒子滤波在被动目标跟踪中的应用

    邓小龙; 谢剑英; 杨煜普

    2005-01-01

    As a new method for dealing with any nonlinear or non-Gaussian distributions, based on the Monte Carlo methods and Bayesian filtering, particle filters (PF) are favored by researchers and widely applied in many fields. Based on particle filtering, an improved extended Kalman filter (EKF) proposal distribution is presented. Evaluation of the weights is simplified and other improved techniques including the residual resampling step and Markov Chain Monte Carlo method are introduced for target tracking. Performances of the EKF, basic PF and the improved PF are compared in target tracking examples. The simulation results confirm that the improved particle filter outperforms the others.

  15. Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter.

    Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

    2017-01-17

    The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor's stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

  16. Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

    Seongwan Kim

    2017-01-01

    Full Text Available The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor, usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

  17. On the use of particle filters for electromagnetic tracking in high dose rate brachytherapy

    Götz, Th I.; Lahmer, G.; Brandt, T.; Kallis, K.; Strnad, V.; Bert, Ch; Hensel, B.; Tomé, A. M.; Lang, E. W.

    2017-10-01

    Modern radiotherapy of female breast cancers often employs high dose rate brachytherapy, where a radioactive source is moved inside catheters, implanted in the female breast, according to a prescribed treatment plan. Source localization relative to the patient’s anatomy is determined with solenoid sensors whose spatial positions are measured with an electromagnetic tracking system. Precise sensor dwell position determination is of utmost importance to assure irradiation of the cancerous tissue according to the treatment plan. We present a hybrid data analysis system which combines multi-dimensional scaling with particle filters to precisely determine sensor dwell positions in the catheters during subsequent radiation treatment sessions. Both techniques are complemented with empirical mode decomposition for the removal of superimposed breathing artifacts. We show that the hybrid model robustly and reliably determines the spatial positions of all catheters used during the treatment and precisely determines any deviations of actual sensor dwell positions from the treatment plan. The hybrid system only relies on sensor positions measured with an EMT system and relates them to the spatial positions of the implanted catheters as initially determined with a computed x-ray tomography.

  18. Users' intention to continue using social fitness-tracking apps: expectation confirmation theory and social comparison theory perspective.

    Li, Jia; Liu, Xuan; Ma, Ling; Zhang, Weiqiang

    2018-03-05

    The key step in changing health behavior is understanding why users continue to use fitness apps. Therefore, we intend to investigate the users' intention to continue using social fitness-tracking apps. We identify two major forces driving continuous behavior. Expectation confirmation is the internal driving force and social comparison is the external driving force. A survey was conducted to test this proposed research model. We obtained 211 valid questionnaires. Our results indicate that activity amount ranking (p fitness-tracking apps. In addition, the impact of activity amount ranking and activity frequency ranking on continuous intention is moderated by expectation confirmation. Meanwhile, as the upward comparison tendency increases, the positive effect of confirmation on continuous intention decreases (p Social rank expectation and confirmation are the primary driving forces of continuous intention in individuals using fitness-tracking apps. Social rank is a meaningful and straightforward measurement individuals can use to evaluate their activity performance. An upward comparison tendency weakens the effect of confirmation on continuous intention.

  19. A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers

    Liu, Zhuowei; Chen, Shuxin; Wu, Hao; He, Renke; Hao, Lin

    2018-01-01

    In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely. To solve the problem, this paper proposed a novel PHD filter, called Student’s t mixture PHD (STM-PHD) filter. The proposed filter models the heavy-tailed process noise and measurement noise as a Student’s t distribution as well as approximates the multi-target intensity as a mixture of Student’s t components to be propagated in time. Then, a closed PHD recursion is obtained based on Student’s t approximation. Our approach can make full use of the heavy-tailed characteristic of a Student’s t distribution to handle the situations with heavy-tailed process and the measurement noises. The simulation results verify that the proposed filter can overcome the negative effect generated by outliers and maintain a good tracking accuracy in the simultaneous presence of process and measurement outliers. PMID:29617348

  20. Development of an optimal automatic control law and filter algorithm for steep glideslope capture and glideslope tracking

    Halyo, N.

    1976-01-01

    A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.

  1. Tracking of physical activity, fitness, body composition and diet from adolescence to young adulthood: The Young Hearts Project, Northern Ireland

    Savage J Maurice

    2004-10-01

    Full Text Available Abstract Background The assumption that lifestyles formed early in life track into adulthood has been used to justify the targeting of health promotion programmes towards children and adolescents. The aim of the current study was to use data from the Northern Ireland Young Hearts Project to ascertain the extent of tracking, between adolescence and young adulthood, of physical activity, aerobic fitness, selected anthropometric variables, and diet. Methods Males (n 245 and females (n 231 were assessed at age 15 y, and again in young adulthood [mean (SD age 22 (1.6 y]. At both timepoints, height, weight and skinfold thicknesses were measured, and physical activity and diet were assessed by questionnaire and diet history method respectively. At 15y, fitness was assessed using the 20 metre shuttle run, while at young adulthood, the PWC170 cycle ergometer test was used. For each measurement made at 15y, subjects were ranked into 'low' (L1; lowest 25%, 'medium' (M1; middle 50% or 'high' (H1; highest 25% categories. At young adulthood, similar categories (L2, M2, H2 were created. The extent of tracking of each variable over time was calculated using 3 × 3 matrices constructed using these two sets of categories, and summarised using kappa (κ statistics. Results Tracking of diet and fitness was poor (κ ≤ 0.20 in both sexes, indicating substantial drift of subjects between the low, medium and high categories over time. The tracking of physical activity in males was fair (κ 0.202, but was poor in females (κ 0.021. In contrast, anthropometric variables such as weight, body mass index and sum of skinfolds tracked more strongly in females (κ 0.540, κ 0.307, κ 0.357 respectively than in males (κ 0.337, κ 0.199, κ 0.216 respectively. Conclusions The poor tracking of fitness and diet in both sexes, and physical activity in females, suggests that these aspects of adolescent lifestyle are unlikely to be predictive of behaviours in young adulthood. In

  2. Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach

    Miran, Sina; Akram, Sahar; Sheikhattar, Alireza; Simon, Jonathan Z.; Zhang, Tao; Babadi, Behtash

    2018-01-01

    Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach). To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1) Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2) Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3) Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our proposed

  3. Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach

    Sina Miran

    2018-05-01

    Full Text Available Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG and electroencephalography (EEG. To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach or vice versa (the encoding approach. To produce robust results, these procedures require multiple trials for training purposes. Also, their decoding accuracy drops significantly when operating at high temporal resolutions. Thus, they are not well-suited for emerging real-time applications such as smart hearing aid devices or brain-computer interface systems, where training data might be limited and high temporal resolutions are desired. In this paper, we close this gap by developing an algorithmic pipeline for real-time decoding of the attentional state. Our proposed framework consists of three main modules: (1 Real-time and robust estimation of encoding or decoding coefficients, achieved by sparse adaptive filtering, (2 Extracting reliable markers of the attentional state, and thereby generalizing the widely-used correlation-based measures thereof, and (3 Devising a near real-time state-space estimator that translates the noisy and variable attention markers to robust and statistically interpretable estimates of the attentional state with minimal delay. Our proposed algorithms integrate various techniques including forgetting factor-based adaptive filtering, ℓ1-regularization, forward-backward splitting algorithms, fixed-lag smoothing, and Expectation Maximization. We validate the performance of our

  4. Computer Vision Tracking Using Particle Filters for 3D Position Estimation

    2014-03-27

    List of Acronyms Acronym Definition AFIT Air Force Institute of Technology ASIR Auxiliary Sampling Importance Re-sampling BPF Bootstrap Particle Filter...Auxiliary Sampling Importance Re-sampling ( ASIR ) filter, and Regularized Particle Filter (RPF), also seek to eliminate weight collapse through a variety

  5. KALMAN FILTER BASED FEATURE ANALYSIS FOR TRACKING PEOPLE FROM AIRBORNE IMAGES

    B. Sirmacek

    2012-09-01

    Full Text Available Recently, analysis of man events in real-time using computer vision techniques became a very important research field. Especially, understanding motion of people can be helpful to prevent unpleasant conditions. Understanding behavioral dynamics of people can also help to estimate future states of underground passages, shopping center like public entrances, or streets. In order to bring an automated solution to this problem, we propose a novel approach using airborne image sequences. Although airborne image resolutions are not enough to see each person in detail, we can still notice a change of color components in the place where a person exists. Therefore, we propose a color feature detection based probabilistic framework in order to detect people automatically. Extracted local features behave as observations of the probability density function (pdf of the people locations to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf. First, we use estimated pdf to detect boundaries of dense crowds. After that, using background information of dense crowds and previously extracted local features, we detect other people in non-crowd regions automatically for each image in the sequence. We benefit from Kalman filtering to track motion of detected people. To test our algorithm, we use a stadium entrance image data set taken from airborne camera system. Our experimental results indicate possible usage of the algorithm in real-life man events. We believe that the proposed approach can also provide crucial information to police departments and crisis management teams to achieve more detailed observations of people in large open area events to prevent possible accidents or unpleasant conditions.

  6. Motivation and User Engagement in Fitness Tracking: Heuristics for Mobile Healthcare Wearables

    Stavros Asimakopoulos

    2017-01-01

    Full Text Available Wearable fitness trackers have gained a new level of popularity due to their ambient data gathering and analysis. This has signalled a trend toward self-efficacy and increased motivation among users of these devices. For consumers looking to improve their health, fitness trackers offer a way to more readily gain motivation via the personal data-based insights the devices offer. However, the user experience (UX that accompanies wearables is critical to helping users interpret, understand, gain motivation and act on their data. Despite this, there is little evidence as to specific aspects of fitness tracker user engagement and long-term motivation. We report on a 4-week situated diary study and Healthcare Technology Self-efficacy (HTSE questionnaire assessment of 34 users of two popular American fitness trackers: JawBone and FitBit. The study results illustrate design implications and requirements for fitness trackers and other self-efficacy mobile healthcare applications.

  7. Finding the Right Fit: Understanding Health Tracking in Workplace Wellness Programs

    Chung, Chia-Fang; Jensen, Nanna Gorm; Shklovski, Irina

    2017-01-01

    Workplace health and wellness programs are increasingly integrating personal health tracking technologies, such as Fitbit and Apple Watch. Many question whether these technologies truly support employees in their pursuit of better wellness levels, raising objections about workplace surveillance...... and further blurring of boundaries between work and personal life. We conducted a study to understand how tracking tools are adopted in wellness programs and employees' opinions about these programs. We find that employees are generally positive about incentivized health tracking in the workplace, as it helps...... raise awareness of activity levels. However, there is a gap between the intentions of the programs and individual experiences and health goals. This sometimes results in confusion and creates barriers to participation. Even if this gap can be addressed, health tracking in the workplace...

  8. Impact of Physician Education and a Dedicated Inferior Vena Cava Filter Tracking System on Inferior Vena Cava Filter Use and Retrieval Rates Across a Large US Health Care Region.

    Wang, Stephen L; Cha, Hsien-Hwa A; Lin, James R; Francis, Bolanos; Elizabeth, Wakley; Martin, Porras; Rajan, Sudhir

    2016-05-01

    To evaluate the effects of physician familiarity with current evidence and guidelines on inferior vena cava (IVC) filter use and the availability of IVC filter tracking infrastructure on retrieval rates. Fourteen continuing medical education-approved in-hospital grand rounds covering evidence-based review of the literature on IVC filter efficacy, patient-centered outcomes, guidelines for IVC filter indications, and complications were performed across a large United States (US) health care region serving more than 3.5 million members. A computer-based IVC filter tracking system was deployed simultaneously. IVC filter use, rates of attempted retrieval, and fulfillment of guidelines for IVC filter indications were retrospectively evaluated at each facility for 12 months before intervention (n = 427) and for 12 months after intervention (n = 347). After education, IVC filter use decreased 18.7%, with a member enrollment-adjusted decrease of 22.2%, despite an increasing IVC filter use trend for 4 years. Reduction in IVC filter use at each facility strongly correlated with physician attendance at grand rounds (r = -0.69; P = .007). Rates of attempted retrieval increased from 38.9% to 54.0% (P = .0006), with similar rates of successful retrieval (82.3% before education and 85.8% after education on first attempt). Improvement in IVC filter retrieval attempts correlated with physician attendance at grand rounds (r = 0.51; P = .051). IVC filter dwell times at first retrieval attempt were similar (10.2 wk before and 10.8 wk after). Physician education dramatically reduced IVC filter use across a large US health care region, and represents a learning opportunity for physicians who request and place them. Education and a novel tracking system improved rates of retrieval for IVC filter devices. Copyright © 2016 SIR. Published by Elsevier Inc. All rights reserved.

  9. Autonomous underwater vehicle motion tracking using a Kalman filter for sensor fusion

    Holtzhausen, S

    2008-11-01

    Full Text Available it will be shown how a Kalman Filter is used to estimate the position of an autonomous vehicle in a three dimensional space. The Kalman filter is used to estimate movement and position using measurements from multiple sensors...

  10. Frequency-scanning interferometry using a time-varying Kalman filter for dynamic tracking measurements.

    Jia, Xingyu; Liu, Zhigang; Tao, Long; Deng, Zhongwen

    2017-10-16

    Frequency scanning interferometry (FSI) with a single external cavity diode laser (ECDL) and time-invariant Kalman filtering is an effective technique for measuring the distance of a dynamic target. However, due to the hysteresis of the piezoelectric ceramic transducer (PZT) actuator in the ECDL, the optical frequency sweeps of the ECDL exhibit different behaviors, depending on whether the frequency is increasing or decreasing. Consequently, the model parameters of Kalman filter appear time varying in each iteration, which produces state estimation errors with time-invariant filtering. To address this, in this paper, a time-varying Kalman filter is proposed to model the instantaneous movement of a target relative to the different optical frequency tuning durations of the ECDL. The combination of the FSI method with the time-varying Kalman filter was theoretically analyzed, and the simulation and experimental results show the proposed method greatly improves the performance of dynamic FSI measurements.

  11. Real-time tracking for virtual environments using scaat kalman filtering and unsynchronised cameras

    Rasmussen, Niels Tjørnly; Störring, Morritz; Moeslund, Thomas B.

    2006-01-01

    This paper presents a real-time outside-in camera-based tracking system for wireless 3D pose tracking of a user’s head and hand in a virtual environment. The system uses four unsynchronised cameras as sensors and passive retroreflective markers arranged in rigid bodies as targets. In order to ach...

  12. Multi-agent target tracking using particle filters enhanced with context data

    Claessens, R

    2015-05-01

    Full Text Available The proposed framework for Multi-Agent Target Tracking supports i) tracking of objects and ii) search and rescue based on the fusion of very heterogeneous data. The system is based on a novel approach to fusing sensory observations, intelligence...

  13. Tracking Weight Change, Insulin Resistance, Stress, and Aerobic Fitness over 4 Years of College

    Hopper, Mari K.; Moninger, Shana Lynn

    2017-01-01

    Objective: To determine if weight gain is accompanied by development of insulin resistance (IR) during 4 years in college. Participants: Two cohorts of college students were enrolled in fall semesters 2009 and 2010 and tracked for 4 years. Methods: Following a 12-hour fast, subjects reported for measurement of body mass index (BMI), perceived…

  14. H(infinity)/H(2)/Kalman filtering of linear dynamical systems via variational techniques with applications to target tracking

    Rawicz, Paul Lawrence

    In this thesis, the similarities between the structure of the H infinity, H2, and Kalman filters are examined. The filters used in this examination have been derived through duality to the full information controller. In addition, a direct variation of parameters derivation of the Hinfinity filter is presented for both continuous and discrete time (staler case). Direct and controller dual derivations using differential games exist in the literature and also employ variational techniques. Using a variational, rather than a differential games, viewpoint has resulted in a simple relationship between the Riccati equations that arise from the derivation and the results of the Bounded Real Lemma. This same relation has previously been found in the literature and used to relate the Riccati inequality for linear systems to the Hamilton Jacobi inequality for nonlinear systems when implementing the Hinfinity controller. The Hinfinity, H2, and Kalman filters are applied to the two-state target tracking problem. In continuous time, closed form analytic expressions for the trackers and their performance are determined. To evaluate the trackers using a neutral, realistic, criterion, the probability of target escape is developed. That is, the probability that the target position error will be such that the target is outside the radar beam width resulting in a loss of measurement. In discrete time, a numerical example, using the probability of target escape, is presented to illustrate the differences in tracker performance.

  15. Random-subset fitting of digital holograms for fast three-dimensional particle tracking [invited].

    Dimiduk, Thomas G; Perry, Rebecca W; Fung, Jerome; Manoharan, Vinothan N

    2014-09-20

    Fitting scattering solutions to time series of digital holograms is a precise way to measure three-dimensional dynamics of microscale objects such as colloidal particles. However, this inverse-problem approach is computationally expensive. We show that the computational time can be reduced by an order of magnitude or more by fitting to a random subset of the pixels in a hologram. We demonstrate our algorithm on experimentally measured holograms of micrometer-scale colloidal particles, and we show that 20-fold increases in speed, relative to fitting full frames, can be attained while introducing errors in the particle positions of 10 nm or less. The method is straightforward to implement and works for any scattering model. It also enables a parallelization strategy wherein random-subset fitting is used to quickly determine initial guesses that are subsequently used to fit full frames in parallel. This approach may prove particularly useful for studying rare events, such as nucleation, that can only be captured with high frame rates over long times.

  16. An efficient incremental learning mechanism for tracking concept drift in spam filtering.

    Jyh-Jian Sheu

    Full Text Available This research manages in-depth analysis on the knowledge about spams and expects to propose an efficient spam filtering method with the ability of adapting to the dynamic environment. We focus on the analysis of email's header and apply decision tree data mining technique to look for the association rules about spams. Then, we propose an efficient systematic filtering method based on these association rules. Our systematic method has the following major advantages: (1 Checking only the header sections of emails, which is different from those spam filtering methods at present that have to analyze fully the email's content. Meanwhile, the email filtering accuracy is expected to be enhanced. (2 Regarding the solution to the problem of concept drift, we propose a window-based technique to estimate for the condition of concept drift for each unknown email, which will help our filtering method in recognizing the occurrence of spam. (3 We propose an incremental learning mechanism for our filtering method to strengthen the ability of adapting to the dynamic environment.

  17. Real-time track-less Cherenkov ring fitting trigger system based on Graphics Processing Units

    Ammendola, R.; Biagioni, A.; Chiozzi, S.; Cretaro, P.; Cotta Ramusino, A.; Di Lorenzo, S.; Fantechi, R.; Fiorini, M.; Frezza, O.; Gianoli, A.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Piccini, M.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Vicini, P.

    2017-12-01

    The parallel computing power of commercial Graphics Processing Units (GPUs) is exploited to perform real-time ring fitting at the lowest trigger level using information coming from the Ring Imaging Cherenkov (RICH) detector of the NA62 experiment at CERN. To this purpose, direct GPU communication with a custom FPGA-based board has been used to reduce the data transmission latency. The GPU-based trigger system is currently integrated in the experimental setup of the RICH detector of the NA62 experiment, in order to reconstruct ring-shaped hit patterns. The ring-fitting algorithm running on GPU is fed with raw RICH data only, with no information coming from other detectors, and is able to provide more complex trigger primitives with respect to the simple photodetector hit multiplicity, resulting in a higher selection efficiency. The performance of the system for multi-ring Cherenkov online reconstruction obtained during the NA62 physics run is presented.

  18. Extended Kalman Filtering to estimate temperature and irradiation for maximum power point tracking of a photovoltaic module

    Docimo, D.J.; Ghanaatpishe, M.; Mamun, A.

    2017-01-01

    This paper develops an algorithm for estimating photovoltaic (PV) module temperature and effective irradiation level. The power output of a PV system depends directly on both of these states. Estimating the temperature and irradiation allows for improved state-based control methods while eliminating the need of additional sensors. Thermal models and irradiation estimators have been developed in the literature, but none incorporate feedback for estimation. This paper outlines an Extended Kalman Filter for temperature and irradiation estimation. These estimates are, in turn, used within a novel state-based controller that tracks the maximum power point of the PV system. Simulation results indicate this state-based controller provides up to an 8.5% increase in energy produced per day as compared to an impedance matching controller. A sensitivity analysis is provided to examine the impact state estimate errors have on the ability to find the optimal operating point of the PV system. - Highlights: • Developed a temperature and irradiation estimator for photovoltaic systems. • Designed an Extended Kalman Filter to handle model and measurement uncertainty. • Developed a state-based controller for maximum power point tracking (MPPT). • Validated combined estimator/controller algorithm for different weather conditions. • Algorithm increases energy captured up to 8.5% over traditional MPPT algorithms.

  19. Application Mail Tracking Using RSA Algorithm As Security Data and HOT-Fit a Model for Evaluation System

    Permadi, Ginanjar Setyo; Adi, Kusworo; Gernowo, Rahmad

    2018-02-01

    RSA algorithm give security in the process of the sending of messages or data by using 2 key, namely private key and public key .In this research to ensure and assess directly systems are made have meet goals or desire using a comprehensive evaluation methods HOT-Fit system .The purpose of this research is to build a information system sending mail by applying methods of security RSA algorithm and to evaluate in uses the method HOT-Fit to produce a system corresponding in the faculty physics. Security RSA algorithm located at the difficulty of factoring number of large coiled factors prima, the results of the prime factors has to be done to obtain private key. HOT-Fit has three aspects assessment, in the aspect of technology judging from the system status, the quality of system and quality of service. In the aspect of human judging from the use of systems and satisfaction users while in the aspect of organization judging from the structure and environment. The results of give a tracking system sending message based on the evaluation acquired.

  20. Application Mail Tracking Using RSA Algorithm As Security Data and HOT-Fit a Model for Evaluation System

    Setyo Permadi Ginanjar

    2018-01-01

    Full Text Available RSA algorithm give security in the process of the sending of messages or data by using 2 key, namely private key and public key .In this research to ensure and assess directly systems are made have meet goals or desire using a comprehensive evaluation methods HOT-Fit system .The purpose of this research is to build a information system sending mail by applying methods of security RSA algorithm and to evaluate in uses the method HOT-Fit to produce a system corresponding in the faculty physics. Security RSA algorithm located at the difficulty of factoring number of large coiled factors prima, the results of the prime factors has to be done to obtain private key. HOT-Fit has three aspects assessment, in the aspect of technology judging from the system status, the quality of system and quality of service. In the aspect of human judging from the use of systems and satisfaction users while in the aspect of organization judging from the structure and environment. The results of give a tracking system sending message based on the evaluation acquired.

  1. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    Ma, Jian; Lu, Chen; Liu, Hongmei

    2015-01-01

    The aircraft environmental control system (ECS) is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF) and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF) and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger.

  2. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    Jian Ma

    Full Text Available The aircraft environmental control system (ECS is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger.

  3. A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

    Hongxiao Yu

    2015-05-01

    Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

  4. Convolutional Neural Network for Track Seed Filtering at the CMS HLT

    CERN. Geneva

    2018-01-01

    Collider will constantly bring nominal luminosity increase, with the ultimate goal of reaching a peak luminosity of $5 · 10^{34} cm^{−2} s^{−1}$ for ATLAS and CMS experiments planned for the High Luminosity LHC (HL-LHC) upgrade. This rise in luminosity will directly result in an increased number of simultaneous proton collisions (pileup), up to 200, that will pose new challenges for the CMS detector and, specifically, for track reconstruction in the Silicon Pixel Tracker. One of the first steps of the track finding workflow is the creation of track seeds, i.e. compatible pairs of hits from different detector layers, that are subsequently fed to to higher level pattern recognition steps. However the set of compatible hit pairs is highly affected by combinatorial background resulting in the next steps of the tracking algorithm to process a significant fraction of fake doublets. A possible way of reducing this effect is taking into account the shape of the hit pixel cluster to check the compatibility bet...

  5. Performance Analysis and Design Strategy for a Second-Order, Fixed-Gain, Position-Velocity-Measured (α-β-η-θ Tracking Filter

    Kenshi Saho

    2017-07-01

    Full Text Available We present a strategy for designing an α - β - η - θ filter, a fixed-gain moving-object tracking filter using position and velocity measurements. First, performance indices and stability conditions for the filter are analytically derived. Then, an optimal gain design strategy using these results is proposed and its relationship to the position-velocity-measured (PVM Kalman filter is shown. Numerical analyses demonstrate the effectiveness of the proposed strategy, as well as a performance improvement over the traditional position-only-measured α - β filter. Moreover, we apply an α - β - η - θ filter designed using this strategy to ultra-wideband Doppler radar tracking in numerical simulations. We verify that the proposed strategy can easily design the gains for an α - β - η - θ filter based on the performance of the ultra-wideband Doppler radar and a rough approximation of the target’s acceleration. Moreover, its effectiveness in predicting the steady state performance in designing the position-velocity-measured Kalman filter is also demonstrated.

  6. Kalman滤波在井下人员跟踪定位中的应用%Application of Kalman filter in underground personnel tracking and positioning

    罗宇锋; 刘勇; 李芳

    2013-01-01

    In view of problem that RSSI location algorithm does not have continuity in positioning process,the paper proposed an underground personnel positioning method with continuity based on Kalman filter.The method adopts Kalman filter to filter processing position coordinates of underground personnel estimated by RSSI location algorithm,and established a Kalman filter model on the basis of this coordinate in order to real-timely track underground personnel.The experimental results show that the positioning method based on Kalman filter has accurate tracking effect,and can improve real-time performance and tracking accuracy of underground personnel tracking and positioning system.%针对基于RSSI定位算法在定位过程中不具备连续性问题,提出了一种基于Kalman滤波的连续性并下人员定位方法.采用Kalman滤波对基于RSSI定位算法估算出的井下人员位置坐标进行滤波处理,在此坐标的基础上,建立Kalman滤波模型,利用Kalman滤波实现对井下人员的实时跟踪.实验结果表明,基于Kalman滤波的定位方法对井下人员的跟踪效果较好,提高了系统的实时性和跟踪精度.

  7. Adaptive projective filters

    Dikusar, N.D.

    1993-01-01

    The new approach to solving of the finding problem is proposed. The method is based on Discrete Projective Transformations (DPT), the List Square Fitting (LSF) and uses the information feedback in tracing for linear or quadratic track segments (TS). The fast and stable with respect to measurement errors and background points recurrent algorithm is suggested. The algorithm realizes the family of digital adaptive projective filters (APF) with known nonlinear weight functions-projective invariants. APF can be used in adequate control systems for collection, processing and compression of data, including tracking problems for the wide class of detectors. 10 refs.; 9 figs

  8. Structural functional associations of the orbit in thyroid eye disease: Kalman filters to track extraocular rectal muscles

    Chaganti, Shikha; Nelson, Katrina; Mundy, Kevin; Luo, Yifu; Harrigan, Robert L.; Damon, Steve; Fabbri, Daniel; Mawn, Louise; Landman, Bennett

    2016-03-01

    Pathologies of the optic nerve and orbit impact millions of Americans and quantitative assessment of the orbital structures on 3-D imaging would provide objective markers to enhance diagnostic accuracy, improve timely intervention, and eventually preserve visual function. Recent studies have shown that the multi-atlas methodology is suitable for identifying orbital structures, but challenges arise in the identification of the individual extraocular rectus muscles that control eye movement. This is increasingly problematic in diseased eyes, where these muscles often appear to fuse at the back of the orbit (at the resolution of clinical computed tomography imaging) due to inflammation or crowding. We propose the use of Kalman filters to track the muscles in three-dimensions to refine multi-atlas segmentation and resolve ambiguity due to imaging resolution, noise, and artifacts. The purpose of our study is to investigate a method of automatically generating orbital metrics from CT imaging and demonstrate the utility of the approach by correlating structural metrics of the eye orbit with clinical data and visual function measures in subjects with thyroid eye disease. The pilot study demonstrates that automatically calculated orbital metrics are strongly correlated with several clinical characteristics. Moreover, it is shown that the superior, inferior, medial and lateral rectus muscles obtained using Kalman filters are each correlated with different categories of functional deficit. These findings serve as foundation for further investigation in the use of CT imaging in the study, analysis and diagnosis of ocular diseases, specifically thyroid eye disease.

