The Rao-Blackwellized Particle Filter: A Filter Bank Implementation
Directory of Open Access Journals (Sweden)
Karlsson Rickard
2010-01-01
Full Text Available For computational efficiency, it is important to utilize model structure in particle filtering. One of the most important cases occurs when there exists a linear Gaussian substructure, which can be efficiently handled by Kalman filters. This is the standard formulation of the Rao-Blackwellized particle filter (RBPF. This contribution suggests an alternative formulation of this well-known result that facilitates reuse of standard filtering components and which is also suitable for object-oriented programming. Our RBPF formulation can be seen as a Kalman filter bank with stochastic branching and pruning.
2006-06-01
infinite particles [39]. As computational power increases, estimators based on particle filtering will only improve their characterization of the...levi- atio~ii of the kernel depenident on thle uiminber of particles samnpledl at that poin t aii(l th le (’iil~i-l cal covariance miatrix of the...potent ial to I ecoimie a powerful estimation techiniquie. As evbncd y tests wvithi Swiss Planger (lata, they prov’ide 104 s~it ilali I)etortla ii8CC 10o
Multiple object tracking in molecular bioimaging by Rao-Blackwellized marginal particle filtering.
Smal, I; Meijering, E; Draegestein, K; Galjart, N; Grigoriev, I; Akhmanova, A; van Royen, M E; Houtsmuller, A B; Niessen, W
2008-12-01
Time-lapse fluorescence microscopy imaging has rapidly evolved in the past decade and has opened new avenues for studying intracellular processes in vivo. Such studies generate vast amounts of noisy image data that cannot be analyzed efficiently and reliably by means of manual processing. Many popular tracking techniques exist but often fail to yield satisfactory results in the case of high object densities, high noise levels, and complex motion patterns. Probabilistic tracking algorithms, based on Bayesian estimation, have recently been shown to offer several improvements over classical approaches, by better integration of spatial and temporal information, and the possibility to more effectively incorporate prior knowledge about object dynamics and image formation. In this paper, we extend our previous work in this area and propose an improved, fully automated particle filtering algorithm for the tracking of many subresolution objects in fluorescence microscopy image sequences. It involves a new track management procedure and allows the use of multiple dynamics models. The accuracy and reliability of the algorithm are further improved by applying marginalization concepts. Experiments on synthetic as well as real image data from three different biological applications clearly demonstrate the superiority of the algorithm compared to previous particle filtering solutions.
Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric
2017-12-01
This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.
Gating Techniques for Rao-Blackwellized Monte Carlo Data Association Filter
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Yazhao Wang
2014-01-01
Full Text Available This paper studies the Rao-Blackwellized Monte Carlo data association (RBMCDA filter for multiple target tracking. The elliptical gating strategies are redesigned and incorporated into the framework of the RBMCDA filter. The obvious benefit is the reduction of the time cost because the data association procedure can be carried out with less validated measurements. In addition, the overlapped parts of the neighboring validation regions are divided into several separated subregions according to the possible origins of the validated measurements. In these subregions, the measurement uncertainties can be taken into account more reasonably than those of the simple elliptical gate. This would help to achieve higher tracking ability of the RBMCDA algorithm by a better association prior approximation. Simulation results are provided to show the effectiveness of the proposed gating techniques.
Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation
Semper, Sean R.; Crassidis, John L.; George, Jemin; Mukherjee, Siddharth; Singla, Puneet
2015-01-01
each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in
Multitarget Tracking by Improved Particle Filter Based on Unscented Transform
Directory of Open Access Journals (Sweden)
Yazhao Wang
2013-01-01
Full Text Available This paper considers the problem of multitarget tracking in cluttered environment. To reduce the dependency on the noise priori knowledge, an improved particle filtering (PF data association approach is presented based on the filter (HF. This approach can achieve higher robustness in the condition that the measurement noise prior is unknown. Because of the limitations of the HF in nonlinear tracking, we first present the unscented filter (HUF by embedding the unscented transform (UT into the extended filter (HEF structure. Then the HUF is incorporated into the Rao-Blackwellized particle filter (RBPF framework to update the particles. Simulation results are provided to demonstrate the effectiveness of the proposed algorithms in linear and nonlinear multitarget tracking.
Gibbs Sampler-Based λ-Dynamics and Rao-Blackwell Estimator for Alchemical Free Energy Calculation.
Ding, Xinqiang; Vilseck, Jonah Z; Hayes, Ryan L; Brooks, Charles L
2017-06-13
λ-dynamics is a generalized ensemble method for alchemical free energy calculations. In traditional λ-dynamics, the alchemical switch variable λ is treated as a continuous variable ranging from 0 to 1 and an empirical estimator is utilized to approximate the free energy. In the present article, we describe an alternative formulation of λ-dynamics that utilizes the Gibbs sampler framework, which we call Gibbs sampler-based λ-dynamics (GSLD). GSLD, like traditional λ-dynamics, can be readily extended to calculate free energy differences between multiple ligands in one simulation. We also introduce a new free energy estimator, the Rao-Blackwell estimator (RBE), for use in conjunction with GSLD. Compared with the current empirical estimator, the advantage of RBE is that RBE is an unbiased estimator and its variance is usually smaller than the current empirical estimator. We also show that the multistate Bennett acceptance ratio equation or the unbinned weighted histogram analysis method equation can be derived using the RBE. We illustrate the use and performance of this new free energy computational framework by application to a simple harmonic system as well as relevant calculations of small molecule relative free energies of solvation and binding to a protein receptor. Our findings demonstrate consistent and improved performance compared with conventional alchemical free energy methods.
The Rao-Blackwellized marginal M-SMC filter for Bayesian multi-target tracking and labelling
Aoki, E.H.; Boers, Y.; Svensson, L.; Mandal, Pranab K.; Bagchi, Arunabha
In multi-target tracking (MTT), we are often interested not only in finding the position of the objects, but also allowing individual objects to be uniquely identified with the passage of time, by placing a label on each track. In some situations, however, observability conditions do not allow us to
Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters
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Wen Xu
2016-10-01
Full Text Available Time-varying volatility is common in macroeconomic data and has been incorporated into macroeconomic models in recent work. Dynamic panel data models have become increasingly popular in macroeconomics to study common relationships across countries or regions. This paper estimates dynamic panel data models with stochastic volatility by maximizing an approximate likelihood obtained via Rao-Blackwellized particle filters. Monte Carlo studies reveal the good and stable performance of our particle filter-based estimator. When the volatility of volatility is high, or when regressors are absent but stochastic volatility exists, our approach can be better than the maximum likelihood estimator which neglects stochastic volatility and generalized method of moments (GMM estimators.
A novel particle filter approach for indoor positioning by fusing WiFi and inertial sensors
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Zhu Nan
2015-12-01
Full Text Available WiFi fingerprinting is the method of recording WiFi signal strength from access points (AP along with the positions at which they were recorded, and later matching those to new measurements for indoor positioning. Inertial positioning utilizes the accelerometer and gyroscopes for pedestrian positioning. However, both methods have their limitations, such as the WiFi fluctuations and the accumulative error of inertial sensors. Usually, the filtering method is used for integrating the two approaches to achieve better location accuracy. In the real environments, especially in the indoor field, the APs could be sparse and short range. To overcome the limitations, a novel particle filter approach based on Rao Blackwellized particle filter (RBPF is presented in this paper. The indoor environment is divided into several local maps, which are assumed to be independent of each other. The local areas are estimated by the local particle filter, whereas the global areas are combined by the global particle filter. The algorithm has been investigated by real field trials using a WiFi tablet on hand with an inertial sensor on foot. It could be concluded that the proposed method reduces the complexity of the positioning algorithm obviously, as well as offers a significant improvement in position accuracy compared to other conventional algorithms, allowing indoor positioning error below 1.2 m.
DEFF Research Database (Denmark)
Lehn-Schiøler, Tue; Erdogmus, Deniz; Principe, Jose C.
2004-01-01
Using a Parzen density estimator any distribution can be approximated arbitrarily close by a sum of kernels. In particle filtering this fact is utilized to estimate a probability density function with Dirac delta kernels; when the distribution is discretized it becomes possible to solve an otherw......Using a Parzen density estimator any distribution can be approximated arbitrarily close by a sum of kernels. In particle filtering this fact is utilized to estimate a probability density function with Dirac delta kernels; when the distribution is discretized it becomes possible to solve...
Particle flow superpositional GLMB filter
Saucan, Augustin-Alexandru; Li, Yunpeng; Coates, Mark
2017-05-01
In this paper we propose a Superpositional Marginalized δ-GLMB (SMδ-GLMB) filter for multi-target tracking and we provide bootstrap and particle flow particle filter implementations. Particle filter implementations of the marginalized δ-GLMB filter are computationally demanding. As a first contribution we show that for the specific case of superpositional observation models, a reduced complexity update step can be achieved by employing a superpositional change of variables. The resulting SMδ-GLMB filter can be readily implemented using the unscented Kalman filter or particle filtering methods. As a second contribution, we employ particle flow to produce a measurement-driven importance distribution that serves as a proposal in the SMδ-GLMB particle filter. In high-dimensional state systems or for highly- informative observations the generic particle filter often suffers from weight degeneracy or otherwise requires a prohibitively large number of particles. Particle flow avoids particle weight degeneracy by guiding particles to regions where the posterior is significant. Numerical simulations showcase the reduced complexity and improved performance of the bootstrap SMδ-GLMB filter with respect to the bootstrap Mδ-GLMB filter. The particle flow SMδ-GLMB filter further improves the accuracy of track estimates for highly informative measurements.
Particle Filtering With Invertible Particle Flow
Li, Yunpeng; Coates, Mark
2017-08-01
A key challenge when designing particle filters in high-dimensional state spaces is the construction of a proposal distribution that is close to the posterior distribution. Recent advances in particle flow filters provide a promising avenue to avoid weight degeneracy; particles drawn from the prior distribution are migrated in the state-space to the posterior distribution by solving partial differential equations. Numerous particle flow filters have been proposed based on different assumptions concerning the flow dynamics. Approximations are needed in the implementation of all of these filters; as a result the articles do not exactly match a sample drawn from the desired posterior distribution. Past efforts to correct the discrepancies involve expensive calculations of importance weights. In this paper, we present new filters which incorporate deterministic particle flows into an encompassing particle filter framework. The valuable theoretical guarantees concerning particle filter performance still apply, but we can exploit the attractive performance of the particle flow methods. The filters we describe involve a computationally efficient weight update step, arising because the embedded particle flows we design possess an invertible mapping property. We evaluate the proposed particle flow particle filters' performance through numerical simulations of a challenging multi-target multi-sensor tracking scenario and complex high-dimensional filtering examples.
Law, Kody
2016-01-06
This talk will pertain to the filtering of partially observed diffusions, with discrete-time observations. It is assumed that only biased approximations of the diffusion can be obtained, for choice of an accuracy parameter indexed by l. A multilevel estimator is proposed, consisting of a telescopic sum of increment estimators associated to the successive levels. The work associated to O( 2) mean-square error between the multilevel estimator and average with respect to the filtering distribution is shown to scale optimally, for example as O( 2) for optimal rates of convergence of the underlying diffusion approximation. The method is illustrated on some toy examples as well as estimation of interest rate based on real S&P 500 stock price data.
Gaussian particle flow implementation of PHD filter
Zhao, Lingling; Wang, Junjie; Li, Yunpeng; Coates, Mark J.
2016-05-01
Particle filter and Gaussian mixture implementations of random finite set filters have been proposed to tackle the issue of jointly estimating the number of targets and their states. The Gaussian mixture PHD (GM-PHD) filter has a closed-form expression for the PHD for linear and Gaussian target models, and extensions using the extended Kalman filter or unscented Kalman Filter have been developed to allow the GM-PHD filter to accommodate mildly nonlinear dynamics. Errors resulting from linearization or model mismatch are unavoidable. A particle filter implementation of the PHD filter (PF-PHD) is more suitable for nonlinear and non-Gaussian target models. The particle filter implementations are much more computationally expensive and performance can suffer when the proposal distribution is not a good match to the posterior. In this paper, we propose a novel implementation of the PHD filter named the Gaussian particle flow PHD filter (GPF-PHD). It employs a bank of particle flow filters to approximate the PHD; these play the same role as the Gaussian components in the GM-PHD filter but are better suited to non-linear dynamics and measurement equations. Using the particle flow filter allows the GPF-PHD filter to migrate particles to the dense regions of the posterior, which leads to higher efficiency than the PF-PHD. We explore the performance of the new algorithm through numerical simulations.
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
Field of Particle Filters Image Inpainting
DEFF Research Database (Denmark)
Cuzol, Anne; Pedersen, Kim Steenstrup; Nielsen, Mads
2008-01-01
We present a novel algorithm for solving the image inpainting problem based on a field of locally interacting particle filters. Image inpainting, also known as image completion, is concerned with the problem of filling image regions with new visually plausible data. In order to avoid the difficulty...... of solving the problem globally for the region to be inpainted, we introduce a field of local particle filters. The states of the particle filters are image patches. Global consistency is enforced by a Markov random field image model which connects neighbouring particle filters. The benefit of using locally...... interacting particle filters is that several competing hypotheses on inpainting solutions are kept active, allowing the method to provide globally consistent solutions on problems where other local methods may fail. We provide examples of applications of the developed method. Keywords: Inpainting · Image...
Bridging the ensemble Kalman filter and particle filters
Energy Technology Data Exchange (ETDEWEB)
Stordal, Andreas Stoerksen; Karlsen, Hans A.; Naevdal, Geir; Skaug, Hans J.; Valles, Brice
2009-12-15
The nonlinear filtering problem occurs in many scientific areas. Sequential Monte Carlo solutions with the correct asymptotic behavior such as particle filters exist but they are computationally too expensive when working with high-dimensional systems. The ensemble Kalman filter is a more robust method that has shown promising results with a small sample size but the samples are not guaranteed to come from the true posterior distribution. By approximating the model error with Gaussian kernels we get the advantage of both a Kalman correction and a weighting step. The resulting Gaussian mixture filter has the advantage of both a local Kalman type correction and the weighting/re sampling step of a particle filter. The Gaussian mixture approximation relies on a tunable bandwidth parameter which often has to be kept quite large in order to avoid weight collapse in high dimensions. As a result, the Kalman correction is too large to capture highly non-Gaussian posterior distributions. In this paper we have extended the Gaussian mixture filter (Hoteit et al., 2008b) and also made the connection to particle filters more transparent. In particular we introduce a tuning parameter for the importance weights. In the last part of the paper we have performed a simulation experiment with the Lorenz40 model where our method has been compared to the EnKF and a full implementation of a particle filter. The results clearly indicate that the new method has advantages compared to the standard EnKF. (Author)
Particle Kalman Filtering: A Nonlinear Framework for Ensemble Kalman Filters
Hoteit, Ibrahim
2010-09-19
Optimal nonlinear filtering consists of sequentially determining the conditional probability distribution functions (pdf) of the system state, given the information of the dynamical and measurement processes and the previous measurements. Once the pdfs are obtained, one can determine different estimates, for instance, the minimum variance estimate, or the maximum a posteriori estimate, of the system state. It can be shown that, many filters, including the Kalman filter (KF) and the particle filter (PF), can be derived based on this sequential Bayesian estimation framework. In this contribution, we present a Gaussian mixture‐based framework, called the particle Kalman filter (PKF), and discuss how the different EnKF methods can be derived as simplified variants of the PKF. We also discuss approaches to reducing the computational burden of the PKF in order to make it suitable for complex geosciences applications. We use the strongly nonlinear Lorenz‐96 model to illustrate the performance of the PKF.