  9. Assessment of the pseudo-tracking approach for the calculation of material acceleration and pressure fields from time-resolved PIV: part II. Spatio-temporal filtering

    van Gent, P. L.; Schrijer, F. F. J.; van Oudheusden, B. W.

    2018-04-01

    The present study characterises the spatio-temporal filtering associated with pseudo-tracking. A combined theoretical and numerical assessment is performed that uses the relatively simple flow case of a two-dimensional Taylor vortex as analytical test case. An additional experimental assessment considers the more complex flow of a low-speed axisymmetric base flow, for which time-resolved tomographic PIV measurements and microphone measurements were obtained. The results of these assessments show how filtering along Lagrangian tracks leads to amplitude modulation of flow structures. A cut-off track length and spatial resolution are specified to support future applications of the pseudo-tracking approach. The experimental results show a fair agreement between PIV and microphone pressure data in terms of fluctuation levels and pressure frequency spectra. The coherence and correlation between microphone and PIV pressure measurements were found to be substantial and almost independent of the track length, indicating that the low-frequency behaviour of the flow could be reproduced regardless of the track length. It is suggested that a spectral analysis can be used inform the selection of a suitable track length and to estimate the local error margin of reconstructed pressure values.

  10. High resolution vertical profiles of wind, temperature and humidity obtained by computer processing and digital filtering of radiosonde and radar tracking data from the ITCZ experiment of 1977

    Danielson, E. F.; Hipskind, R. S.; Gaines, S. E.

    1980-01-01

    Results are presented from computer processing and digital filtering of radiosonde and radar tracking data obtained during the ITCZ experiment when coordinated measurements were taken daily over a 16 day period across the Panama Canal Zone. The temperature relative humidity and wind velocity profiles are discussed.

  11. Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study.

    Xie, Junqing; Wen, Dong; Liang, Lizhong; Jia, Yuxi; Gao, Li; Lei, Jianbo

    2018-04-12

    Wearable devices have attracted much attention from the market in recent years for their fitness monitoring and other health-related metrics; however, the accuracy of fitness tracking results still plays a major role in health promotion. The aim of this study was to evaluate the accuracy of a host of latest wearable devices in measuring fitness-related indicators under various seminatural activities. A total of 44 healthy subjects were recruited, and each subject was asked to simultaneously wear 6 devices (Apple Watch 2, Samsung Gear S3, Jawbone Up3, Fitbit Surge, Huawei Talk Band B3, and Xiaomi Mi Band 2) and 2 smartphone apps (Dongdong and Ledongli) to measure five major health indicators (heart rate, number of steps, distance, energy consumption, and sleep duration) under various activity states (resting, walking, running, cycling, and sleeping), which were then compared with the gold standard (manual measurements of the heart rate, number of steps, distance, and sleep, and energy consumption through oxygen consumption) and calculated to determine their respective mean absolute percentage errors (MAPEs). Wearable devices had a rather high measurement accuracy with respect to heart rate, number of steps, distance, and sleep duration, with a MAPE of approximately 0.10, whereas poor measurement accuracy was observed for energy consumption (calories), indicated by a MAPE of up to 0.44. The measurements varied for the same indicator measured by different fitness trackers. The variation in measurement of the number of steps was the highest (Apple Watch 2: 0.42; Dongdong: 0.01), whereas it was the lowest for heart rate (Samsung Gear S3: 0.34; Xiaomi Mi Band 2: 0.12). Measurements differed insignificantly for the same indicator measured under different states of activity; the MAPE of distance and energy measurements were in the range of 0.08 to 0.17 and 0.41 to 0.48, respectively. Overall, the Samsung Gear S3 performed the best for the measurement of heart rate under

  12. Developing a software for tracking the memory states of the machines in the LHCb Filter Farm

    Jain, Harshit

    2017-01-01

    The LHCb Event Filter Farm consists of more than 1500 server nodes with a total amount of roughly 65 TB operating memory .The memory is crucial for the success of the LHCb experiment, since the proton-proton collisions are temporarily stored on these memory modules. Unfortunately, the aging nodes of the server farm occasionally suffer losses of their memory modules. The lower the available memory, the lower performance we can get out of it. Inducing the users or administrators to pay attention to this matter is inefficient. One needs to upgrade it to an acceptable way. The aim of this project was to develop a software to monitor a set of test machines. The software stores the data of the memory sticks in advance in a database which will be used for future reference. Then it checks the memory sticks at a future time instant to find any failures. In the case of any such losses the software looks up in the database to find out which memory sticks have lost and displays all information of those sticks in a log fi...

  13. A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

    Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth

    2015-01-01

    In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. (author)

  14. An adaptive compensation algorithm for temperature drift of micro-electro-mechanical systems gyroscopes using a strong tracking Kalman filter.

    Feng, Yibo; Li, Xisheng; Zhang, Xiaojuan

    2015-05-13

    We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF), the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to -2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation.

  15. An Adaptive Compensation Algorithm for Temperature Drift of Micro-Electro-Mechanical Systems Gyroscopes Using a Strong Tracking Kalman Filter

    Yibo Feng

    2015-05-01

    Full Text Available We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF, the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to −2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation.

  16. Alignment with Kalman filter fitted tracks and reconstruction of $B^{0}_{s} \\to J/\\psi \\phi$ decays

    Amoraal, Jan Mennis; Hulsbergen, W D

    2011-01-01

    The LHC at CERN provides a new testing ground for the Standard Model of elementary particles as well an opportunity to further explore the mysteries and expand our knowledge of Nature. The Standard Model is a theory based on experimental observations of particle interactions at collider experiments and at cosmic ray experiments. Despite the successes of the Standard Model it does not provide a complete picture of the beautiful intricately woven tapestry called Nature. To further explore the finest threads of this tapestry and to validate or exclude the Standard Model or extensions thereof, so-called New Physics Models, particle physicists at the LHC have built precision instruments to measure fundamental parameters, which may reveal New Physics, with the highest possible precision. A case in point is the weak mixing phase s, a key measurement of the LHCb experiment, which can be accessed via $B^{0}_{s} \\to J/\\psi\\phi$ decays. According to the Standard Model this phase is expected to small, approximately $\\phi...

  17. Digital Inequalities in the Use of Self-Tracking Diet and Fitness Apps: Interview Study on the Influence of Social, Economic, and Cultural Factors

    Chauvel, Louis

    2018-01-01

    Background Digital devices are driving economic and social transformations, but assessing the uses, perceptions, and impact of these new technologies on diet and physical activity remains a major societal challenge. Objective We aimed to determine under which social, economic, and cultural conditions individuals in France were more likely to be actively invested in the use of self-tracking diet and fitness apps for better health behaviors. Methods Existing users of 3 diet and fitness self-tracking apps (Weight Watchers, MyFitnessPal, and sport apps) were recruited from 3 regions of France. We interviewed 79 individuals (Weight Watchers, n=37; MyFitnessPal, n=20; sport apps, n=22). In-depth semistructured interviews were conducted with each participant, using open-ended questions about their use of diet and fitness apps. A triangulation of methods (content, textual, and quantitative analyses) was performed. Results We found 3 clusters of interviewees who differed by social background and curative goal linked to use under constraint versus preventive goal linked to chosen use, and intensity of their self-quantification efforts and participation in social networks. Interviewees used the apps for a diversity of uses, including measurement, tracking, quantification, and participation in digital communities. A digital divide was highlighted, comprising a major social gap. Social conditions for appropriation of self-tracking devices included sociodemographic factors, life course stages, and cross-cutting factors of heterogeneity. Conclusions Individuals from affluent or intermediate social milieus were most likely to use the apps and to participate in the associated online social networks. These interviewees also demonstrated a preventive approach to a healthy lifestyle. Individuals from lower milieus were more reluctant to use digital devices relating to diet and physical activity or to participate in self-quantification. The results of the study have major implications

  18. Tracking the business cycle of the Euro area: A multivariate model-based band-pass filter

    Azevedo, J.M.; Koopman, S.J.; Rua, A.

    2006-01-01

    This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition model. The underlying multivariate dynamic factor model relies on specific formulations for trend and cycle components and produces smooth business cycle indicators with bandpass filter properties.

  19. An adaptive unscented Kalman filter-based adaptive tracking control for wheeled mobile robots with control constrains in the presence of wheel slipping

    Mingyue Cui

    2016-09-01

    Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.

  20. Parameter estimation of a three-axis spacecraft simulator using recursive least-squares approach with tracking differentiator and Extended Kalman Filter

    Xu, Zheyao; Qi, Naiming; Chen, Yukun

    2015-12-01

    Spacecraft simulators are widely used to study the dynamics, guidance, navigation, and control of a spacecraft on the ground. A spacecraft simulator can have three rotational degrees of freedom by using a spherical air-bearing to simulate a frictionless and micro-gravity space environment. The moment of inertia and center of mass are essential for control system design of ground-based three-axis spacecraft simulators. Unfortunately, they cannot be known precisely. This paper presents two approaches, i.e. a recursive least-squares (RLS) approach with tracking differentiator (TD) and Extended Kalman Filter (EKF) method, to estimate inertia parameters. The tracking differentiator (TD) filter the noise coupled with the measured signals and generate derivate of the measured signals. Combination of two TD filters in series obtains the angular accelerations that are required in RLS (TD-TD-RLS). Another method that does not need to estimate the angular accelerations is using the integrated form of dynamics equation. An extended TD (ETD) filter which can also generate the integration of the function of signals is presented for RLS (denoted as ETD-RLS). States and inertia parameters are estimated simultaneously using EKF. The observability is analyzed. All proposed methods are illustrated by simulations and experiments.

  1. Tracking Architecture Based on Dual-Filter with State Feedback and Its Application in Ultra-Tight GPS/INS Integration.

    Zhang, Xi; Miao, Lingjuan; Shao, Haijun

    2016-05-02

    If a Kalman Filter (KF) is applied to Global Positioning System (GPS) baseband signal preprocessing, the estimates of signal phase and frequency can have low variance, even in highly dynamic situations. This paper presents a novel preprocessing scheme based on a dual-filter structure. Compared with the traditional model utilizing a single KF, this structure avoids carrier tracking being subjected to code tracking errors. Meanwhile, as the loop filters are completely removed, state feedback values are adopted to generate local carrier and code. Although local carrier frequency has a wide fluctuation, the accuracy of Doppler shift estimation is improved. In the ultra-tight GPS/Inertial Navigation System (INS) integration, the carrier frequency derived from the external navigation information is not viewed as the local carrier frequency directly. That facilitates retaining the design principle of state feedback. However, under harsh conditions, the GPS outputs may still bear large errors which can destroy the estimation of INS errors. Thus, an innovative integrated navigation filter is constructed by modeling the non-negligible errors in the estimated Doppler shifts, to ensure INS is properly calibrated. Finally, field test and semi-physical simulation based on telemetered missile trajectory validate the effectiveness of methods proposed in this paper.

  2. Track reconstruction in CMS high luminosity environment

    AUTHOR|(CDS)2067159

    2016-01-01

    The CMS tracker is the largest silicon detector ever built, covering 200 square meters and providing an average of 14 high-precision measurements per track. Tracking is essential for the reconstruction of objects like jets, muons, electrons and tau leptons starting from the raw data from the silicon pixel and strip detectors. Track reconstruction is widely used also at trigger level as it improves objects tagging and resolution.The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compat...

  3. Track reconstruction in CMS high luminosity environment

    Goetzmann, Christophe

    2014-01-01

    The CMS tracker is the largest silicon detector ever built, covering 200 square meters and providing an average of 14 high-precision measurements per track. Tracking is essential for the reconstruction of objects like jets, muons, electrons and tau leptons starting from the raw data from the silicon pixel and strip detectors. Track reconstruction is widely used also at trigger level as it improves objects tagging and resolution.The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compat...

  4. Text-mining as a methodology to assess eating disorder-relevant factors: Comparing mentions of fitness tracking technology across online communities.

    McCaig, Duncan; Bhatia, Sudeep; Elliott, Mark T; Walasek, Lukasz; Meyer, Caroline

    2018-05-07

    Text-mining offers a technique to identify and extract information from a large corpus of textual data. As an example, this study presents the application of text-mining to assess and compare interest in fitness tracking technology across eating disorder and health-related online communities. A list of fitness tracking technology terms was developed, and communities (i.e., 'subreddits') on a large online discussion platform (Reddit) were compared regarding the frequency with which these terms occurred. The corpus used in this study comprised all comments posted between May 2015 and January 2018 (inclusive) on six subreddits-three eating disorder-related, and three relating to either fitness, weight-management, or nutrition. All comments relating to the same 'thread' (i.e., conversation) were concatenated, and formed the cases used in this study (N = 377,276). Within the eating disorder-related subreddits, the findings indicated that a 'pro-eating disorder' subreddit, which is less recovery focused than the other eating disorder subreddits, had the highest frequency of fitness tracker terms. Across all subreddits, the weight-management subreddit had the highest frequency of the fitness tracker terms' occurrence, and MyFitnessPal was the most frequently mentioned fitness tracker. The technique exemplified here can potentially be used to assess group differences to identify at-risk populations, generate and explore clinically relevant research questions in populations who are difficult to recruit, and scope an area for which there is little extant literature. The technique also facilitates methodological triangulation of research findings obtained through more 'traditional' techniques, such as surveys or interviews. © 2018 Wiley Periodicals, Inc.

  5. Filtering for vision tracking

    Erik Cuevas J.

    2006-01-01

    Full Text Available El filtro de Kalman ha sido usado exitosamente en diferentes aplicaciones de predicción o determinación del estado de un sistema. Un campo importante en la visión por computadora es el seguimiento de objetos. Diferentes tipos de movimiento así como el ocultamiento de objetos a seguir pueden obstaculizar la labor de seguimiento. En este trabajo, se presenta el uso del filtro de Kalman para el seguimiento de objetos. Además se considera tanto la capacidad del filtro para tolerar pequeños ocultamientos del objeto así como el uso del filtro de Kalman extendido para el modelaje de movimientos complejos

  6. A Method of Time-Varying Rayleigh Channel Tracking in MIMO Radio System

    GONG Yan-fei; HE Zi-shu; HAN Chun-lin

    2005-01-01

    A method of MIMO channel tracking based on Kalman filter and MMSE-DFE is proposed. The Kalman filter tracks the time-varying channel by using the MMSE-DFE decision and the MMSE-DFE conducts the next decision by using the channel estimates produced by the Kalman filter. Polynomial fitting is used to bridge the gap between the channel estimates produced by the Kalman filter and those needed for the DFE decision. Computer simulation demonstrates that this method can track the MIMO time-varying channel effectively.

  7. Primer uticaja filtriranja slike u sistemima za praćenje ciljeva primenom termovizije / An example of image filtering in target tracking systems with thermal imagery

    Zvonko M. Radosavljević

    2003-07-01

    Full Text Available U radu je dat primer primene jedne vrste niskofrekventnog filtriranja sa usrednjavanjem, koje se primenjuje u sistemima za detekciju i praćenje ciljeva u vazdušnom prostoru primenom termovizije. Date su dve metode filtriranja slike. Prva metoda koristi niskofrekventno konvoluciono filtriranje a druga usrednjavajući filtar na osnovu srednje vrednosti nivoa sivog. Ovi filtri su primenjeni u sistemima za praćenje uz pomoć infracrvenih senzora. Određivanje nivoa praga filtriranja vrši se uz pomoć statističkih osobina slike. Veoma važan korak u procesu praćenja je određivanje prozora praćenja, koji maze biti, po dimenzijama, fiksan ili adaptibilan. Pogrešna procena o postojanju cilja u prozoru može se doneti u slučaju prisustva šuma pozadine, predpojačavača, detektora, itd. Filtriranje je neophodan korak u ovim sistemima, kao značajan činilac U povećanju brzine i tačnosti praćenja. / A case of image filtering in air target detecting and tracking systems is described in this paper. Two image filtering methods are given. The first method is performed using a low pass convolving filter and the second one uses the mean value of gray level filter. The main goal of the cited filtering is implementation in IR (infra red systems. Some statistical features of the images were used for selecting the threshold level. The next step in the algorithm is the determination of a 'tracking window' that can be fixed or adaptive in size. A false estimation of a target existing in the window may be influenced by the background noise, low noise amplifier detector, etc.

  8. Digital Inequalities in the Use of Self-Tracking Diet and Fitness Apps: Interview Study on the Influence of Social, Economic, and Cultural Factors.

    Régnier, Faustine; Chauvel, Louis

    2018-04-20

    Digital devices are driving economic and social transformations, but assessing the uses, perceptions, and impact of these new technologies on diet and physical activity remains a major societal challenge. We aimed to determine under which social, economic, and cultural conditions individuals in France were more likely to be actively invested in the use of self-tracking diet and fitness apps for better health behaviors. Existing users of 3 diet and fitness self-tracking apps (Weight Watchers, MyFitnessPal, and sport apps) were recruited from 3 regions of France. We interviewed 79 individuals (Weight Watchers, n=37; MyFitnessPal, n=20; sport apps, n=22). In-depth semistructured interviews were conducted with each participant, using open-ended questions about their use of diet and fitness apps. A triangulation of methods (content, textual, and quantitative analyses) was performed. We found 3 clusters of interviewees who differed by social background and curative goal linked to use under constraint versus preventive goal linked to chosen use, and intensity of their self-quantification efforts and participation in social networks. Interviewees used the apps for a diversity of uses, including measurement, tracking, quantification, and participation in digital communities. A digital divide was highlighted, comprising a major social gap. Social conditions for appropriation of self-tracking devices included sociodemographic factors, life course stages, and cross-cutting factors of heterogeneity. Individuals from affluent or intermediate social milieus were most likely to use the apps and to participate in the associated online social networks. These interviewees also demonstrated a preventive approach to a healthy lifestyle. Individuals from lower milieus were more reluctant to use digital devices relating to diet and physical activity or to participate in self-quantification. The results of the study have major implications for public health: the digital self

  9. CATS: a cellular automaton for tracking in silicon for the HERA-B vertex detector

    Abt, I.; Emeliyanov, D.; Kisel, I.; Masciocchi, S.

    2002-01-01

    The new track reconstruction program CATS developed for the Vertex Detector System of the HERA-B experiment at DESY is presented. It employs a cellular automaton for track searching and the Kalman filter for track fitting. This results in a very fast algorithm that combines highly efficient track recognition with accurate and reliable track parameter estimation. To reduce the computational cost of the fit an optimized numerical implementation of the Kalman filter is used. Alternative approaches to the track reconstruction in the VDS are also discussed. Since 1999, after extensive tests on simulated data, CATS has been employed to reconstruct experimental data collected in HERA-B. Results regarding tracking performance, the accuracy of track parameter estimates and CPU time consumption are presented

  10. A comparative study of track reconstruction methods in the context of CMS physics

    Winkler, M.

    2002-05-01

    This thesis deals mainly with the problem of reconstructing the tracks of charged particles from the measurements recorded by the CMS Tracker, in particular with track fitting. The task of the track fit is to use the available information (the subsets of hits belonging to the track of a particle found by a track finder) in a statistically optimal way for the estimation of the track parameters and the associated errors. Due to the high track multiplicity at LHC and the large background of noise hits, combinatorial methods such as the Kalman filter may have problems in the association of hits to tracks, and their results will be biased in the case of wrong hits assigned to a track. Recently developped non-linear, adaptive methods such as the deterministic annealing filter and the multi track filter try to solve the assignment problem during the track fit, by determining an assignment probability of a hit to a track. The methods are studied in the CMS Tracker using various event topologies. (author)

  11. A Signal Decomposition Method for Ultrasonic Guided Wave Generated from Debonding Combining Smoothed Pseudo Wigner-Ville Distribution and Vold–Kalman Filter Order Tracking

    Junhua Wu

    2017-01-01

    Full Text Available Carbon fibre composites have a promising application future of the vehicle, due to its excellent physical properties. Debonding is a major defect of the material. Analyses of wave packets are critical for identification of the defect on ultrasonic nondestructive evaluation and testing. In order to isolate different components of ultrasonic guided waves (GWs, a signal decomposition algorithm combining Smoothed Pseudo Wigner-Ville distribution and Vold–Kalman filter order tracking is presented. In the algorithm, the time-frequency distribution of GW is first obtained by using Smoothed Pseudo Wigner-Ville distribution. The frequencies of different modes are computed based on summation of the time-frequency coefficients in the frequency direction. On the basis of these frequencies, isolation of different modes is done by Vold–Kalman filter order tracking. The results of the simulation signal and the experimental signal reveal that the presented algorithm succeeds in decomposing the multicomponent signal into monocomponents. Even though components overlap in corresponding Fourier spectrum, they can be isolated by using the presented algorithm. So the frequency resolution of the presented method is promising. Based on this, we can do research about defect identification, calculation of the defect size, and locating the position of the defect.

  12. Ultra-Fast Tracking Power Supply with 4th order Output Filter and Fixed-Frequency Hysteretic Control

    Høyerby, Mikkel Christian Wendelboe; Andersen, Michael Andreas E.

    2008-01-01

    A practical solution is presented for the design of a non-isolated DC/DC power converter with very low output ripple voltage and very fast output voltage step response. The converter is intended for use as an envelope tracking power supply for an RFPA (Radio Frequency Power Amplifier) in a Tetra2...

  13. Tracking of overweight and obesity from early childhood to adolescence in a population-based cohort - the Tromsø Study, Fit Futures.

    Evensen, Elin; Wilsgaard, Tom; Furberg, Anne-Sofie; Skeie, Guri

    2016-05-10

    Obesity is a serious childhood health problem today. Studies have shown that overweight and obesity tend to be stable (track) from birth, through childhood and adolescence, to adulthood. However, existing studies are heterogeneous; there is still no consensus on the strength of the association between high birth weight or high body mass index (BMI) early in life and overweight and obesity later in life, nor on the appropriate age or target group for intervention and prevention efforts. This study aimed to determine the presence and degree of tracking of overweight and obesity and development in BMI and BMI standard deviation scores (SDS) from childhood to adolescence in the Fit Futures cohort from North Norway. Using a retrospective cohort design, data on 532 adolescents from the Fit Futures cohort were supplemented with height and weight data from childhood health records, and BMI was calculated at 2-4, 5-7, and 15-17 years of age. Participants were categorized into weight classes by BMI according to the International Obesity Taskforce's age- and sex-specific cut-off values for children 2-18 years of age (thinness: adult BMI obesity: adult BMI ≥30 kg/m(2)). Non-parametric tests, Cohen's weighted Kappa statistic and logistic regression were used in the analyses. The prevalence of overweight and obesity combined, increased from 11.5 % at 2-4 years of age and 13.7 % at 5-7 years of age, to 20.1 % at 15-17 years of age. Children who were overweight/obese at 5-7 years of age had increased odds of being overweight/obese at 15-17 years of age, compared to thin/normal weight children (crude odds ratio: 11.1, 95 % confidence interval: 6.4-19.2). Six out of 10 children who were overweight/obese at 5-7 years of age were overweight/obese at 15-17 years of age. The prevalence of overweight and obesity increased with age. We found a moderate indication of tracking of overweight/obesity from childhood to adolescence. Preventive and treatment initiatives among children at

  14. CMS reconstruction improvements for the tracking in large pileup events

    Rovere, M

    2015-01-01

    The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compatible with the increasing instantaneous luminosity of LHC, resulting in a large number of primary vertices and tracks per bunch crossing.The major upgrade put in place during the present LHC Long Shutdown will allow the tracking code to comply with the conditions expected during RunII and the much larger pileup. In particular, new algorithms that are intrinsically more robust in high occupancy conditions were developed, iteration...

  15. Track reconstruction algorithms for the CBM experiment at FAIR

    Lebedev, Andrey; Hoehne, Claudia; Kisel, Ivan; Ososkov, Gennady

    2010-01-01

    The Compressed Baryonic Matter (CBM) experiment at the future FAIR accelerator complex at Darmstadt is being designed for a comprehensive measurement of hadron and lepton production in heavy-ion collisions from 8-45 AGeV beam energy, producing events with large track multiplicity and high hit density. The setup consists of several detectors including as tracking detectors the silicon tracking system (STS), the muon detector (MUCH) or alternatively a set of Transition Radiation Detectors (TRD). In this contribution, the status of the track reconstruction software including track finding, fitting and propagation is presented for the MUCH and TRD detectors. The track propagation algorithm takes into account an inhomogeneous magnetic field and includes accurate calculation of multiple scattering and energy losses in the detector material. Track parameters and covariance matrices are estimated using the Kalman filter method and a Kalman filter modification by assigning weights to hits and using simulated annealing. Three different track finder algorithms based on track following have been developed which either allow for track branches, just select nearest hits or use the mentioned weighting method. The track reconstruction efficiency for central Au+Au collisions at 25 AGeV beam energy using events from the UrQMD model is at the level of 93-95% for both detectors.

  16. ISED: Constructing a high-resolution elevation road dataset from massive, low-quality in-situ observations derived from geosocial fitness tracking data.

    Grant McKenzie

    Full Text Available Gaining access to inexpensive, high-resolution, up-to-date, three-dimensional road network data is a top priority beyond research, as such data would fuel applications in industry, governments, and the broader public alike. Road network data are openly available via user-generated content such as OpenStreetMap (OSM but lack the resolution required for many tasks, e.g., emergency management. More importantly, however, few publicly available data offer information on elevation and slope. For most parts of the world, up-to-date digital elevation products with a resolution of less than 10 meters are a distant dream and, if available, those datasets have to be matched to the road network through an error-prone process. In this paper we present a radically different approach by deriving road network elevation data from massive amounts of in-situ observations extracted from user-contributed data from an online social fitness tracking application. While each individual observation may be of low-quality in terms of resolution and accuracy, taken together they form an accurate, high-resolution, up-to-date, three-dimensional road network that excels where other technologies such as LiDAR fail, e.g., in case of overpasses, overhangs, and so forth. In fact, the 1m spatial resolution dataset created in this research based on 350 million individual 3D location fixes has an RMSE of approximately 3.11m compared to a LiDAR-based ground-truth and can be used to enhance existing road network datasets where individual elevation fixes differ by up to 60m. In contrast, using interpolated data from the National Elevation Dataset (NED results in 4.75m RMSE compared to the base line. We utilize Linked Data technologies to integrate the proposed high-resolution dataset with OpenStreetMap road geometries without requiring any changes to the OSM data model.

  17. ISED: Constructing a high-resolution elevation road dataset from massive, low-quality in-situ observations derived from geosocial fitness tracking data.

    McKenzie, Grant; Janowicz, Krzysztof

    2017-01-01

    Gaining access to inexpensive, high-resolution, up-to-date, three-dimensional road network data is a top priority beyond research, as such data would fuel applications in industry, governments, and the broader public alike. Road network data are openly available via user-generated content such as OpenStreetMap (OSM) but lack the resolution required for many tasks, e.g., emergency management. More importantly, however, few publicly available data offer information on elevation and slope. For most parts of the world, up-to-date digital elevation products with a resolution of less than 10 meters are a distant dream and, if available, those datasets have to be matched to the road network through an error-prone process. In this paper we present a radically different approach by deriving road network elevation data from massive amounts of in-situ observations extracted from user-contributed data from an online social fitness tracking application. While each individual observation may be of low-quality in terms of resolution and accuracy, taken together they form an accurate, high-resolution, up-to-date, three-dimensional road network that excels where other technologies such as LiDAR fail, e.g., in case of overpasses, overhangs, and so forth. In fact, the 1m spatial resolution dataset created in this research based on 350 million individual 3D location fixes has an RMSE of approximately 3.11m compared to a LiDAR-based ground-truth and can be used to enhance existing road network datasets where individual elevation fixes differ by up to 60m. In contrast, using interpolated data from the National Elevation Dataset (NED) results in 4.75m RMSE compared to the base line. We utilize Linked Data technologies to integrate the proposed high-resolution dataset with OpenStreetMap road geometries without requiring any changes to the OSM data model.

  18. The Complexity of H-wave Amplitude Fluctuations and Their Bilateral Cross-Covariance Are Modified According to the Previous Fitness History of Young Subjects under Track Training

    Maria E. Ceballos-Villegas

    2017-11-01

    Full Text Available The Hoffmann reflex (H-wave is produced by alpha-motoneuron activation in the spinal cord. A feature of this electromyography response is that it exhibits fluctuations in amplitude even during repetitive stimulation with the same intensity of current. We herein explore the hypothesis that physical training induces plastic changes in the motor system. Such changes are evaluated with the fractal dimension (FD analysis of the H-wave amplitude-fluctuations (H-wave FD and the cross-covariance (CCV between the bilateral H-wave amplitudes. The aim of this study was to compare the H-wave FD as well as the CCV before and after track training in sedentary individuals and athletes. The training modality in all subjects consisted of running three times per week (for 13 weeks in a concrete road of 5 km. Given the different physical condition of sedentary vs. athletes, the running time between sedentary and athletes was different. After training, the FD was significantly increased in sedentary individuals but significantly reduced in athletes, although there were no changes in spinal excitability in either group of subjects. Moreover, the CCV between bilateral H-waves exhibited a significant increase in athletes but not in sedentary individuals. These differential changes in the FD and CCV indicate that the plastic changes in the complexity of the H-wave amplitude fluctuations as well as the synaptic inputs to the Ia-motoneuron systems of both legs were correlated to the previous fitness history of the subjects. Furthermore, these findings demonstrate that the FD and CCV can be employed as indexes to study plastic changes in the human motor system.

  19. The Complexity of H-wave Amplitude Fluctuations and Their Bilateral Cross-Covariance Are Modified According to the Previous Fitness History of Young Subjects under Track Training.

    Ceballos-Villegas, Maria E; Saldaña Mena, Juan J; Gutierrez Lozano, Ana L; Sepúlveda-Cañamar, Francisco J; Huidobro, Nayeli; Manjarrez, Elias; Lomeli, Joel

    2017-01-01

    The Hoffmann reflex (H-wave) is produced by alpha-motoneuron activation in the spinal cord. A feature of this electromyography response is that it exhibits fluctuations in amplitude even during repetitive stimulation with the same intensity of current. We herein explore the hypothesis that physical training induces plastic changes in the motor system. Such changes are evaluated with the fractal dimension (FD) analysis of the H-wave amplitude-fluctuations (H-wave FD) and the cross-covariance (CCV) between the bilateral H-wave amplitudes. The aim of this study was to compare the H-wave FD as well as the CCV before and after track training in sedentary individuals and athletes. The training modality in all subjects consisted of running three times per week (for 13 weeks) in a concrete road of 5 km. Given the different physical condition of sedentary vs. athletes, the running time between sedentary and athletes was different. After training, the FD was significantly increased in sedentary individuals but significantly reduced in athletes, although there were no changes in spinal excitability in either group of subjects. Moreover, the CCV between bilateral H-waves exhibited a significant increase in athletes but not in sedentary individuals. These differential changes in the FD and CCV indicate that the plastic changes in the complexity of the H-wave amplitude fluctuations as well as the synaptic inputs to the Ia-motoneuron systems of both legs were correlated to the previous fitness history of the subjects. Furthermore, these findings demonstrate that the FD and CCV can be employed as indexes to study plastic changes in the human motor system.

  20. Common barrel and forward CA tracking algorithm

    Mykhailo, Pugach [Goethe-Universitaet, Frankfurt (Germany); Frankfurt Institute for Advanced Studies, Frankfurt (Germany); KINR, Kyiv (Ukraine); Gorbunov, Sergey; Kisel, Ivan [Goethe-Universitaet, Frankfurt (Germany); Frankfurt Institute for Advanced Studies, Frankfurt (Germany); Collaboration: PANDA-Collaboration

    2016-07-01

    There are complex detector setups which consist of barrel (cylindrical) and forward parts, and such systems require a special approach in the registered charged particles track finding procedure. Currently the tracking procedure might be performed in both parts of such detector independently from each other, but the final goal on this direction is a creation of a combined tracking, which will work in both parts of the detector simultaneously. The basic algorithm is based on Kalman Filter (KF) and Cellular Automata (CA). And the tracking procedure in such a complex system is rather extraordinary as far as it requires 2 different models to describe the state vector of segments of the reconstructed track in the mathematical apparatus of the KF-algorithm. To overcome this specifics a mathematical apparatus of transition matrices must be developed and implemented, so that one can transfer from one track model to another. Afterwards the work of the CA is performed, which reduces to segments sorting, their union into track-candidates and selection of the best candidates by the chi-square criteria after fitting of the track-candidate by the KF. In this report the algorithm, status and perspectives of such combined tracking are described.

  1. Making tracks

    Anon.

    1986-10-15

    In many modern tracking chambers, the sense wires, rather than being lined up uniformly, are grouped into clusters to facilitate the pattern recognition process. However, with higher energy machines providing collisions richer in secondary particles, event reconstruction becomes more complicated. A Caltech / Illinois / SLAC / Washington group developed an ingenious track finding and fitting approach for the Mark III detector used at the SPEAR electron-positron ring at SLAC (Stanford). This capitalizes on the detector's triggering, which uses programmable logic circuits operating in parallel, each 'knowing' the cell patterns for all tracks passing through a specific portion of the tracker (drift chamber)

  2. Particle filter in vision tracking

    Erik Cuevas J.

    2007-01-01

    Full Text Available El filtro de Kalman ha sido usado exitosamente en diferentes aplicaciones de predicción o determinación del estado de un sistema. Un campo importante en la visión por computadora es el seguimiento de objetos. Diferentes tipos de movimiento así como el ocultamiento de objetos a seguir pueden obstaculizar la labor de seguimiento. En este trabajo, se presenta el uso del filtro de Kalman para el seguimiento de objetos. Además se considera tanto la capacidad del filtro para tolerar pequeños ocultamientos del objeto así como el uso del filtro de Kalman extendido para el modelaje de movimientos complejos.

  3. Perspectives on Nonlinear Filtering

    Law, Kody

    2015-01-01

    The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

  4. Perspectives on Nonlinear Filtering

    Law, Kody

    2015-01-07

    The solution to the problem of nonlinear filtering may be given either as an estimate of the signal (and ideally some measure of concentration), or as a full posterior distribution. Similarly, one may evaluate the fidelity of the filter either by its ability to track the signal or its proximity to the posterior filtering distribution. Hence, the field enjoys a lively symbiosis between probability and control theory, and there are plenty of applications which benefit from algorithmic advances, from signal processing, to econometrics, to large-scale ocean, atmosphere, and climate modeling. This talk will survey some recent theoretical results involving accurate signal tracking with noise-free (degenerate) dynamics in high-dimensions (infinite, in principle, but say d between 103 and 108 , depending on the size of your application and your computer), and high-fidelity approximations of the filtering distribution in low dimensions (say d between 1 and several 10s).

  5. Application of Knowledge-Based Techniques to Tracking Function

    Farina, A

    2006-01-01

    ...: historical survey of stochastic filtering theory; overview of tracking systems with some details on mono-sensor and multi-sensor tracking, evolution of filtering logics, evolution of correlation logics, and presentation of recent findings on non...

  6. Thermal Tracking of Sports Players

    Gade, Rikke; Moeslund, Thomas B.

    2014-01-01

    We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline...

  7. LHCb Kalman Filter cross architecture studies

    Hugo, Daniel; Pérez, Cámpora

    2017-10-01

    The 2020 upgrade of the LHCb detector will vastly increase the rate of collisions the Online system needs to process in software, in order to filter events in real time. 30 million collisions per second will pass through a selection chain, where each step is executed conditional to its prior acceptance. The Kalman Filter is a fit applied to all reconstructed tracks which, due to its time characteristics and early execution in the selection chain, consumes 40% of the whole reconstruction time in the current trigger software. This makes the Kalman Filter a time-critical component as the LHCb trigger evolves into a full software trigger in the Upgrade. I present a new Kalman Filter algorithm for LHCb that can efficiently make use of any kind of SIMD processor, and its design is explained in depth. Performance benchmarks are compared between a variety of hardware architectures, including x86_64 and Power8, and the Intel Xeon Phi accelerator, and the suitability of said architectures to efficiently perform the LHCb Reconstruction process is determined.

  8. The relationship between physical fitness and clustered risk, and tracking of clustered risk from adolescence to young adulthood: eight years follow-up in the Danish Youth and Sport Study

    Grønfeldt Vivian

    2004-03-01

    Full Text Available Abstract Introduction Cardiovascular disease (CVD is usually caused by high levels of many risk factors simultaneously over many years. Therefore, it is of great interest to study if subjects stay within rank order over time in both the biological risk factors and the behaviour that influences these risk factors. Many studies have described stability (tracking in single risk factors, especially in children where hard endpoints are lacking, but few have analysed tracking in clustered risk. Methods Two examinations were conducted 8 years apart. The first time, 133 males and 172 females were 16–19 years of age. Eight years later, 98 males and 137 females participated. They were each time ranked into quartiles by sex in four CVD risk factors all related to the metabolic syndrome. Risk factors were the ratio between total cholesterol and HDL, triglyceride, systolic BP and body fat. The upper quartile was defined as being at risk, and if a subject had two or more risk factors, he/she was defined as a case (15–20 % of the subjects. Odds ratios (OR for being a case was calculated between quartiles of fitness in both cross-sectional studies. The stability of combined risk was calculated as the OR between cases and non-cases at the first examination to be a case at the second examination. Results ORs for having two or more risk factors between quartiles of fitness were 3.1, 3.8 and 4.9 for quartiles two to four, respectively. At the second examination, OR were 0.7, 3.5 and 4.9, respectively. The probability for "a case" at the first examination to be "a case" at the second was 6.0. Conclusions The relationship between an exposure like physical fitness and CVD risk factors is much stronger when clustering of risk factors are analysed compared to the relationship to single risk factors. The stability over time in multiple risk factors analysed together is strong. This relationship should be seen in the light of moderate or weak tracking of single risk

  9. Interface of the general fitting tool GENFIT2 in PandaRoot

    Prencipe, Elisabetta; Spataro, Stefano; Stockmanns, Tobias; PANDA Collaboration

    2017-10-01

    \\bar{{{P}}}ANDA is a planned experiment at FAIR (Darmstadt) with a cooled antiproton beam in a range [1.5; 15] GeV/c, allowing a wide physics program in nuclear and particle physics. It is the only experiment worldwide, which combines a solenoid field (B=2T) and a dipole field (B=2Tm) in a spectrometer with a fixed target topology, in that energy regime. The tracking system of \\bar{{{P}}}ANDA involves the presence of a high performance silicon vertex detector, a GEM detector, a straw-tubes central tracker, a forward tracking system, and a luminosity monitor. The offline tracking algorithm is developed within the PandaRoot framework, which is a part of the FairRoot project. The tool here presented is based on algorithms containing the Kalman Filter equations and a deterministic annealing filter. This general fitting tool (GENFIT2) offers to users also a Runge-Kutta track representation, and interfaces with Millepede II (useful for alignment) and RAVE (vertex finder). It is independent on the detector geometry and the magnetic field map, and written in C++ object-oriented modular code. Several fitting algorithms are available with GENFIT2, with user-adjustable parameters; therefore the tool is of friendly usage. A check on the fit convergence is done by GENFIT2 as well. The Kalman-Filter-based algorithms have a wide range of applications; among those in particle physics they can perform extrapolations of track parameters and covariance matrices. The adoptions of the PandaRoot framework to connect to Genfit2 are described, and the impact of GENFIT2 on the physics simulations of \\bar{{{P}}}ANDA are shown: significant improvement is reported for those channels where a good low momentum tracking is required (pT < 400 MeV/c).

  10. Box-particle intensity filter

    Schikora, Marek; Gning, Amadou; Mihaylova, Lyudmila; Cremers, Daniel; Koch, Wofgang; Streit, Roy

    2012-01-01

    This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables thi...

  11. Development of etched nuclear tracks

    Somogyi, G.

    1980-01-01

    The theoretical description of the evolution of etched tracks in solid state nuclear track detectors is considered for different initial conditions, for the cases of constant and varying track etch rates, isotropic and anisotropic bulk etching as well as for thick and thin detectors. It is summarized how one can calculate the main parameters of etch-pit geometry, the track length, the axes of a surface track opening, track profile and track contour. The application of the theory of etch-track evolution is demonstrated with selected practical problems. Attention is paid to certain questions related to the determination of unknown track parameters and calculation of surface track sizes. Finally, the theory is extended to the description of the perforation and etch-hole evolution process in thin detectors, which is of particular interest for track radiography and nuclear filter production. (orig.)

  12. Development of etched nuclear tracks

    Somogyi, G.

    1979-01-01

    The theoretical description of the evolution of etched tracks in solid state nuclear track detectors is considered for different initial conditions, for the cases of constant and varying track etch rates, isotopic and unisotropic bulk etching as well as for thick and thin detectors. It is summarized how the main parameters of etch-pit geometry, the track length, the axes of a surface track opening, the track profile and the track contour can be calculated. The application of the theory of etch-track evolution is demonstrated with selected practical problems. Attention is paid to certain questions related to the determination of unknown track parameters and calculation of surface track sizes. Finally, the theory is extended to the description of the perforation and etch-hole evolution process in thin detectors, which is of particular interest for track radiography and nuclear filter production. (author)

  13. Calculation of track and vertex errors for detector design studies

    Harr, R.

    1995-01-01

    The Kalman Filter technique has come into wide use for charged track reconstruction in high-energy physics experiments. It is also well suited for detector design studies, allowing for the efficient estimation of optimal track covariance matrices without the need of a hit level Monte Carlo simulation. Although much has been published about the Kalman filter equations, there is a lack of previous literature explaining how to implement the equations. In this paper, the operators necessary to implement the Kalman filter equations for two common detector configurations are worked out: a central detector in a uniform solenoidal magnetic field, and a fixed-target detector with no magnetic field in the region of the interactions. With the track covariance matrices in hand, vertex and invariant mass errors are readily calculable. These quantities are particularly interesting for evaluating experiments designed to study weakly decaying particles which give rise to displaced vertices. The optimal vertex errors are obtained via a constrained vertex fit. Solutions are presented to the constrained vertex problem with and without kinematic constraints. Invariant mass errors are obtained via propagation of errors; the use of vertex constrained track parameters is discussed. Many of the derivations are new or previously unpublished

  14. Filter arrays

    Page, Ralph H.; Doty, Patrick F.

    2017-08-01

    The various technologies presented herein relate to a tiled filter array that can be used in connection with performance of spatial sampling of optical signals. The filter array comprises filter tiles, wherein a first plurality of filter tiles are formed from a first material, the first material being configured such that only photons having wavelengths in a first wavelength band pass therethrough. A second plurality of filter tiles is formed from a second material, the second material being configured such that only photons having wavelengths in a second wavelength band pass therethrough. The first plurality of filter tiles and the second plurality of filter tiles can be interspersed to form the filter array comprising an alternating arrangement of first filter tiles and second filter tiles.

  15. Online track and vertex reconstruction on GPUs for the Mu3e experiment

    Bruch, Dorothea vom [Institut fuer Kernphysik, Johannes Gutenberg-Universitaet Mainz (Germany); Collaboration: Mu3e-Collaboration

    2016-07-01

    The Mu3e experiment searches for the lepton flavour violating decay μ → eee, aiming at a branching ratio sensitivity better than 10{sup -16}.To reach this sensitivity, muon rates above 10{sup 9} μ/s are required. A high precision silicon tracking detector combined with excellent timing resolution from scintillating fibers and tiles will measure the momenta, vertices and timing of the decay products of muons stopped in the target to suppress background. The trigger-less readout system will deliver about 100 GB/s of zero-suppressed data. A network of optical links and switching FPGAs sends the complete detector data for a time slice to one node of the filter farm. An FPGA inside the filter farm PC transfers the event data to the GPU via PCIe direct memory access. The GPU finds and fits tracks using a 3D tracking algorithm for multiple scattering dominated resolution. In a second step, a three track vertex fit is performed, allowing for a reduction of the output data rate to below 100 MB/s by removing combinatorial background. The talk discusses the data flow from the FPGA to the GPU as well as the implementation and performance of the track and vertex fits on the GPU.

  16. Box-particle probability hypothesis density filtering

    Schikora, M.; Gning, A.; Mihaylova, L.; Cremers, D.; Koch, W.

    2014-01-01

    This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic, and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small number of box-p...

  17. Fitness club

    Fitness club

    2011-01-01

    General fitness Classes Enrolments are open for general fitness classes at CERN taking place on Monday, Wednesday, and Friday lunchtimes in the Pump Hall (building 216). There are shower facilities for both men and women. It is possible to pay for 1, 2 or 3 classes per week for a minimum of 1 month and up to 6 months. Check out our rates and enrol at: http://cern.ch/club-fitness Hope to see you among us! CERN Fitness Club fitness.club@cern.ch  

  18. Thermal Tracking of Sports Players

    Rikke Gade

    2014-07-01

    Full Text Available We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

  19. Thermal tracking of sports players.

    Gade, Rikke; Moeslund, Thomas B

    2014-07-29

    We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

  20. Updating the OMERACT filter

    Kirwan, John R; Boers, Maarten; Hewlett, Sarah

    2014-01-01

    OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Filter provides guidelines for the development and validation of outcome measures for use in clinical research. The "Truth" section of the OMERACT Filter presupposes an explicit framework for identifying the relevant core outcomes...... for defining core areas of measurement ("Filter 2.0 Core Areas of Measurement") was presented at OMERACT 11 to explore areas of consensus and to consider whether already endorsed core outcome sets fit into this newly proposed framework. METHODS: Discussion groups critically reviewed the extent to which case......, presentation, and clarity of the framework were questioned. The discussion groups and subsequent feedback highlighted 20 such issues. CONCLUSION: These issues will require resolution to reach consensus on accepting the proposed Filter 2.0 framework of Core Areas as the basis for the selection of Core Outcome...

  1. Rectifier Filters

    Y. A. Bladyko

    2010-01-01

    Full Text Available The paper contains definition of a smoothing factor which is suitable for any rectifier filter. The formulae of complex smoothing factors have been developed for simple and complex passive filters. The paper shows conditions for application of calculation formulae and filters

  2. Fitness Club

    Fitness Club

    2011-01-01

    The CERN Fitness Club is organising Zumba Classes on the first Wednesday of each month, starting 7 September (19.00 – 20.00). What is Zumba®? It’s an exhilarating, effective, easy-to-follow, Latin-inspired, calorie-burning dance fitness-party™ that’s moving millions of people toward joy and health. Above all it’s great fun and an excellent work out. Price: 22 CHF/person Sign-up via the following form: https://espace.cern.ch/club-fitness/Lists/Zumba%20Subscription/NewForm.aspx For more info: fitness.club@cern.ch

  3. Kaon Filtering For CLAS Data

    McNabb, J.

    2001-01-01

    The analysis of data from CLAS is a multi-step process. After the detectors for a given running period have been calibrated, the data is processed in the so called pass-1 cooking. During the pass-1 cooking each event is reconstructed by the program a1c which finds particle tracks and computes momenta from the raw data. The results are then passed on to several data monitoring and filtering utilities. In CLAS software, a filter is a parameterless function which returns an integer indicating whether an event should be kept by that filter or not. There is a main filter program called g1-filter which controls several specific filters and outputs several files, one for each filter. These files may then be analyzed separately, allowing individuals interested in one reaction channel to work from smaller files than using the whole data set would require. There are several constraints on what the filter functions should do. Obviously, the filtered files should be as small as possible, however the filter should also not reject any events that might be used in the later analysis for which the filter was intended

  4. People detection and tracking using RGB-D cameras for mobile robots

    Hengli Liu

    2016-09-01

    Full Text Available People detection and tracking is an essential capability for mobile robots in order to achieve natural human–robot interaction. In this article, a human detection and tracking system is designed and validated for mobile robots using color data with depth information RGB-depth (RGB-D cameras. The whole framework is composed of human detection, tracking and re-identification. Firstly, ground points and ceiling planes are removed to reduce computation effort. A prior-knowledge guided random sample consensus fitting algorithm is used to detect the ground plane and ceiling points. All left points are projected onto the ground plane and subclusters are segmented for candidate detection. Meanshift clustering with an Epanechnikov kernel is conducted to partition different points into subclusters. We propose the new idea of spatial region of interest plan view maps which are employed to identify human candidates from point cloud subclusters. Here, a depth-weighted histogram is extracted online to feature a human candidate. Then, a particle filter algorithm is adopted to track the human’s motion. The integration of the depth-weighted histogram and particle filter provides a precise tool to track the motion of human objects. Finally, data association is set up to re-identify humans who are tracked. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.

  5. Track and vertex reconstruction on GPUs for the Mu3e experiment

    Bruch, Dorothea vom; Kozlinskiy, Alexandr [Physikalisches Institut, Universitaet Heidelberg (Germany); Berger, Niklaus [Institut fuer Kernphysik, Universitaet Mainz (Germany); Collaboration: Mu3e-Collaboration

    2015-07-01

    The Mu3e experiment searches for the lepton flavour violating decay μ → eee, aiming at a branching ratio sensitivity better than 10{sup -16}. To reach this sensitivity, muon rates above 10{sup 9} μ/s are required. A high precision silicon pixel tracking detector combined with excellent timing resolution from scintillating fibers and tiles will measure the momenta, vertices and timing of the decay products of muons stopped in the target to suppress background. The trigger-less readout system will deliver about 100 GB/s of zero-suppressed data. A network of optical links and switching FPGAs sends the complete detector data for a time slice to one node of the filter farm. An FPGA inside the filter farm PC transfers the event data to the GPU via PCIe direct memory access. The GPU finds and fits tracks using a 3D tracking algorithm for multiple scattering dominated resolution. In a second step, a three track vertex fit is performed, allowing for a reduction of the output data rate to below 100 MB/s by removing combinatorial background. The talk discusses the implementation of the fits on the GPU, which processes 10{sup 10} combinations of hits from three layers per second.

  6. Fodbold Fitness

    Bennike, Søren

    Samfundet forandrer sig og ligeså gør danskernes idrætsmønstre. Fodbold Fitness, der er afhandlingens omdrejningspunkt, kan iagttages som en reaktion på disse forandringer. Afhandlingen ser nærmere på Fodbold Fitness og implementeringen af dette, der ingenlunde er nogen let opgave. Bennike bidrager...

  7. Fitness cost

    Nielsen, Karen L.; Pedersen, Thomas M.; Udekwu, Klas I.

    2012-01-01

    phage types, predominantly only penicillin resistant. We investigated whether isolates of this epidemic were associated with a fitness cost, and we employed a mathematical model to ask whether these fitness costs could have led to the observed reduction in frequency. Bacteraemia isolates of S. aureus...... from Denmark have been stored since 1957. We chose 40 S. aureus isolates belonging to phage complex 83A, clonal complex 8 based on spa type, ranging in time of isolation from 1957 to 1980 and with varyous antibiograms, including both methicillin-resistant and -susceptible isolates. The relative fitness...... of each isolate was determined in a growth competition assay with a reference isolate. Significant fitness costs of 215 were determined for the MRSA isolates studied. There was a significant negative correlation between number of antibiotic resistances and relative fitness. Multiple regression analysis...

  8. An efficient central DOA tracking algorithm for multiple incoherently distributed sources

    Hassen, Sonia Ben; Samet, Abdelaziz

    2015-12-01

    In this paper, we develop a new tracking method for the direction of arrival (DOA) parameters assuming multiple incoherently distributed (ID) sources. The new approach is based on a simple covariance fitting optimization technique exploiting the central and noncentral moments of the source angular power densities to estimate the central DOAs. The current estimates are treated as measurements provided to the Kalman filter that model the dynamic property of directional changes for the moving sources. Then, the covariance-fitting-based algorithm and the Kalman filtering theory are combined to formulate an adaptive tracking algorithm. Our algorithm is compared to the fast approximated power iteration-total least square-estimation of signal parameters via rotational invariance technique (FAPI-TLS-ESPRIT) algorithm using the TLS-ESPRIT method and the subspace updating via FAPI-algorithm. It will be shown that the proposed algorithm offers an excellent DOA tracking performance and outperforms the FAPI-TLS-ESPRIT method especially at low signal-to-noise ratio (SNR) values. Moreover, the performances of the two methods increase as the SNR values increase. This increase is more prominent with the FAPI-TLS-ESPRIT method. However, their performances degrade when the number of sources increases. It will be also proved that our method depends on the form of the angular distribution function when tracking the central DOAs. Finally, it will be shown that the more the sources are spaced, the more the proposed method can exactly track the DOAs.

  9. A New Filtering Algorithm Utilizing Radial Velocity Measurement

    LIU Yan-feng; DU Zi-cheng; PAN Quan

    2005-01-01

    Pulse Doppler radar measurements consist of range, azimuth, elevation and radial velocity. Most of the radar tracking algorithms in engineering only utilize position measurement. The extended Kalman filter with radial velocity measureneut is presented, then a new filtering algorithm utilizing radial velocity measurement is proposed to improve tracking results and the theoretical analysis is also given. Simulation results of the new algorithm, converted measurement Kalman filter, extended Kalman filter are compared. The effectiveness of the new algorithm is verified by simulation results.

  10. Customization of the GENFIT2 Fitting Package in P̅ANDA

    Prencipe Elisabetta

    2016-01-01

    Full Text Available The availability of a cooled antiproton beam in the energy range from 2.0 to 5.5 GeV will allow the P̅ANDA experiment, planned for operation in FAIR (Darmstadt, Germany, to perform a wide nuclear and particle physics program. P̅ANDA is the only experiment worldwide in that energy regime that combines a solenoidal magnetic field (B = 2 T and a dipole field (maximum bending power equal to 2 Tm in a fixed-target experiment. The offline tracking algorithm is developed within the PandaRoot framework, which is part of the FairRoot project. Here the GENFIT2 package is presented. The tool contains an implementation of the Kalman filter and the deterministic annealing filter for charged particle track reconstruction, together with a Runge-Kutta track representation. It also interfaces with Millipede II and RAVE, for alignment and vertex reconstruction, respectively. The performance of this track-fitting package for the P̅ANDA experiment is shown for the first time, within the PandaRoot framework. For those channels where a good low momentum tracking is required, i.e. pT <350 MeV/c, an improvement by a factor of about two is shown.

  11. Real Time 3D Facial Movement Tracking Using a Monocular Camera

    Yanchao Dong

    2016-07-01

    Full Text Available The paper proposes a robust framework for 3D facial movement tracking in real time using a monocular camera. It is designed to estimate the 3D face pose and local facial animation such as eyelid movement and mouth movement. The framework firstly utilizes the Discriminative Shape Regression method to locate the facial feature points on the 2D image and fuses the 2D data with a 3D face model using Extended Kalman Filter to yield 3D facial movement information. An alternating optimizing strategy is adopted to fit to different persons automatically. Experiments show that the proposed framework could track the 3D facial movement across various poses and illumination conditions. Given the real face scale the framework could track the eyelid with an error of 1 mm and mouth with an error of 2 mm. The tracking result is reliable for expression analysis or mental state inference.

  12. Kalman Filtering with Real-Time Applications

    Chui, Charles K

    2009-01-01

    Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering.

  13. Stack filter classifiers

    Porter, Reid B [Los Alamos National Laboratory; Hush, Don [Los Alamos National Laboratory

    2009-01-01

    Just as linear models generalize the sample mean and weighted average, weighted order statistic models generalize the sample median and weighted median. This analogy can be continued informally to generalized additive modeels in the case of the mean, and Stack Filters in the case of the median. Both of these model classes have been extensively studied for signal and image processing but it is surprising to find that for pattern classification, their treatment has been significantly one sided. Generalized additive models are now a major tool in pattern classification and many different learning algorithms have been developed to fit model parameters to finite data. However Stack Filters remain largely confined to signal and image processing and learning algorithms for classification are yet to be seen. This paper is a step towards Stack Filter Classifiers and it shows that the approach is interesting from both a theoretical and a practical perspective.