Merging particle filter for sequential data assimilation
Directory of Open Access Journals (Sweden)
S. Nakano
2007-07-01
Full Text Available A new filtering technique for sequential data assimilation, the merging particle filter (MPF, is proposed. The MPF is devised to avoid the degeneration problem, which is inevitable in the particle filter (PF, without prohibitive computational cost. In addition, it is applicable to cases in which a nonlinear relationship exists between a state and observed data where the application of the ensemble Kalman filter (EnKF is not effectual. In the MPF, the filtering procedure is performed based on sampling of a forecast ensemble as in the PF. However, unlike the PF, each member of a filtered ensemble is generated by merging multiple samples from the forecast ensemble such that the mean and covariance of the filtered distribution are approximately preserved. This merging of multiple samples allows the degeneration problem to be avoided. In the present study, the newly proposed MPF technique is introduced, and its performance is demonstrated experimentally.
Particle filters for random set models
Ristic, Branko
2013-01-01
“Particle Filters for Random Set Models” presents coverage of state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based on the Monte Carlo statistical method. The resulting algorithms, known as particle filters, in the last decade have become one of the essential tools for stochastic filtering, with applications ranging from navigation and autonomous vehicles to bio-informatics and finance. While particle filters have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. These recent developments have dramatically widened the scope of applications, from single to multiple appearing/disappearing objects, from precise to imprecise measurements and measurement models. This book...
SAR Image Enhancement using Particle Filters
National Aeronautics and Space Administration — In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a...
Efficient particle filtering through residual nudging
Luo, Xiaodong
2013-05-15
We introduce an auxiliary technique, called residual nudging, to the particle filter to enhance its performance in cases where it performs poorly. The main idea of residual nudging is to monitor and, if necessary, adjust the residual norm of a state estimate in the observation space so that it does not exceed a pre-specified threshold. We suggest a rule to choose the pre-specified threshold, and construct a state estimate accordingly to achieve this objective. Numerical experiments suggest that introducing residual nudging to a particle filter may (substantially) improve its performance, in terms of filter accuracy and/or stability against divergence, especially when the particle filter is implemented with a relatively small number of particles. © 2013 Royal Meteorological Society.
An Improved Sequential Smoothing Particle Filtering Method
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Cao Shijie
2017-01-01
Full Text Available In order to cope with the challenges of non-cooperative targets such as stealth targets to modern radar, especially when traditional threshold detection and tracking methods can hardly detect fast-moving stealth targets, technological innovation has long been required. In this paper we have proposed a new algorithm which can reduce computational cost and improve tracking accuracy. Firstly, the number of particles in the traditional particle filter is reduced and a small number of sampling points are derived from the possible distribution of the target to be tracked, each given a proper weight. Then, the transformed sampling points are sequentially smoothed. And finally, the target positions are estimated. The simulation results show that the proposed algorithm is more accurate than the traditional particle filter algorithm and has lower computational complexity. In the case when SNR is between 0dB to 15dB, a total of 100 Monte Carlo simulations are carried out, obtaining a high detection probability. The detection probability of the improved algorithm is higher than that of the existing particle filter at 7dB. Also, the computational cost is lower than the existing particle filter algorithm.
Marginalized Particle Filtering Framework for Tuning of Ensemble Filters
Czech Academy of Sciences Publication Activity Database
Šmídl, Václav; Hofman, Radek
2011-01-01
Roč. 139, č. 11 (2011), s. 3589-3599 ISSN 0027-0644 R&D Projects: GA MV VG20102013018; GA ČR GP102/08/P250 Institutional research plan: CEZ:AV0Z10750506 Keywords : ensemble finter * marginalized particle filter * data assimilation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.688, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/smidl-0367533.pdf
Tracking Deforming Objects using Particle Filtering for Geometric Active Contours
National Research Council Canada - National Science Library
Rathi, Yogesh; Vaswani, Namrata; Tannenbaum, Allen; Yezzi, Anthony
2007-01-01
.... Tracking algorithms using Kalman filters or particle filters have been proposed for finite dimensional representations of shape, but these are dependent on the chosen parametrization and cannot...
Analyzing Meteoroid Flights Using Particle Filters
Sansom, E. K.; Rutten, M. G.; Bland, P. A.
2017-02-01
Fireball observations from camera networks provide position and time information along the trajectory of a meteoroid that is transiting our atmosphere. The complete dynamical state of the meteoroid at each measured time can be estimated using Bayesian filtering techniques. A particle filter is a novel approach to modeling the uncertainty in meteoroid trajectories and incorporates errors in initial parameters, the dynamical model used, and observed position measurements. Unlike other stochastic approaches, a particle filter does not require predefined values for initial conditions or unobservable trajectory parameters. The Bunburra Rockhole fireball, observed by the Australian Desert Fireball Network (DFN) in 2007, is used to determine the effectiveness of a particle filter for use in fireball trajectory modeling. The final mass is determined to be 2.16+/- 1.33 {kg} with a final velocity of 6030+/- 216 {{m}} {{{s}}}-1, similar to previously calculated values. The full automatability of this approach will allow an unbiased evaluation of all events observed by the DFN and lead to a better understanding of the dynamical state and size frequency distribution of asteroid and cometary debris in the inner solar system.
Computationally efficient angles-only tracking with particle flow filters
Costa, Russell; Wettergren, Thomas A.
2015-05-01
Particle filters represent the current state of the art in nonlinear, non-Gaussian filtering. They are easy to implement and have been applied in numerous domains. That being said, particle filters can be impractical for problems with state dimensions greater than four, if some other problem specific efficiencies can't be identified. This "curse of dimensionality" makes particle filters a computationally burdensome approach, and the associated re-sampling makes parallel processing difficult. In the past several years an alternative to particle filters dubbed particle flows has emerged as a (potentially) much more efficient method to solving non-linear, non-Gaussian problems. Particle flow filtering (unlike particle filtering) is a deterministic approach, however, its implementation entails solving an under-determined system of partial differential equations which has infinitely many potential solutions. In this work we apply the filters to angles-only target motion analysis problems in order to quantify the (if any) computational gains over standard particle filtering approaches. In particular we focus on the simplest form of particle flow filter, known as the exact particle flow filter. This form assumes a Gaussian prior and likelihood function of the unknown target states and is then linearized as is standard practice for extended Kalman filters. We implement both particle filters and particle flows and perform numerous numerical experiments for comparison.
A Stable Particle Filter in High-Dimensions
Beskos, Alex; Crisan, Dan; Jasra, Ajay; Kamatani, Kengo; Zhou, Yan
2014-01-01
We consider the numerical approximation of the filtering problem in high dimensions, that is, when the hidden state lies in $\\mathbb{R}^d$ with $d$ large. For low dimensional problems, one of the most popular numerical procedures for consistent inference is the class of approximations termed particle filters or sequential Monte Carlo methods. However, in high dimensions, standard particle filters (e.g. the bootstrap particle filter) can have a cost that is exponential in $d$ for the algorithm...
Particle Filtering Applied to Musical Tempo Tracking
Directory of Open Access Journals (Sweden)
Malcolm D. Macleod
2004-11-01
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.
Distributed SLAM using improved particle filter for mobile robot localization.
Pei, Fujun; Wu, Mei; Zhang, Simin
2014-01-01
The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle filter use in distributed SLAM was improved in two aspects. First, we improved the important function of the local filters in particle filter. The adaptive values were used to replace a set of constants in the computational process of importance function, which improved the robustness of the particle filter. Second, an information fusion method was proposed by mixing the innovation method and the number of effective particles method, which combined the advantages of these two methods. And this paper extends the previously known convergence results for particle filter to prove that improved particle filter converges to the optimal filter in mean square as the number of particles goes to infinity. The experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system to have a better tolerance and robustness.
Distributed SLAM Using Improved Particle Filter for Mobile Robot Localization
Directory of Open Access Journals (Sweden)
Fujun Pei
2014-01-01
Full Text Available The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle filter use in distributed SLAM was improved in two aspects. First, we improved the important function of the local filters in particle filter. The adaptive values were used to replace a set of constants in the computational process of importance function, which improved the robustness of the particle filter. Second, an information fusion method was proposed by mixing the innovation method and the number of effective particles method, which combined the advantages of these two methods. And this paper extends the previously known convergence results for particle filter to prove that improved particle filter converges to the optimal filter in mean square as the number of particles goes to infinity. The experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system to have a better tolerance and robustness.
Implementation and performance of FPGA-accelerated particle flow filter
Charalampidis, Dimitrios; Jilkov, Vesselin P.; Wu, Jiande
2015-09-01
The particle flow filters, proposed by Daum & Hwang, provide a powerful means for density-based nonlinear filtering but their computation is intense and may be prohibitive for real-time applications. This paper proposes a design for superfast implementation of the exact particle flow filter using a field-programmable gate array (FPGA) as a parallel environment to speedup computation. Simulation results from a nonlinear filtering example are presented to demonstrate that using FPGA can dramatically accelerate particle flow filters through parallelization at the expense of a tolerable loss in accuracy as compared to nonparallel implementation.
Nonlinear Adaptive Filters based on Particle Swarm Optimization
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Faten BEN ARFIA
2009-07-01
Full Text Available This paper presents a particle swarm optimization (PSO algorithm to adjust the parameters of the nonlinear filter and to make this type of the filters more powerful for the elimination of the Gaussian noise and also the impulse noise. In this paper we apply the particle swarm optimization to the rational filters and we completed this work with the comparison between our results and other adaptive nonlinear filters like the LMS adaptive median filters and the no-adaptive rational filter.
Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters*
Hoteit, Ibrahim
2012-02-01
This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. The authors show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman filter (PKF). In the PKF, the solution of a nonlinear filtering problem is expressed as the weighted average of an “ensemble of Kalman filters” operating in parallel. Running an ensemble of Kalman filters is, however, computationally prohibitive for realistic atmospheric and oceanic data assimilation problems. For this reason, the authors consider the construction of the PKF through an “ensemble” of ensemble Kalman filters (EnKFs) instead, and call the implementation the particle EnKF (PEnKF). It is shown that different types of the EnKFs can be considered as special cases of the PEnKF. Similar to the situation in the particle filter, the authors also introduce a resampling step to the PEnKF in order to reduce the risk of weights collapse and improve the performance of the filter. Numerical experiments with the strongly nonlinear Lorenz-96 model are presented and discussed.
Non-linear DSGE Models and The Optimized Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper improves the accuracy and speed of particle filtering for non-linear DSGE models with potentially non-normal shocks. This is done by introducing a new proposal distribution which i) incorporates information from new observables and ii) has a small optimization step that minimizes...... the distance to the optimal proposal distribution. A particle filter with this proposal distribution is shown to deliver a high level of accuracy even with relatively few particles, and this filter is therefore much more efficient than the standard particle filter....
Bayesian auxiliary particle filters for estimating neural tuning parameters.
Mountney, John; Sobel, Marc; Obeid, Iyad
2009-01-01
A common challenge in neural engineering is to track the dynamic parameters of neural tuning functions. This work introduces the application of Bayesian auxiliary particle filters for this purpose. Based on Monte-Carlo filtering, Bayesian auxiliary particle filters use adaptive methods to model the prior densities of the state parameters being tracked. The observations used are the neural firing times, modeled here as a Poisson process, and the biological driving signal. The Bayesian auxiliary particle filter was evaluated by simultaneously tracking the three parameters of a hippocampal place cell and compared to a stochastic state point process filter. It is shown that Bayesian auxiliary particle filters are substantially more accurate and robust than alternative methods of state parameter estimation. The effects of time-averaging on parameter estimation are also evaluated.
Human-Manipulator Interface Using Particle Filter
Directory of Open Access Journals (Sweden)
Guanglong Du
2014-01-01
Full Text Available This paper utilizes a human-robot interface system which incorporates particle filter (PF and adaptive multispace transformation (AMT to track the pose of the human hand for controlling the robot manipulator. This system employs a 3D camera (Kinect to determine the orientation and the translation of the human hand. We use Camshift algorithm to track the hand. PF is used to estimate the translation of the human hand. Although a PF is used for estimating the translation, the translation error increases in a short period of time when the sensors fail to detect the hand motion. Therefore, a methodology to correct the translation error is required. What is more, to be subject to the perceptive limitations and the motor limitations, human operator is hard to carry out the high precision operation. This paper proposes an adaptive multispace transformation (AMT method to assist the operator to improve the accuracy and reliability in determining the pose of the robot. The human-robot interface system was experimentally tested in a lab environment, and the results indicate that such a system can successfully control a robot manipulator.
A nested sampling particle filter for nonlinear data assimilation
Elsheikh, Ahmed H.
2014-04-15
We present an efficient nonlinear data assimilation filter that combines particle filtering with the nested sampling algorithm. Particle filters (PF) utilize a set of weighted particles as a discrete representation of probability distribution functions (PDF). These particles are propagated through the system dynamics and their weights are sequentially updated based on the likelihood of the observed data. Nested sampling (NS) is an efficient sampling algorithm that iteratively builds a discrete representation of the posterior distributions by focusing a set of particles to high-likelihood regions. This would allow the representation of the posterior PDF with a smaller number of particles and reduce the effects of the curse of dimensionality. The proposed nested sampling particle filter (NSPF) iteratively builds the posterior distribution by applying a constrained sampling from the prior distribution to obtain particles in high-likelihood regions of the search space, resulting in a reduction of the number of particles required for an efficient behaviour of particle filters. Numerical experiments with the 3-dimensional Lorenz63 and the 40-dimensional Lorenz96 models show that NSPF outperforms PF in accuracy with a relatively smaller number of particles. © 2013 Royal Meteorological Society.
PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE
Directory of Open Access Journals (Sweden)
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.
Generalized Gromov method for stochastic particle flow filters
Daum, Fred; Huang, Jim; Noushin, Arjang
2017-05-01
We describe a new algorithm for stochastic particle flow filters using Gromov's method. We derive a simple exact formula for Q in certain special cases. The purpose of using stochastic particle flow is two fold: improve estimation accuracy of the state vector and improve the accuracy of uncertainty quantification. Q is the covariance matrix of the diffusion for particle flow corresponding to Bayes' rule.
Integrating the Projective Transform with Particle Filtering for Visual Tracking
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Beghdadi A
2011-01-01
Full Text Available This paper presents the projective particle filter, a Bayesian filtering technique integrating the projective transform, which describes the distortion of vehicle trajectories on the camera plane. The characteristics inherent to traffic monitoring, and in particular the projective transform, are integrated in the particle filtering framework in order to improve the tracking robustness and accuracy. It is shown that the projective transform can be fully described by three parameters, namely, the angle of view, the height of the camera, and the ground distance to the first point of capture. This information is integrated in the importance density so as to explore the feature space more accurately. By providing a fine distribution of the samples in the feature space, the projective particle filter outperforms the standard particle filter on different tracking measures. First, the resampling frequency is reduced due to a better fit of the importance density for the estimation of the posterior density. Second, the mean squared error between the feature vector estimate and the true state is reduced compared to the estimate provided by the standard particle filter. Third, the tracking rate is improved for the projective particle filter, hence decreasing track loss.