  14. Fitness Club

    Fitness Club

    2012-01-01

    Open to All: http://cern.ch/club-fitness  fitness.club@cern.ch Boxing Your supervisor makes your life too tough ! You really need to release the pressure you've been building up ! Come and join the fit-boxers. We train three times a week in Bd 216, classes for beginners and advanced available. Visit our website cern.ch/Boxing General Fitness Escape from your desk with our general fitness classes, to strengthen your heart, muscles and bones, improve you stamina, balance and flexibility, achieve new goals, be more productive and experience a sense of well-being, every Monday, Wednesday and Friday lunchtime, Tuesday mornings before work and Thursday evenings after work – join us for one of our monthly fitness workshops. Nordic Walking Enjoy the great outdoors; Nordic Walking is a great way to get your whole body moving and to significantly improve the condition of your muscles, heart and lungs. It will boost your energy levels no end. Pilates A body-conditioning technique de...

  15. Filter apparatus

    Butterworth, D.J.

    1980-01-01

    This invention relates to liquid filters, precoated by replaceable powders, which are used in the production of ultra pure water required for steam generation of electricity. The filter elements are capable of being installed and removed by remote control so that they can be used in nuclear power reactors. (UK)

  16. Hydrodynamics of microbial filter feeding

    Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia

    2017-01-01

    Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate......-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude......; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet...

  17. Nanoscale measurements of proton tracks using fluorescent nuclear track detectors

    Sawakuchi, Gabriel O., E-mail: gsawakuchi@mdanderson.org; Sahoo, Narayan [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and Graduate School of Biomedical Sciences, The University of Texas, Houston, Texas 77030 (United States); Ferreira, Felisberto A. [Department of Nuclear Physics, University of Sao Paulo, SP 05508-090 (Brazil); McFadden, Conor H. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Hallacy, Timothy M. [Biophysics Program, Harvard University, Cambridge, Massachusetts 02138 (United States); Granville, Dal A. [Department of Medical Physics, The Ottawa Hospital Cancer Centre, Ottawa, Ontario K1H 8L6 (Canada); Akselrod, Mark S. [Crystal Growth Division, Landauer, Inc., Stillwater, Oklahoma 74074 (United States)

    2016-05-15

    Purpose: The authors describe a method in which fluorescence nuclear track detectors (FNTDs), novel track detectors with nanoscale spatial resolution, are used to determine the linear energy transfer (LET) of individual proton tracks from proton therapy beams by allowing visualization and 3D reconstruction of such tracks. Methods: FNTDs were exposed to proton therapy beams with nominal energies ranging from 100 to 250 MeV. Proton track images were then recorded by confocal microscopy of the FNTDs. Proton tracks in the FNTD images were fit by using a Gaussian function to extract fluorescence amplitudes. Histograms of fluorescence amplitudes were then compared with LET spectra. Results: The authors successfully used FNTDs to register individual proton tracks from high-energy proton therapy beams, allowing reconstruction of 3D images of proton tracks along with delta rays. The track amplitudes from FNTDs could be used to parameterize LET spectra, allowing the LET of individual proton tracks from therapeutic proton beams to be determined. Conclusions: FNTDs can be used to directly visualize proton tracks and their delta rays at the nanoscale level. Because the track intensities in the FNTDs correlate with LET, they could be used further to measure LET of individual proton tracks. This method may be useful for measuring nanoscale radiation quantities and for measuring the LET of individual proton tracks in radiation biology experiments.

  18. Hydrodynamics of microbial filter feeding.

    Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia; Walther, Jens H; Kiørboe, Thomas; Andersen, Anders

    2017-08-29

    Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate amounts of water. Also, the trade-off in the filter spacing remains unexplored, despite its simple formulation: A filter too coarse will allow suitably sized prey to pass unintercepted, whereas a filter too fine will cause strong flow resistance. We quantify the feeding flow of the filter-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), something notoriously difficult to visualize but sporadically observed in the related choanocytes (sponges). A CFD model with a flagellar vane correctly predicts the filtration rate of D. grandis , and using a simple model we can account for the filtration rates of other microbial filter feeders. We finally predict how optimum filter mesh size increases with cell size in microbial filter feeders, a prediction that accords very well with observations. We expect our results to be of significance for small-scale biophysics and trait-based ecological modeling.

  19. Kalman filtering with real-time applications

    Chui, Charles K

    2017-01-01

    This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help de...

  20. Fitness club

    Fitness club

    2013-01-01

      Nordic Walking Classes Come join the Nordic walking classes and outings offered by the CERN Fitness Club starting September 2013. Our licensed instructor Christine offers classes for people who’ve never tried Nordic Walking and who would like to learn the technique, and outings for people who have completed the classes and enjoy going out as a group. Course 1: Tuesdays 12:30 - 13:30 24 September, 1 October, 8 October, 15 October Course 2: Tuesdays 12:30 - 13:30 5 November, 12 November, 19 November, 26 November Outings will take place on Thursdays (12:30 to 13:30) from 12 September 2013. We meet at the CERN Club Barracks car park (close to Entrance A) 10 minutes before departure. Prices: 50 CHF for 4 classes, including the 10 CHF Club membership. Payments made directly to instructor. Renting Poles: Poles can be rented from Christine at 5 CHF / hour. Subscription: Please subscribe at: http://cern.ch/club-fitness Looking forward to seeing you among us! Fitness Club FitnessClub@c...

  1. Fitness Club

    Fitness Club

    2012-01-01

    Get in Shape for Summer with the CERN Fitness Club Saturday 23 June 2012 from 14:30 to 16.30 (doors open at 14.00) Germana’s Fitness Workshop. Build strength and stamina, sculpt and tone your body and get your heart pumping with Germana’s workout mixture of Cardio Attack, Power Pump, Power Step, Cardio Combat and Cross-Training. Where: 216 (Pump room – equipped with changing rooms and showers). What to wear: comfortable clothes and indoor sports shoes + bring a drink! How much: 15 chf Sign up here: https://espace.cern.ch/club-fitness/Lists/Test_Subscription/NewForm.aspx? Join the Party and dance yourself into shape at Marco + Marials Zumba Masterclass. Saturday 30 June 2012 from 15:00 to 16:30 Marco + Mariel’s Zumba Masterclass Where: 216 (Pump room – equipped with changing rooms and showers). What to wear: comfortable clothes and indoor sports shoes + bring a drink! How much: 25 chf Sign up here: https://espace.cern.ch/club-fitness/Lists/Zumba%20...

  2. Fitness Club

    Fitness Club

    2010-01-01

    Nordic Walking Please note that the subscriptions for the general fitness classes from July to December are open: Subscriptions general fitness classes Jul-Dec 2010 Sign-up to the Fitness Club mailing list here Nordic Walking: Sign-up to the Nordic Walking mailing list here Beginners Nordic walking lessons Monday Lunchtimes (rdv 12:20 for 12:30 departure) 13.09/20.09/27.09/04.10 11.10/18.10/08.11/15.11 22.11/29.11/06.12/20.12 Nordic walking lessons Tuesday evenings (rdv 17:50 for 18:00 departure) 07.09/14.09/21.09/28.09 05.10/12.10/19.10/26.10 Intermediate/Advanced Nordic walking outings (follow the nordic walking lessons before signing up for the outings) every Thursday from 16.09 - 16.12, excluding 28.10 and 09.12 Subscriptions and info: fitness.club@cern.ch  

  3. Fitness Club

    Fitness Club

    2012-01-01

      The CERN Fitness Club is pleased to announce its new early morning class which will be taking place on: Tuesdays from 24th April 07:30 to 08:15 216 (Pump Hall, close to entrance C) – Facilities include changing rooms and showers. The Classes: The early morning classes will focus on workouts which will help you build not only strength and stamina, but will also improve your balance, and coordination. Our qualified instructor Germana will accompany you throughout the workout  to ensure you stay motivated so you achieve the best results. Sign up and discover the best way to start your working day full of energy! How to subscribe? We invite you along to a FREE trial session, if you enjoy the activity, please sign up via our website: https://espace.cern.ch/club-fitness/Activities/SUBSCRIBE.aspx. * * * * * * * * Saturday 28th April Get in shape for the summer at our fitness workshop and zumba dance party: Fitness workshop with Germana 13:00 to 14:30 - 216 (Pump Hall) Price...

  4. Mixed labelling in multitarget particle filtering

    Boers, Y.; Sviestins, Egils; Driessen, Hans

    2010-01-01

    The so-called mixed labelling problem inherent to a joint state multitarget particle filter implementation is treated. The mixed labelling problem would be prohibitive for track extraction from a joint state multitarget particle filter. It is shown, using the theory of Markov chains, that the mixed

  5. Filter systems

    Vanin, V.R.

    1990-01-01

    The multidetector systems for high resolution gamma spectroscopy are presented. The observable parameters for identifying nuclides produced simultaneously in the reaction are analysed discussing the efficiency of filter systems. (M.C.K.)

  6. Hotels Make Room for Fitness.

    Koszuta, Laurie Einstein

    1986-01-01

    Hotels, in hopes of gaining a competitive edge, are offering workout rooms, exercise equipment, fitness trails, and jogging tracks, but no standards have been set for safety of the facilities or staff preparedness in exercise screening, equipment use, injury prevention, or first aid. (MT)

  7. Mobile Tracking Systems Using Meter Class Reflective Telescopes

    Sturzenbecher, K.; Ehrhorn, B.

    This paper is a discussion on the use of large reflective telescopes on mobile tracking systems with modern instrument control systems. Large optics can be defined as reflective telescopes with an aperture of at least 20 inches in diameter. New carbon composite construction techniques allow for larger, stronger, and lighter telescopes ranging from 240 pounds for a 20 inch, to 800 pounds for a 32 inch, making them ideal for mobile tracking systems. These telescopes have better light gathering capability and produce larger images with greater detail at a longer range than conventional refractive lenses. In a mobile configuration these systems provide the ability to move the observation platform to the optimal location anywhere in the world. Mounting and systems integration - We will discuss how large telescopes can be physically fit to the mobile tracking system and the integration with the tracking systems' digital control system. We will highlight the remote control capabilities. We will discuss special calibration techniques available in a modern instrument control system such as star calibration, calibration of sensors. Tracking Performance - We will discuss the impact of using large telescopes on the performance of the mobile tracking system. We will highlight the capabilities for auto-tracking and sidereal rate tracking in a mobile mount. Large optics performance - We will discuss the advantages of two-mirror Ritchey-Chrétien reflective optics which offer in-focus imaging across the spectrum, from visible to Long Wave Infrared. These zero expansion optics won't lose figure or focus during temperature changes. And the carbon composite telescope tube is thermally inert. The primary mirror is a modern lightweight "dish" mirror for low thermal mass and is center supported/self balancing. Applications - We will discuss Visible - IR Imaging requirements, Optical Rangefinders, and capabilities for special filters to increase resolution in difficult conditions such as

  8. Robust visual tracking via multi-task sparse learning

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

    2012-01-01

    In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates

  9. Fitness Club

    Fitness Club

    2012-01-01

    Nordic Walking Classes Sessions of four classes of one hour each are held on Tuesdays. RDV barracks parking at Entrance A, 10 minutes before class time. Session 1 =  11.09 / 18.09 / 25.09 / 02.10, 18:15 - 19:15 Session 2 = 25.09 / 02.10 / 09.10 / 16.10, 12:30 - 13:30 Session 3 = 23.10 / 30.10 / 06.11 / 13.11, 12:30 - 13:30 Session 4 = 20.11 / 27.11 / 04.12 / 11.12, 12:30 - 13:30 Prices 40 CHF per session + 10 CHF club membership 5 CHF/hour pole rental Check out our schedule and enroll at http://cern.ch/club-fitness   Hope to see you among us!  fitness.club@cern.ch In spring 2012 there was a long-awaited progress in CERN Fitness club. We have officially opened a Powerlifting @ CERN, and the number of members of the new section has been increasing since then reaching 70+ people in less than 4 months. Powerlifting is a strength sport, which is simple as 1-2-3 and efficient. The "1-2-3" are the three basic lifts (bench press...

  10. Linear Regression Based Real-Time Filtering

    Misel Batmend

    2013-01-01

    Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.

  11. Track reconstruction at the ILC: the ILD tracking software

    Gaede, Frank; Aplin, Steven; Rosemann, Christoph; Voutsinas, Georgios; Glattauer, Robin

    2014-01-01

    One of the key requirements for Higgs physics at the International Linear Collider ILC is excellent track reconstruction with very good momentum and impact parameter resolution. ILD is one of the two detector concepts at the ILC. Its central tracking system comprises of an outer Si-tracker, a highly granular TPC, an intermediate silicon tracker and a pixel vertex detector, and it is complemented by silicon tracking disks in the forward direction. Large hit densities from beam induced coherent electron-positron pairs at the ILC pose an additional challenge to the pattern recognition algorithms. We present the recently developed new ILD tracking software, the pattern recognition algorithms that are using clustering techniques, Cellular Automatons and Kalman filter based track extrapolation. The performance of the ILD tracking system is evaluated using a detailed simulation including dead material, gaps and imperfections.

  12. Bottom loaded filter for radioactive liquid

    Wendland, W.G.

    1980-01-01

    A specification is given for a bottom loaded filter assembly for filtering radioactive liquids through a replaceable cartridge filter, which includes a lead-filled jacket enveloping a housing having a chamber therein for the filter cartridge. A track arrangement carries a hatch for sealing the chamber. A spacer plug supports the cartridge within guide means associated with the inlet conduit in the chamber. The plug and cartridge drop out of the chamber when the hatch is unbolted and moved laterally of the chamber along the track. During cartridge replacement a new plug and cartridge are supported in the guide means by a spacer bar inserted across the track means under the chamber. The hatch is then slid under the chamber and bolted to a flange on the housing, engaging an O-ring to seal the chamber. (author)

  13. Manifold Regularized Correlation Object Tracking.

    Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

    2018-05-01

    In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

  14. Fitness club

    Fitness club

    2013-01-01

    Nordic Walking Classes New session of 4 classes of 1 hour each will be held on Tuesdays in May 2013. Meet at the CERN barracks parking at Entrance A, 10 minutes before class time. Dates and time: 07.05, 14.05, 21.05 and 28.05, fom  12 h 30 to 13 h 30 Prices: 40 CHF per session + 10 CHF club membership – 5 CHF / hour pole rental Check out our schedule and enroll at http://cern.ch/club-fitness Hope to see you among us! 

  15. Scheme of adaptive polarization filtering based on Kalman model

    Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

    2006-01-01

    A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

  16. Developmental pathways of fitness, and not baseline, predict fitness status at the end of childhood

    Rodrigues, Luis Paulo; Stodden, David F.; Lopes, Vítor P.

    2013-01-01

    It is generally described that children fitness levels increase along childhood. Complementary to this idea is the notion that the tracking of children’s fitness is good to moderate during this developmental time, and that baseline (initial values) of fitness are determinant on fitness development. The importance of developmental pathways has been recently reinforced by a theoretical argument that predicts that healthy lifestyle trajectories will evolve through either a positive or n...

  17. Application and Optimization of Kalman Filter for Baseband Signal Processing of GPS Receivers

    He Yanpin

    2016-01-01

    Full Text Available High sensitivity tracking in GPS receiver is required in many weak signal circumstances. The key of improving sensitivity is the optimization of the loop filter in tracking. As Kalman filter is the most optimized linear filter, it is used in many engineering fields. This article introduced the application of Kalman filter as the loop filter of the carrier tracking loop in GPS receiver, to improve tracking sensitivity. The traditional loop filter is replaced. Simulation results show that the new structure improves the tracking sensitivity by 6dB and can make the tracking loop more robust when the navigation signal is languishing. The optimization of theKalman filter is also analysed, which further improves the sensitivity by 4dB.

  18. Bottom loaded filter for radioactive liquids

    Wendland, W.G.

    1980-01-01

    A bottom loaded filter assembly for filtering radioactive liquids through a replaceable cartridge filter is disclosed. The filter assembly includes a lead-filled jacket enveloping a housing having a chamber therein for the filter cartridge. A track arrangement carries a hatch for sealing the chamber. A spacer plug supports the cartridge within guide means associated with the inlet conduit in the chamber. The plug and cartridge drop out of the chamber when the hatch is unbolted and move laterally of the chamber. During cartridge replacement, a new plug and cartridge are supported in the guide means by a spacer bar inserted across the track means under the chamber. The hatch is then slid under the chamber and bolted to the vessel, engaging an o-ring to seal the chamber

  19. The intractable cigarette 'filter problem'.

    Harris, Bradford

    2011-05-01

    When lung cancer fears emerged in the 1950s, cigarette companies initiated a shift in cigarette design from unfiltered to filtered cigarettes. Both the ineffectiveness of cigarette filters and the tobacco industry's misleading marketing of the benefits of filtered cigarettes have been well documented. However, during the 1950s and 1960s, American cigarette companies spent millions of dollars to solve what the industry identified as the 'filter problem'. These extensive filter research and development efforts suggest a phase of genuine optimism among cigarette designers that cigarette filters could be engineered to mitigate the health hazards of smoking. This paper explores the early history of cigarette filter research and development in order to elucidate why and when seemingly sincere filter engineering efforts devolved into manipulations in cigarette design to sustain cigarette marketing and mitigate consumers' concerns about the health consequences of smoking. Relevant word and phrase searches were conducted in the Legacy Tobacco Documents Library online database, Google Patents, and media and medical databases including ProQuest, JSTOR, Medline and PubMed. 13 tobacco industry documents were identified that track prominent developments involved in what the industry referred to as the 'filter problem'. These reveal a period of intense focus on the 'filter problem' that persisted from the mid-1950s to the mid-1960s, featuring collaborations between cigarette producers and large American chemical and textile companies to develop effective filters. In addition, the documents reveal how cigarette filter researchers' growing scientific knowledge of smoke chemistry led to increasing recognition that filters were unlikely to offer significant health protection. One of the primary concerns of cigarette producers was to design cigarette filters that could be economically incorporated into the massive scale of cigarette production. The synthetic plastic cellulose acetate

  20. Fast Filter Central Drift Chamber Program. MAC Note 404

    Ford, W.T.

    1979-01-01

    A fast filter of the central detector tracking program was developed and tested. The search for tracks is conducted as in the full linking program - from the outermost layer hit to the next layer in. Any hit is accepted within a road centered which is large enough to allow for stero displacement and any curvature. With the fast filter, this is continued to the innermost layer, with five or more hits accepted as a track

  1. Generalised Filtering

    Karl Friston

    2010-01-01

    Full Text Available We describe a Bayesian filtering scheme for nonlinear state-space models in continuous time. This scheme is called Generalised Filtering and furnishes posterior (conditional densities on hidden states and unknown parameters generating observed data. Crucially, the scheme operates online, assimilating data to optimize the conditional density on time-varying states and time-invariant parameters. In contrast to Kalman and Particle smoothing, Generalised Filtering does not require a backwards pass. In contrast to variational schemes, it does not assume conditional independence between the states and parameters. Generalised Filtering optimises the conditional density with respect to a free-energy bound on the model's log-evidence. This optimisation uses the generalised motion of hidden states and parameters, under the prior assumption that the motion of the parameters is small. We describe the scheme, present comparative evaluations with a fixed-form variational version, and conclude with an illustrative application to a nonlinear state-space model of brain imaging time-series.

  2. Filter This

    Audrey Barbakoff

    2011-03-01

    Full Text Available In the Library with the Lead Pipe welcomes Audrey Barbakoff, a librarian at the Milwaukee Public Library, and Ahniwa Ferrari, Virtual Experience Manager at the Pierce County Library System in Washington, for a point-counterpoint piece on filtering in libraries. The opinions expressed here are those of the authors, and are not endorsed by their employers. [...

  3. Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

    Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

    2015-01-01

    The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

  4. Kinematic Fitting of Detached Vertices

    Mattione, Paul [Rice Univ., Houston, TX (United States)

    2007-05-01

    The eg3 experiment at the Jefferson Lab CLAS detector aims to determine the existence of the $\\Xi_{5}$ pentaquarks and investigate the excited $\\Xi$ states. Specifically, the exotic $\\Xi_{5}^{--}$ pentaquark will be sought by first reconstructing the $\\Xi^{-}$ particle through its weak decays, $\\Xi^{-}\\to\\pi^{-}\\Lambda$ and $\\Lambda\\to\\pi^{-}$. A kinematic fitting routine was developed to reconstruct the detached vertices of these decays, where confidence level cuts on the fits are used to remove background events. Prior to fitting these decays, the exclusive reaction $\\gamma D\\rightarrow pp\\pi^{-}$ was studied in order to correct the track measurements and covariance matrices of the charged particles. The $\\Lambda\\rightarrow p\\pi^{-}$ and $\\Xi^{-}\\to\\pi^{-}\\Lambda$ decays were then investigated to demonstrate that the kinematic fitting routine reconstructs the decaying particles and their detached vertices correctly.

  5. Multi-filter spectrophotometry of quasar environments

    Craven, Sally E.; Hickson, Paul; Yee, Howard K. C.

    1993-01-01

    A many-filter photometric technique for determining redshifts and morphological types, by fitting spectral templates to spectral energy distributions, has good potential for application in surveys. Despite success in studies performed on simulated data, the results have not been fully reliable when applied to real, low signal-to-noise data. We are investigating techniques to improve the fitting process.

  6. Drift chamber tracking with neural networks

    Lindsey, C.S.; Denby, B.; Haggerty, H.

    1992-10-01

    We discuss drift chamber tracking with a commercial log VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed

  7. Kalman Filter Application to Symmetrical Fault Detection during Power Swing

    Khodaparast, Jalal; Silva, Filipe Miguel Faria da; Khederzadeh, M.

    2016-01-01

    capability of Kalman Filter. The proposed index is calculated by assessing the difference between predicted and actual samples of impedance. The predicted impedance samples are obtained using Kalman filter and Taylor expansion, which is used in this paper to track the phasor precisely. Second order of Taylor...... expansion is used to decrease corrugation effect of impedance estimation and increase the reliability of proposed method. The instantaneous estimation and prediction capability of Kalman filter are two reasons for proposing utilizing Kalman filter....

  8. PolarTrack: Optical Outside-In Device Tracking that Exploits Display Polarization

    Rädle, Roman; Jetter, Hans-Christian; Fischer, Jonathan

    2018-01-01

    PolarTrack is a novel camera-based approach to detecting and tracking mobile devices inside the capture volume. In PolarTrack, a polarization filter continuously rotates in front of an off-the-shelf color camera, which causes the displays of observed devices to periodically blink in the camera feed....... The periodic blinking results from the physical characteristics of current displays, which shine polarized light either through an LC overlay to produce images or through a polarizer to reduce light reflections on OLED displays. PolarTrack runs a simple detection algorithm on the camera feed to segment...... displays and track their locations and orientations, which makes PolarTrack particularly suitable as a tracking system for cross-device interaction with mobile devices. Our evaluation of PolarTrack's tracking quality and comparison with state-of-the-art camera-based multi-device tracking showed a better...

  9. Tracking populations of Phytophthora ramorum within trees and across the South-western Oregon tanoak (Notholithocarpus densiflorus) forest with DNA fingerprinting and the relative fitness of dominant and rare individuals

    Jennifer Britt; Everett Hansen

    2011-01-01

    Since the discovery of Phytophthora ramorum Werres, De Cock & Man In't Veld in south-western Oregon forests in 2001, newly infected areas are detected each year. Yet, there are still gaps in our knowledge about how the pathogen spreads or where new infections come from. Our study aims to track the spread of P. ramorum...

  10. Stabilization diagrams using operational modal analysis and sliding filters

    Olsen, Peter; Juul, Martin Ørum Ørhem; Tarpø, Marius Glindtvad

    2017-01-01

    This paper presents a filtering technique for doing effective operational modal analysis. The result of the filtering method is construction of stabilization diagram that clearly separates physical poles from spurious noise poles needed for unbiased fitting. A band pass filter is moved slowly over...

  11. Color and motion-based particle filter target tracking in a network of overlapping cameras with multi-threading and GPGPU Rastreo de objetivos por medio de filtros de partículas basados en color y movimiento en una red de cámaras con multi-hilo y GPGPU

    Jorge Francisco Madrigal Díaz

    2013-03-01

    Full Text Available This paper describes an efficient implementation of multiple-target multiple-view tracking in video-surveillance sequences. It takes advantage of the capabilities of multiple core Central Processing Units (CPUs and of graphical processing units under the Compute Unifie Device Arquitecture (CUDA framework. The principle of our algorithm is 1 in each video sequence, to perform tracking on all persons to track by independent particle filters and 2 to fuse the tracking results of all sequences. Particle filters belong to the category of recursive Bayesian filters. They update a Monte-Carlo representation of the posterior distribution over the target position and velocity. For this purpose, they combine a probabilistic motion model, i.e. prior knowledge about how targets move (e.g. constant velocity and a likelihood model associated to the observations on targets. At this first level of single video sequences, the multi-threading library Threading Buildings Blocks (TBB has been used to parallelize the processing of the per-target independent particle filters. Afterwards at the higher level, we rely on General Purpose Programming on Graphical Processing Units (generally termed as GPGPU through CUDA in order to fuse target-tracking data collected on multiple video sequences, by solving the data association problem. Tracking results are presented on various challenging tracking datasets.Este artículo describe una implementación eficiente de un algoritmo de seguimiento de múlti­ples objetivos en múltiples vistas en secuencias de video vigilancia. Aprovecha las capacidades de las Unidades Centrales de Procesamiento (CPUs, por sus siglas en inglés de múltiples núcleos y de las unidades de procesamiento gráfico, bajo el entorno de desarrollo de Arquitec­tura Unificada de Dispositivos de Cómputo (CUDA, por sus siglas en inglés. El principio de nuestro algoritmo es: 1 aplicar el seguimiento visual en cada secuencia de video sobre todas las

  12. Automatic detection, tracking and sensor integration

    Trunk, G. V.

    1988-06-01

    This report surveys the state of the art of automatic detection, tracking, and sensor integration. In the area of detection, various noncoherent integrators such as the moving window integrator, feedback integrator, two-pole filter, binary integrator, and batch processor are discussed. Next, the three techniques for controlling false alarms, adapting thresholds, nonparametric detectors, and clutter maps are presented. In the area of tracking, a general outline is given of a track-while-scan system, and then a discussion is presented of the file system, contact-entry logic, coordinate systems, tracking filters, maneuver-following logic, tracking initiating, track-drop logic, and correlation procedures. Finally, in the area of multisensor integration the problems of colocated-radar integration, multisite-radar integration, radar-IFF integration, and radar-DF bearing strobe integration are treated.

  13. Bag filters

    Yoshida, M; Komeda, I; Takizaki, K

    1982-01-01

    Bag filters are widely used throughout the cement industry for recovering raw materials and products and for improving the environment. Their general mechanism, performance and advantages are shown in a classification table, and there are comparisons and explanations. The outer and inner sectional construction of the Shinto ultra-jet collector for pulverized coal is illustrated and there are detailed descriptions of dust cloud prevention, of measures used against possible sources of ignition, of oxygen supply and of other topics. Finally, explanations are given of matters that require careful and comprehensive study when selecting equipment.

  14. Digital filters

    Hamming, Richard W

    1997-01-01

    Digital signals occur in an increasing number of applications: in telephone communications; in radio, television, and stereo sound systems; and in spacecraft transmissions, to name just a few. This introductory text examines digital filtering, the processes of smoothing, predicting, differentiating, integrating, and separating signals, as well as the removal of noise from a signal. The processes bear particular relevance to computer applications, one of the focuses of this book.Readers will find Hamming's analysis accessible and engaging, in recognition of the fact that many people with the s

  15. Automated cloud tracking system for the Akatsuki Venus Climate Orbiter data

    Ogohara, Kazunori; Kouyama, Toru; Yamamoto, Hiroki; Sato, Naoki; Takagi, Masahiro; Imamura, Takeshi

    2012-02-01

    Japanese Venus Climate Orbiter, Akatsuki, is cruising to approach to Venus again although its first Venus orbital insertion (VOI) has been failed. At present, we focus on the next opportunity of VOI and the following scientific observations.We have constructed an automated cloud tracking system for processing data obtained by Akatsuki in the present study. In this system, correction of the pointing of the satellite is essentially important for improving accuracy of the cloud motion vectors derived using the cloud tracking. Attitude errors of the satellite are reduced by fitting an ellipse to limb of an imaged Venus disk. Next, longitude-latitude distributions of brightness (cloud patterns) are calculated to make it easy to derive the cloud motion vectors. The grid points are distributed at regular intervals in the longitude-latitude coordinate. After applying the solar zenith correction and a highpass filter to the derived longitude-latitude distributions of brightness, the cloud features are tracked using pairs of images. As a result, we obtain cloud motion vectors on longitude-latitude grid points equally spaced. These entire processes are pipelined and automated, and are applied to all data obtained by combinations of cameras and filters onboard Akatsuki. It is shown by several tests that the cloud motion vectors are determined with a sufficient accuracy. We expect that longitude-latitude data sets created by the automated cloud tracking system will contribute to the Venus meteorology.

  16. Particle tracking

    Mais, H.; Ripken, G.; Wrulich, A.; Schmidt, F.

    1986-02-01

    After a brief description of typical applications of particle tracking in storage rings and after a short discussion of some limitations and problems related with tracking we summarize some concepts and methods developed in the qualitative theory of dynamical systems. We show how these concepts can be applied to the proton ring HERA. (orig.)

  17. Timber tracking

    Düdder, Boris; Ross, Omry

    2017-01-01

    Managing and verifying forest products in a value chain is often reliant on easily manipulated document or digital tracking methods - Chain of Custody Systems. We aim to create a new means of tracking timber by developing a tamper proof digital system based on Blockchain technology. Blockchain...

  18. High Pass Filtering of Satellite Altimeter Data,

    1982-10-01

    bathymetry [7] and filtered data tracks (N = 3, X = 200 km) near the Clipperton Fracture Zone just East of the Christmas Island Ridge. Along the multiple...We also notice a negative signature associated with the Clipperton Fracture Zone and extending over all the tracks. It may indicate a trough covered...in Mid-Pacific Seamount Province..Mid-Iat tic and near the Western Clipperton Fracture Zone respectively. These charts arc to he overlaid by Figures

  19. Hamiltonian inclusive fitness: a fitter fitness concept.

    Costa, James T

    2013-01-01

    In 1963-1964 W. D. Hamilton introduced the concept of inclusive fitness, the only significant elaboration of Darwinian fitness since the nineteenth century. I discuss the origin of the modern fitness concept, providing context for Hamilton's discovery of inclusive fitness in relation to the puzzle of altruism. While fitness conceptually originates with Darwin, the term itself stems from Spencer and crystallized quantitatively in the early twentieth century. Hamiltonian inclusive fitness, with Price's reformulation, provided the solution to Darwin's 'special difficulty'-the evolution of caste polymorphism and sterility in social insects. Hamilton further explored the roles of inclusive fitness and reciprocation to tackle Darwin's other difficulty, the evolution of human altruism. The heuristically powerful inclusive fitness concept ramified over the past 50 years: the number and diversity of 'offspring ideas' that it has engendered render it a fitter fitness concept, one that Darwin would have appreciated.

  20. The relationship between physical fitness and clustered risk, and tracking of clustered risk from adolescence to young adulthood: eight years follow-up in the Danish Youth and Sport Study

    Andersen, Lars Bo; Hasselstrøm, Henriette; Hansen, Stig Eiberg

    2004-01-01

    was defined as being at risk, and if a subject had two or more risk factors, he/she was defined as a case (15-20 % of the subjects). Odds ratios (OR) for being a case was calculated between quartiles of fitness in both cross-sectional studies. The stability of combined risk was calculated as the OR between...... cases and non-cases at the first examination to be a case at the second examination. RESULTS: ORs for having two or more risk factors between quartiles of fitness were 3.1, 3.8 and 4.9 for quartiles two to four, respectively. At the second examination, OR were 0.7, 3.5 and 4.9, respectively....... The probability for "a case" at the first examination to be "a case" at the second was 6.0. CONCLUSIONS: The relationship between an exposure like physical fitness and CVD risk factors is much stronger when clustering of risk factors are analysed compared to the relationship to single risk factors. The stability...

  1. Learning Rotation for Kernel Correlation Filter

    Hamdi, Abdullah

    2017-08-11

    Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks. However it suffers from problems that affect its performance like occlusion, rotation and scale change. This paper tries to tackle the problem of rotation by reformulating the optimization problem for learning the correlation filter. This modification (RKCF) includes learning rotation filter that utilizes circulant structure of HOG feature to guesstimate rotation from one frame to another and enhance the detection of KCF. Hence it gains boost in overall accuracy in many of OBT50 detest videos with minimal additional computation.

  2. Convergent Filter Bases

    Coghetto Roland

    2015-09-01

    Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.

  3. Why tracks

    Burchart, J.; Kral, J.

    1979-01-01

    A comparison is made of two methods of determining the age of rocks, ie., the krypton-argon method and the fission tracks method. The former method is more accurate but is dependent on the temperature and on the grain size of the investigated rocks (apatites, biotites, muscovites). As for the method of fission tracks, the determination is not dependent on grain size. This method allows dating and the determination of uranium concentration and distribution in rocks. (H.S.)

  4. Miniaturized dielectric waveguide filters

    Sandhu, MY; Hunter, IC

    2016-01-01

    Design techniques for a new class of integrated monolithic high-permittivity ceramic waveguide filters are presented. These filters enable a size reduction of 50% compared to air-filled transverse electromagnetic filters with the same unloaded Q-factor. Designs for Chebyshev and asymmetric generalised Chebyshev filter and a diplexer are presented with experimental results for an 1800 MHz Chebyshev filter and a 1700 MHz generalised Chebyshev filter showing excellent agreement with theory.

  5. Enhanced online convolutional neural networks for object tracking

    Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

    2018-04-01

    In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

  6. Manifold Regularized Correlation Object Tracking

    Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

    2017-01-01

    In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped fr...

  7. Selection vector filter framework

    Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.

    2003-10-01

    We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.

  8. AER image filtering

    Gómez-Rodríguez, F.; Linares-Barranco, A.; Paz, R.; Miró-Amarante, L.; Jiménez, G.; Civit, A.

    2007-05-01

    Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows real-time virtual massive connectivity among huge number of neurons located on different chips.[1] By exploiting high speed digital communication circuits (with nano-seconds timing), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Neurons generate "events" according to their activity levels. That is, more active neurons generate more events per unit time and access the interchip communication channel more frequently than neurons with low activity. In Neuromorphic system development, AER brings some advantages to develop real-time image processing system: (1) AER represents the information like time continuous stream not like a frame; (2) AER sends the most important information first (although this depends on the sender); (3) AER allows to process information as soon as it is received. When AER is used in artificial vision field, each pixel is considered like a neuron, so pixel's intensity is represented like a sequence of events; modifying the number and the frequency of these events, it is possible to make some image filtering. In this paper we present four image filters using AER: (a) Noise addition and suppression, (b) brightness modification, (c) single moving object tracking and (d) geometrical transformations (rotation, translation, reduction and magnification). For testing and debugging, we use USB-AER board developed by Robotic and Technology of Computers Applied to Rehabilitation (RTCAR) research group. This board is based on an FPGA, devoted to manage the AER functionality. This board also includes a micro-controlled for USB communication, 2 Mbytes RAM and 2 AER ports (one for input and one for output).

  9. The ATLAS Track Extrapolation Package

    Salzburger, A

    2007-01-01

    The extrapolation of track parameters and their associated covariances to destination surfaces of different types is a very frequent process in the event reconstruction of high energy physics experiments. This is amongst other reasons due to the fact that most track and vertex fitting techniques are based on the first and second momentum of the underlying probability density distribution. The correct stochastic or deterministic treatment of interactions with the traversed detector material is hereby crucial for high quality track reconstruction throughout the entire momentum range of final state particles that are produced in high energy physics collision experiments. This document presents the main concepts, the algorithms and the implementation of the newly developed, powerful ATLAS track extrapolation engine. It also emphasises on validation procedures, timing measurements and the integration into the ATLAS offline reconstruction software.

  10. ALICE HLT high speed tracking on GPU

    Gorbunov, Sergey; Aamodt, Kenneth; Alt, Torsten; Appelshauser, Harald; Arend, Andreas; Bach, Matthias; Becker, Bruce; Bottger, Stefan; Breitner, Timo; Busching, Henner; Chattopadhyay, Sukalyan; Cleymans, Jean; Cicalo, Corrado; Das, Indranil; Djuvsland, Oystein; Engel, Heiko; Erdal, Hege Austrheim; Fearick, Roger; Haaland, Oystein Senneset; Hille, Per Thomas; Kalcher, Sebastian; Kanaki, Kalliopi; Kebschull, Udo Wolfgang; Kisel, Ivan; Kretz, Matthias; Lara, Camillo; Lindal, Sven; Lindenstruth, Volker; Masoodi, Arshad Ahmad; Ovrebekk, Gaute; Panse, Ralf; Peschek, Jorg; Ploskon, Mateusz; Pocheptsov, Timur; Ram, Dinesh; Rascanu, Theodor; Richter, Matthias; Rohrich, Dieter; Ronchetti, Federico; Skaali, Bernhard; Smorholm, Olav; Stokkevag, Camilla; Steinbeck, Timm Morten; Szostak, Artur; Thader, Jochen; Tveter, Trine; Ullaland, Kjetil; Vilakazi, Zeblon; Weis, Robert; Yin, Zhong-Bao; Zelnicek, Pierre

    2011-01-01

    The on-line event reconstruction in ALICE is performed by the High Level Trigger, which should process up to 2000 events per second in proton-proton collisions and up to 300 central events per second in heavy-ion collisions, corresponding to an inp ut data stream of 30 GB/s. In order to fulfill the time requirements, a fast on-line tracker has been developed. The algorithm combines a Cellular Automaton method being used for a fast pattern recognition and the Kalman Filter method for fitting of found trajectories and for the final track selection. The tracker was adapted to run on Graphics Processing Units (GPU) using the NVIDIA Compute Unified Device Architecture (CUDA) framework. The implementation of the algorithm had to be adjusted at many points to allow for an efficient usage of the graphics cards. In particular, achieving a good overall workload for many processor cores, efficient transfer to and from the GPU, as well as optimized utilization of the different memories the GPU offers turned out to be cri...

  11. Fitness Tracker for Weight Lifting Style Workouts

    Wihl, B. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-02-01

    This document proposes an early, high level design for a fitness tracking system which can automatically log weight lifting style workouts. The system will provide an easy to use interface both physically through the use of several wireless wristband style motion trackers worn on the limbs, and graphically through a smartphone application. Exercise classification will be accomplished by calibration of the user’s specific motions. The system will accurately track a user’s workout, miscounting no more than one repetition in every 20, have sufficient battery life to last several hours, work with existing smartphones and have a cost similar to those of current fitness tracking devices. This document presents the mission background, current state-of-theart, stakeholders and their expectations, the proposed system’s context and concepts, implementation concepts, system requirements, first sublevel function decomposition, possible risks for the system, and a reflection on the design process.

  12. Recirculating electric air filter

    Bergman, W.

    1985-01-09

    An electric air filter cartridge has a cylindrical inner high voltage electrode, a layer of filter material, and an outer ground electrode formed of a plurality of segments moveably connected together. The outer electrode can be easily opened to remove or insert filter material. Air flows through the two electrodes and the filter material and is exhausted from the center of the inner electrode.

  13. Online Tracking

    ... can disable blocking on those sites. Tagged with: computer security , cookies , Do Not Track , personal information , privacy June ... email Looking for business guidance on privacy and ... The Federal Trade Commission (FTC) is the nation’s consumer protection agency. The FTC works to prevent fraudulent, deceptive ...

  14. Physical Fitness Assessment.

    Valdes, Alice

    This document presents baseline data on physical fitness that provides an outline for assessing the physical fitness of students. It consists of 4 tasks and a 13-item questionnaire on fitness-related behaviors. The fitness test evaluates cardiorespiratory endurance by a steady state jog; muscular strength and endurance with a two-minute bent-knee…

  15. Unge, sundhed og fitness

    Jensen, Jens-Ole

    2003-01-01

    Artiklen redegør for udbredelsen af fitness blandt unge og diskuterer, hvor det er blevet så populært at dyrke fitness.......Artiklen redegør for udbredelsen af fitness blandt unge og diskuterer, hvor det er blevet så populært at dyrke fitness....

  16. Where does fitness fit in theories of perception?

    Anderson, Barton L

    2015-12-01

    Interface theory asserts that neither our perceptual experience of the world nor the scientific constructs used to describe the world are veridical. The primary argument used to uphold this claim is that (1) evolution is driven by a process of natural selection that favors fitness over veridicality, and (2) payoffs do not vary monotonically with truth. I argue that both the arguments used to bolster this claim and the conclusions derived from it are flawed. Interface theory assumes that perception evolved to directly track fitness but fails to consider the role of adaptation on ontogenetic time scales. I argue that the ubiquity of nonmonotonic payoff functions requires that (1) perception tracks "truth" for species that adapt on ontogenetic time scales and (2) that perception should be distinct from utility. These conditions are required to pursue an adaptive strategy to mitigate homeostatic imbalances. I also discuss issues with the interface metaphor, the particular formulation of veridicality that is considered, and the relationship of interface theory to the history of ideas on these topics.

  17. Reconstructing events, from electronic signals to tracks

    CERN. Geneva

    2015-01-01

    Reconstructing tracks in the events taken by LHC experiments is one of the most challenging and computationally expensive software tasks to be carried out in the data processing chain. A typical LHC event is composed of multiple p-p interactions, each leaving signals from many charged particles in the detector and jus building up an environment of unprecedented complexity. In the lecture I will give an overview of event reconstruction in a typical High Energy Physics experiment. After an introduction to particle tracking detectors I will discuss the concepts and techniques required to master the tracking challenge at the LHC. I will explain how track propagation in a realistic detector works, present different techniques for track fitting and track finding. At the end we will see how all of those techniques play together in the ATLAS track reconstruction application.

  18. Passive Power Filters

    Künzi, R.

    2015-06-15

    Power converters require passive low-pass filters which are capable of reducing voltage ripples effectively. In contrast to signal filters, the components of power filters must carry large currents or withstand large voltages, respectively. In this paper, three different suitable filter struc tures for d.c./d.c. power converters with inductive load are introduced. The formulas needed to calculate the filter components are derived step by step and practical examples are given. The behaviour of the three discussed filters is compared by means of the examples. P ractical aspects for the realization of power filters are also discussed.

  19. Effect of cross-correlation on track-to-track fusion

    Saha, Rajat K.

    1994-07-01

    Since the advent of target tracking systems employing a diverse mixture of sensors, there has been increasing recognition by air defense system planners and other military system analysts of the need to integrate these tracks so that a clear air picture can be obtained in a command center. A popular methodology to achieve this goal is to perform track-to-track fusion, which performs track-to-track association as well as kinematic state vector fusion. This paper seeks to answer analytically the extent of improvement achievable by means of kinetic state vector fusion when the tracks are obtained from dissimilar sensors (e.g., Radar/ESM/IRST/IFF). It is well known that evaluation of the performance of state vector fusion algorithms at steady state must take into account the effects of cross-correlation between eligible tracks introduced by the input noise which, unfortunately, is often neglected because of added computational complexity. In this paper, an expression for the steady-state cross-covariance matrix for a 2D state vector track-to-track fusion is obtained. This matrix is shown to be a function of the parameters of the Kalman filters associated with the candidate tracks being fused. Conditions for positive definiteness of the cross-covariance matrix have been derived and the effect of positive definiteness on performance of track-to-track fusion is also discussed.

  20. Filter replacement lifetime prediction

    Hamann, Hendrik F.; Klein, Levente I.; Manzer, Dennis G.; Marianno, Fernando J.

    2017-10-25

    Methods and systems for predicting a filter lifetime include building a filter effectiveness history based on contaminant sensor information associated with a filter; determining a rate of filter consumption with a processor based on the filter effectiveness history; and determining a remaining filter lifetime based on the determined rate of filter consumption. Methods and systems for increasing filter economy include measuring contaminants in an internal and an external environment; determining a cost of a corrosion rate increase if unfiltered external air intake is increased for cooling; determining a cost of increased air pressure to filter external air; and if the cost of filtering external air exceeds the cost of the corrosion rate increase, increasing an intake of unfiltered external air.

  1. The DOe Silicon Track Trigger

    Steinbrueck, Georg

    2003-01-01

    We describe a trigger preprocessor to be used by the DOe experiment for selecting events with tracks from the decay of long-lived particles. This Level 2 impact parameter trigger utilizes information from the Silicon Microstrip Tracker to reconstruct tracks with improved spatial and momentum resolutions compared to those obtained by the Level 1 tracking trigger. It is constructed of VME boards with much of the logic existing in programmable processors. A common motherboard provides the I/O infrastructure and three different daughter boards perform the tasks of identifying the roads from the tracking trigger data, finding the clusters in the roads in the silicon detector, and fitting tracks to the clusters. This approach provides flexibility for the design, testing and maintenance phases of the project. The track parameters are provided to the trigger framework in 25 μs. The effective impact parameter resolution for high-momentum tracks is 35 μm, dominated by the size of the Tevatron beam

  2. Optimization of filter loading

    Turney, J.H.; Gardiner, D.E.; Sacramento Municipal Utility District, Herald, CA)

    1985-01-01

    The introduction of 10 CFR Part 61 has created potential difficulties in the disposal of spent cartridge filters. When this report was prepared, Rancho Seco had no method of packaging and disposing of class B or C filters. This work examined methods to minimize the total operating cost of cartridge filters while maintaining them below the class A limit. It was found that by encapsulating filters in cement the filter operating costs could be minimized

  3. Limiting enclosures - Filtering fittings for air or gas

    1981-05-01

    The aim of this experimental standard is the determination of the general characteristics of air or gas filtration equipment for limiting enclosures in application of the standard M 62-202. Application are made on enclosures or enclosure lines used for works on radioactive materials, toxic or dangerous chemicals, materials sensitive to atmospheric components or requiring a steril atmosphere [fr

  4. Low-rank sparse learning for robust visual tracking

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

    2012-01-01

    In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm

  5. An inventory of the South African fitness industry

    Among many of the key players within the South African fitness industry, there ..... Tennis courts. Indoor track .... to track the influence of this initiative on the growth of the industry, both in ... members have NQF-aligned qualifications in their field.

  6. The intractable cigarette ‘filter problem’

    2011-01-01

    Background When lung cancer fears emerged in the 1950s, cigarette companies initiated a shift in cigarette design from unfiltered to filtered cigarettes. Both the ineffectiveness of cigarette filters and the tobacco industry's misleading marketing of the benefits of filtered cigarettes have been well documented. However, during the 1950s and 1960s, American cigarette companies spent millions of dollars to solve what the industry identified as the ‘filter problem’. These extensive filter research and development efforts suggest a phase of genuine optimism among cigarette designers that cigarette filters could be engineered to mitigate the health hazards of smoking. Objective This paper explores the early history of cigarette filter research and development in order to elucidate why and when seemingly sincere filter engineering efforts devolved into manipulations in cigarette design to sustain cigarette marketing and mitigate consumers' concerns about the health consequences of smoking. Methods Relevant word and phrase searches were conducted in the Legacy Tobacco Documents Library online database, Google Patents, and media and medical databases including ProQuest, JSTOR, Medline and PubMed. Results 13 tobacco industry documents were identified that track prominent developments involved in what the industry referred to as the ‘filter problem’. These reveal a period of intense focus on the ‘filter problem’ that persisted from the mid-1950s to the mid-1960s, featuring collaborations between cigarette producers and large American chemical and textile companies to develop effective filters. In addition, the documents reveal how cigarette filter researchers' growing scientific knowledge of smoke chemistry led to increasing recognition that filters were unlikely to offer significant health protection. One of the primary concerns of cigarette producers was to design cigarette filters that could be economically incorporated into the massive scale of cigarette

  7. Kalman Orbit Optimized Loop Tracking

    Young, Lawrence E.; Meehan, Thomas K.

    2011-01-01

    Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

  8. Laboratory for filter testing

    Paluch, W.

    1987-07-01

    Filters used for mine draining in brown coal surface mines are tested by the Mine Draining Department of Poltegor. Laboratory tests of new types of filters developed by Poltegor are analyzed. Two types of tests are used: tests of scale filter models and tests of experimental units of new filters. Design and operation of the test stands used for testing mechanical properties and hydraulic properties of filters for coal mines are described: dimensions, pressure fluctuations, hydraulic equipment. Examples of testing large-diameter filters for brown coal mines are discussed.

  9. Method of mounting filter elements and mounting therefor

    Karelin, J.; Neumann, G.M.

    1981-01-01

    A process for the insertion and exchange of the filter elements for suspended matter is performed from the clean-air-side. During the insertion of a filter element, a plastic tube (Which encircles the circumference of the filter element and which exceeds in its length the layer thickness of the filter element several times) is tightly connected in its middle section with the side walls, which side walls form a border around the filter element; and then the open end of the plastic tube, which faces the frame, is connected by way of a tight fit with a ring, which is actually known and which surrounds the orifice of the frame into which the filter element is inserted. The filter element is connected with the frame by means of tightening devices, and the outer free end of the tube is turned inside out and around the filter element for the purpose of unhindered air passage through the filter layer, that during the exchange of the contaminated filter element, the outer open end of the tube is heat sealed. The filter element is disconnected and removed from the frame by flipping down of the tightening devices, and the tube is heat sealed in the section between the filter element and the frame, and, that during the insertion of a new filter element, a new tube is attached by way of tight fitting to the ring of the frame , which tube is at its middle section tightly connected with the filter element, and which tube is attached to the ring of the frame in an actually known by overlapping of the heat-sealed tube rest. The tube rest is pulled onto the new tube and pulled off the ring, and the filter element is tightly connected with the frame by means of the tightening devices

  10. Evolution of the SOFIA tracking control system

    Fiebig, Norbert; Jakob, Holger; Pfüller, Enrico; Röser, Hans-Peter; Wiedemann, Manuel; Wolf, Jürgen

    2014-07-01

    The airborne observatory SOFIA (Stratospheric Observatory for Infrared Astronomy) is undergoing a modernization of its tracking system. This included new, highly sensitive tracking cameras, control computers, filter wheels and other equipment, as well as a major redesign of the control software. The experiences along the migration path from an aged 19" VMbus based control system to the application of modern industrial PCs, from VxWorks real-time operating system to embedded Linux and a state of the art software architecture are presented. Further, the concept is presented to operate the new camera also as a scientific instrument, in parallel to tracking.

  11. FITS: a function-fitting program

    Balestrini, S.J.; Chezem, C.G.

    1982-01-01

    FITS is an iterating computer program that adjusts the parameters of a function to fit a set of data points according to the least squares criterion and then lists and plots the results. The function can be programmed or chosen from a library that is provided. The library can be expanded to include up to 99 functions. A general plotting routine, contained in the program but useful in its own right, is described separately in an Appendix.

  12. NONLINEAR ESTIMATION METHODS FOR AUTONOMOUS TRACKED VEHICLE WITH SLIP

    ZHOU Bo; HAN Jianda

    2007-01-01

    In order to achieve precise, robust autonomous guidance and control of a tracked vehicle, a kinematic model with longitudinal and lateral slip is established. Four different nonlinear filters are used to estimate both state vector and time-varying parameter vector of the created model jointly. The first filter is the well-known extended Kalman filter. The second filter is an unscented version of the Kalman filter. The third one is a particle filter using the unscented Kalman filter to generate the importance proposal distribution. The last one is a novel and guaranteed filter that uses a linear set-membership estimator and can give an ellipsoid set in which the true state lies. The four different approaches have different complexities, behavior and advantages that are surveyed and compared.

  13. Contrast effects of a gadolinium filter

    Burgess, A.E.

    1981-01-01

    Several authors have suggested using heavy metal filters with K edges in the diagnostic energy range to reduce the width of the x-ray spectrum and hence reduce patient radiation exposure. This spectral narrowing also increases subject contrast and permits an increase in tube potential. Results of contrast measurements are presented for a 250 mu gadolinium filter. It was found that aluminum filter contrast could be matched by using 8 to 10 kVp higher potential with the gadolinium filter. Similar results were found for calcium tungstate and rare-earth screens. Measurements were also done to determine skin exposure and mAs ratios for both constant contrast and constant kVp technique conversion methods. A simple theory with one adjustable parameter gives a reasonable fit to the experimental results

  14. Family Activities for Fitness

    Grosse, Susan J.

    2009-01-01

    This article discusses how families can increase family togetherness and improve physical fitness. The author provides easy ways to implement family friendly activities for improving and maintaining physical health. These activities include: walking, backyard games, and fitness challenges.

  15. Sensory Pollution from Bag Filters, Carbon Filters and Combinations

    Bekö, Gabriel; Clausen, Geo; Weschler, Charles J.

    2008-01-01

    by an upstream pre-filter (changed monthly), an EU7 filter protected by an upstream activated carbon (AC) filter, and EU7 filters with an AC filter either downstream or both upstream and downstream. In addition, two types of stand-alone combination filters were evaluated: a bag-type fiberglass filter...... that contained AC and a synthetic fiber cartridge filter that contained AC. Air that had passed through used filters was most acceptable for those sets in which an AC filter was used downstream of the particle filter. Comparable air quality was achieved with the stand-alone bag filter that contained AC...

  16. HEPA Filter Vulnerability Assessment

    GUSTAVSON, R.D.

    2000-01-01

    This assessment of High Efficiency Particulate Air (HEPA) filter vulnerability was requested by the USDOE Office of River Protection (ORP) to satisfy a DOE-HQ directive to evaluate the effect of filter degradation on the facility authorization basis assumptions. Within the scope of this assessment are ventilation system HEPA filters that are classified as Safety-Class (SC) or Safety-Significant (SS) components that perform an accident mitigation function. The objective of the assessment is to verify whether HEPA filters that perform a safety function during an accident are likely to perform as intended to limit release of hazardous or radioactive materials, considering factors that could degrade the filters. Filter degradation factors considered include aging, wetting of filters, exposure to high temperature, exposure to corrosive or reactive chemicals, and exposure to radiation. Screening and evaluation criteria were developed by a site-wide group of HVAC engineers and HEPA filter experts from published empirical data. For River Protection Project (RPP) filters, the only degradation factor that exceeded the screening threshold was for filter aging. Subsequent evaluation of the effect of filter aging on the filter strength was conducted, and the results were compared with required performance to meet the conditions assumed in the RPP Authorization Basis (AB). It was found that the reduction in filter strength due to aging does not affect the filter performance requirements as specified in the AB. A portion of the HEPA filter vulnerability assessment is being conducted by the ORP and is not part of the scope of this study. The ORP is conducting an assessment of the existing policies and programs relating to maintenance, testing, and change-out of HEPA filters used for SC/SS service. This document presents the results of a HEPA filter vulnerability assessment conducted for the River protection project as requested by the DOE Office of River Protection

  17. Sparse adaptive filters for echo cancellation

    Paleologu, Constantin

    2011-01-01

    Adaptive filters with a large number of coefficients are usually involved in both network and acoustic echo cancellation. Consequently, it is important to improve the convergence rate and tracking of the conventional algorithms used for these applications. This can be achieved by exploiting the sparseness character of the echo paths. Identification of sparse impulse responses was addressed mainly in the last decade with the development of the so-called ``proportionate''-type algorithms. The goal of this book is to present the most important sparse adaptive filters developed for echo cancellati

  18. Computer code FIT

    Rohmann, D.; Koehler, T.

    1987-02-01

    This is a description of the computer code FIT, written in FORTRAN-77 for a PDP 11/34. FIT is an interactive program to decude position, width and intensity of lines of X-ray spectra (max. length of 4K channels). The lines (max. 30 lines per fit) may have Gauss- or Voigt-profile, as well as exponential tails. Spectrum and fit can be displayed on a Tektronix terminal. (orig.) [de

  19. Bias aware Kalman filters

    Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan

    2006-01-01

    This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....

  20. Simon-nitinol filter

    Simon, M.; Kim, D.; Porter, D.H.; Kleshinski, S.