Simultaneous Eye Tracking and Blink Detection with Interactive Particle Filters
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Mohan M. Trivedi
2008-04-01
Full Text Available We present a system that simultaneously tracks eyes and detects eye blinks. Two interactive particle filters are used for this purpose, one for the closed eyes and the other one for the open eyes. Each particle filter is used to track the eye locations as well as the scales of the eye subjects. The set of particles that gives higher confidence is defined as the primary set and the other one is defined as the secondary set. The eye location is estimated by the primary particle filter, and whether the eye status is open or closed is also decided by the label of the primary particle filter. When a new frame comes, the secondary particle filter is reinitialized according to the estimates from the primary particle filter. We use autoregression models for describing the state transition and a classification-based model for measuring the observation. Tensor subspace analysis is used for feature extraction which is followed by a logistic regression model to give the posterior estimation. The performance is carefully evaluated from two aspects: the blink detection rate and the tracking accuracy. The blink detection rate is evaluated using videos from varying scenarios, and the tracking accuracy is given by comparing with the benchmark data obtained using the Vicon motion capturing system. The setup for obtaining benchmark data for tracking accuracy evaluation is presented and experimental results are shown. Extensive experimental evaluations validate the capability of the algorithm.
Parallelization of Sigma Point and Particle Filters Project
National Aeronautics and Space Administration — Research on utilizing inexpensive and personal-level parallel computing architectures to speed up the implementation of the class of particle filters is proposed....
Model Adaptation for Prognostics in a Particle Filtering Framework
National Aeronautics and Space Administration — One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated....
Turbine Engine Performance Estimation using Particle Filters Project
National Aeronautics and Space Administration — Development of a nonlinear particle filter for engine performance is proposed. The approach employs NASA high-fidelity C-MAPSS40K engine model as the central...
Resampling Algorithms for Particle Filters: A Computational Complexity Perspective
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Miodrag Bolić
2004-11-01
Full Text Available Newly developed resampling algorithms for particle filters suitable for real-time implementation are described and their analysis is presented. The new algorithms reduce the complexity of both hardware and DSP realization through addressing common issues such as decreasing the number of operations and memory access. Moreover, the algorithms allow for use of higher sampling frequencies by overlapping in time the resampling step with the other particle filtering steps. Since resampling is not dependent on any particular application, the analysis is appropriate for all types of particle filters that use resampling. The performance of the algorithms is evaluated on particle filters applied to bearings-only tracking and joint detection and estimation in wireless communications. We have demonstrated that the proposed algorithms reduce the complexity without performance degradation.
Distributed Monte Carlo Information Fusion and Distributed Particle Filtering
2014-08-24
gossip procedure to arrive at a consensus about the likelihoods of particles. The selective gossip procedure shares particles based upon weights. This...focuses commu- nication on the particles that contain the most informa- tion. Oreshkin and Coates (2010) also use a gossip con- sensus approach to...Applied Probability. Chapman and Hall. Üstebay, D., Coates, M., and Rabbat, M. (2011). Dis- tributed auxiliary particle filters using selective gossip . In
Bayesian signal processing classical, modern, and particle filtering methods
Candy, James V
2016-01-01
This book aims to give readers a unified Bayesian treatment starting from the basics (Baye's rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on "Sequential Bayesian Detection," a new section on "Ensemble Kalman Filters" as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to "fill-in-the gaps" of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical "sanity testing" lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed an...
Numerical experiments for Gromov's stochastic particle flow filters
Daum, Fred; Noushin, Arjang; Huang, Jim
2017-05-01
We show the results of numerical experiments for a new algorithm for stochastic particle flow filters designed using Gromov's method. We derive a simple exact formula for Q in certain special cases. The purpose of using stochastic particle flow is two fold: improve estimation accuracy of the state vector and improve the accuracy of uncertainty quantification. Q is the covariance matrix of the diffusion for particle flow corresponding to Bayes' rule.
Designing a Wien Filter Model with General Particle Tracer
Mitchell, John; Hofler, Alicia
2017-09-01
The Continuous Electron Beam Accelerator Facility injector employs a beamline component called a Wien filter which is typically used to select charged particles of a certain velocity. The Wien filter is also used to rotate the polarization of a beam for parity violation experiments. The Wien filter consists of perpendicular electric and magnetic fields. The electric field changes the spin orientation, but also imposes a transverse kick which is compensated for by the magnetic field. The focus of this project was to create a simulation of the Wien filter using General Particle Tracer. The results from these simulations were vetted against machine data to analyze the accuracy of the Wien model. Due to the close agreement between simulation and experiment, the data suggest that the Wien filter model is accurate. The model allows a user to input either the desired electric or magnetic field of the Wien filter along with the beam energy as parameters, and is able to calculate the perpendicular field strength required to keep the beam on axis. The updated model will aid in future diagnostic tests of any beamline component downstream of the Wien filter, and allow users to easily calculate the electric and magnetic fields needed for the filter to function properly. Funding support provided by DOE Office of Science's Student Undergraduate Laboratory Internship program.
Particle filter-based prognostic approach for railway track geometry
Mishra, Madhav; Odelius, Johan; Thaduri, Adithya; Nissen, Arne; Rantatalo, Matti
2017-11-01
Track degradation of ballasted railway track systems has to be measured on a regular basis, and these tracks must be maintained by tamping. Tamping aims to restore the geometry to its original shape to ensure an efficient, comfortable and safe transportation system. To minimize the disturbance introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. This paper proposes a particle filter-based prognostic approach for railway track degradation; this approach is demonstrated by examining different railway switches. The standard deviation of the longitudinal track degradation is studied, and forecasts of the maintenance limit intersection are derived. The particle filter-based prognostic results are compared with the standard regression method results for four railway switches, and the particle filter method shows similar or better result for the four cases. For longer prediction times, the error of the proposed method is equal to or smaller than that of the regression method. The main advantage of the particle filter-based prognostic approach is its ability to generate a probabilistic result based on input parameters with uncertainties. The distributions of the input parameters propagate through the filter, and the remaining useful life is presented using a particle distribution.
Nonlinear data assimilation using synchronization in a particle filter
Rodrigues-Pinheiro, Flavia; Van Leeuwen, Peter Jan
2017-04-01
Current data assimilation methods still face problems in strongly nonlinear cases. A promising solution is a particle filter, which provides a representation of the model probability density function by a discrete set of particles. However, the basic particle filter does not work in high-dimensional cases. The performance can be improved by considering the proposal density freedom. A potential choice of proposal density might come from the synchronisation theory, in which one tries to synchronise the model with the true evolution of a system using one-way coupling via the observations. In practice, an extra term is added to the model equations that damps growth of instabilities on the synchronisation manifold. When only part of the system is observed synchronization can be achieved via a time embedding, similar to smoothers in data assimilation. In this work, two new ideas are tested. First, ensemble-based time embedding, similar to an ensemble smoother or 4DEnsVar is used on each particle, avoiding the need for tangent-linear models and adjoint calculations. Tests were performed using Lorenz96 model for 20, 100 and 1000-dimension systems. Results show state-averaged synchronisation errors smaller than observation errors even in partly observed systems, suggesting that the scheme is a promising tool to steer model states to the truth. Next, we combine these efficient particles using an extension of the Implicit Equal-Weights Particle Filter, a particle filter that ensures equal weights for all particles, avoiding filter degeneracy by construction. Promising results will be shown on low- and high-dimensional Lorenz96 models, and the pros and cons of these new ideas will be discussed.
Model Adaptation for Prognostics in a Particle Filtering Framework
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Bhaskar Saha
2011-01-01
Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.
Model Adaptation for Prognostics in a Particle Filtering Framework
Saha, Bhaskar; Goebel, Kai Frank
2011-01-01
One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.
Fast, parallel implementation of particle filtering on the GPU architecture
Gelencsér-Horváth, Anna; Tornai, Gábor János; Horváth, András; Cserey, György
2013-12-01
In this paper, we introduce a modified cellular particle filter (CPF) which we mapped on a graphics processing unit (GPU) architecture. We developed this filter adaptation using a state-of-the art CPF technique. Mapping this filter realization on a highly parallel architecture entailed a shift in the logical representation of the particles. In this process, the original two-dimensional organization is reordered as a one-dimensional ring topology. We proposed a proof-of-concept measurement on two models with an NVIDIA Fermi architecture GPU. This design achieved a 411- μs kernel time per state and a 77-ms global running time for all states for 16,384 particles with a 256 neighbourhood size on a sequence of 24 states for a bearing-only tracking model. For a commonly used benchmark model at the same configuration, we achieved a 266- μs kernel time per state and a 124-ms global running time for all 100 states. Kernel time includes random number generation on the GPU with curand. These results attest to the effective and fast use of the particle filter in high-dimensional, real-time applications.
Particle loading rates for HVAC filters, heat exchangers, and ducts.
Waring, M S; Siegel, J A
2008-06-01
The rate at which airborne particulate matter deposits onto heating, ventilation, and air-conditioning (HVAC) components is important from both indoor air quality (IAQ) and energy perspectives. This modeling study predicts size-resolved particle mass loading rates for residential and commercial filters, heat exchangers (i.e. coils), and supply and return ducts. A parametric analysis evaluated the impact of different outdoor particle distributions, indoor emission sources, HVAC airflows, filtration efficiencies, coils, and duct system complexities. The median predicted residential and commercial loading rates were 2.97 and 130 g/m(2) month for the filter loading rates, 0.756 and 4.35 g/m(2) month for the coil loading rates, 0.0051 and 1.00 g/month for the supply duct loading rates, and 0.262 g/month for the commercial return duct loading rates. Loading rates are more dependent on outdoor particle distributions, indoor sources, HVAC operation strategy, and filtration than other considered parameters. The results presented herein, once validated, can be used to estimate filter changing and coil cleaning schedules, energy implications of filter and coil loading, and IAQ impacts associated with deposited particles. The results in this paper suggest important factors that lead to particle deposition on HVAC components in residential and commercial buildings. This knowledge informs the development and comparison of control strategies to limit particle deposition. The predicted mass loading rates allow for the assessment of pressure drop and indoor air quality consequences that result from particle mass loading onto HVAC system components.
Groot, S.; Harmanny, R.; Driessen, H.; Yarovoy, A.
2013-01-01
In this article, a novel motion model-based particle filter implementation is proposed to classify human motion and to estimate key state variables, such as motion type, i.e. running or walking, and the subject’s height. Micro-Doppler spectrum is used as the observable information. The system and
Distributed Particle Filter for Target Tracking: With Reduced Sensor Communications
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Tadesse Ghirmai
2016-09-01
Full Text Available For efficient and accurate estimation of the location of objects, a network of sensors can be used to detect and track targets in a distributed manner. In nonlinear and/or non-Gaussian dynamic models, distributed particle filtering methods are commonly applied to develop target tracking algorithms. An important consideration in developing a distributed particle filtering algorithm in wireless sensor networks is reducing the size of data exchanged among the sensors because of power and bandwidth constraints. In this paper, we propose a distributed particle filtering algorithm with the objective of reducing the overhead data that is communicated among the sensors. In our algorithm, the sensors exchange information to collaboratively compute the global likelihood function that encompasses the contribution of the measurements towards building the global posterior density of the unknown location parameters. Each sensor, using its own measurement, computes its local likelihood function and approximates it using a Gaussian function. The sensors then propagate only the mean and the covariance of their approximated likelihood functions to other sensors, reducing the communication overhead. The global likelihood function is computed collaboratively from the parameters of the local likelihood functions using an average consensus filter or a forward-backward propagation information exchange strategy.
Micro-particle filter made in SU-8 for biomedical applications
DEFF Research Database (Denmark)
Noeth, Nadine-Nicole; Keller, Stephan Urs; Fetz, Stefanie
2009-01-01
We have integrated a micro-particle filter in a polymer cantilever to filter micro-particles from a fluid while simultaneously measuring the amount of filtered particles. In a 3,8 mum thick SU-8 cantilever a filter was integrated with pore sizes between 3 and 30 mum. The chip was inserted...... in a microfluidic system and water with differently sized polystyrene beads was pumped through the filter. Particles which are larger than the pore sizes, cannot pass the filter and will increase the flow resistance of the cantilever. With more and more captured particles the cantilever starts to deflect, which can...
A Graphics Processing Unit Implementation of the Particle Filter
Hendeby, Gustaf; Hol, Jeroen; Karlsson, Rickard; Gustafsson, Fredrik
2007-01-01
Modern graphics cards for computers, and especially their graphics processing units (GPUs), are designed for fast rendering of graphics. In order to achieve this GPUs are equipped with a parallel architecture which can be exploited for general-purpose computing on GPU (GPGPU) as a complement to the central processing unit (CPU). In this paper GPGPU techniques are used to make a parallel GPU implementation of state-of-the-art recursive Bayesian estimation using particle filters (PF). The modif...
On-line probabilistic classification with particle filters
DEFF Research Database (Denmark)
Højen-Sørensen, Pedro; de Freitas, N.; Fog, Torben L.
2000-01-01
We apply particle filters to the problem of on-line classification with possibly overlapping classes. This allows us to compute the probabilities of class membership as the classes evolve. Although we adopt neural network classifiers, the work can be extended to any other parametric classification...... scheme. We demonstrate our methodology on a simple example and on the problem of fault detection of dynamically operated marine diesel engines....
Tsai, Candace Su-Jung; Hofmann, Mario; Hallock, Marilyn; Ellenbecker, Michael; Kong, Jing
2015-11-01
This study performed a workplace evaluation of emission control using available air sampling filters and characterized the emitted particles captured in filters. Characterized particles were contained in the exhaust gas released from carbon nanotube (CNT) synthesis using chemical vapor deposition (CVD). Emitted nanoparticles were collected on grids to be analyzed using transmission electron microscopy (TEM). CNT clusters in the exhaust gas were collected on filters for investigation. Three types of filters, including Nalgene surfactant-free cellulose acetate (SFCA), Pall A/E glass fiber, and Whatman QMA quartz filters, were evaluated as emission control measures, and particles deposited in the filters were characterized using scanning transmission electron microscopy (STEM) to further understand the nature of particles emitted from this CNT production. STEM analysis for collected particles on filters found that particles deposited on filter fibers had a similar morphology on all three filters, that is, hydrophobic agglomerates forming circular beaded clusters on hydrophilic filter fibers on the collecting side of the filter. CNT agglomerates were found trapped underneath the filter surface. The particle agglomerates consisted mostly of elemental carbon regardless of the shapes. Most particles were trapped in filters and no particles were found in the exhaust downstream from A/E and quartz filters, while a few nanometer-sized and submicrometer-sized individual particles and filament agglomerates were found downstream from the SFCA filter. The number concentration of particles with diameters from 5 nm to 20 µm was measured while collecting particles on grids at the exhaust piping. Total number concentration was reduced from an average of 88,500 to 700 particle/cm(3) for the lowest found for all filters used. Overall, the quartz filter showed the most consistent and highest particle reduction control, and exhaust particles containing nanotubes were successfully
Local Ensemble Kalman Particle Filters for efficient data assimilation
Robert, Sylvain
2016-01-01
Ensemble methods such as the Ensemble Kalman Filter (EnKF) are widely used for data assimilation in large-scale geophysical applications, as for example in numerical weather prediction (NWP). There is a growing interest for physical models with higher and higher resolution, which brings new challenges for data assimilation techniques because of the presence of non-linear and non-Gaussian features that are not adequately treated by the EnKF. We propose two new localized algorithms based on the Ensemble Kalman Particle Filter (EnKPF), a hybrid method combining the EnKF and the Particle Filter (PF) in a way that maintains scalability and sample diversity. Localization is a key element of the success of EnKFs in practice, but it is much more challenging to apply to PFs. The algorithms that we introduce in the present paper provide a compromise between the EnKF and the PF while avoiding some of the problems of localization for pure PFs. Numerical experiments with a simplified model of cumulus convection based on a...