    1989-01-01

    This paper discusses a filter that exploits the thermal shape-memory properties of the nitinol alloy to achieve an optimized filter shape and a fine-bore introducer. Experimental methods and materials are given and results are analyzed

  1. LHCb: The LHCb tracking concept and performance

    Rodrigues, E

    2009-01-01

    The LHCb tracking system is designed to reconstruct charged particle trajectories in the forward spectrometer, in view of high precision studies of CP-violating phenomena and searches for rare b-hadron decays at the LHC. The system is composed of four major subdetectors and a dedicated magnet, providing an excellent momentum resolution just above 0.4%. The tracking model is based on the innovative trajectories concept introduced by the BaBar collaboration to reconstruct and fit the tracks, and has been further developed and improved. It is now able to cope with realistic geometries and misalignments in a sophisticated, robust and detector-independent way. The LHCb tracking concept including the interplay of various complementary pattern recognition algorithms and the bi-directional Kalman fitter will be described. The current performance of the tracking, based on the latest simulations, will be presented. Recent results obtained with the first LHC beam tracks from injection tests will be discussed.

  2. An FPGA based track finder for the L1 trigger of the CMS experiment at the High Luminosity LHC

    Tomalin, Ian; Ball, Fionn Amhairghen; Balzer, Matthias Norbert; Boudoul, Gaelle; Brooke, James John; Caselle, Michele; Calligaris, Luigi; Cieri, Davide; Clement, Emyr John; Dutta, Suchandra; Hall, Geoffrey; Harder, Kristian; Hobson, Peter; Iles, Gregory Michiel; James, Thomas Owen; Manolopoulos, Konstantinos; Matsushita, Takashi; Morton, Alexander; Newbold, David; Paramesvaran, Sudarshan; Pesaresi, Mark Franco; Pozzobon, Nicola; Reid, Ivan; Rose, A. W; Sander, Oliver; Shepherd-Themistocleous, Claire; Shtipliyski, Antoni; Schuh, Thomas; Skinnari, Louise; Summers, Sioni Paris; Tapper, Alexander; Thea, Alessandro; Uchida, Kirika; Vichoudis, Paschalis; Viret, Sebastien; Weber, M; Aggleton, Robin Cameron

    2017-12-14

    A new tracking detector is under development for use by the CMS experiment at the High-Luminosity LHC (HL-LHC). A crucial requirement of this upgrade is to provide the ability to reconstruct all charged particle tracks with transverse momentum above 2-3 GeV within 4$\\mu$s so they can be used in the Level-1 trigger decision. A concept for an FPGA-based track finder using a fully time-multiplexed architecture is presented, where track candidates are reconstructed using a projective binning algorithm based on the Hough Transform, followed by a combinatorial Kalman Filter. A hardware demonstrator using MP7 processing boards has been assembled to prove the entire system functionality, from the output of the tracker readout boards to the reconstruction of tracks with fitted helix parameters. It successfully operates on one eighth of the tracker solid angle acceptance at a time, processing events taken at 40 MHz, each with up to 200 superimposed proton-proton interactions, whilst satisfying the latency requirement. ...

  3. MST Filterability Tests

    Poirier, M. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Burket, P. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Duignan, M. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2015-03-12

    The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). The low filter flux through the ARP has limited the rate at which radioactive liquid waste can be treated. Recent filter flux has averaged approximately 5 gallons per minute (gpm). Salt Batch 6 has had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. In addition, at the time the testing started, SRR was assessing the impact of replacing the 0.1 micron filter with a 0.5 micron filter. This report describes testing of MST filterability to investigate the impact of filter pore size and MST particle size on filter flux and testing of filter enhancers to attempt to increase filter flux. The authors constructed a laboratory-scale crossflow filter apparatus with two crossflow filters operating in parallel. One filter was a 0.1 micron Mott sintered SS filter and the other was a 0.5 micron Mott sintered SS filter. The authors also constructed a dead-end filtration apparatus to conduct screening tests with potential filter aids and body feeds, referred to as filter enhancers. The original baseline for ARP was 5.6 M sodium salt solution with a free hydroxide concentration of approximately 1.7 M.3 ARP has been operating with a sodium concentration of approximately 6.4 M and a free hydroxide concentration of approximately 2.5 M. SRNL conducted tests varying the concentration of sodium and free hydroxide to determine whether those changes had a significant effect on filter flux. The feed slurries for the MST filterability tests were composed of simple salts (NaOH, NaNO2, and NaNO3) and MST (0.2 – 4.8 g/L). The feed slurry for the filter enhancer tests contained simulated salt batch 6 supernate, MST, and filter enhancers.

  4. Use of astronomy filters in fluorescence microscopy.

    Piper, Jörg

    2012-02-01

    Monochrome astronomy filters are well suited for use as excitation or suppression filters in fluorescence microscopy. Because of their particular optical design, such filters can be combined with standard halogen light sources for excitation in many fluorescent probes. In this "low energy excitation," photobleaching (fading) or other irritations of native specimens are avoided. Photomicrographs can be taken from living motile fluorescent specimens also with a flash so that fluorescence images can be created free from indistinctness caused by movement. Special filter cubes or dichroic mirrors are not needed for our method. By use of suitable astronomy filters, fluorescence microscopy can be carried out with standard laboratory microscopes equipped with condensers for bright-field (BF) and dark-field (DF) illumination in transmitted light. In BF excitation, the background brightness can be modulated in tiny steps up to dark or black. Moreover, standard industry microscopes fitted with a vertical illuminator for examinations of opaque probes in DF or BF illumination based on incident light (wafer inspections, for instance) can also be used for excitation in epi-illumination when adequate astronomy filters are inserted as excitatory and suppression filters in the illuminating and imaging light path. In all variants, transmission bands can be modulated by transmission shift.

  5. Tracking Subpixel Targets with Critically Sampled Optical Sensors

    2012-09-01

    LEFT BLANK xii LIST OF ACRONYMS AND ABBREVIATIONS PSF point spread function SNR signal-to-noise ratio SLAM simultaneous localization and tracking EO... LIDAR light detection and ranging FOV field of view RMS root mean squared PF particle filter TBD track before detect MCMC monte carlo markov chain

  6. Robust visual tracking via structured multi-task sparse learning

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

    2012-01-01

    In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary

  7. Rank Detector Preprocessor for Glint Reduction in a Tracking Radar

    Guest, IW

    1993-04-01

    Full Text Available A rank detector is used to defect instantaneous received power fades in tracking radar. On detection of a fade, censorship of the angular position measurement is implemented in a Kalman tracking filter. It is shown that this technique can typically...

  8. Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

    Alam, Mohammad S.; Bhuiyan, Sharif M. A.

    2014-01-01

    In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

  9. Latent tracks in polymeric etched track detectors

    Yamauchi, Tomoya

    2013-01-01

    Track registration properties in polymeric track detectors, including Poly(allyl diglycol carbonate), Bispenol A polycarbonate, Poly(ethylen terephtarate), and Polyimide, have been investigated by means of Fourie transform Infararede FT-IR spectrometry. Chemical criterion on the track formation threshold has been proposes, in stead of the conventional physical track registration models. (author)

  10. Tracking telecommuting

    Stastny, P.

    2007-03-15

    Many employees are now choosing to work from home using laptops and telephones. Employers in the oil and gas industry are now reaping a number of benefits from their telecommuting employees, including increased productivity; higher levels of employee satisfaction, and less absenteeism. Providing a telecommunication option can prove to be advantageous for employers wishing to hire or retain employees. Telecommuting may also help to reduce greenhouse gas (GHG) emissions. This article provided details of Teletrips Inc., a company that aids in the production of corporate social responsibility reports. Teletrips provides reports that document employee savings in time, vehicle depreciation maintenance, and gasoline costs. Teletrips currently tracks 12 companies in Calgary, and plans to grow through the development of key technology partnerships. The company is also working with the federal government to provide their clients with emission trading credits, and has forged a memorandum of understanding with the British Columbia government for tracking emissions. Calgary now openly supports telecommuting and is encouraging businesses in the city to adopt telecommuting on a larger scale. It was concluded that the expanding needs for road infrastructure and the energy used by cars to move workers in and out of the city are a massive burden to the city's tax base. 1 fig.

  11. INNER TRACKING

    P. Sharp

    The CMS Inner Tracking Detector continues to make good progress. The Objective for 2006 was to complete all of the CMS Tracker sub-detectors and to start the integration of the sub-detectors into the Tracker Support Tube (TST). The Objective for 2007 is to deliver to CMS a completed, installed, commissioned and calibrated Tracking System (Silicon Strip and Pixels) aligned to < 100µ in April 2008 ready for the first physics collisions at LHC. In November 2006 all of the sub-detectors had been delivered to the Tracker Integration facility (TIF) at CERN and the tests and QA procedures to be carried out on each sub-detector before integration had been established. In December 2006, TIB/TID+ was integrated into TOB+, TIB/TID- was being prepared for integration, and TEC+ was undergoing tests at the final tracker operating temperature (-100 C) in the Lyon cold room. In February 2007, TIB/TID- has been integrated into TOB-, and the installation of the pixel support tube and the services for TI...

  12. Development and validation of a Kalman filter-based model for vehicle slip angle estimation

    Gadola, M.; Chindamo, D.; Romano, M.; Padula, F.

    2014-01-01

    It is well known that vehicle slip angle is one of the most difficult parameters to measure on a vehicle during testing or racing activities. Moreover, the appropriate sensor is very expensive and it is often difficult to fit to a car, especially on race cars. We propose here a strategy to eliminate the need for this sensor by using a mathematical tool which gives a good estimation of the vehicle slip angle. A single-track car model, coupled with an extended Kalman filter, was used in order to achieve the result. Moreover, a tuning procedure is proposed that takes into consideration both nonlinear and saturation characteristics typical of vehicle lateral dynamics. The effectiveness of the proposed algorithm has been proven by both simulation results and real-world data.

  13. High Degree Cubature Federated Filter for Multisensor Information Fusion with Correlated Noises

    Lijun Wang

    2016-01-01

    Full Text Available This paper proposes an improved high degree cubature federated filter for the nonlinear fusion system with cross-correlation between process and measurement noises at the same time using the fifth-degree cubature rule and the decorrelated principle in its local filters. The master filter of the federated filter adopts the no-reset mode to fuse local estimates of local filters to generate a global estimate according to the scalar weighted rule. The air-traffic maneuvering target tracking simulations are performed between the proposed filter and the fifth-degree cubature federated filter. Simulations results demonstrate that the proposed filter not only can achieve almost the same accuracy as the fifth-degree cubature federated filter with independent white noises, but also has superior performance to the fifth-degree cubature federated filter while the noises are cross-correlated at the same time.

  14. Multiple hypothesis tracking for the cyber domain

    Schwoegler, Stefan; Blackman, Sam; Holsopple, Jared; Hirsch, Michael J.

    2011-09-01

    This paper discusses how methods used for conventional multiple hypothesis tracking (MHT) can be extended to domain-agnostic tracking of entities from non-kinematic constraints such as those imposed by cyber attacks in a potentially dense false alarm background. MHT is widely recognized as the premier method to avoid corrupting tracks with spurious data in the kinematic domain but it has not been extensively applied to other problem domains. The traditional approach is to tightly couple track maintenance (prediction, gating, filtering, probabilistic pruning, and target confirmation) with hypothesis management (clustering, incompatibility maintenance, hypothesis formation, and Nassociation pruning). However, by separating the domain specific track maintenance portion from the domain agnostic hypothesis management piece, we can begin to apply the wealth of knowledge gained from ground and air tracking solutions to the cyber (and other) domains. These realizations led to the creation of Raytheon's Multiple Hypothesis Extensible Tracking Architecture (MHETA). In this paper, we showcase MHETA for the cyber domain, plugging in a well established method, CUBRC's INFormation Engine for Real-time Decision making, (INFERD), for the association portion of the MHT. The result is a CyberMHT. We demonstrate the power of MHETA-INFERD using simulated data. Using metrics from both the tracking and cyber domains, we show that while no tracker is perfect, by applying MHETA-INFERD, advanced nonkinematic tracks can be captured in an automated way, perform better than non-MHT approaches, and decrease analyst response time to cyber threats.

  15. A comparison of wearable fitness devices.

    Kaewkannate, Kanitthika; Kim, Soochan

    2016-05-24

    Wearable trackers can help motivate you during workouts and provide information about your daily routine or fitness in combination with your smartphone without requiring potentially disruptive manual calculations or records. This paper summarizes and compares wearable fitness devices, also called "fitness trackers" or "activity trackers." These devices are becoming increasingly popular in personal healthcare, motivating people to exercise more throughout the day without the need for lifestyle changes. The various choices in the market for wearable devices are also increasing, with customers searching for products that best suit their personal needs. Further, using a wearable device or fitness tracker can help people reach a fitness goal or finish line. Generally, companies display advertising for these kinds of products and depict them as beneficial, user friendly, and accurate. However, there are no objective research results to prove the veracity of their words. This research features subjective and objective experimental results, which reveal that some devices perform better than others. The four most popular wristband style wearable devices currently on the market (Withings Pulse, Misfit Shine, Jawbone Up24, and Fitbit Flex) are selected and compared. The accuracy of fitness tracking is one of the key components for fitness tracking, and some devices perform better than others. This research shows subjective and objective experimental results that are used to compare the accuracy of four wearable devices in conjunction with user friendliness and satisfaction of 7 real users. In addition, this research matches the opinions between reviewers on an Internet site and those of subjects when using the device. Withings Pulse is the most friendly and satisfactory from the users' viewpoint. It is the most accurate and repeatable for step and distance tracking, which is the most important measurement of fitness tracking, followed by Fitbit Flex, Jawbone Up24, and Misfit

  16. A comparison of wearable fitness devices

    Kanitthika Kaewkannate

    2016-05-01

    Full Text Available Abstract Background Wearable trackers can help motivate you during workouts and provide information about your daily routine or fitness in combination with your smartphone without requiring potentially disruptive manual calculations or records. This paper summarizes and compares wearable fitness devices, also called “fitness trackers” or “activity trackers.” These devices are becoming increasingly popular in personal healthcare, motivating people to exercise more throughout the day without the need for lifestyle changes. The various choices in the market for wearable devices are also increasing, with customers searching for products that best suit their personal needs. Further, using a wearable device or fitness tracker can help people reach a fitness goal or finish line. Generally, companies display advertising for these kinds of products and depict them as beneficial, user friendly, and accurate. However, there are no objective research results to prove the veracity of their words. This research features subjective and objective experimental results, which reveal that some devices perform better than others. Methods The four most popular wristband style wearable devices currently on the market (Withings Pulse, Misfit Shine, Jawbone Up24, and Fitbit Flex are selected and compared. The accuracy of fitness tracking is one of the key components for fitness tracking, and some devices perform better than others. This research shows subjective and objective experimental results that are used to compare the accuracy of four wearable devices in conjunction with user friendliness and satisfaction of 7 real users. In addition, this research matches the opinions between reviewers on an Internet site and those of subjects when using the device. Results Withings Pulse is the most friendly and satisfactory from the users’ viewpoint. It is the most accurate and repeatable for step and distance tracking, which is the most important measurement of

  17. Rotationally invariant correlation filtering

    Schils, G.F.; Sweeney, D.W.

    1985-01-01

    A method is presented for analyzing and designing optical correlation filters that have tailored rotational invariance properties. The concept of a correlation of an image with a rotation of itself is introduced. A unified theory of rotation-invariant filtering is then formulated. The unified approach describes matched filters (with no rotation invariance) and circular-harmonic filters (with full rotation invariance) as special cases. The continuum of intermediate cases is described in terms of a cyclic convolution operation over angle. The angular filtering approach allows an exact choice for the continuous trade-off between loss of the correlation energy (or specificity regarding the image) and the amount of rotational invariance desired

  18. FITS: a function-fitting program

    Balestrini, S.J.; Chezem, C.G.

    1982-08-01

    FITS is an iterating computer program that adjusts the parameters of a function to fit a set of data points according to the least squares criterion and then lists and plots the results. The function can be programmed or chosen from a library that is provided. The library can be expanded to include up to 99 functions. A general plotting routine, contained in the program but useful in its own right, is described separately in Appendix A. An example problem file and its solution is given in Appendix B.

  19. A Synthetic Algorithm for Tracking a Moving Object in a Multiple-Dynamic Obstacles Environment Based on Kinematically Planar Redundant Manipulators

    Hongzhe Jin

    2017-01-01

    Full Text Available This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.

  20. Retina-Inspired Filter.

    Doutsi, Effrosyni; Fillatre, Lionel; Antonini, Marc; Gaulmin, Julien

    2018-07-01

    This paper introduces a novel filter, which is inspired by the human retina. The human retina consists of three different layers: the Outer Plexiform Layer (OPL), the inner plexiform layer, and the ganglionic layer. Our inspiration is the linear transform which takes place in the OPL and has been mathematically described by the neuroscientific model "virtual retina." This model is the cornerstone to derive the non-separable spatio-temporal OPL retina-inspired filter, briefly renamed retina-inspired filter, studied in this paper. This filter is connected to the dynamic behavior of the retina, which enables the retina to increase the sharpness of the visual stimulus during filtering before its transmission to the brain. We establish that this retina-inspired transform forms a group of spatio-temporal Weighted Difference of Gaussian (WDoG) filters when it is applied to a still image visible for a given time. We analyze the spatial frequency bandwidth of the retina-inspired filter with respect to time. It is shown that the WDoG spectrum varies from a lowpass filter to a bandpass filter. Therefore, while time increases, the retina-inspired filter enables to extract different kinds of information from the input image. Finally, we discuss the benefits of using the retina-inspired filter in image processing applications such as edge detection and compression.

  1. A tool for filtering information in complex systems

    Tumminello, M.; Aste, T.; Di Matteo, T.; Mantegna, R. N.

    2005-07-01

    We introduce a technique to filter out complex data sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation-based graphs, giving filtered graphs that preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0), triangular loops and four-element cliques are formed. The application of this filtering procedure to 100 stocks in the U.S. equity markets shows that such loops and cliques have important and significant relationships with the market structure and properties. This paper was submitted directly (Track II) to the PNAS office.Abbreviations: MST, minimum spanning tree; PMFG, Planar Maximally Filtered Graph; r-clique, clique of r elements.

  2. Study of different filters

    Cochinal, R.; Rouby, R.

    1959-01-01

    This note first contains a terminology related to filters and to their operation, and then proposes an overview of general characteristics of filters such as load loss with respect to gas rate, efficiency, and clogging with respect to filter pollution. It also indicates standard aerosols which are generally used, how they are dosed, and how efficiency is determined with a standard aerosol. Then, after a presentation of the filtration principle, this note reports the study of several filters: glass wool, filter papers provided by different companies, Teflon foam, English filters, Teflon wool, sintered Teflonite, quartz wool, polyvinyl chloride foam, synthetic filter, sintered bronze. The third part reports the study of some aerosol and dust separators

  3. Changing ventilation filters

    Hackney, S.

    1980-01-01

    A filter changing unit has a door which interlocks with the door of a filter chamber so as to prevent contamination of the outer surfaces of the doors by radioactive material collected on the filter element and a movable support which enables a filter chamber thereonto to be stored within the unit in such a way that the doors of the unit and the filter chamber can be replaced. The door pivots and interlocks with another door by means of a bolt, a seal around the periphery lip of the first door engages the periphery of the second door to seal the gap. A support pivots into a lower filter element storage position. Inspection windows and glove ports are provided. The unit is releasably connected to the filter chamber by bolts engaging in a flange provided around an opening. (author)

  4. Balanced microwave filters

    Hong, Jiasheng; Medina, Francisco; Martiacuten, Ferran

    2018-01-01

    This book presents and discusses strategies for the design and implementation of common-mode suppressed balanced microwave filters, including, narrowband, wideband, and ultra-wideband filters This book examines differential-mode, or balanced, microwave filters by discussing several implementations of practical realizations of these passive components. Topics covered include selective mode suppression, designs based on distributed and semi-lumped approaches, multilayer technologies, defect ground structures, coupled resonators, metamaterials, interference techniques, and substrate integrated waveguides, among others. Divided into five parts, Balanced Microwave Filters begins with an introduction that presents the fundamentals of balanced lines, circuits, and networks. Part 2 covers balanced transmission lines with common-mode noise suppression, including several types of common-mode filters and the application of such filters to enhance common-mode suppression in balanced bandpass filters. Next, Part 3 exa...

  5. Tracking Porters

    Bruun, Maja Hojer; Krause-Jensen, Jakob; Saltofte, Margit

    2015-01-01

    . In this chapter, we argue that although anthropology has its specific methodology – including a myriad of ethnographic data-gathering tools, techniques, analytical approaches and theories – it must first and foremost be understood as a craft. Anthropology as craft requires a specific ‘anthropological sensibility......’ that differs from the standardized procedures of normal science. To establish our points we use an example of problem-based project work conducted by a group of Techno-Anthropology students at Aalborg University, we focus on key aspects of this craft and how the students began to learn it: For two weeks...... the students followed the work of a group of porters. Drawing on anthropological concepts and research strategies the students gained crucial insights about the potential effects of using tracking technologies in the hospital....

  6. Fibre tracking

    Gaillard, J.M.

    1994-03-01

    A large-size scintillating plastic fibre tracking detector was built as part of the upgrade of the UA2 central detector at the SPS proton-antiproton collider. The cylindrical fibre detector of average radius of 40 cm consisted of 60000 plastic fibres with an active length of 2.1 m. One of the main motivations was to improve the electron identification. The fibre ends were bunched to be coupled to read-out systems of image intensifier plus CCD, 32 in total. The quality and the reliability of the UA2 fibre detector performance exceeded expectations throughout its years of operation. A few examples of the use of image intensifiers and of scintillating fibres in biological instrumentation are described. (R.P.) 11 refs., 15 figs., 2 tabs

  7. Event-triggered cooperative target tracking in wireless sensor networks

    Lu Kelin

    2016-10-01

    Full Text Available Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measurements. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership measurements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.

  8. Whole Protein Native Fitness Potentials

    Faraggi, Eshel; Kloczkowski, Andrzej

    2013-03-01

    Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

  9. Getting CSR communication fit

    Schmeltz, Line

    2017-01-01

    Companies experience increasing legal and societal pressure to communicate about their corporate social responsibility (CSR) engagements from a number of different publics. One very important group is that of young consumers who are predicted to be the most important and influential consumer group...... in the near future. From a value- theoretical base, this article empirically explores the role and applicability of ‘fit’ in strategic CSR communication targeted at young consumers. Point of departure is taken in the well-known strategic fit (a logical link between a company’s CSR commitment and its core...... values) and is further developed by introducing two additional fits, the CSR- Consumer fit and the CSR-Consumer-Company fit (Triple Fit). Through a sequential design, the three fits are empirically tested and their potential for meeting young consumers’ expectations for corporate CSR messaging...

  10. Fragment Impact Toolkit (FIT)

    Shevitz, Daniel Wolf [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Key, Brian P. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Garcia, Daniel B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-05

    The Fragment Impact Toolkit (FIT) is a software package used for probabilistic consequence evaluation of fragmenting sources. The typical use case for FIT is to simulate an exploding shell and evaluate the consequence on nearby objects. FIT is written in the programming language Python and is designed as a collection of interacting software modules. Each module has a function that interacts with the other modules to produce desired results.

  11. Adaptive Colour Feature Identification in Image for Object Tracking

    Feng Su

    2012-01-01

    Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

  12. Pose Tracking Algorithm of an Endoscopic Surgery Robot Wrist

    Wang, L; Yin, H L; Meng, Q

    2006-01-01

    In recent two decades, more and more research on the endoscopic surgery has been carried out [2]. Most of the work focuses on the development of the robot in the field of robotics and the navigation of the surgery tools based on computer graphics. But the tracking and locating of the EndoWrist is also a very important aspect. This paper deals with the the tracking algorithm of the EndoWrist's pose (position and orientation). The linear tracking of the position is handled by the Kalman Filter. The quaternion-based nonlinear orientation tracking is implemented with the Extended Kalman Filter. The most innovative point of this paper is the parameterization of the motion model of the Extended Kalman Filter

  13. Pose Tracking Algorithm of an Endoscopic Surgery Robot Wrist

    Wang, L [Chinese-German Institute of Automatic Control Engineering, Tongji University (China); Yin, H L [Chinese-German Institute of Automatic Control Engineering, Tongji University (China); Meng, Q [Shanghai University of Electric Power (China)

    2006-10-15

    In recent two decades, more and more research on the endoscopic surgery has been carried out [2]. Most of the work focuses on the development of the robot in the field of robotics and the navigation of the surgery tools based on computer graphics. But the tracking and locating of the EndoWrist is also a very important aspect. This paper deals with the the tracking algorithm of the EndoWrist's pose (position and orientation). The linear tracking of the position is handled by the Kalman Filter. The quaternion-based nonlinear orientation tracking is implemented with the Extended Kalman Filter. The most innovative point of this paper is the parameterization of the motion model of the Extended Kalman Filter.

  14. Contrast Gain Control Model Fits Masking Data

    Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

  15. Filter material charging apparatus for filter assembly for radioactive contaminants

    Goldsmith, J.M.; O'Nan, A. Jr.

    1977-01-01

    A filter charging apparatus for a filter assembly is described. The filter assembly includes a housing with at least one filter bed therein and the filter charging apparatus for adding filter material to the filter assembly includes a tank with an opening therein, the tank opening being disposed in flow communication with opposed first and second conduit means, the first conduit means being in flow communication with the filter assembly housing and the second conduit means being in flow communication with a blower means. Upon activation of the blower means, the blower means pneumatically conveys the filter material from the tank to the filter housing

  16. Multi-template Scale-Adaptive Kernelized Correlation Filters

    Bibi, Adel Aamer

    2015-12-07

    This paper identifies the major drawbacks of a very computationally efficient and state-of-the-art-tracker known as the Kernelized Correlation Filter (KCF) tracker. These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear combination of taps from the previous frame). In our approach, we update the scale of the tracker by maximizing over the posterior distribution of a grid of scales. As for the filter update, we prove and show that it is possible to use all previous training examples to update the filter taps very efficiently using fixed-point optimization. We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015.

  17. Multi-template Scale-Adaptive Kernelized Correlation Filters

    Bibi, Adel Aamer; Ghanem, Bernard

    2015-01-01

    This paper identifies the major drawbacks of a very computationally efficient and state-of-the-art-tracker known as the Kernelized Correlation Filter (KCF) tracker. These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear combination of taps from the previous frame). In our approach, we update the scale of the tracker by maximizing over the posterior distribution of a grid of scales. As for the filter update, we prove and show that it is possible to use all previous training examples to update the filter taps very efficiently using fixed-point optimization. We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015.

  18. A New Track Reconstruction Algorithm suitable for Parallel Processing based on Hit Triplets and Broken Lines

    Schöning André

    2016-01-01

    Full Text Available Track reconstruction in high track multiplicity environments at current and future high rate particle physics experiments is a big challenge and very time consuming. The search for track seeds and the fitting of track candidates are usually the most time consuming steps in the track reconstruction. Here, a new and fast track reconstruction method based on hit triplets is proposed which exploits a three-dimensional fit model including multiple scattering and hit uncertainties from the very start, including the search for track seeds. The hit triplet based reconstruction method assumes a homogeneous magnetic field which allows to give an analytical solutions for the triplet fit result. This method is highly parallelizable, needs fewer operations than other standard track reconstruction methods and is therefore ideal for the implementation on parallel computing architectures. The proposed track reconstruction algorithm has been studied in the context of the Mu3e-experiment and a typical LHC experiment.

  19. Occlusion Handling in Videos Object Tracking: A Survey

    Lee, B Y; Liew, L H; Cheah, W S; Wang, Y C

    2014-01-01

    Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

  20. Occlusion Handling in Videos Object Tracking: A Survey

    Lee, B. Y.; Liew, L. H.; Cheah, W. S.; Wang, Y. C.

    2014-02-01

    Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

  1. Robust Visual Tracking Using the Bidirectional Scale Estimation

    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.

  2. Volcano monitoring using the Global Positioning System: Filtering strategies

    Larson, K.M.; Cervelli, Peter; Lisowski, M.; Miklius, Asta; Segall, P.; Owen, S.

    2001-01-01

    Permanent Global Positioning System (GPS) networks are routinely used for producing improved orbits and monitoring secular tectonic deformation. For these applications, data are transferred to an analysis center each day and routinely processed in 24-hour segments. To use GPS for monitoring volcanic events, which may last only a few hours, real-time or near real-time data processing and subdaily position estimates are valuable. Strategies have been researched for obtaining station coordinates every 15 min using a Kalman filter; these strategies have been tested on data collected by a GPS network on Kilauea Volcano. Data from this network are tracked continuously, recorded every 30 s, and telemetered hourly to the Hawaiian Volcano Observatory. A white noise model is heavily impacted by data outages and poor satellite geometry, but a properly constrained random walk model fits the data well. Using a borehole tiltmeter at Kilauea's summit as ground-truth, solutions using different random walk constraints were compared. This study indicates that signals on the order of 5 mm/h are resolvable using a random walk standard deviation of 0.45 cm/???h. Values lower than this suppress small signals, and values greater than this have significantly higher noise at periods of 1-6 hours. Copyright 2001 by the American Geophysical Union.

  3. Tracking Boulders

    2006-01-01

    13 March 2006 This Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) image shows a portion of a trough in the Sirenum Fossae region. On the floor and walls of the trough, large -- truck- to house-sized -- boulders are observed at rest. However, there is evidence in this image for the potential for mobility. In the central portion of the south (bottom) wall, a faint line of depressions extends from near the middle of the wall, down to the rippled trough floor, ending very near one of the many boulders in the area. This line of depressions is a boulder track; it indicates the path followed by the boulder as it trundled downslope and eventually came to rest on the trough floor. Because it is on Mars, even when the boulder is sitting still, this once-rolling stone gathers no moss. Location near: 29.4oS, 146.6oW Image width: 3 km (1.9 mi) Illumination from: upper left Season: Southern Summer

  4. INNER TRACKING

    P. Sharp

    The CMS Inner Tracking Detector continues to make good progress. The successful commissioning of ~ 25% of the Silicon Strip Tracker was completed in the Tracker Integration Facility (TIF) at CERN in July 2007 and the Tracker has since been prepared for moving and installation into CMS at P5. The Tracker was ready to move on schedule in September 2007. The Installation of the Tracker cooling pipes and LV cables between Patch Panel 1 (PP1) on the inside the CMS magnet cryostat, and the cooling plants and power system racks on the balconies has been completed. The optical fibres from PP1 to the readout FEDs in the USC have been installed, together with the Tracker cable channels, in parallel with the installation of the EB/HB services. All of the Tracker Safety, Power, DCS and the VME Readout Systems have been installed at P5 and are being tested and commissioned with CMS. It is planned to install the Tracker into CMS before Christmas. The Tracker will then be connected to the pre-installed services on Y...

  5. INNER TRACKING

    P. Sharp

    The CMS Inner Tracking Detector continues to make good progress. The successful commissioning of ~ 25% of the Silicon Strip Tracker was completed in the Tracker Integration Facility (TIF) at CERN on 18 July 2007 and the Tracker has since been prepared for moving and installation into CMS at P5. The Tracker will be ready to move on schedule in September 2007. The Installation of the Tracker cooling pipes and LV cables between Patch Panel 1 (PP1) on the inside the CMS magnet cryostat, and the cooling plants and power system racks on the balconies has been completed. The optical fibres from PP1 to the readout FEDs in the USC will be installed in parallel with the installation of the EB/HB services, and will be completed in October. It is planned to install the Tracker into CMS at the end of October, after the completion of the installation of the EB/HB services. The Tracker will then be connected to the pre-installed services on YB0 and commissioned with CMS in December. The FPix and BPix continue to make ...

  6. The stochastic filtering problem: a brief historical account

    Crisan, Dan

    2014-01-01

    Onwards from the mid-twentieth century, the stochastic filtering problem has caught the attention of thousands of mathematicians, engineers, statisticians, and computer scientists. Its applications span the whole spectrum of human endeavour, including satellite tracking, credit risk estimation, human genome analysis, and speech recognition. Stochastic filtering has engendered a surprising number of mathematical techniques for its treatment and has played an important role in...

  7. Concentric Split Flow Filter

    Stapleton, Thomas J. (Inventor)

    2015-01-01

    A concentric split flow filter may be configured to remove odor and/or bacteria from pumped air used to collect urine and fecal waste products. For instance, filter may be designed to effectively fill the volume that was previously considered wasted surrounding the transport tube of a waste management system. The concentric split flow filter may be configured to split the air flow, with substantially half of the air flow to be treated traveling through a first bed of filter media and substantially the other half of the air flow to be treated traveling through the second bed of filter media. This split flow design reduces the air velocity by 50%. In this way, the pressure drop of filter may be reduced by as much as a factor of 4 as compare to the conventional design.

  8. Recirculating electric air filter for use in confined spaces

    Bergman, W.; Biermann, A.; Kuhl, W.

    1985-01-01

    We have developed recirculating electric air filters for use in confined spaces where the existing ventilation system is not adequate for removing suspended particles. Two experimental filters were built and evaluated, both of which consisted of a cylindrical cartridge filter fitted over an air blower. In one design the cylindrical cartridge is a disposable unit with the electrodes and filter medium built as an integrated unit. The second design has a cylindrical cartridge that can be easily disassembled to allow replacement of the filter medium. Both designs were evaluated in a 354-ft 3 test cell using NaCl aerosols. The second design was installed and evaluated in a chamber where highly radioactive 238 PuO 2 powder is formed into pellets. We have derived equations that describe the theory of recirculating air filters. The predicted performance compares well with experimental measurements under controlled conditions. 2 refs., 7 figs., 1 tab. (DT)

  9. Hybrid Filter Membrane

    Laicer, Castro; Rasimick, Brian; Green, Zachary

    2012-01-01

    Cabin environmental control is an important issue for a successful Moon mission. Due to the unique environment of the Moon, lunar dust control is one of the main problems that significantly diminishes the air quality inside spacecraft cabins. Therefore, this innovation was motivated by NASA s need to minimize the negative health impact that air-suspended lunar dust particles have on astronauts in spacecraft cabins. It is based on fabrication of a hybrid filter comprising nanofiber nonwoven layers coated on porous polymer membranes with uniform cylindrical pores. This design results in a high-efficiency gas particulate filter with low pressure drop and the ability to be easily regenerated to restore filtration performance. A hybrid filter was developed consisting of a porous membrane with uniform, micron-sized, cylindrical pore channels coated with a thin nanofiber layer. Compared to conventional filter media such as a high-efficiency particulate air (HEPA) filter, this filter is designed to provide high particle efficiency, low pressure drop, and the ability to be regenerated. These membranes have well-defined micron-sized pores and can be used independently as air filters with discreet particle size cut-off, or coated with nanofiber layers for filtration of ultrafine nanoscale particles. The filter consists of a thin design intended to facilitate filter regeneration by localized air pulsing. The two main features of this invention are the concept of combining a micro-engineered straight-pore membrane with nanofibers. The micro-engineered straight pore membrane can be prepared with extremely high precision. Because the resulting membrane pores are straight and not tortuous like those found in conventional filters, the pressure drop across the filter is significantly reduced. The nanofiber layer is applied as a very thin coating to enhance filtration efficiency for fine nanoscale particles. Additionally, the thin nanofiber coating is designed to promote capture of

  10. TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers.

    Matysik, Artur; Kraut, Rachel S

    2014-05-01

    Single molecule tracking (SMT) analysis of fluorescently tagged lipid and protein probes is an attractive alternative to ensemble averaged methods such as fluorescence correlation spectroscopy (FCS) or fluorescence recovery after photobleaching (FRAP) for measuring diffusion in artificial and plasma membranes. The meaningful estimation of diffusion coefficients and their errors is however not straightforward, and is heavily dependent on sample type, acquisition method, and equipment used. Many approaches require advanced computing and programming skills for their implementation. Here we present TrackArt software, an accessible graphic interface for simulation and complex analysis of multiple particle paths. Imported trajectories can be filtered to eliminate spurious or corrupted tracks, and are then analyzed using several previously described methodologies, to yield single or multiple diffusion coefficients, their population fractions, and estimated errors. We use TrackArt to analyze the single-molecule diffusion behavior of a sphingolipid analog SM-Atto647N, in mica supported DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) bilayers. Fitting with a two-component diffusion model confirms the existence of two separate populations of diffusing particles in these bilayers on mica. As a demonstration of the TrackArt workflow, we characterize and discuss the effective activation energies required to increase the diffusion rates of these populations, obtained from Arrhenius plots of temperature-dependent diffusion. Finally, TrackArt provides a simulation module, allowing the user to generate models with multiple particle trajectories, diffusing with different characteristics. Maps of domains, acting as impermeable or permeable obstacles for particles diffusing with given rate constants and diffusion coefficients, can be simulated or imported from an image. Importantly, this allows one to use simulated data with a known diffusion behavior as a comparison for results

  11. Fitness: Tips for Staying Motivated

    Healthy Lifestyle Fitness Fitness is for life. Motivate yourself with these practical tips. By Mayo Clinic Staff Have ... 27, 2015 Original article: http://www.mayoclinic.org/healthy-lifestyle/fitness/in-depth/fitness/art-20047624 . Mayo Clinic ...

  12. Backflushable filter insert

    Keith, R.C.; Vandenberg, T.; Randolph, M.C.; Lewis, T.B.; Gillis, P.J. Jr.

    1988-01-01

    Filter elements are mounted on a tube plate beneath an accumulator chamber whose wall is extended by skirt and flange to form a closure for the top of pressure vessel. The accumulator chamber is annular around a central pipe which serves as the outlet for filtered water passing from the filter elements. The chamber contains filtered compressed air from supply. Periodically the filtration of water is stopped and vessel is drained. Then a valve is opened, allowing the accumulated air to flow from chamber up a pipe and down pipe, pushing the filtered water from pipe back through the filter elements to clean them. The accumulator chamber is so proportioned, relative to the volume of the system communicating therewith during backflushing, that the equilibrium pressure during backflushing cannot exceed the pressure rating of the vessel. However a line monitors the pressure at the top of the vessel, and if it rises too far a bleed valve is automatically opened to depressurise the system. The chamber is intended to replace the lid of an existing vessel to convert a filter using filter aid to one using permanent filter elements. (author)

  13. Updating the OMERACT filter

    Wells, George; Beaton, Dorcas E; Tugwell, Peter

    2014-01-01

    The "Discrimination" part of the OMERACT Filter asks whether a measure discriminates between situations that are of interest. "Feasibility" in the OMERACT Filter encompasses the practical considerations of using an instrument, including its ease of use, time to complete, monetary costs......, and interpretability of the question(s) included in the instrument. Both the Discrimination and Reliability parts of the filter have been helpful but were agreed on primarily by consensus of OMERACT participants rather than through explicit evidence-based guidelines. In Filter 2.0 we wanted to improve this definition...

  14. Nanofiber Filters Eliminate Contaminants

    2009-01-01

    With support from Phase I and II SBIR funding from Johnson Space Center, Argonide Corporation of Sanford, Florida tested and developed its proprietary nanofiber water filter media. Capable of removing more than 99.99 percent of dangerous particles like bacteria, viruses, and parasites, the media was incorporated into the company's commercial NanoCeram water filter, an inductee into the Space Foundation's Space Technology Hall of Fame. In addition to its drinking water filters, Argonide now produces large-scale nanofiber filters used as part of the reverse osmosis process for industrial water purification.

  15. Filters in nuclear facilities

    Berg, K.H.; Wilhelm, J.G.

    1985-01-01

    The topics of the nine papers given include the behavior of HEPA filters during exposure to air flows of high humidity as well as of high differential pressure, the development of steel-fiber filters suitable for extreme operating conditions, and the occurrence of various radioactive iodine species in the exhaust air from boiling water reactors. In an introductory presentation the German view of the performance requirements to be met by filters in nuclear facilities as well as the present status of filter quality assurance are discussed. (orig.) [de

  16. Washing method of filter

    Izumidani, Masakiyo; Tanno, Kazuo.

    1978-01-01

    Purpose: To enable automatic filter operation and facilitate back-washing operation by back-washing filters used in a bwr nuclear power plant utilizing an exhaust gas from a ventilator or air conditioner. Method: Exhaust gas from an exhaust pipe of an ventilator or air conditioner is pressurized in a compressor and then introduced in a back-washing gas tank. Then, the exhaust gas pressurized to a predetermined pressure is blown from the inside to the outside of a filter to thereby separate impurities collected on the filter elements and introduce them to a waste tank. (Furukawa, Y.)

  17. Elastic tracking versus neural network tracking for very high multiplicity problems

    Harlander, M.; Gyulassy, M.

    1991-04-01

    A new Elastic Tracking (ET) algorithm is proposed for finding tracks in very high multiplicity and noisy environments. It is based on a dynamical reinterpretation and generalization of the Radon transform and is related to elastic net algorithms for geometrical optimization. ET performs an adaptive nonlinear fit to noisy data with a variable number of tracks. Its numerics is more efficient than that of the traditional Radon or Hough transform method because it avoids binning of phase space and the costly search for valid minima. Spurious local minima are avoided in ET by introducing a time-dependent effective potential. The method is shown to be very robust to noise and measurement error and extends tracking capabilities to much higher track densities than possible via local road finding or even the novel Denby-Peterson neural network tracking algorithms. 12 refs., 2 figs

  18. Robust Object Tracking Using Valid Fragments Selection.

    Zheng, Jin; Li, Bo; Tian, Peng; Luo, Gang

    Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.

  19. Multiradar tracking for theater missile defense

    Sviestins, Egils

    1995-09-01

    A prototype system for tracking tactical ballistic missiles using multiple radars has been developed. The tracking is based on measurement level fusion (`true' multi-radar) tracking. Strobes from passive sensors can also be used. We describe various features of the system with some emphasis on the filtering technique. This is based on the Interacting Multiple Model framework where the states are Free Flight, Drag, Boost, and Auxiliary. Measurement error modeling includes the signal to noise ratio dependence; outliers and miscorrelations are handled in the same way. The launch point is calculated within one minute from the detection of the missile. The impact point, and its uncertainty region, is calculated continually by extrapolating the track state vector using the equations of planetary motion.

  20. Robust lane detection and tracking using multiple visual cues under stochastic lane shape conditions

    Huang, Zhi; Fan, Baozheng; Song, Xiaolin

    2018-03-01

    As one of the essential components of environment perception techniques for an intelligent vehicle, lane detection is confronted with challenges including robustness against the complicated disturbance and illumination, also adaptability to stochastic lane shapes. To overcome these issues, we proposed a robust lane detection method named classification-generation-growth-based (CGG) operator to the detected lines, whereby the linear lane markings are identified by synergizing multiple visual cues with the a priori knowledge and spatial-temporal information. According to the quality of linear lane fitting, the linear and linear-parabolic models are dynamically switched to describe the actual lane. The Kalman filter with adaptive noise covariance and the region of interests (ROI) tracking are applied to improve the robustness and efficiency. Experiments were conducted with images covering various challenging scenarios. The experimental results evaluate the effectiveness of the presented method for complicated disturbances, illumination, and stochastic lane shapes.

  1. Online multi-modal robust non-negative dictionary learning for visual tracking.

    Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

    2015-01-01

    Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

  2. Limitations of inclusive fitness.

    Allen, Benjamin; Nowak, Martin A; Wilson, Edward O

    2013-12-10

    Until recently, inclusive fitness has been widely accepted as a general method to explain the evolution of social behavior. Affirming and expanding earlier criticism, we demonstrate that inclusive fitness is instead a limited concept, which exists only for a small subset of evolutionary processes. Inclusive fitness assumes that personal fitness is the sum of additive components caused by individual actions. This assumption does not hold for the majority of evolutionary processes or scenarios. To sidestep this limitation, inclusive fitness theorists have proposed a method using linear regression. On the basis of this method, it is claimed that inclusive fitness theory (i) predicts the direction of allele frequency changes, (ii) reveals the reasons for these changes, (iii) is as general as natural selection, and (iv) provides a universal design principle for evolution. In this paper we evaluate these claims, and show that all of them are unfounded. If the objective is to analyze whether mutations that modify social behavior are favored or opposed by natural selection, then no aspect of inclusive fitness theory is needed.

  3. The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

    Farrell Steven

    2017-01-01

    Full Text Available Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM and convolutional neural networks to find and fit tracks in toy detector data.

  4. The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

    Farrell, Steven; Anderson, Dustin; Calafiura, Paolo; Cerati, Giuseppe; Gray, Lindsey; Kowalkowski, Jim; Mudigonda, Mayur; Prabhat; Spentzouris, Panagiotis; Spiropoulou, Maria; Tsaris, Aristeidis; Vlimant, Jean-Roch; Zheng, Stephan

    2017-08-01

    Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data.

  5. GOSSIP: SED fitting code

    Franzetti, Paolo; Scodeggio, Marco

    2012-10-01

    GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.

  6. Fitness Club / Nordic Walking

    Fitness Club

    2011-01-01

    Nordic Walking at CERN Enrollments are open for Nordic Walking courses and outings at CERN. Classes will be on Tuesdays as of 20 September, and outings for the more experienced will be on Thursdays as of 15 September. We meet at the CERN Club barracks car park (near entrance A). • 18:00 to 19:00 on 20 & 27 September, as well as 4 & 11 October. Check out our schedule and rates and enroll at: http://cern.ch/club-fitness Hope to see you among us! CERN Fitness Club fitness.club@cern.ch  

  7. Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

    Simon, Dan; Simon, Donald L.

    2005-01-01

    Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

  8. Multilevel ensemble Kalman filter

    Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  9. Neutron Beam Filters

    Adib, M.

    2011-01-01

    The purpose of filters is to transmit neutrons with selected energy, while remove unwanted ones from the incident neutron beam. This reduces the background, and the number of spurious. The types of commonly used now-a-day neutron filters and their properties are discussed in the present work. There are three major types of neutron filters. The first type is filter of selective thermal neutron. It transmits the main reflected neutrons from a crystal monochromate, while reject the higher order contaminations accompanying the main one. Beams coming from the moderator always contain unwanted radiation like fast neutrons and gamma-rays which contribute to experimental background and to the biological hazard potential. Such filter type is called filter of whole thermal neutron spectrum. The third filter type is it transmits neutrons with energies in the resonance energy range (En . 1 KeV). The main idea of such neutron filter technique is the use of large quantities of a certain material which have the deep interference minima in its total neutron cross-section. By transmitting reactor neutrons through bulk layer of such material, one can obtain the quasimonochromatic neutron lines instead of white reactor spectrum.

  10. Side loading filter apparatus

    Reynolds, K.E.

    1981-01-01

    A side loading filter chamber for use with radioactive gases is described. The equipment incorporates an inexpensive, manually operated, mechanism for aligning filter units with a number of laterally spaced wall openings and for removing the units from the chamber. (U.K.)

  11. Multilevel ensemble Kalman filter

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  12. Personal Dosemeter of Thermal Neutron Using A Cr-39 Detector with Filter Natural LiF

    Sofyan, Hasnel; Thamrin, M.Thoyib

    1996-01-01

    The research of personal dosemeter for thermal neutron using Cr-39 detector with different thicknesses of natural LiF filter was carried out. The irradiation of Cr-39 detector with neutron source from reactor research TRIGA mark II of Rikkyo University Tokyo, Japan. Nuclear track was counted by automatic method with ASPECT ver.4.22 Series A4T124 software and manual method for correction. The result of research, the maximum of nuclear tracks was obtained at 8 mm of LiF filter was 10 mm with 11,630x10E-5 track/neutron for air radiation. And on phantom radiation, the thickness of filter was 10 mm with 11,630x10E-5 track/neutron. Its values were 3.6 and 7.5 bigger than the response of Cr-39 non filter in air and on phantom radiation, respectively

  13. Image processing algorithm for robot tracking in reactor vessel

    Kim, Tae Won; Choi, Young Soo; Lee, Sung Uk; Jeong, Kyung Min; Kim, Nam Kyun

    2011-01-01

    In this paper, we proposed an image processing algorithm to find the position of an underwater robot in the reactor vessel. Proposed algorithm is composed of Modified SURF(Speeded Up Robust Feature) based on Mean-Shift and CAMSHIFT(Continuously Adaptive Mean Shift Algorithm) based on color tracking algorithm. Noise filtering using luminosity blend method and color clipping are preprocessed. Initial tracking area for the CAMSHIFT is determined by using modified SURF. And then extracting the contour and corner points in the area of target tracked by CAMSHIFT method. Experiments are performed at the reactor vessel mockup and verified to use in the control of robot by visual tracking

  14. Filtering and prediction

    Fristedt, B; Krylov, N

    2007-01-01

    Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. The main focus is then on filtering out the errors and extracting from the observations the most precise information about the object, which itself may or may not be moving in a somewhat random fashion. Next comes the prediction step where, using information about the past behavior of the object, one tries to predict its future path. The first three chapters of the book deal with discrete probability spaces, random variables, conditioning, Markov chains, and filtering of discrete Markov chains. The next three chapters deal with the more sophisticated notions of conditioning in nondiscrete situations, filtering of continuous-space Markov chains, and of Wiener process. Filtering and prediction of stationary sequences is discussed in the last two chapters. The authors believe that they have succeeded in presenting necessary ideas in an elementary manner without sacrificing the rigor too much. Such rig...

  15. Filter cake breaker systems

    Garcia, Marcelo H.F. [Poland Quimica Ltda., Duque de Caxias, RJ (Brazil)

    2004-07-01

    Drilling fluids filter cakes are based on a combination of properly graded dispersed particles and polysaccharide polymers. High efficiency filter cakes are formed by these combination , and their formation on wellbore walls during the drilling process has, among other roles, the task of protecting the formation from instantaneous or accumulative invasion of drilling fluid filtrate, granting stability to well and production zones. Filter cake minimizes contact between drilling fluid filtrate and water, hydrocarbons and clay existent in formations. The uniform removal of the filter cake from the entire interval is a critical factor of the completion process. The main methods used to breaking filter cake are classified into two groups, external or internal, according to their removal mechanism. The aim of this work is the presentation of these mechanisms as well their efficiency. (author)

  16. Sub-micron filter

    Tepper, Frederick [Sanford, FL; Kaledin, Leonid [Port Orange, FL

    2009-10-13

    Aluminum hydroxide fibers approximately 2 nanometers in diameter and with surface areas ranging from 200 to 650 m.sup.2/g have been found to be highly electropositive. When dispersed in water they are able to attach to and retain electronegative particles. When combined into a composite filter with other fibers or particles they can filter bacteria and nano size particulates such as viruses and colloidal particles at high flux through the filter. Such filters can be used for purification and sterilization of water, biological, medical and pharmaceutical fluids, and as a collector/concentrator for detection and assay of microbes and viruses. The alumina fibers are also capable of filtering sub-micron inorganic and metallic particles to produce ultra pure water. The fibers are suitable as a substrate for growth of cells. Macromolecules such as proteins may be separated from each other based on their electronegative charges.

  17. Tracking Filters for Estimation of Jet Engine Deterioration

    National Aeronautics and Space Administration — This presentation will review the use of knowledge management in the development and support of Condition Based Maintenance (CBM) systems for complex systems with...

  18. Multiple Model Particle Filtering For Multi-Target Tracking

    Hero, Alfred; Kreucher, Chris; Kastella, Keith

    2004-01-01

    .... The details of this method have been presented elsewhere 1. One feature of real targets is that they are poorly described by a single kinematic model Target behavior may change dramatically i.e...

  19. Measuring Your Fitness Level

    ... online calculator. If you'd rather do the math yourself, divide your weight in pounds by your ... Human Services recommends one of the following activity levels for adult fitness and health benefits: 150 minutes ...

  20. The universal Higgs fit

    Giardino, P. P.; Kannike, K.; Masina, I.

    2014-01-01

    We perform a state-of-the-art global fit to all Higgs data. We synthesise them into a 'universal' form, which allows to easily test any desired model. We apply the proposed methodology to extract from data the Higgs branching ratios, production cross sections, couplings and to analyse composite...... Higgs models, models with extra Higgs doublets, supersymmetry, extra particles in the loops, anomalous top couplings, and invisible Higgs decays into Dark Matter. Best fit regions lie around the Standard Model predictions and are well approximated by our 'universal' fit. Latest data exclude the dilaton...... as an alternative to the Higgs, and disfavour fits with negative Yukawa couplings. We derive for the first time the SM Higgs boson mass from the measured rates, rather than from the peak positions, obtaining M-h = 124.4 +/- 1.6 GeV....

  1. ACSM Fit Society Page

    ... fitness topics. Expert commentary and features on exercise, nutrition, sports and health offer tips and techniques for maintaining ... Special Populations 2011 -- Behavior Change & Exercise Adherence 2011 -- ... Preparing for Fall Sports 2009 -- Cancer and Exercise 2008 -- Group Exercise 2008 -- ...

  2. Driver fitness medical guidelines.

    2009-09-01

    This guide provides guidance to assist licensing agencies in making decisions about an individuals fitness for driving. This is the first attempt to produce a consolidated document covering medical conditions included in the task agreement between...

  3. Monolithic Integrated Ceramic Waveguide Filters

    Hunter, IC; Sandhu, MY

    2014-01-01

    Design techniques for a new class of integrated monolithic high permittivity ceramic waveguide filters are presented. These filters enable a size reduction of 50% compared to air-filled TEM filters with the same unloaded Q-Factor. Designs for both chebyshev and asymmetric generalized chebyshev filter are presented, with experimental results for an 1800 MHz chebyshev filter showing excellent agreement with theory.

  4. A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters

    Danilo Pelusi

    2018-03-01

    Full Text Available The goodness of Infinite Impulse Response (IIR digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA. In this way, a Fuzzy Gravitational Search Algorithm (FGSA is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.

  5. The Langley Fitness Center

    1993-01-01

    NASA Langley recognizes the importance of healthy employees by committing itself to offering a complete fitness program. The scope of the program focuses on promoting overall health and wellness in an effort to reduce the risks of illness and disease and to increase productivity. This is accomplished through a comprehensive Health and Fitness Program offered to all NASA employees. Various aspects of the program are discussed.

  6. dftools: Distribution function fitting

    Obreschkow, Danail

    2018-05-01

    dftools, written in R, finds the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a mass function (D=1), a mass-size distribution (D=2) or the mass-spin-morphology distribution (D=3). Unlike most common fitting approaches, this method accurately accounts for measurement in uncertainties and complex selection functions.

  7. Face Recognition and Tracking in Videos

    Swapnil Vitthal Tathe

    2017-07-01

    Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

  8. Filtered-X Affine Projection Algorithms for Active Noise Control Using Volterra Filters

    Sicuranza Giovanni L

    2004-01-01

    Full Text Available We consider the use of adaptive Volterra filters, implemented in the form of multichannel filter banks, as nonlinear active noise controllers. In particular, we discuss the derivation of filtered-X affine projection algorithms for homogeneous quadratic filters. According to the multichannel approach, it is then easy to pass from these algorithms to those of a generic Volterra filter. It is shown in the paper that the AP technique offers better convergence and tracking capabilities than the classical LMS and NLMS algorithms usually applied in nonlinear active noise controllers, with a limited complexity increase. This paper extends in two ways the content of a previous contribution published in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03, Grado, Italy, June 2003. First of all, a general adaptation algorithm valid for any order of affine projections is presented. Secondly, a more complete set of experiments is reported. In particular, the effects of using multichannel filter banks with a reduced number of channels are investigated and relevant results are shown.