Independent motion detection with a rival penalized adaptive particle filter
Becker, Stefan; Hübner, Wolfgang; Arens, Michael
2014-10-01
Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic
Channel Tracking Using Particle Filtering in Unresolvable Multipath Environments
Directory of Open Access Journals (Sweden)
Tanya Bertozzi
2004-11-01
Full Text Available We propose a new timing error detector for timing tracking loops inside the Rake receiver in spread spectrum systems. Based on a particle filter, this timing error detector jointly tracks the delays of each path of the frequency-selective channels. Instead of using a conventional channel estimator, we have introduced a joint time delay and channel estimator with almost no additional computational complexity. The proposed scheme avoids the drawback of the classical early-late gate detector which is not able to separate closely spaced paths. Simulation results show that the proposed detectors outperform the conventional early-late gate detector in indoor scenarios.
Localization of acoustic sources using a decentralized particle filter
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Gerstoft Peter
2011-01-01
Full Text Available Abstract This paper addresses the decentralized localization of an acoustic source in a (wireless sensor network based on the underlying partial differential equation (PDE. The PDE is transformed into a distributed state-space model and augmented by a source model. Inferring the source state amounts to a non-linear non-Gaussian Bayesian estimation problem for whose solution we implement a decentralized particle filter (PF operating within and across clusters of sensor nodes. The aggregation of the local posterior distributions from all clusters is achieved via an enhanced version of the maximum consensus algorithm. Numerical simulations illustrate the performance of our scheme.
Hesar, Hamed Danandeh; Mohebbi, Maryam
2017-05-01
In this paper, a model-based Bayesian filtering framework called the "marginalized particle-extended Kalman filter (MP-EKF) algorithm" is proposed for electrocardiogram (ECG) denoising. This algorithm does not have the extended Kalman filter (EKF) shortcoming in handling non-Gaussian nonstationary situations because of its nonlinear framework. In addition, it has less computational complexity compared with particle filter. This filter improves ECG denoising performance by implementing marginalized particle filter framework while reducing its computational complexity using EKF framework. An automatic particle weighting strategy is also proposed here that controls the reliance of our framework to the acquired measurements. We evaluated the proposed filter on several normal ECGs selected from MIT-BIH normal sinus rhythm database. To do so, artificial white Gaussian and colored noises as well as nonstationary real muscle artifact (MA) noise over a range of low SNRs from 10 to -5 dB were added to these normal ECG segments. The benchmark methods were the EKF and extended Kalman smoother (EKS) algorithms which are the first model-based Bayesian algorithms introduced in the field of ECG denoising. From SNR viewpoint, the experiments showed that in the presence of Gaussian white noise, the proposed framework outperforms the EKF and EKS algorithms in lower input SNRs where the measurements and state model are not reliable. Owing to its nonlinear framework and particle weighting strategy, the proposed algorithm attained better results at all input SNRs in non-Gaussian nonstationary situations (such as presence of pink noise, brown noise, and real MA). In addition, the impact of the proposed filtering method on the distortion of diagnostic features of the ECG was investigated and compared with EKF/EKS methods using an ECG diagnostic distortion measure called the "Multi-Scale Entropy Based Weighted Distortion Measure" or MSEWPRD. The results revealed that our proposed
Audiovisual Head Orientation Estimation with Particle Filtering in Multisensor Scenarios
Directory of Open Access Journals (Sweden)
Javier Hernando
2007-07-01
Full Text Available This article presents a multimodal approach to head pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video conferencing. Determining the individuals head orientation is the basis for many forms of more sophisticated interactions between humans and technical devices and can also be used for automatic sensor selection (camera, microphone in communications or video surveillance systems. The use of particle filters as a unified framework for the estimation of the head orientation for both monomodal and multimodal cases is proposed. In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras. Audio information is processed to estimate the direction of the voice produced by a speaker making use of the directivity characteristics of the head radiation pattern. Furthermore, two different particle filter multimodal information fusion schemes for combining the audio and video streams are analyzed in terms of accuracy and robustness. In the first one, fusion is performed at a decision level by combining each monomodal head pose estimation, while the second one uses a joint estimation system combining information at data level. Experimental results conducted over the CLEAR 2006 evaluation database are reported and the comparison of the proposed multimodal head pose estimation algorithms with the reference monomodal approaches proves the effectiveness of the proposed approach.
Nonlinear EEG Decoding Based on a Particle Filter Model
Directory of Open Access Journals (Sweden)
Jinhua Zhang
2014-01-01
Full Text Available While the world is stepping into the aging society, rehabilitation robots play a more and more important role in terms of both rehabilitation treatment and nursing of the patients with neurological diseases. Benefiting from the abundant contents of movement information, electroencephalography (EEG has become a promising information source for rehabilitation robots control. Although the multiple linear regression model was used as the decoding model of EEG signals in some researches, it has been considered that it cannot reflect the nonlinear components of EEG signals. In order to overcome this shortcoming, we propose a nonlinear decoding model, the particle filter model. Two- and three-dimensional decoding experiments were performed to test the validity of this model. In decoding accuracy, the results are comparable to those of the multiple linear regression model and previous EEG studies. In addition, the particle filter model uses less training data and more frequency information than the multiple linear regression model, which shows the potential of nonlinear decoding models. Overall, the findings hold promise for the furtherance of EEG-based rehabilitation robots.
Joint Audio-Visual Tracking Using Particle Filters
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Dmitry N. Zotkin
2002-11-01
Full Text Available It is often advantageous to track objects in a scene using multimodal information when such information is available. We use audio as a complementary modality to video data, which, in comparison to vision, can provide faster localization over a wider field of view. We present a particle-filter based tracking framework for performing multimodal sensor fusion for tracking people in a videoconferencing environment using multiple cameras and multiple microphone arrays. One advantage of our proposed tracker is its ability to seamlessly handle temporary absence of some measurements (e.g., camera occlusion or silence. Another advantage is the possibility of self-calibration of the joint system to compensate for imprecision in the knowledge of array or camera parameters by treating them as containing an unknown statistical component that can be determined using the particle filter framework during tracking. We implement the algorithm in the context of a videoconferencing and meeting recording system. The system also performs high-level semantic analysis of the scene by keeping participant tracks, recognizing turn-taking events and recording an annotated transcript of the meeting. Experimental results are presented. Our system operates in real-time and is shown to be robust and reliable.
Audiovisual Head Orientation Estimation with Particle Filtering in Multisensor Scenarios
Canton-Ferrer, Cristian; Segura, Carlos; Casas, Josep R.; Pardàs, Montse; Hernando, Javier
2007-12-01
This article presents a multimodal approach to head pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video conferencing. Determining the individuals head orientation is the basis for many forms of more sophisticated interactions between humans and technical devices and can also be used for automatic sensor selection (camera, microphone) in communications or video surveillance systems. The use of particle filters as a unified framework for the estimation of the head orientation for both monomodal and multimodal cases is proposed. In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras. Audio information is processed to estimate the direction of the voice produced by a speaker making use of the directivity characteristics of the head radiation pattern. Furthermore, two different particle filter multimodal information fusion schemes for combining the audio and video streams are analyzed in terms of accuracy and robustness. In the first one, fusion is performed at a decision level by combining each monomodal head pose estimation, while the second one uses a joint estimation system combining information at data level. Experimental results conducted over the CLEAR 2006 evaluation database are reported and the comparison of the proposed multimodal head pose estimation algorithms with the reference monomodal approaches proves the effectiveness of the proposed approach.
Multi-prediction particle filter for efficient parallelized implementation
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Chu Chun-Yuan
2011-01-01
Full Text Available Abstract Particle filter (PF is an emerging signal processing methodology, which can effectively deal with nonlinear and non-Gaussian signals by a sample-based approximation of the state probability density function. The particle generation of the PF is a data-independent procedure and can be implemented in parallel. However, the resampling procedure in the PF is a sequential task in natural and difficult to be parallelized. Based on the Amdahl's law, the sequential portion of a task limits the maximum speed-up of the parallelized implementation. Moreover, large particle number is usually required to obtain an accurate estimation, and the complexity of the resampling procedure is highly related to the number of particles. In this article, we propose a multi-prediction (MP framework with two selection approaches. The proposed MP framework can reduce the required particle number for target estimation accuracy, and the sequential operation of the resampling can be reduced. Besides, the overhead of the MP framework can be easily compensated by parallel implementation. The proposed MP-PF alleviates the global sequential operation by increasing the local parallel computation. In addition, the MP-PF is very suitable for multi-core graphics processing unit (GPU platform, which is a popular parallel processing architecture. We give prototypical implementations of the MP-PFs on multi-core GPU platform. For the classic bearing-only tracking experiments, the proposed MP-PF can be 25.1 and 15.3 times faster than the sequential importance resampling-PF with 10,000 and 20,000 particles, respectively. Hence, the proposed MP-PF can enhance the efficiency of the parallelization.
A novel particle SGS model based on differential filter for LES of particle-laden turbulent flows
Park, George; Urzay, Javier; Moin, Parviz
2015-11-01
When performing LES of particle-turbulence interactions, proper modelling of the effect of subgrid-scale (SGS) fluid motions on the particle dynamics is critical for accurate prediction of particle dispersion. Existing particle SGS models recover the missing SGS fluid velocities required in the particle equation of motion by assuming stochastic evolution of SGS fluctuations seen by particles, or by deconvolving the LES solution with an approximate inverse of the filter. In this study, we investigate the use of the differential filter for deconvolution-based particle SGS modelling. Deconvolution with a differential filter is potentially an attractive alternative to the existing Pade-filter based approximate deconvolution techniques. Exact deconvolution can be done trivially with differential filter, because the filter is defined in the inverse-filter form, and the method can be easily extended to unstructured grids. LES of one-way coupled particle-turbulence interaction in isotropic turbulence is performed, and model performance is analysed in terms of particle dispersion statistics. A dynamic procedure for determining the coefficient related to the filter width is under development, and the resulting formulation will be compared to constant coefficient models. This study was supported by DOE PSAAP2 Program.
Drinovec, Luka; Gregorič, Asta; Zotter, Peter; Wolf, Robert; Bruns, Emily Anne; Prévôt, André S. H.; Petit, Jean-Eudes; Favez, Olivier; Sciare, Jean; Arnold, Ian J.; Chakrabarty, Rajan K.; Moosmüller, Hans; Filep, Agnes; Močnik, Griša
2017-03-01
Black carbon is a primary aerosol tracer for high-temperature combustion emissions and can be used to characterize the time evolution of its sources. It is correlated with a decrease in public health and contributes to atmospheric warming. Black carbon measurements are usually conducted with absorption filter photometers, which are prone to several artifacts, including the filter-loading effect - a saturation of the instrumental response due to the accumulation of the sample in the filter matrix. In this paper, we investigate the hypothesis that this filter-loading effect depends on the optical properties of particles present in the filter matrix, especially on the black carbon particle coating. We conducted field campaigns in contrasting environments to determine the influence of source characteristics, particle age and coating on the magnitude of the filter-loading effect. High-time-resolution measurements of the filter-loading parameter in filter absorption photometers show daily and seasonal variations of the effect. The variation is most pronounced in the near-infrared region, where the black carbon mass concentration is determined. During winter, the filter-loading parameter value increases with the absorption Ångström exponent. It is suggested that this effect is related to the size of the black carbon particle core as the wood burning (with higher values of the absorption Ångström exponent) produces soot particles with larger diameters. A reduction of the filter-loading effect is correlated with the availability of the coating material. As the coating of ambient aerosols is reduced or removed, the filter-loading parameter increases. Coatings composed of ammonium sulfate and secondary organics seem to be responsible for the variation of the loading effect. The potential source contribution function analysis shows that high values of the filter-loading parameter in the infrared are indicative of local pollution, whereas low values of the filter
Kabrein, H.; Hariri, A.; Leman, A. M.; Noraini, N. M. R.; Yusof, M. Z. M.; Afandi, A.
2017-09-01
Heating ventilation and air conditioning system (HVAC) is very important for offices building and human health. The combining filter method was used to reduce the air pollution indoor such as that particulate matter and gases pollution that affected in health and productivity. Using particle filters in industrial HVAC systems (factories and manufacturing process) does not enough to remove all the indoor pollution. The main objective of this study is to investigate the impact of combination filters for particle and gases removal efficiency. The combining method is by using two filters (particulate filter pre-filter and carbon filter) to reduce particle matter and gases respectively. The purpose of this study is to use minimum efficiency reporting value (MERV filter) rating 13 and activated carbon filter (ACF) to remove indoor air pollution and controlling the air change rate to enhance the air quality and energy saving. It was concluded that the combination filter showed good removal efficiency of particle up to 90.76% and 89.25% for PM10 and PM2.5 respectively. The pressure drop across the filters was small compared with the high-efficiency filters. The filtration efficiency of combination filters after three months’ was better than efficiency by the new MERV filter alone.
Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm
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Hyun-Tae Cho
2016-01-01
Full Text Available Due to the growing number of vehicles using the national road networks that link major urban centers, traffic noise is becoming a major issue in relation to the transportation system. Thus, it is important to determine noise model parameters to predict road traffic noise levels as part of an environmental assessment, according to traffic volume and pavement surface type. To determine the parameters of a noise prediction model, statistical pass-by and close proximity tests are required. This paper provides a parameter determination procedure for noise prediction models through an adaptive particle filter (PF algorithm, based on using a weigh-in-motion system, which obtains vehicle velocities and types, as well as step-up microphones, which measure the combined noises emitted by various vehicle types. Finally, an evaluation of the adaptive noise parameter determination algorithm was carried out to assess the agreement between predictions and measurements.
Modular particle filtering FPGA hardware architecture for brain machine interfaces.
Mountney, John; Obeid, Iyad; Silage, Dennis
2011-01-01
As the computational complexities of neural decoding algorithms for brain machine interfaces (BMI) increase, their implementation through sequential processors becomes prohibitive for real-time applications. This work presents the field programmable gate array (FPGA) as an alternative to sequential processors for BMIs. The reprogrammable hardware architecture of the FPGA provides a near optimal platform for performing parallel computations in real-time. The scalability and reconfigurability of the FPGA accommodates diverse sets of neural ensembles and a variety of decoding algorithms. Throughput is significantly increased by decomposing computations into independent parallel hardware modules on the FPGA. This increase in throughput is demonstrated through a parallel hardware implementation of the auxiliary particle filtering signal processing algorithm.
Numerical simulation of DPF filter for selected regimes with deposited soot particles
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Kovařík Petr
2012-04-01
Full Text Available For the purpose of accumulation of particulate matter from Diesel engine exhaust gas, particle filters are used (referred to as DPF or FAP filters in the automotive industry. However, the cost of these filters is quite high. As the emission limits become stricter, the requirements for PM collection are rising accordingly. Particulate matters are very dangerous for human health and these are not invisible for human eye. They can often cause various diseases of the respiratory tract, even what can cause lung cancer. Performed numerical simulations were used to analyze particle filter behavior under various operating modes. The simulations were especially focused on selected critical states of particle filter, when engine is switched to emergency regime. The aim was to prevent and avoid critical situations due the filter behavior understanding. The numerical simulations were based on experimental analysis of used diesel particle filters.
Energy Technology Data Exchange (ETDEWEB)
Kohl, M.; Larsen, Thommy; Carlsen, Kirsten; Mulvad Jeppesen, L.