  9. Online track reconstruction at hadron colliders

    Amerio, Silvia; Bettini, Marco; Nicoletto, Marino; Crescioli, Francesco; Bucciantonio, Martina; DELL'ORSO, Mauro; Piendibene, Marco; VOLPI, Guido; Annovi, Alberto; Catastini, Pierluigi; Giannetti, Paola; Lucchesi, Donatella

    2010-01-01

    Real time event reconstruction plays a fundamental role in High Energy Physics experiments. Reducing the rate of data to be saved on tape from millions to hundreds per second is critical. In order to increase the purity of the collected samples, rate reduction has to be coupled with the capability to simultaneously perform a first selection of the most interesting events. A fast and efficient online track reconstruction is important to effectively trigger on leptons and/or displaced tracks from b-quark decays. This talk will be an overview of online tracking techniques in different HEP environments: we will show how H1 experiment at HERA faced the challenges of online track reconstruction implementing pattern matching and track linking algorithms on CAMs and FPGAs in the Fast Track Processor (FTT). The pattern recognition technique is also at the basis of the Silicon Vertex Trigger (SVT) at the CDF experiment at Tevatron: coupled to a very fast fitting phase, SVT allows to trigger on displaced tracks, thus greatly increasing the efficiency for the hadronic B decay modes. A recent upgrade of the SVT track fitter, the Giga-fitter, can perform more than 1 fit/ns and further improves the CDF online trigger capabilities at high luminosity. At SLHC, where luminosities will be 2 orders of magnitude greater than Tevatron, online tracking will be much more challenging: we will describe CMS future plans for a Level-1 track trigger and the Fast Tracker (FTK) processor at the ATLAS experiment, based on the Giga-fitter architecture and designed to provide high quality tracks reconstructed over the entire detector in time for a Level-2 trigger decision.luminosity. At SLHC, where luminosities will be 2 orders of magnitude greater than Tevatron, online tracking will be much more challenging: we will describe CMS future plans for a Level-1 track trigger and the Fast Tracker (FTK) processor at the Atlas experiment, based on the Giga-fitter architecture and designed to provide high

  10. How Can I Keep Track of Physical Activity and Eating?

    ... ANSWERS by heart Lifestyle + Risk Reduction Fitness + Weight Management How Can I Keep Track of Physical Activity and Healthy Eating? Food Diary — Once you’ve set your eating goals, use this sample chart to track your efforts. WEEK: ________________________ DAY: ________________________ Food or Beverage Amount Number of Calories Grams of Saturated Fat ...

  11. Hypersonic sliding target tracking in near space

    Xiang-yu Zhang

    2015-12-01

    Full Text Available To improve the tracking accuracy of hypersonic sliding target in near space, the influence of target hypersonic movement on radar detection and tracking is analyzed, and an IMM tracking algorithm is proposed based on radial velocity compensating and cancellation processing of high dynamic biases under the earth centered earth fixed (ECEF coordinate. Based on the analysis of effect of target hypersonic movement, a measurement model is constructed to reduce the filter divergence which is caused by the model mismatch. The high dynamic biases due to the target hypersonic movement are approximately compensated through radial velocity estimation to achieve the hypersonic target tracking at low systematic biases in near space. The high dynamic biases are further eliminated by the cancellation processing of different radars, in which the track association problem can be solved when the dynamic biases are low. An IMM algorithm based on constant acceleration (CA, constant turning (CT and Singer models is used to achieve the hypersonic sliding target tracking in near space. Simulation results show that the target tracking in near space can be achieved more effectively by using the proposed algorithm.

  12. Solar tracking system

    Okandan, Murat; Nielson, Gregory N.

    2016-07-12

    Solar tracking systems, as well as methods of using such solar tracking systems, are disclosed. More particularly, embodiments of the solar tracking systems include lateral supports horizontally positioned between uprights to support photovoltaic modules. The lateral supports may be raised and lowered along the uprights or translated to cause the photovoltaic modules to track the moving sun.

  13. Ceramic fiber reinforced filter

    Stinton, David P.; McLaughlin, Jerry C.; Lowden, Richard A.

    1991-01-01

    A filter for removing particulate matter from high temperature flowing fluids, and in particular gases, that is reinforced with ceramic fibers. The filter has a ceramic base fiber material in the form of a fabric, felt, paper of the like, with the refractory fibers thereof coated with a thin layer of a protective and bonding refractory applied by chemical vapor deposition techniques. This coating causes each fiber to be physically joined to adjoining fibers so as to prevent movement of the fibers during use and to increase the strength and toughness of the composite filter. Further, the coating can be selected to minimize any reactions between the constituents of the fluids and the fibers. A description is given of the formation of a composite filter using a felt preform of commercial silicon carbide fibers together with the coating of these fibers with pure silicon carbide. Filter efficiency approaching 100% has been demonstrated with these filters. The fiber base material is alternately made from aluminosilicate fibers, zirconia fibers and alumina fibers. Coating with Al.sub.2 O.sub.3 is also described. Advanced configurations for the composite filter are suggested.

  14. Real-time Non-linear Target Tracking Control of Wheeled Mobile Robots

    YU Wenyong

    2006-01-01

    A control strategy for real-time target tracking for wheeled mobile robots is presented. Using a modified Kalman filter for environment perception, a novel tracking control law derived from Lyapunov stability theory is introduced. Tuning of linear velocity and angular velocity with mechanical constraints is applied. The proposed control system can simultaneously solve the target trajectory prediction, real-time tracking, and posture regulation problems of a wheeled mobile robot. Experimental results illustrate the effectiveness of the proposed tracking control laws.

  15. Rules, culture, and fitness.

    Baum, W M

    1995-01-01

    Behavior analysis risks intellectual isolation unless it integrates its explanations with evolutionary theory. Rule-governed behavior is an example of a topic that requires an evolutionary perspective for a full understanding. A rule may be defined as a verbal discriminative stimulus produced by the behavior of a speaker under the stimulus control of a long-term contingency between the behavior and fitness. As a discriminative stimulus, the rule strengthens listener behavior that is reinforced in the short run by socially mediated contingencies, but which also enters into the long-term contingency that enhances the listener's fitness. The long-term contingency constitutes the global context for the speaker's giving the rule. When a rule is said to be "internalized," the listener's behavior has switched from short- to long-term control. The fitness-enhancing consequences of long-term contingencies are health, resources, relationships, or reproduction. This view ties rules both to evolutionary theory and to culture. Stating a rule is a cultural practice. The practice strengthens, with short-term reinforcement, behavior that usually enhances fitness in the long run. The practice evolves because of its effect on fitness. The standard definition of a rule as a verbal statement that points to a contingency fails to distinguish between a rule and a bargain ("If you'll do X, then I'll do Y"), which signifies only a single short-term contingency that provides mutual reinforcement for speaker and listener. In contrast, the giving and following of a rule ("Dress warmly; it's cold outside") can be understood only by reference also to a contingency providing long-term enhancement of the listener's fitness or the fitness of the listener's genes. Such a perspective may change the way both behavior analysts and evolutionary biologists think about rule-governed behavior.

  16. The singular value filter: a general filter design strategy for PCA-based signal separation in medical ultrasound imaging.

    Mauldin, F William; Lin, Dan; Hossack, John A

    2011-11-01

    A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, which we refer to as the blind source separation (BSS) method, as well as a simple frequency-based finite impulse response (FIR) filter used as a baseline for comparison. The performance of each filter was quantified in simulated lesion images as well as experimental cardiac ultrasound data. SVF was demonstrated in both simulation and experimental results, over a wide range of imaging conditions, to outperform the BSS and FIR filtering methods in terms of contrast-to-noise ratio (CNR) and motion tracking performance. In experimental mouse heart data, SVF provided excellent artifact suppression with an average CNR improvement of 1.8 dB with over 40% reduction in displacement tracking error. It was further demonstrated from simulation and experimental results that SVF provided superior clutter rejection, as reflected in larger CNR values, when filtering was achieved using complex pulse-echo received data and non-binary filter coefficients.

  17. Circuits and filters handbook

    Chen, Wai-Kai

    2003-01-01

    A bestseller in its first edition, The Circuits and Filters Handbook has been thoroughly updated to provide the most current, most comprehensive information available in both the classical and emerging fields of circuits and filters, both analog and digital. This edition contains 29 new chapters, with significant additions in the areas of computer-aided design, circuit simulation, VLSI circuits, design automation, and active and digital filters. It will undoubtedly take its place as the engineer's first choice in looking for solutions to problems encountered in the design, analysis, and behavi

  18. EMI filter design

    Ozenbaugh, Richard Lee

    2011-01-01

    With today's electrical and electronics systems requiring increased levels of performance and reliability, the design of robust EMI filters plays a critical role in EMC compliance. Using a mix of practical methods and theoretical analysis, EMI Filter Design, Third Edition presents both a hands-on and academic approach to the design of EMI filters and the selection of components values. The design approaches covered include matrix methods using table data and the use of Fourier analysis, Laplace transforms, and transfer function realization of LC structures. This edition has been fully revised

  19. Randomized Filtering Algorithms

    Katriel, Irit; Van Hentenryck, Pascal

    2008-01-01

    of AllDifferent and is generalization, the Global Cardinality Constraint. The first delayed filtering scheme is a Monte Carlo algorithm: its running time is superior, in the worst case, to that of enforcing are consistency after every domain event, while its filtering effectiveness is analyzed...... in the expected sense. The second scheme is a Las Vegas algorithm using filtering triggers: Its effectiveness is the same as enforcing are consistency after every domain event, while in the expected case it is faster by a factor of m/n, where n and m are, respectively, the number of nodes and edges...

  20. Fit by Five.

    Wells, Maureen

    1978-01-01

    Describes a preschool program in which all skills, including academic and social skills, are taught through movement. Children are introduced to over 300 physical activities and sports in a year's time including: balance beam, parallel bars, trampoline, swimming, hockey, basketball, golf, archery, track, and volleyball. (JMB)

  1. Regularized Adaptive Notch Filters for Acoustic Howling Suppression

    Gil-Cacho, Pepe; van Waterschoot, Toon; Moonen, Marc

    2009-01-01

    In this paper, a method for the suppression of acoustic howling is developed, based on adaptive notch filters (ANF) with regularization (RANF). The method features three RANFs working in parallel to achieve frequency tracking, howling detection and suppression. The ANF-based approach to howling...

  2. Particle tracking from image sequences of complex plasma crystals

    Hadziavdic, Vedad; Melandsoe, Frank; Hanssen, Alfred

    2006-01-01

    In order to gather information about the physics of the complex plasma crystals from the experimental data, particles have to be tracked through a sequence of images. An application of the Kalman filter for that purpose is presented, using a one-dimensional approximation of the particle dynamics as a model for the filter. It is shown that Kalman filter is capable of tracking dust particles even with high levels of measurement noise. An inherent part of the Kalman filter, the innovation process, can be used to estimate values of the physical system parameters from the experimental data. The method is shown to be able to estimate the characteristic oscillation frequency from noisy data

  3. Spectral analysis and filter theory in applied geophysics

    Buttkus, Burkhard

    2000-01-01

    This book is intended to be an introduction to the fundamentals and methods of spectral analysis and filter theory and their appli­ cations in geophysics. The principles and theoretical basis of the various methods are described, their efficiency and effectiveness eval­ uated, and instructions provided for their practical application. Be­ sides the conventional methods, newer methods arediscussed, such as the spectral analysis ofrandom processes by fitting models to the ob­ served data, maximum-entropy spectral analysis and maximum-like­ lihood spectral analysis, the Wiener and Kalman filtering methods, homomorphic deconvolution, and adaptive methods for nonstation­ ary processes. Multidimensional spectral analysis and filtering, as well as multichannel filters, are given extensive treatment. The book provides a survey of the state-of-the-art of spectral analysis and fil­ ter theory. The importance and possibilities ofspectral analysis and filter theory in geophysics for data acquisition, processing an...

  4. Metalcasting: Filtering Molten Metal

    Lauren Poole; Lee Recca

    1999-01-01

    A more efficient method has been created to filter cast molten metal for impurities. Read about the resulting energy and money savings that can accrue to many different industries from the use of this exciting new technology

  5. HEPA air filter (image)

    ... pet dander and other irritating allergens from the air. Along with other methods to reduce allergens, such ... controlling the amount of allergens circulating in the air. HEPA filters can be found in most air ...

  6. Updating the OMERACT filter

    Tugwell, Peter; Boers, Maarten; D'Agostino, Maria-Antonietta

    2014-01-01

    OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Filter provides guidelines for the development and validation of outcome measures for use in clinical research. The "Truth" section of the OMERACT Filter requires that criteria be met to demonstrate that the outcome instrument meets...... the criteria for content, face, and construct validity. METHODS: Discussion groups critically reviewed a variety of ways in which case studies of current OMERACT Working Groups complied with the Truth component of the Filter and what issues remained to be resolved. RESULTS: The case studies showed...... that there is broad agreement on criteria for meeting the Truth criteria through demonstration of content, face, and construct validity; however, several issues were identified that the Filter Working Group will need to address. CONCLUSION: These issues will require resolution to reach consensus on how Truth...

  7. Paul Rodgersi filter Kohilas

    2000-01-01

    28. I Kohila keskkoolis kohaspetsiifiline skulptuur ja performance "Filter". Kooli 130. aastapäeva tähistava ettevõtmise eesotsas oli skulptor Paul Rodgers ja kaks viimase klassi noormeest ئ Marko Heinmäe, Hendrik Karm.

  8. Fitting the Phenomenological MSSM

    AbdusSalam, S S; Quevedo, F; Feroz, F; Hobson, M

    2010-01-01

    We perform a global Bayesian fit of the phenomenological minimal supersymmetric standard model (pMSSM) to current indirect collider and dark matter data. The pMSSM contains the most relevant 25 weak-scale MSSM parameters, which are simultaneously fit using `nested sampling' Monte Carlo techniques in more than 15 years of CPU time. We calculate the Bayesian evidence for the pMSSM and constrain its parameters and observables in the context of two widely different, but reasonable, priors to determine which inferences are robust. We make inferences about sparticle masses, the sign of the $\\mu$ parameter, the amount of fine tuning, dark matter properties and the prospects for direct dark matter detection without assuming a restrictive high-scale supersymmetry breaking model. We find the inferred lightest CP-even Higgs boson mass as an example of an approximately prior independent observable. This analysis constitutes the first statistically convergent pMSSM global fit to all current data.

  9. TPC track distortions III: fiat lux

    Boyko, I; Dydak, F; Elagin, A; Gostkin, M; Guskov, A; Koreshev, V; Nefedov, Y; Nikolaev, K; Veenhof, R; Wotschack, J; Zhemchugov, A

    2005-01-01

    We present a comprehensive overview and final summary of all four types of static track distortions seen in the HARP TPC, in terms of physical origins, mathematical modelling, and correction algorithms. 'Static'™ distortions are defined as not depending on the event time within the 400 ms long accelerator spill. Calculated static distortions are compared with measurements from cosmic-muon tracks. We characterize track distortions by the r phi residuals of cluster positions with respect to the transverse projection of a helical trajectory constrained by hits in the RPC overlap regions. This method provides a fixed TPC-external reference system (by contrast to the co-moving coordinate system associated with a fit) which solely permits to identify individually, and measure quantitatively, the static TPC track distortions arising from (i) the inhomogeneity of the solenoidal magnetic field, (ii) the inhomogeneity of the electric field from the high-voltage mismatch between the inner and outer TPC field cages, (...

  10. Spatial filter issues

    Murray, J.E.; Estabrook, K.G.; Milam, D.; Sell, W.D.; Van Wonterghem, R.M.; Feil, M.D.; Rubenchick, A.M.

    1996-01-01

    Experiments and calculations indicate that the threshold pressure in spatial filters for distortion of a transmitted pulse scales approximately as I O.2 and (F number-sign) 2 over the intensity range from 10 14 to 2xlO 15 W/CM 2 . We also demonstrated an interferometric diagnostic that will be used to measure the scaling relationships governing pinhole closure in spatial filters

  11. Microwave Resonators and Filters

    2015-12-22

    1 Microwave Resonators and Filters Daniel E. Oates MIT Lincoln Laboratory 244 Wood St. Lexington, MA 02478 USA Email: oates@ll.mit.edu...explained in other chapters, the surface resistance of superconductors at microwave frequencies can be as much as three orders of magnitude lower than the...resonators and filters in the first edition of this handbook (Z.-Y. Shen 2003) discussed the then state of the art of microwave frequency applications

  12. Staging with spatial filters

    Glaze, J.

    1974-01-01

    It is known that small scale beam instabilities limit the focusable energy that can be achieved from a terawatt laser chain. Spatial filters are currently being used on CYCLOPS to ameliorate this problem. Realizing the full advantage of such a filter, however, may require certain staging modifications. A staging methodology is discussed that should be applicable to the CYCLOPS, 381, and SHIVA systems. Experiments are in progress on CYCLOPS that will address directly the utility of the proposed approach

  13. A fit method for the determination of inherent filtration with diagnostic x-ray units

    Meghzifene, K; Nowotny, R; Aiginger, H

    2006-01-01

    A method for the determination of total inherent filtration for clinical x-ray units using attenuation curves was devised. A model for the calculation of x-ray spectra is used to calculate kerma values which are then adjusted to the experimental data in minimizing the sum of the squared relative differences in kerma using a modified simplex fit process. The model considers tube voltage, voltage ripple, anode angle and additional filters. Fit parameters are the thickness of an additional inherent Al filter and a general normalization factor. Nineteen sets of measurements including attenuation data for three tube voltages and five Al-filter settings each were obtained. Relative differences of experimental and calculated kerma using the data for the additional filter thickness are within a range of -7.6% to 6.4%. Quality curves, i.e. the relationship of additional filtration to HVL, are often used to determine filtration but the results show that standard quality curves do not reflect the variety of conditions encountered in practice. To relate the thickness of the additional filter to the condition of the anode surface, the data fits were also made using tungsten as the filter material. These fits gave an identical fit quality compared to aluminium with a tungsten filter thickness of 2.12-8.21 μm which is within the range of the additional absorbing layers determined for rough anodes

  14. Strength Training: For Overall Fitness

    Healthy Lifestyle Fitness Strength training is an important part of an overall fitness program. Here's what strength training can do for ... is a key component of overall health and fitness for everyone. Lean muscle mass naturally diminishes with ...

  15. Inorganic UV filters

    Eloísa Berbel Manaia

    2013-06-01

    Full Text Available Nowadays, concern over skin cancer has been growing more and more, especially in tropical countries where the incidence of UVA/B radiation is higher. The correct use of sunscreen is the most efficient way to prevent the development of this disease. The ingredients of sunscreen can be organic and/or inorganic sun filters. Inorganic filters present some advantages over organic filters, such as photostability, non-irritability and broad spectrum protection. Nevertheless, inorganic filters have a whitening effect in sunscreen formulations owing to the high refractive index, decreasing their esthetic appeal. Many techniques have been developed to overcome this problem and among them, the use of nanotechnology stands out. The estimated amount of nanomaterial in use must increase from 2000 tons in 2004 to a projected 58000 tons in 2020. In this context, this article aims to analyze critically both the different features of the production of inorganic filters (synthesis routes proposed in recent years and the permeability, the safety and other characteristics of the new generation of inorganic filters.

  16. Resonator memories and optical novelty filters

    Anderson, Dana Z.; Erle, Marie C.

    Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

  17. OpenCV and TYZX : video surveillance for tracking.

    He, Jim; Spencer, Andrew; Chu, Eric

    2008-08-01

    As part of the National Security Engineering Institute (NSEI) project, several sensors were developed in conjunction with an assessment algorithm. A camera system was developed in-house to track the locations of personnel within a secure room. In addition, a commercial, off-the-shelf (COTS) tracking system developed by TYZX was examined. TYZX is a Bay Area start-up that has developed its own tracking hardware and software which we use as COTS support for robust tracking. This report discusses the pros and cons of each camera system, how they work, a proposed data fusion method, and some visual results. Distributed, embedded image processing solutions show the most promise in their ability to track multiple targets in complex environments and in real-time. Future work on the camera system may include three-dimensional volumetric tracking by using multiple simple cameras, Kalman or particle filtering, automated camera calibration and registration, and gesture or path recognition.

  18. OpenCV and TYZX : video surveillance for tracking

    He, Jim; Spencer, Andrew; Chu, Eric

    2008-01-01

    As part of the National Security Engineering Institute (NSEI) project, several sensors were developed in conjunction with an assessment algorithm. A camera system was developed in-house to track the locations of personnel within a secure room. In addition, a commercial, off-the-shelf (COTS) tracking system developed by TYZX was examined. TYZX is a Bay Area start-up that has developed its own tracking hardware and software which we use as COTS support for robust tracking. This report discusses the pros and cons of each camera system, how they work, a proposed data fusion method, and some visual results. Distributed, embedded image processing solutions show the most promise in their ability to track multiple targets in complex environments and in real-time. Future work on the camera system may include three-dimensional volumetric tracking by using multiple simple cameras, Kalman or particle filtering, automated camera calibration and registration, and gesture or path recognition

  19. Etched track radiometers in radon measurements: a review

    Nikolaev, V A

    1999-01-01

    Passive radon radiometers, based on alpha particle etched track detectors, are very attractive for the assessment of radon exposure. The present review considers various devices used for measurement of the volume activity of radon isotopes and their daughters and determination of equilibrium coefficients. Such devices can be classified into 8 groups: (i) open or 'bare' detectors, (ii) open chambers, (iii) sup 2 sup 2 sup 2 Rn chambers with an inlet filter, (iv) advanced sup 2 sup 2 sup 2 Rn radiometers, (v) multipurpose radiometers, (vi) radiometers based on a combination of etched track detectors and an electrostatic field, (vii) radiometers based on etched track detectors and activated charcoal and (viii) devices for the measurement of radon isotopes and/or radon daughters by means of track parameter measurements. Some of them such as the open detector and the chamber with an inlet filter have a variety of modifications and are applied widely both in geophysical research and radon dosimetric surveys. At the...

  20. Integrated tracking, classification, and sensor management theory and applications

    Krishnamurthy, Vikram; Vo, Ba-Ngu

    2012-01-01

    A unique guide to the state of the art of tracking, classification, and sensor management. This book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking approaches, target classification procedures, and large scale sensor management problem-solving techniques.

  1. A difference tracking algorithm based on discrete sine transform

    Liu, HaoPeng; Yao, Yong; Lei, HeBing; Wu, HaoKun

    2018-04-01

    Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.

  2. Research on the Filtering Algorithm in Speed and Position Detection of Maglev Trains

    Chunhui Dai

    2011-07-01

    Full Text Available This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train’s structure, the permanent magnet electrodynamic suspension (EDS train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

  3. Research on the filtering algorithm in speed and position detection of maglev trains.

    Dai, Chunhui; Long, Zhiqiang; Xie, Yunde; Xue, Song

    2011-01-01

    This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS) train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train's structure, the permanent magnet electrodynamic suspension (EDS) train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD) and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

  4. Improving NEC Fit

    2015-09-01

    TAD Temporary Additional Duty TFMMS Total Force Manpower Management System UIC Unit Identification Code USFFC United States Fleet Forces Command...not include sailors on temporary additional duty ( TAD ). In addition, for class average Fit, we excluded units that had billets but no onboard

  5. Reliability and Model Fit

    Stanley, Leanne M.; Edwards, Michael C.

    2016-01-01

    The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…

  6. Automatically processed alpha-track radon monitor

    Langner, G.H. Jr.

    1993-01-01

    An automatically processed alpha-track radon monitor is provided which includes a housing having an aperture allowing radon entry, and a filter that excludes the entry of radon daughters into the housing. A flexible track registration material is located within the housing that records alpha-particle emissions from the decay of radon and radon daughters inside the housing. The flexible track registration material is capable of being spliced such that the registration material from a plurality of monitors can be spliced into a single strip to facilitate automatic processing of the registration material from the plurality of monitors. A process for the automatic counting of radon registered by a radon monitor is also provided

  7. Automatic track counting with an optic RAM-based instrument

    Staderini, E.M.; Castellano, Alfredo

    1986-01-01

    A new image sensor, the optic RAM, is now used in a microprocessor controlled instrument to read and digitize images from CR39 solid state nuclear track detectors. The system performs image analysis, filtering, tracks counting and evaluation in a fully automatic way, not requiring an optic microscope, nor photographic or television devices. The proposed system is a very compact and low power device. (author)

  8. Optimal Control Strategy for Marine Ssp Podded Propulsion Motor Based on Strong Tracking-Epf

    Yao Wenlong

    2015-09-01

    Full Text Available Aiming at the non-linearity of state equation and observation equation of SSP (Siemen Schottel Propulsor propulsion motor, an improved particle filter algorithm based on strong tracking extent Kalman filter (ST-EKF was presented, and it was imported into the marine SSP propulsion motor control system. The strong tracking filter was used to update particles in the new algorithm and produce importance densities. As a result, the problems of particle degeneracy and sample impoverishment were ameliorated, the propulsion motor states and the rotor resistance were estimated simultaneously using strong track filter (STF, and the tracking ability of marine SSP propulsion motor control system was improved. Simulation result shown that the improved EPF algorithm was not only improving the prediction accuracy of the motor states and the rotor resistance, but also it can satisfy the requirement of navigation in harbor. It had the better accuracy than EPF algorithm.

  9. daptive Filter Used as a Dynamic Compensator in Automatic Gauge Control of Strip Rolling Processes

    N. ROMAN

    2010-12-01

    Full Text Available The paper deals with a control structure of the strip thickness in a rolling mill of quarto type (AGC – Automatic Gauge Control. It performs two functions: the compensation of errors induced by unideal dynamics of the tracking systems lead by AGC system and the control adaptation to the change of dynamic properties of the tracking systems. The compensation of dynamical errors is achieved through inverse models of the tracking system, implemented as adaptive filters.

  10. Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters

    Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.

    2016-11-01

    Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.

  11. Choosing and using astronomical filters

    Griffiths, Martin

    2014-01-01

    As a casual read through any of the major amateur astronomical magazines will demonstrate, there are filters available for all aspects of optical astronomy. This book provides a ready resource on the use of the following filters, among others, for observational astronomy or for imaging: Light pollution filters Planetary filters Solar filters Neutral density filters for Moon observation Deep-sky filters, for such objects as galaxies, nebulae and more Deep-sky objects can be imaged in much greater detail than was possible many years ago. Amateur astronomers can take

  12. Persistent Aerial Tracking

    Mueller, Matthias

    2016-01-01

    persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc

  13. Renewable Energy Tracking Systems

    Renewable energy generation ownership can be accounted through tracking systems. Tracking systems are highly automated, contain specific information about each MWh, and are accessible over the internet to market participants.

  14. Forward tracking detectors

    Abstract. Forward tracking is an essential part of a detector at the international linear collider (ILC). The requirements for forward tracking are explained and the proposed solutions in the detector concepts are shown.

  15. Fitting PAC spectra with stochastic models: PolyPacFit

    Zacate, M. O., E-mail: zacatem1@nku.edu [Northern Kentucky University, Department of Physics and Geology (United States); Evenson, W. E. [Utah Valley University, College of Science and Health (United States); Newhouse, R.; Collins, G. S. [Washington State University, Department of Physics and Astronomy (United States)

    2010-04-15

    PolyPacFit is an advanced fitting program for time-differential perturbed angular correlation (PAC) spectroscopy. It incorporates stochastic models and provides robust options for customization of fits. Notable features of the program include platform independence and support for (1) fits to stochastic models of hyperfine interactions, (2) user-defined constraints among model parameters, (3) fits to multiple spectra simultaneously, and (4) any spin nuclear probe.

  16. Anti-clogging filter system

    Brown, Erik P.

    2015-05-19

    An anti-clogging filter system for filtering a fluid containing large particles and small particles includes an enclosure with at least one individual elongated tubular filter element in the enclosure. The individual elongated tubular filter element has an internal passage, a closed end, an open end, and a filtering material in or on the individual elongated tubular filter element. The fluid travels through the open end of the elongated tubular element and through the internal passage and through the filtering material. An anti-clogging element is positioned on or adjacent the individual elongated tubular filter element and provides a fluid curtain that preferentially directs the larger particulates to one area of the filter material allowing the remainder of the filter material to remain more efficient.

  17. Efficient simulations of fluid flow coupled with poroelastic deformations in pleated filters

    Calo, Victor M.; Iliev, Dimitar; Iliev, Oleg; Kirsch, Ralf; Lakdawala, Zahra; Printsypar, Galina

    2015-01-01

    model describes a free fluid flow coupled with a flow in porous media in a domain that contains the filtering media. To discretize the complex computational domain we use quadrilateral boundary fitted grids which resolve porous-fluid interfaces

  18. Multilevel ensemble Kalman filtering

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  19. Multilevel ensemble Kalman filtering

    Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  20. Extensive fitness and human cooperation

    van Hateren, J. H.

    2015-01-01

    Evolution depends on the fitness of organisms, the expected rate of reproducing. Directly getting offspring is the most basic form of fitness, but fitness can also be increased indirectly by helping genetically related individuals (such as kin) to increase their fitness. The combined effect is known