2006-09-15
Emission of particles into the atmosphere is one of the biggest air pollution problems of our times. The emission of particles causes severe health problems such as respiratory and circulatory diseases, lung cancer, asthma, bronchitis and even causes premature deaths. The emission of particles comes from a number of different sources, where traffic is a considerable contributor. The effects of particle emissions from the traffic on the population are substantial, as the emission comes from mobile sources which create a high local pollution in city areas and in consequence high exposure of the local population. Exhaust particle emissions come mainly from diesel engines, and the introduction of particle filters would have a considerable impact on particle emissions. Vehicle emissions regulation is controlled by the EU. The coming emission regulation, EURO 5, is expected to be put into effect by the beginning of 2010. The current suggestions for the EURO 5 restrictions on particles are set so strict that they will be impossible to fulfil without a particle filter. This report performs a socio-economic analysis on the introduction of particle filters on all light vehicles (<3,500 kg). The analysis assumes that all newly registered diesel powered cars and vans should have a factory installed particle filter from the beginning of 2007. This thereby gives a period of three years before implementation of the EURO 5. (au)
Daum, Fred; Huang, Jim
2016-05-01
We describe many open problems for research in particle flows to compute Bayes' rule for nonlinear filters, Bayesian decisions and Bayesian learning as well as transport. Particle flow mitigates particle degeneracy, which is the main cause of the curse of dimensionality for particle filters. Particle flow filters are many orders of magnitude faster to compute in real time compared with standard particle filters for the same accuracy for difficult high dimensional problems.
Multi-target Particle Filter Tracking Algorithm Based on Wireless Sensor Networks
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Liu Hong-Xia
2014-05-01
Full Text Available In order to improve the multi-target tracking efficiency for wireless sensor networks and solve the problem of data transmission, analyzed existing particle filter tracking algorithm, ensure that one of the core technology for wireless sensor network performance. In this paper, from the basic theory of target tracking, in-depth analysis on the basis of the principle of particle filter, based on dynamic clustering, proposed the multi-target Kalman particle filter (MEPF algorithm, through the expansion of Calman filter (EKF to generate the proposal distribution, a reduction in the required number of particles to improve the particle filter accuracy at the same time, reduce the computational complexity of target tracking algorithm, thus reducing the energy consumption. Application results show that the MEPF in the proposed algorithm can achieve better tracking of target tracking and forecasting, in a small number of particles still has good tracking accuracy.
Particle filtering based structural assessment with acoustic emission sensing
Yan, Wuzhao; Abdelrahman, Marwa; Zhang, Bin; Ziehl, Paul
2017-02-01
Nuclear structures are designed to withstand severe loading events under various stresses. Over time, aging of structural systems constructed with concrete and steel will occur. This deterioration may reduce service life of nuclear facilities and/or lead to unnecessary or untimely repairs. Therefore, online monitoring of structures in nuclear power plants and waste storage has drawn significant attention in recent years. Of many existing non-destructive evaluation and structural monitoring approaches, acoustic emission is promising for assessment of structural damage because it is non-intrusive and is sensitive to corrosion and crack growth in reinforced concrete elements. To provide a rapid, actionable, and graphical means for interpretation Intensity Analysis plots have been developed. This approach provides a means for classification of damage. Since the acoustic emission measurement is only an indirect indicator of structural damage, potentially corrupted by non-genuine data, it is more suitable to estimate the states of corrosion and cracking in a Bayesian estimation framework. In this paper, we will utilize the accelerated corrosion data from a specimen at the University of South Carolina to develop a particle filtering-based diagnosis and prognosis algorithm. Promising features of the proposed algorithm are described in terms of corrosion state estimation and prediction of degradation over time to a predefined threshold.
Nonlinear Vibration Signal Tracking of Large Offshore Bridge Stayed Cable Based on Particle Filter
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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.
Ultrafine particle removal by residential heating, ventilating, and air-conditioning filters.
Stephens, B; Siegel, J A
2013-12-01
This work uses an in situ filter test method to measure the size-resolved removal efficiency of indoor-generated ultrafine particles (approximately 7-100 nm) for six new commercially available filters installed in a recirculating heating, ventilating, and air-conditioning (HVAC) system in an unoccupied test house. The fibrous HVAC filters were previously rated by the manufacturers according to ASHRAE Standard 52.2 and ranged from shallow (2.5 cm) fiberglass panel filters (MERV 4) to deep-bed (12.7 cm) electrostatically charged synthetic media filters (MERV 16). Measured removal efficiency ranged from 0 to 10% for most ultrafine particles (UFP) sizes with the lowest rated filters (MERV 4 and 6) to 60-80% for most UFP sizes with the highest rated filter (MERV 16). The deeper bed filters generally achieved higher removal efficiencies than the panel filters, while maintaining a low pressure drop and higher airflow rate in the operating HVAC system. Assuming constant efficiency, a modeling effort using these measured values for new filters and other inputs from real buildings shows that MERV 13-16 filters could reduce the indoor proportion of outdoor UFPs (in the absence of indoor sources) by as much as a factor of 2-3 in a typical single-family residence relative to the lowest efficiency filters, depending in part on particle size. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
An improved particle filtering algorithm for aircraft engine gas-path fault diagnosis
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Qihang Wang
2016-07-01
Full Text Available In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.
Cantilever-based micro-particle filter with simultaneous single particle detection
DEFF Research Database (Denmark)
Noeth, Nadine-Nicole; Keller, Stephan Sylvest; Boisen, Anja
2011-01-01
-particles from a liquid. A hole-array is integrated into a micro-cantilever, which is inserted into a microfluidic channel perpendicular to the flow. A metal pad at the apex of the cantilever enables an optical read-out of the deflection of the cantilever. When a micro-particle is too large to pass a hole...... in the cantilever, clogging of the holes increases the flow resistance of the cantilever. This causes a bending of the device, which can be detected by the optical read-out system. By arranging an array of such cantilevers with different hole sizes, separation by size can be achieved. In this paper a proof...... of concept of the device is demonstrated by filtering and counting 20 mu m polystyrene beads dispersed in an aqueous solution....
An efficient multiple particle filter based on the variational Bayesian approach
Ait-El-Fquih, Boujemaa
2015-12-07
This paper addresses the filtering problem in large-dimensional systems, in which conventional particle filters (PFs) remain computationally prohibitive owing to the large number of particles needed to obtain reasonable performances. To overcome this drawback, a class of multiple particle filters (MPFs) has been recently introduced in which the state-space is split into low-dimensional subspaces, and then a separate PF is applied to each subspace. In this paper, we adopt the variational Bayesian (VB) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs to be generated. In a numerical test, the proposed VBMPF behaves better than the PF and MPF.
Energy Technology Data Exchange (ETDEWEB)
Yang, Juan; Stewart, Marc; Maupin, Gary D.; Herling, Darrell R.; Zelenyuk, Alla
2009-04-15
Diesel offers higher fuel efficiency, but produces higher exhaust particulate matter. Diesel particulate filters are presently the most efficient means to reduce these emissions. These filters typically trap particles in two basic modes: at the beginning of the exposure cycle the particles are captured in the filter holes, and at longer times the particles form a "cake" on which particles are trapped. Eventually the "cake" removed by oxidation and the cycle is repeated. We have investigated the properties and behavior of two commonly used filters: silicon carbide (SiC) and cordierite (DuraTrap® RC) by exposing them to nearly-spherical ammonium sulfate particles. We show that the transition from deep bed filtration to "cake" filtration can easily be identified by recording the change in pressure across the filters as a function of exposure. We investigated performance of these filters as a function of flow rate and particle size. The filters trap small and large particles more efficiently than particles that are ~80 to 200 nm in aerodynamic diameter. A comparison between the experimental data and a simulation using incompressible lattice-Boltzmann model shows very good qualitative agreement, but the model overpredicts the filter’s trapping efficiency.
National Research Council Canada - National Science Library
Salman, H
2008-01-01
.... To illustrate the main advantages of our formulation over existing filters, we compare our method to the perturbed observation Ensemble Kalman filter and a particle filter with Gaussian resampling...
MapReduce particle filtering with exact resampling and deterministic runtime
Thiyagalingam, Jeyarajan; Kekempanos, Lykourgos; Maskell, Simon
2017-12-01
Particle filtering is a numerical Bayesian technique that has great potential for solving sequential estimation problems involving non-linear and non-Gaussian models. Since the estimation accuracy achieved by particle filters improves as the number of particles increases, it is natural to consider as many particles as possible. MapReduce is a generic programming model that makes it possible to scale a wide variety of algorithms to Big data. However, despite the application of particle filters across many domains, little attention has been devoted to implementing particle filters using MapReduce. In this paper, we describe an implementation of a particle filter using MapReduce. We focus on a component that what would otherwise be a bottleneck to parallel execution, the resampling component. We devise a new implementation of this component, which requires no approximations, has O( N) spatial complexity and deterministic O((log N)2) time complexity. Results demonstrate the utility of this new component and culminate in consideration of a particle filter with 224 particles being distributed across 512 processor cores.
Particle filtering with path sampling and an application to a bimodal ocean current model
Weare, Jonathan
2009-07-01
This paper introduces a recursive particle filtering algorithm designed to filter high dimensional systems with complicated non-linear and non-Gaussian effects. The method incorporates a parallel marginalization (PMMC) step in conjunction with the hybrid Monte Carlo (HMC) scheme to improve samples generated by standard particle filters. Parallel marginalization is an efficient Markov chain Monte Carlo (MCMC) strategy that uses lower dimensional approximate marginal distributions of the target distribution to accelerate equilibration. As a validation the algorithm is tested on a 2516 dimensional, bimodal, stochastic model motivated by the Kuroshio current that runs along the Japanese coast. The results of this test indicate that the method is an attractive alternative for problems that require the generality of a particle filter but have been inaccessible due to the limitations of standard particle filtering strategies.
Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua
2017-05-01
With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.
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Cui Jia
2017-05-01
Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.
A particle filtering approach for spatial arrival time tracking in ocean acoustics.
Jain, Rashi; Michalopoulou, Zoi-Heleni
2011-06-01
The focus of this work is on arrival time and amplitude estimation from acoustic signals recorded at spatially separated hydrophones in the ocean. A particle filtering approach is developed that treats arrival times as "targets" and tracks their "location" across receivers, also modeling arrival time gradient. The method is evaluated via Monte Carlo simulations and is compared to a maximum likelihood estimator, which does not relate arrivals at neighboring receivers. The comparison demonstrates a significant advantage in using the particle filter. It is also shown that posterior probability density functions of times and amplitudes become readily available with particle filtering. © 2011 Acoustical Society of America
Effects of Na and Ca on particle size; Effect of filtering on UV absorbance
U.S. Environmental Protection Agency — Effects of Na and Ca on particle size; Effect of filtering on UV absorbance. This dataset is associated with the following publication: Bouchard, D., C. Knightes, X....
Ramesh, Nisha; Tasdizen, Tolga
2014-10-01
Bayesian frameworks are commonly used in tracking algorithms. An important example is the particle filter, where a stochastic motion model describes the evolution of the state, and the observation model relates the noisy measurements to the state. Particle filters have been used to track the lineage of cells. Propagating the shape model of the cell through the particle filter is beneficial for tracking. We approximate arbitrary shapes of cells with a novel implicit convex function. The importance sampling step of the particle filter is defined using the cost associated with fitting our implicit convex shape model to the observations. Our technique is capable of tracking the lineage of cells for nonmitotic stages. We validate our algorithm by tracking the lineage of retinal and lens cells in zebrafish embryos.
Advances in Uncertainty Representation and Management for Particle Filtering Applied to Prognostics
National Aeronautics and Space Administration — Particle filters (PF) have been established as the de facto state of the art in failure prognosis. They combine advantages of the rigors of Bayesian estimation to...
Directory of Open Access Journals (Sweden)
S. J. Noh
2011-10-01
Full Text Available Data assimilation techniques have received growing attention due to their capability to improve prediction. Among various data assimilation techniques, sequential Monte Carlo (SMC methods, known as "particle filters", are a Bayesian learning process that has the capability to handle non-linear and non-Gaussian state-space models. In this paper, we propose an improved particle filtering approach to consider different response times of internal state variables in a hydrologic model. The proposed method adopts a lagged filtering approach to aggregate model response until the uncertainty of each hydrologic process is propagated. The regularization with an additional move step based on the Markov chain Monte Carlo (MCMC methods is also implemented to preserve sample diversity under the lagged filtering approach. A distributed hydrologic model, water and energy transfer processes (WEP, is implemented for the sequential data assimilation through the updating of state variables. The lagged regularized particle filter (LRPF and the sequential importance resampling (SIR particle filter are implemented for hindcasting of streamflow at the Katsura catchment, Japan. Control state variables for filtering are soil moisture content and overland flow. Streamflow measurements are used for data assimilation. LRPF shows consistent forecasts regardless of the process noise assumption, while SIR has different values of optimal process noise and shows sensitive variation of confidential intervals, depending on the process noise. Improvement of LRPF forecasts compared to SIR is particularly found for rapidly varied high flows due to preservation of sample diversity from the kernel, even if particle impoverishment takes place.
Array of micro-machined mass energy micro-filters for charged particles
Stalder, Roland E. (Inventor); Van Zandt, Thomas R. (Inventor); Hecht, Michael H. (Inventor); Grunthaner, Frank J. (Inventor)
1996-01-01
An energy filter for charged particles includes a stack of micro-machined wafers including plural apertures passing through the stack of wafers, focusing electrodes bounding charged particle paths through the apertures, an entrance orifice to each of the plural apertures and an exit orifice from each of the plural apertures and apparatus for biasing the focusing electrodes with an electrostatic potential corresponding to an energy pass band of the filter.
Interacting multiple-models, state augmented Particle Filtering for fault diagnostics
Compare, Michele; Baraldi, Piero; Turati, Pietro; Zio, Enrico
2015-01-01
International audience; Particle Filtering (PF) is a model-based, filtering technique, which has drawn the attention of the Prognostic and Health Management (PHM) community due to its applicability to nonlinear models with non-additive and non-Gaussian noise. When multiple physical models can describe the evolution of the degradation of a component, the PF approach can be based on Multiple Swarms (MS) of particles, each one evolving according to a different model, from which to select the mos...
A fast ellipse extended target PHD filter using box-particle implementation
Zhang, Yongquan; Ji, Hongbing; Hu, Qi
2018-01-01
This paper presents a box-particle implementation of the ellipse extended target probability hypothesis density (ET-PHD) filter, called the ellipse extended target box particle PHD (EET-BP-PHD) filter, where the extended targets are described as a Poisson model developed by Gilholm et al. and the term ;box; is here equivalent to the term ;interval; used in interval analysis. The proposed EET-BP-PHD filter is capable of dynamically tracking multiple ellipse extended targets and estimating the target states and the number of targets, in the presence of clutter measurements, false alarms and missed detections. To derive the PHD recursion of the EET-BP-PHD filter, a suitable measurement likelihood is defined for a given partitioning cell, and the main implementation steps are presented along with the necessary box approximations and manipulations. The limitations and capabilities of the proposed EET-BP-PHD filter are illustrated by simulation examples. The simulation results show that a box-particle implementation of the ET-PHD filter can avoid the high number of particles and reduce computational burden, compared to a particle implementation of that for extended target tracking.
A nowcasting technique based on application of the particle filter blending algorithm
Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai
2017-10-01
To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.
Particle emission characteristics of filter-equipped vacuum cleaners.
Trakumas, S; Willeke, K; Grinshpun, S A; Reponen, T; Mainelis, G; Friedman, W
2001-01-01
Industrial vacuum cleaners with final high-efficiency particulate air (HEPA) filters traditionally have been used for cleanup operations in which all of the nozzle-entrained dust must be collected with high efficiency, for example, after lead-based paint abatement in homes. In this study household vacuum cleaners ranging from $70 to $650 and an industrial vacuum cleaner costing more than $1400 were evaluated relative to their collection efficiency immediately after installing new primary dust collectors in them. Using newly developed testing technology, some of the low-cost household vacuum cleaners equipped with a final HEPA filter were found to have initial overall filtration efficiencies comparable to those of industrial vacuum cleaners equipped with a final HEPA filter. The household vacuum cleaners equipped with a final HEPA filter efficiently collect about 100% of the dry dust entrained by the nozzle. For extensive cleaning efforts and for vacuum cleaning of wet surfaces, however, industrial vacuum cleaners may have an advantage, including ruggedness and greater loading capacity. The methods and findings of this study are applicable to field evaluations of vacuum cleaners.
NASAL FILTERING OF FINE PARTICLES IN CHILDREN VS. ADULTS
Nasal efficiency for removing fine particles may be affected by developmental changes in nasal structure associated with age. In healthy Caucasian children (age 6-13, n=17) and adults (age 18-28, n=11) we measured the fractional deposition (DF) of fine particles (1 and 2um MMAD)...
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.
Numerical study of particle capture efficiency in fibrous filter
Directory of Open Access Journals (Sweden)
Fan Jianhua
2017-01-01
Full Text Available Numerical simulations are performed for transport and deposition of particles over a fixed obstacle in a fluid flow. The effect of particle size and Stokes number on the particle capture efficiency is investigated using two methods. The first one is one-way coupling combining Lattice Boltzmann (LB method with Lagrangian point-like approach. The second one is two-way coupling based on the coupling between Lattice Boltzmann method and discrete element (DE method, which consider the particle influence on the fluid. Then the single fiber collection efficiency characterized by Stokes number (St are simulated by LB-DE methods. Results show that two-way coupling method is more appropriate in our case for particles larger than 8 μm. A good agreement has also been observed between our simulation results and existing correlations for single fiber collection efficiency. The numerical simulations presented in this work are useful to understand the particle transport and deposition and to predict the capture efficiency.
Energy Technology Data Exchange (ETDEWEB)
Viswanathan, Sandeep; Rothamer, David; Zelenyuk, Alla; Stewart, Mark; Bell, David
2017-11-01
The impact of inlet particle properties on the filtration performance of clean and particulate matter (PM) laden cordierite filter samples was evaluated using PM generated by a spark-ignition direct-injection (SIDI) engine fuelled with tier II EEE certification gasoline. Prior to the filtration experiments, a scanning mobility particle spectrometer (SMPS) was used to measure the electrical-mobility based particle size distribution (PSD) in the SIDI exhaust from distinct engine operating conditions. An advanced aerosol characterization system that comprised of a centrifugal particle mass analyser (CPMA), a differential mobility analyser (DMA), and a single particle mass spectrometer (SPLAT II) was used to obtain additional information on the SIDI particulate, including particle composition, mass, and dynamic shape factors (DSFs) in the transition () and free-molecular () flow regimes. During the filtration experiments, real-time measurements of PSDs upstream and downstream of the filter sample were used to estimate the filtration performance and the total trapped mass within the filter using an integrated particle size distribution method. The filter loading process was paused multiple times to evaluate the filtration performance in the partially loaded state. The change in vacuum aerodynamic diameter () distribution of mass-selected particles was examined for flow through the filter to identify whether preferential capture of particles of certain shapes occurred in the filter. The filter was also probed using different inlet PSDs to understand their impact on particle capture within the filter sample. Results from the filtration experiment suggest that pausing the filter loading process and subsequently performing the filter probing experiments did not impact the overall evolution of filtration performance. Within the present distribution of particle sizes, filter efficiency was independent of particle shape potentially due to the diffusion-dominant filtration
Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper shows how non-linear DSGE models with potential non-normal shocks can be estimated by Quasi-Maximum Likelihood based on the Central Difference Kalman Filter (CDKF). The advantage of this estimator is that evaluating the quasi log-likelihood function only takes a fraction of a second...
A Gaussian process guided particle filter for tracking 3D human pose in video.
Sedai, Suman; Bennamoun, Mohammed; Huynh, Du Q
2013-11-01
In this paper, we propose a hybrid method that combines Gaussian process learning, a particle filter, and annealing to track the 3D pose of a human subject in video sequences. Our approach, which we refer to as annealed Gaussian process guided particle filter, comprises two steps. In the training step, we use a supervised learning method to train a Gaussian process regressor that takes the silhouette descriptor as an input and produces multiple output poses modeled by a mixture of Gaussian distributions. In the tracking step, the output pose distributions from the Gaussian process regression are combined with the annealed particle filter to track the 3D pose in each frame of the video sequence. Our experiments show that the proposed method does not require initialization and does not lose tracking of the pose. We compare our approach with a standard annealed particle filter using the HumanEva-I dataset and with other state of the art approaches using the HumanEva-II dataset. The evaluation results show that our approach can successfully track the 3D human pose over long video sequences and give more accurate pose tracking results than the annealed particle filter.
A variational Bayesian multiple particle filtering scheme for large-dimensional systems
Ait-El-Fquih, Boujemaa
2016-06-14
This paper considers the Bayesian filtering problem in high-dimensional nonlinear state-space systems. In such systems, classical particle filters (PFs) are impractical due to the prohibitive number of required particles to obtain reasonable performances. One approach that has been introduced to overcome this problem is the concept of multiple PFs (MPFs), where the state-space is split into low-dimensional subspaces and then a separate PF is applied to each subspace. Remarkable performances of MPF-like filters motivated our investigation here into a new strategy that combines the variational Bayesian approach to split the state-space with random sampling techniques, to derive a new computationally efficient MPF. The propagation of each particle in the prediction step of the resulting filter requires generating only a single particle in contrast with standard MPFs, for which a set of (children) particles is required. We present simulation results to evaluate the behavior of the proposed filter and compare its performances against standard PF and a MPF.
Effects of a Shroud Tube on Flow Field and Particle Behavior Inside a Bag-Filter Vessel
National Research Council Canada - National Science Library
Park, Seok Joo; Choi, Ho Kyung; Park, Young Ok; Son, Jae Ek
2003-01-01
.... The other ones are collected on the filter surface or passed through it. The particles deposited on the wall surfaces fall into a hopper by gravity, and those collected on filters are removed by back pulse-jet flow...
Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering
Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P.; Tseng, Yiider
2010-01-01
Abstract The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes. PMID:20550894
Development of particle filters for ships; Udvikling af partikelfiltre til skibe
Energy Technology Data Exchange (ETDEWEB)
Jakobsen, O.; Norre Holm, J.; Koecks, M. [Teknologisk Institut, Aarhus (Denmark)
2013-04-01
The project has resulted in a solution with a well-functioning maritime particle filter which reduces the particle emission significantly. The visible smoke from the vessels funnel, which typically is seen while manoeuvring in the harbour, is also reduced to a minimum. The system is constructed in such a way that the exhaust gases can be bypassed around the filter unit, in this situation to ensure the engines operation in case of filter clogging. The system has been provided with safety functions to prevent an excessive exhaust gas back-pressure and there are fitted remote controlled exhaust valves. Some of the challenges in the project have been the requirement from the engine manufacturer of keeping a low turbocharger back-pressure, besides the space conditions aboard the test vessel and the achievement of sufficient temperatures for regeneration of the particle filter. To oppose the requirement of low exhaust gas back-pressure, the filter housing was designed with space for twice as many monoliths as originally planned. In the funnel casing the original installations were removed to make space for the filter housing, and the system was enlarged with electrically controlled exhaust valves to improve the daily operation of the crew. The regeneration issue was solved by mounting electric automatically controlled heating elements in the filter housing and by an ash exhaust system. Regeneration is carried out by the crew when the vessel lies in harbour in the evening after the last tour of the day. Before mounting the particle filter, measurements were carried out aboard, showing a compound of particle emissions with an expected high NO{sub x}-level of 8.33 g/kW, whereas the other emissions were lower than expected at first. Especially HC and CO were very low, but also the particle mass (PM) had a relatively low value of 0.22 g/kWh. After commissioning the particle filter, a significant reduction of 93% of the particle number (N) was observed. A reduction in N was
Directory of Open Access Journals (Sweden)
Birmania Heredia Rivera
2016-10-01
Full Text Available Particulate matter accumulated on car engine air-filters (CAFs was examined in order to investigate the potential use of these devices as efficient samplers for collecting street level air that people are exposed to. The morphology, microstructure, and chemical composition of a variety of particles were studied using scanning electron microscopy (SEM and energy-dispersive X-ray (EDX. The particulate matter accumulated by the CAFs was studied in two categories; the first was of removed particles by friction, and the second consisted of particles retained on the filters. Larger particles with a diameter of 74–10 µm were observed in the first category. In the second one, the detected particles had a diameter between 16 and 0.7 µm. These particles exhibited different morphologies and composition, indicating mostly a soil origin. The elemental composition revealed the presence of three groups: mineral (clay and asphalt, metallic (mainly Fe, and biological particles (vegetal and animal debris. The palynological analysis showed the presence of pollen grains associated with urban plants. These results suggest that CAFs capture a mixture of atmospheric particles, which can be analyzed in order to monitor urban air. Thus, the continuous availability of large numbers of filters and the retroactivity associated to the car routes suggest that these CAFs are very useful for studying the high traffic zones within a city.
Heredia Rivera, Birmania; Gerardo Rodriguez, Martín
2016-01-01
Particulate matter accumulated on car engine air-filters (CAFs) was examined in order to investigate the potential use of these devices as efficient samplers for collecting street level air that people are exposed to. The morphology, microstructure, and chemical composition of a variety of particles were studied using scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). The particulate matter accumulated by the CAFs was studied in two categories; the first was of removed particles by friction, and the second consisted of particles retained on the filters. Larger particles with a diameter of 74–10 µm were observed in the first category. In the second one, the detected particles had a diameter between 16 and 0.7 µm. These particles exhibited different morphologies and composition, indicating mostly a soil origin. The elemental composition revealed the presence of three groups: mineral (clay and asphalt), metallic (mainly Fe), and biological particles (vegetal and animal debris). The palynological analysis showed the presence of pollen grains associated with urban plants. These results suggest that CAFs capture a mixture of atmospheric particles, which can be analyzed in order to monitor urban air. Thus, the continuous availability of large numbers of filters and the retroactivity associated to the car routes suggest that these CAFs are very useful for studying the high traffic zones within a city. PMID:27706087
Modified iterated extended Kalman particle filter for single satellite passive tracking
WU, Panlong; KONG, Jianshou; BO, Yuming
2013-01-01
Single satellite-to-satellite passive tracking techniques have great significance in space surveillance systems. A new passive modified iterated extended Kalman particle filter (MIEKPF) using bearings-only measurements in the Earth-Centered Inertial Coordinate System is proposed. The modified iterated extended Kalman filter (MIEKF), with a new maximum likelihood iteration termination criterion, is used to generate the proposal distribution of the MIEKPF. Moreover, a new measurement u...
A particle filter to reconstruct a free-surface flow from a depth camera
Combès, Benoit; Heitz, Dominique; Guibert, Anthony; Mémin, Etienne
2015-01-01
International audience; We investigate the combined use of a Kinect depth sensor and of a stochastic data assimilation method to recover free-surface flows. More specifically, we use a Weighted ensemble Kalman filter method to reconstruct the complete state of free-surface flows from a sequence of depth images only. This particle filter accounts for model and observations errors. This data assimilation scheme is enhanced with the use of two observations instead of one classically. We evaluate...
Energy Technology Data Exchange (ETDEWEB)
Khan, T.; Ramuhalli, Pradeep; Dass, Sarat
2011-06-30
Flaw profile characterization from NDE measurements is a typical inverse problem. A novel transformation of this inverse problem into a tracking problem, and subsequent application of a sequential Monte Carlo method called particle filtering, has been proposed by the authors in an earlier publication [1]. In this study, the problem of flaw characterization from multi-sensor data is considered. The NDE inverse problem is posed as a statistical inverse problem and particle filtering is modified to handle data from multiple measurement modes. The measurement modes are assumed to be independent of each other with principal component analysis (PCA) used to legitimize the assumption of independence. The proposed particle filter based data fusion algorithm is applied to experimental NDE data to investigate its feasibility.
Directory of Open Access Journals (Sweden)
Williamson Robert C
2006-01-01
Full Text Available Sequential Monte Carlo methods have been recently proposed to deal with the problem of acoustic source localisation and tracking using an array of microphones. Previous implementations make use of the basic bootstrap particle filter, whereas a more general approach involves the concept of importance sampling. In this paper, we develop a new particle filter for acoustic source localisation using importance sampling, and compare its tracking ability with that of a bootstrap algorithm proposed previously in the literature. Experimental results obtained with simulated reverberant samples and real audio recordings demonstrate that the new algorithm is more suitable for practical applications due to its reinitialisation capabilities, despite showing a slightly lower average tracking accuracy. A real-time implementation of the algorithm also shows that the proposed particle filter can reliably track a person talking in real reverberant rooms.
Lehmann, Eric A.; Williamson, Robert C.
2006-12-01
Sequential Monte Carlo methods have been recently proposed to deal with the problem of acoustic source localisation and tracking using an array of microphones. Previous implementations make use of the basic bootstrap particle filter, whereas a more general approach involves the concept of importance sampling. In this paper, we develop a new particle filter for acoustic source localisation using importance sampling, and compare its tracking ability with that of a bootstrap algorithm proposed previously in the literature. Experimental results obtained with simulated reverberant samples and real audio recordings demonstrate that the new algorithm is more suitable for practical applications due to its reinitialisation capabilities, despite showing a slightly lower average tracking accuracy. A real-time implementation of the algorithm also shows that the proposed particle filter can reliably track a person talking in real reverberant rooms.
A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics
Directory of Open Access Journals (Sweden)
Joaquín Míguez
2004-11-01
Full Text Available In recent years, particle filtering has become a powerful tool for tracking signals and time-varying parameters of random dynamic systems. These methods require a mathematical representation of the dynamics of the system evolution, together with assumptions of probabilistic models. In this paper, we present a new class of particle filtering methods that do not assume explicit mathematical forms of the probability distributions of the noise in the system. As a consequence, the proposed techniques are simpler, more robust, and more flexible than standard particle filters. Apart from the theoretical development of specific methods in the new class, we provide computer simulation results that demonstrate the performance of the algorithms in the problem of autonomous positioning of a vehicle in a 2-dimensional space.
Wang, Zhenwu; Hut, Rolf; van de Giesen, Nick
2017-04-01
Particle filtering is a nonlinear and non-Gaussian dynamical filtering system. It has found widespread applications in hydrological data assimilation. In order to solve the loss of particle diversity exiting in resampling process of particle filter, this research proposes an improved particle filter algorithm using genetic algorithm optimization and Gamma test. This method combines the genetic algorithm and Gamma test into the resampling procedure of particle filter to improve the adaptability and performance of particle filter in data assimilation. First, the particles are classified to three different groups based on resampling method. The particles with high weight values remain unchanged. Then genetic algorithm is used to cross and variate the rest of the particles. In the process of the optimization, the Gamma test method is applied for monitoring the quality of the new generated particles. When the gamma statistic stays stable, the algorithm will end the optimization and continue to perturb next observations in particle algorithm. The algorithm is illustrated for the three-dimensional Lorenz model and the much more complex 40-dimensional Lorenz model. The results demonstrate this method can keep the diversity of the particles and enhance the performance of the particle filter, leading to the promising conjecture that the method is applicable to realistic hydrological problems.
RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.
Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na
2015-09-03
Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.
Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications
Directory of Open Access Journals (Sweden)
Anna Elena Tirri
2014-01-01
Full Text Available Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection.
Camera Space Particle Filter for the Robust and Precise Indoor Localization of a Wheelchair
Directory of Open Access Journals (Sweden)
Raul Chavez-Romero
2016-01-01
Full Text Available This paper presents the theoretical development and experimental implementation of a sensing technique for the robust and precise localization of a robotic wheelchair. Estimates of the vehicle’s position and orientation are obtained, based on camera observations of visual markers located at discrete positions within the environment. A novel implementation of a particle filter on camera sensor space (Camera-Space Particle Filter is used to combine visual observations with sensed wheel rotations mapped onto a camera space through an observation function. The camera space particle filter fuses the odometry and vision sensors information within camera space, resulting in a precise update of the wheelchair’s pose. Using this approach, an inexpensive implementation on an electric wheelchair is presented. Experimental results within three structured scenarios and comparative performance using an Extended Kalman Filter (EKF and Camera-Space Particle Filter (CSPF implementations are discussed. The CSPF was found to be more precise in the pose of the wheelchair than the EKF since the former does not require the assumption of a linear system affected by zero-mean Gaussian noise. Furthermore, the time for computational processing for both implementations is of the same order of magnitude.
Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA
Directory of Open Access Journals (Sweden)
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.
Using Gaussian Process Annealing Particle Filter for 3D Human Tracking
Directory of Open Access Journals (Sweden)
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.
Towards filtered drag force model for non-cohesive and cohesive particle-gas flows
Ozel, Ali; Gu, Yile; Milioli, Christian C.; Kolehmainen, Jari; Sundaresan, Sankaran
2017-10-01
Euler-Lagrange simulations of gas-solid flows in unbounded domains have been performed to study sub-grid modeling of the filtered drag force for non-cohesive and cohesive particles. The filtered drag forces under various microstructures and flow conditions were analyzed in terms of various sub-grid quantities: the sub-grid drift velocity, which stems from the sub-grid correlation between the local fluid velocity and the local particle volume fraction, and the scalar variance of solid volume fraction, which is a measure to identify the degree of local inhomogeneity of volume fraction within a filter volume. The results show that the drift velocity and the scalar variance exert systematic effects on the filtered drag force. Effects of particle and domain sizes, gravitational accelerations, and mass loadings on the filtered drag are also studied, and it is shown that these effects can be captured by both sub-grid quantities. Additionally, the effect of cohesion force through the van der Waals interaction on the filtered drag force is investigated, and it is found that there is no significant difference on the dependence of the filtered drag coefficient of cohesive and non-cohesive particles on the sub-grid drift velocity or the scalar variance of solid volume fraction. The assessment of predictabilities of sub-grid quantities was performed by correlation coefficient analyses in a priori manner, and it is found that the drift velocity is superior. However, the drift velocity is not available in "coarse-grid" simulations and a specific closure is needed. A dynamic scale-similarity approach was used to model drift velocity but the predictability of that model is not entirely satisfactory. It is concluded that one must develop a more elaborate model for estimating the drift velocity in "coarse-grid" simulations.
Predictive accuracy of particle filtering in dynamic models supporting outbreak projections.
Safarishahrbijari, Anahita; Teyhouee, Aydin; Waldner, Cheryl; Liu, Juxin; Osgood, Nathaniel D
2017-09-26
While a new generation of computational statistics algorithms and availability of data streams raises the potential for recurrently regrounding dynamic models with incoming observations, the effectiveness of such arrangements can be highly subject to specifics of the configuration (e.g., frequency of sampling and representation of behaviour change), and there has been little attempt to identify effective configurations. Combining dynamic models with particle filtering, we explored a solution focusing on creating quickly formulated models regrounded automatically and recurrently as new data becomes available. Given a latent underlying case count, we assumed that observed incident case counts followed a negative binomial distribution. In accordance with the condensation algorithm, each such observation led to updating of particle weights. We evaluated the effectiveness of various particle filtering configurations against each other and against an approach without particle filtering according to the accuracy of the model in predicting future prevalence, given data to a certain point and a norm-based discrepancy metric. We examined the effectiveness of particle filtering under varying times between observations, negative binomial dispersion parameters, and rates with which the contact rate could evolve. We observed that more frequent observations of empirical data yielded super-linearly improved accuracy in model predictions. We further found that for the data studied here, the most favourable assumptions to make regarding the parameters associated with the negative binomial distribution and changes in contact rate were robust across observation frequency and the observation point in the outbreak. Combining dynamic models with particle filtering can perform well in projecting future evolution of an outbreak. Most importantly, the remarkable improvements in predictive accuracy resulting from more frequent sampling suggest that investments to achieve efficient reporting
Monte Carlo Simulations of New 2D Ripple Filters for Particle Therapy Facilities
DEFF Research Database (Denmark)
Ringbæk, Toke Printz; Weber, Uli; Petersen, Jørgen B.B.
2014-01-01
Introduction: At particle therapy facilities with pencil beam scanning, the implementation of a Ripple Filter (RiFi) broadens the Bragg peak (BP), which leads to fewer energy steps from the accelerator required to obtain a homogeneous dose coverage of the planned target volume (PTV). At the Unive......Introduction: At particle therapy facilities with pencil beam scanning, the implementation of a Ripple Filter (RiFi) broadens the Bragg peak (BP), which leads to fewer energy steps from the accelerator required to obtain a homogeneous dose coverage of the planned target volume (PTV...... expressions for dmax and d0.01 ; both are inversely related to the angular distribution. Increasing scatter from the beam delivery and monitoring system results in reduced dmax and d0.01 . Furthermore, dmax and d0.01 are found to be proportional to the ripple filter period λ. Conclusion: Our findings clearly...
State estimation of nonlinear stochastic systems using a novel meta-heuristic particle filter
DEFF Research Database (Denmark)
Ahmadi, Mohamadreza; Mojallali, Hamed; Izadi-Zamanabadi, Roozbeh
2012-01-01
This paper proposes a new version of the particle filtering (PF) algorithm based on the invasive weed optimization (IWO) method. The sub-optimality of the sampling step in the PF algorithm is prone to estimation errors. In order to avert such approximation errors, this paper suggests applying the...
Particles in swimming pool filters – Does pH determine the DBP formation?
DEFF Research Database (Denmark)
Hansen, Kamilla Marie Speht; Willach, Sarah; Mosbæk, Hans
2012-01-01
countries, and the non-regulated haloacetic acids (HAAs) and haloacetonitriles (HANs) were investigated at 6.0⩽pH⩽8.0, under controlled chlorination conditions. The investigated particles were collected from a hot tub with a drum micro filter. In two series of experiments with either constant initial active...
The impact of sensor errors and building structures on particle filter-based inertial positioning
DEFF Research Database (Denmark)
Toftkjær, Thomas; Kjærgaard, Mikkel Baun
2012-01-01
Positioning systems that do not depend on in-building infrastructures are critical for enabling a range of applications within pervasive computing. Particle filter-based inertial positioning promises infrastructure-less positioning, but previous research has not provided an understanding of how t...
Claveria, R.; Mendez, R. A.; Orchard, M.
2018-01-01
This work addresses the problem of orbital estimation from a Bayesian point of view, using the Particle Filter technique to approximate the posterior distribution of orbital parameters. Additionally, we present a multiple imputation scheme as a means to include partial measurements into the analysis.
Directory of Open Access Journals (Sweden)
M. Morzfeld
2012-06-01
Full Text Available Implicit particle filtering is a sequential Monte Carlo method for data assimilation, designed to keep the number of particles manageable by focussing attention on regions of large probability. These regions are found by minimizing, for each particle, a scalar function F of the state variables. Some previous implementations of the implicit filter rely on finding the Hessians of these functions. The calculation of the Hessians can be cumbersome if the state dimension is large or if the underlying physics are such that derivatives of F are difficult to calculate, as happens in many geophysical applications, in particular in models with partial noise, i.e. with a singular state covariance matrix. Examples of models with partial noise include models where uncertain dynamic equations are supplemented by conservation laws with zero uncertainty, or with higher order (in time stochastic partial differential equations (PDE or with PDEs driven by spatially smooth noise processes. We make the implicit particle filter applicable to such situations by combining gradient descent minimization with random maps and show that the filter is efficient, accurate and reliable because it operates in a subspace of the state space. As an example, we consider a system of nonlinear stochastic PDEs that is of importance in geomagnetic data assimilation.
A baker's dozen of new particle flows for nonlinear filters, Bayesian decisions and transport
Daum, Fred; Huang, Jim
2015-05-01
We describe a baker's dozen of new particle flows to compute Bayes' rule for nonlinear filters, Bayesian decisions and learning as well as transport. Several of these new flows were inspired by transport theory, but others were inspired by physics or statistics or Markov chain Monte Carlo methods.
Computer Vision Tracking Using Particle Filters for 3D Position Estimation
2014-03-27
images taken over time. Currently photogrammetry and videogrammetry are used in a variety of fields from topographic mapping to film motion capture and...5 2.2 Photogrammetry ...focus on particle filters. 2.2 Photogrammetry Photogrammetry is the process of determining 3-D coordinates through images. The mathematical underpinnings
Coupled particle filtering : A new approach for P300-based analysis of mental fatigue
Jarchi, Delaram; Sanei, Saeid; Mohseni, Hamid R.; Lorist, Monicque M.
A new method for investigating mental fatigue based on P300 variability is presented here. In this approach a new coupled particle filtering for tracking variability of P300 subcomponents, i.e., P3a and P3b, across trials is developed. The latency, amplitude, and width of each subcomponent, as the
The effects of particle charge on the performance of a filtering facepiece.
Chen, C C; Huang, S H
1998-04-01
This study quantitatively determined the effect of electrostatic charge on the performance of an electret filtering facepiece. Monodisperse challenge corn oil aerosols with uniform charges were generated using a modified vibrating orifice monodisperse aerosol generator. The aerosol size distributions and concentrations upstream and downstream of an electret filter were measured using an aerodynamic particle sizer, an Aerosizer, and a scanning mobility particle sizer. The aerosol charge was measured by using an aerosol electrometer. The tested electret filter had a packing density of about 0.08, fiber size of 3 microns, and thickness of 0.75 mm. As expected, the primary filtration mechanisms for the micrometer-sized particles are interception and impaction, especially at high face velocities, while electrostatic attraction and diffusion are the filtration mechanisms for submicrometer-sized aerosol particles. The fiber charge density was estimated to be 1.35 x 10(-5) coulomb per square meter. After treatment with isopropanol, most of fiber charges were removed, causing the 0.3-micron aerosol penetration to increase from 36 to 68%. The air resistance of the filter increased slightly after immersion in the isopropanol, probably due to the coating of impurities in isopropanol. The aerosol penetration decreased with increasing aerosol charge. The most penetrating aerosol size became larger as the aerosol charge increased, e.g., from 0.32 to 1.3 microns when the aerosol charge increased from 0 to 500 elementary charges.
Directory of Open Access Journals (Sweden)
Wu Sunyong
2017-06-01
Full Text Available The Track-Before-Detect (TBD algorithm based on the particle filter is proposed for weak extended target detection and tracking in low signal to clutter noise radio. The rod-shaped object is analyzed by dividing the cell on range and azimuth under the Weibull clutter. On the basis of a point target, the likelihood function and particle weights can be obtained by the target spread function. In the TBD algorithm, the binary target variable and the target shape parameters is added to the state vector and the scattering points in the sample collection is given based on the particle filter, which can detect and estimate the target state and the shape parameters under the clutter environment. Simulation results show that the stability of the algorithm is very good.
Directory of Open Access Journals (Sweden)
Wentao Yu
2013-01-01
high. In order to reduce the computation cost of UPF and meanwhile maintain the accuracy, we propose an adaptive unscented particle filter (AUPF algorithm through relative entropy. AUPF can adaptively adjust the number of particles during filtering to reduce the necessary computation and hence improve the real-time capability of UPF. In AUPF, the relative entropy is used to measure the distance between the empirical distribution and the true posterior distribution. The least number of particles for the next step is then decided according to the relative entropy. In order to offset the difference between the proposal distribution, and the true distribution the least number is adjusted thereafter. The ideal performance of AUPF in real robot self-localization is demonstrated.
Particle capture in axial magnetic filters with power law flow model
Abbasov, T; Koksal, M
1999-01-01
A theory of capture of magnetic particle carried by laminar flow of viscous non-Newtonian (power law) fluid in axially ordered filters is presented. The velocity profile of the fluid flow is determined by the Kuwabara-Happel cell model. For the trajectory of the particle, the capture area and the filter performance simple analytical expressions are obtained. These expressions are valid for particle capture processes from both Newtonian and non-Newtonian fluids. For this reason the obtained theoretical results make it possible to widen the application of high-gradient magnetic filtration (HGMF) to other industrial areas. For Newtonian fluids the theoretical results are shown to be in good agreement with the experimental ones reported in the literature. (author)
Shallcross, Gregory; Capecelatro, Jesse
2017-11-01
Compressible particle-laden flows are common in engineering systems. Applications include but are not limited to water injection in high-speed jet flows for noise suppression, rocket-plume surface interactions during planetary landing, and explosions during coal mining operations. Numerically, it is challenging to capture these interactions due to the wide range of length and time scales. Additionally, there are many forms of the multiphase compressible flow equations with volume fraction effects, some of which are conflicting in nature. The purpose of this presentation is to develop the capability to accurately capture particle-shock interactions in systems with a large number of particles from dense to dilute regimes. A thorough derivation of the volume filtered equations is presented. The volume filtered equations are then implemented in a high-order, energy-stable Eulerian-Lagrangian framework. We show this framework is capable of decoupling the fluid mesh from the particle size, enabling arbitrary particle size distributions in the presence of shocks. The proposed method is then assessed against particle-laden shock tube data. Quantities of interest include fluid-phase pressure profiles and particle spreading rates. The effect of collisions in 2D and 3D are also evaluated.
New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.
Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng
2016-05-16
The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.
Sigma-Point Particle Filter for Parameter Estimation in a Multiplicative Noise Environment
Directory of Open Access Journals (Sweden)
Youmin Tang
2011-12-01
Full Text Available A pre-requisite for the “optimal estimate” by the ensemble-based Kalman filter (EnKF is the Gaussian assumption for background and observation errors, which is often violated when the errors are multiplicative, even for a linear system. This study first explores the challenge of the multiplicative noise to the current EnKF schemes. Then, a Sigma Point Kalman Filter based Particle Filter (SPPF is presented as an alternative to solve the issues associated with multiplicative noise. The classic Lorenz '63 model and a higher dimensional Lorenz '96 model are used as test beds for the data assimilation experiments. Performance of the SPPF algorithm is compared against a standard EnKF as well as an advanced square-root Sigma-Point Kalman Filters (SPKF. The results show that the SPPF outperforms the EnKF and the square-root SPKF in the presence of multiplicative noise. The super ensemble structure of the SPPF makes it computationally attractive compared to the standard Particle Filter (PF.
Pseudobrookite-type MgTi2O5 water purification filter with controlled particle morphology
Directory of Open Access Journals (Sweden)
Yuta Nakagoshi
2015-09-01
Full Text Available Pseudobrookite-type oxide-based ceramics, such as Al2TiO5 and MgTi2O5, have recently been studied as porous ceramic membranes. Here, the effect of LiF doping on the morphology of MgTi2O5 particles is presented in detail. Water purification filters were produced using porous MgTi2O5, with different particle morphologies. MgCO3 (basic and TiO2 powders with various LiF contents were wet-ball milled, dried, and then, calcined in air at 1100 °C to obtain the MgTi2O5 powders. The powder compacts were sintered at 1000–1200 °C to produce the MgTi2O5 disk filters. The 0.5 wt.% LiF-doped MgTi2O5 disk filter, with elongated grains, showed well-balanced performance removing boehmite particles with diameter of 0.7 μm. Non-doped MgTi2O5 disk filter with equiaxed grains was suitable for precise filtration.
A Particle Filtering Approach to Joint Passive Radar Tracking and Target Classification
2002-01-01
1998. [46] J. S. Liu, Monte Carlo Strategies in Scientific Computing. New York, NY: Springer Verlag, 2001. [47] D. Crisan and A. Doucet, “A survey...Journal of Computational and Graphical Statistics, vol. 5, no. 1, pp. 1–25, 1996. [61] D. Crisan , “Particle filters — A theoretical perspective,” in...filter for nonlinear problems,” IEE Proceedings–Radar, Sonar, and Navigation, vol. 146, pp. 2–7, February 1999. [63] D. Crisan , P. Del Moral, and T
The Design of Frequency Filters of Iterative Feedback Tuning Using Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Arman Sharifi
2014-01-01
Full Text Available Iterative feedback tuning (IFT is a data-based tuning approach that minimizes a quadratic performance index using some closed-loop experimental data. A control weighting coefficient, known as lambda, and two frequency filters are the most important parameters which can significantly improve the performance of the method. One of the major problems in IFT is tuning these parameters. This paper presents a new approach to tune frequency filters using particle swarm optimization (PSO. At the end, the performance of the proposed method is evaluated by two case study simulations.
Zhang, Xiaomin; Ren, Kan; Wan, Minjie; Gu, Guohua; Chen, Qian
2017-12-01
Infrared search and track technology for small target plays an important role in infrared warning and guidance. In view of the tacking randomness and uncertainty caused by background clutter and noise interference, a robust tracking method for infrared small target based on sample constrained particle filtering and sparse representation is proposed in this paper. Firstly, to distinguish the normal region and interference region in target sub-blocks, we introduce a binary support vector, and combine it with the target sparse representation model, after which a particle filtering observation model based on sparse reconstruction error differences between sample targets is developed. Secondly, we utilize saliency extraction to obtain the high frequency area in infrared image, and make it as a priori knowledge of the transition probability model to limit the particle filtering sampling process. Lastly, the tracking result is brought about via target state estimation and the Bayesian posteriori probability calculation. Theoretical analyses and experimental results show that our method can enhance the state estimation ability of stochastic particles, improve the sparse representation adaptabilities for infrared small targets, and optimize the tracking accuracy for infrared small moving targets.
The new approach for infrared target tracking based on the particle filter algorithm
Sun, Hang; Han, Hong-xia
2011-08-01
Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring, precision, and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection, the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure, but in order to capture the change of the state space, it need a certain amount of particles to ensure samples is enough, and this number will increase in accompany with dimension and increase exponentially, this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining", we expand the classic Mean Shift tracking framework .Based on the previous perspective, we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis, Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism, used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy
Fan, Y. R.; Huang, G. H.; Baetz, B. W.; Li, Y. P.; Huang, K.; Chen, X.; Gao, M.
2017-07-01
This study improved hydrologic data assimilation through integrating the capabilities of particle filter (PF) and ensemble Kalman filter (EnKF) methods, leading to two integrated data assimilation schemes: the coupled EnKF and PF (CEnPF) and parallelized EnKF and PF (PEnPF) approaches. The applicability and usefulness of CEnPF and PEnPF were demonstrated using a conceptual rainfall-runoff model. The performance of two new developed data assimilation methods and traditional EnKF and PF approaches was tested through a synthetic experiment and two real-world cases with one located in the Jing River basin and one located in the Yangtze River basin. The results show that both PEnPF and CEnPF approaches have more opportunities to provide better results for both deterministic and probabilistic predictions than traditional EnKF and PF approaches. Moreover, the computational time of the two integrated methods is manageable. But the proposed PEnPF may need much more time for some large-scale or time-consuming hydrologic models since it generally needs three times of model runs used by EnKF, PF and CEnPF.
Innocenti, Alessio; Marchioli, Cristian; Chibbaro, Sergio
2016-11-01
The Eulerian-Lagrangian approach based on Large-Eddy Simulation (LES) is one of the most promising and viable numerical tools to study particle-laden turbulent flows, when the computational cost of Direct Numerical Simulation (DNS) becomes too expensive. The applicability of this approach is however limited if the effects of the Sub-Grid Scales (SGSs) of the flow on particle dynamics are neglected. In this paper, we propose to take these effects into account by means of a Lagrangian stochastic SGS model for the equations of particle motion. The model extends to particle-laden flows the velocity-filtered density function method originally developed for reactive flows. The underlying filtered density function is simulated through a Lagrangian Monte Carlo procedure that solves a set of Stochastic Differential Equations (SDEs) along individual particle trajectories. The resulting model is tested for the reference case of turbulent channel flow, using a hybrid algorithm in which the fluid velocity field is provided by LES and then used to advance the SDEs in time. The model consistency is assessed in the limit of particles with zero inertia, when "duplicate fields" are available from both the Eulerian LES and the Lagrangian tracking. Tests with inertial particles were performed to examine the capability of the model to capture the particle preferential concentration and near-wall segregation. Upon comparison with DNS-based statistics, our results show improved accuracy and considerably reduced errors with respect to the case in which no SGS model is used in the equations of particle motion.
Wang, Xuemei; Ni, Wenbo
2016-09-01
For loosely coupled INS/GPS integrated navigation systems with low-cost and low-accuracy microelectromechanical device inertial sensors, in order to obtain enough accuracy, a full-state nonlinear dynamic model rather than a linearized error model is much more preferable. Particle filters are particularly for nonlinear and non-Gaussian situations, but typical bootstrap particle filters (BPFs) and some improved particle filters (IPFs) such as auxiliary particle filters (APFs) and Gaussian particle filters (GPFs) cannot solve the mismatch between the importance function and the likelihood function very well. The predicted particles propagated through inertial navigation equations cannot be scattered with certainty within the effective range of current observation when there are large drift errors of the inertial sensors. Therefore, the current observation cannot play the correction role well and these particle filters are invalid to some extent. The proposed IPF firstly estimates the corresponding state bias errors according to the current observation and then corrects the bias errors of the predicted particles before determining the weights and resampling the particles. Simulations and practical experiments both show that the proposed IPF can effectively solve the mismatch between the importance function and the likelihood function of a BPF and compensate the accumulated errors of INSs very well. It has great robustness in a serious noisy scenario.
Real-Time Flood Forecasting System Using Channel Flow Routing Model with Updating by Particle Filter
Kudo, R.; Chikamori, H.; Nagai, A.
2008-12-01
A real-time flood forecasting system using channel flow routing model was developed for runoff forecasting at water gauged and ungaged points along river channels. The system is based on a flood runoff model composed of upstream part models, tributary part models and downstream part models. The upstream part models and tributary part models are lumped rainfall-runoff models, and the downstream part models consist of a lumped rainfall-runoff model for hillslopes adjacent to a river channel and a kinematic flow routing model for a river channel. The flow forecast of this model is updated by Particle filtering of the downstream part model as well as by the extended Kalman filtering of the upstream part model and the tributary part models. The Particle filtering is a simple and powerful updating algorithm for non-linear and non-gaussian system, so that it can be easily applied to the downstream part model without complicated linearization. The presented flood runoff model has an advantage in simlecity of updating procedure to the grid-based distributed models, which is because of less number of state variables. This system was applied to the Gono-kawa River Basin in Japan, and flood forecasting accuracy of the system with both Particle filtering and extended Kalman filtering and that of the system with only extended Kalman filtering were compared. In this study, water gauging stations in the objective basin were divided into two types of stations, that is, reference stations and verification stations. Reference stations ware regarded as ordinary water gauging stations and observed data at these stations are used for calibration and updating of the model. Verification stations ware considered as ungaged or arbitrary points and observed data at these stations are used not for calibration nor updating but for only evaluation of forecasting accuracy. The result confirms that Particle filtering of the downstream part model improves forecasting accuracy of runoff at
Particle Filter for Fault Diagnosis and Robust Navigation of Underwater Robot
DEFF Research Database (Denmark)
Zhao, Bo; Skjetne, Roger; Blanke, Mogens
2014-01-01
A particle filter based robust navigation with fault diagnosis is designed for an underwater robot, where 10 failure modes of sensors and thrusters are considered. The nominal underwater robot and its anomaly are described by a switchingmode hidden Markov model. By extensively running a particle...... filter on the model, the fault diagnosis and robust navigation are achieved. Closed-loop full-scale experimental results show that the proposed method is robust, can diagnose faults effectively, and can provide good state estimation even in cases where multiple faults occur. Comparing with other methods......, the proposed method can diagnose all faults within a single structure, it can diagnose simultaneous faults, and it is easily implemented....
Adaptive hybrid likelihood model for visual tracking based on Gaussian particle filter
Wang, Yong; Tan, Yihua; Tian, Jinwen
2010-07-01
We present a new scheme based on multiple-cue integration for visual tracking within a Gaussian particle filter framework. The proposed method integrates the color, shape, and texture cues of an object to construct a hybrid likelihood model. During the measurement step, the likelihood model can be switched adaptively according to environmental changes, which improves the object representation to deal with the complex disturbances, such as appearance changes, partial occlusions, and significant clutter. Moreover, the confidence weights of the cues are adjusted online through the estimation using a particle filter, which ensures the tracking accuracy and reliability. Experiments are conducted on several real video sequences, and the results demonstrate that the proposed method can effectively track objects in complex scenarios. Compared with previous similar approaches through some quantitative and qualitative evaluations, the proposed method performs better in terms of tracking robustness and precision.
Directory of Open Access Journals (Sweden)
Malek Njah
2014-01-01
Full Text Available Electric wheelchair is one of the many engines used for the movement of aged and disabled people. This paper introduces an obstacle avoidance using deformable virtual zone (DVZ, particle filter to improve localization and fuzzy controller to join desired target. This controller is developed to increase the independence of disabled and aged people, specifically those who suffer not only disability in the lower limbs but also visual disturbances. To overcome these problems, different perceptive abilities or sensors were introduced. In this context, we developed a control system composed by fuzzy controller to join a target, DVZ method for obstacle avoidance, and particle filter for localization. Also, we present the simulation results of the wheelchair navigation system.
Directory of Open Access Journals (Sweden)
Bo Wang
2013-11-01
Full Text Available Shipboard is not an absolute rigid body. Many factors could cause deformations which lead to large errors of mounted devices, especially for the navigation systems. Such errors should be estimated and compensated effectively, or they will severely reduce the navigation accuracy of the ship. In order to estimate the deformation, an unscented particle filter method for estimation of shipboard deformation based on an inertial measurement unit is presented. In this method, a nonlinear shipboard deformation model is built. Simulations demonstrated the accuracy reduction due to deformation. Then an attitude plus angular rate match mode is proposed as a frame to estimate the shipboard deformation using inertial measurement units. In this frame, for the nonlinearity of the system model, an unscented particle filter method is proposed to estimate and compensate the deformation angles. Simulations show that the proposed method gives accurate and rapid deformation estimations, which can increase navigation accuracy after compensation of deformation.
Wang, Bo; Xiao, Xuan; Xia, Yuanqing; Fu, Mengyin
2013-11-15
Shipboard is not an absolute rigid body. Many factors could cause deformations which lead to large errors of mounted devices, especially for the navigation systems. Such errors should be estimated and compensated effectively, or they will severely reduce the navigation accuracy of the ship. In order to estimate the deformation, an unscented particle filter method for estimation of shipboard deformation based on an inertial measurement unit is presented. In this method, a nonlinear shipboard deformation model is built. Simulations demonstrated the accuracy reduction due to deformation. Then an attitude plus angular rate match mode is proposed as a frame to estimate the shipboard deformation using inertial measurement units. In this frame, for the nonlinearity of the system model, an unscented particle filter method is proposed to estimate and compensate the deformation angles. Simulations show that the proposed method gives accurate and rapid deformation estimations, which can increase navigation accuracy after compensation of deformation.
Directory of Open Access Journals (Sweden)
Buddhi Arachchige
2017-11-01
Full Text Available This paper focuses on predicting the End of Life and End of Discharge of Lithium ion batteries using a battery capacity fade model and a battery discharge model. The proposed framework will be able to estimate the Remaining Useful Life (RUL and the Remaining charge through capacity fade and discharge models. A particle filter is implemented that estimates the battery’s State of Charge (SOC and State of Life (SOL by utilizing the battery’s physical data such as voltage, temperature, and current measurements. The accuracy of the prognostic framework has been improved by enhancing the particle filter state transition model to incorporate different environmental and loading conditions without retuning the model parameters. The effect of capacity fade in the reduction of the EOD (End of Discharge time with cycling has also been included, integrating both EOL (End of Life and EOD prediction models in order to get more accuracy in the estimations.
Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction
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Ye Tian
2014-01-01
Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.
Mashiku, Alinda; Garrison, James L.; Carpenter, J. Russell
2012-01-01
The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.
Energy Technology Data Exchange (ETDEWEB)
Stewart, Mark L.; Rector, David R.; Muntean, George G.; Maupin, Gary D.
2004-08-01
Cordierite diesel particulate filters (DPFs) offer one of the most promising aftertreatment technologies to meet the quickly approaching EPA 2007 heavy-duty emissions regulations. A critical, yet poorly understood, component of particulate filter modeling is the representation of soot deposition. The structure and distribution of soot deposits upon and within the ceramic substrate directly influence many of the macroscopic phenomenon of interest, including filtration efficiency, back pressure, and filter regeneration. Intrinsic soot cake properties such as packing density and permeability coefficients remain inadequately characterized. The work reported in this paper involves subgrid modeling techniques which may prove useful in resolving these inadequacies. The technique involves the use of a lattice Boltzmann modeling approach. This approach resolves length scales which are orders of magnitude below those typical of a standard computational fluid dynamics (CFD) representation of an aftertreatment device. Individual soot particles are introduced and tracked as they move through the flow field and are deposited on the filter substrate or previously deposited particles. Electron micrographs of actual soot deposits were taken and compared to the model predictions. Descriptions of the modeling technique and the development of the computational domain are provided. Preliminary results are presented, along with some comparisons with experimental observations.
Malek Njah; Mohamed Jallouli
2014-01-01
Electric wheelchair is one of the many engines used for the movement of aged and disabled people. This paper introduces an obstacle avoidance using deformable virtual zone (DVZ), particle filter to improve localization and fuzzy controller to join desired target. This controller is developed to increase the independence of disabled and aged people, specifically those who suffer not only disability in the lower limbs but also visual disturbances. To overcome these problems, different perceptiv...
Novel Mobile Robot Simultaneous Loclization and Mapping Using Rao-Blackwellised Particle Filter
Directory of Open Access Journals (Sweden)
Li Maohai
2006-09-01
Full Text Available This paper presents the novel method of mobile robot simultaneous localization and mapping (SLAM, which is implemented by using the Rao-Blackwellised particle filter (RBPF for monocular vision-based autonomous robot in unknown indoor environment. The particle filter is combined with unscented Kalman filter (UKF to extending the path posterior by sampling new poses that integrate the current observation. The landmark position estimation and update is implemented through the unscented transform (UT. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem. Monocular CCD camera mounted on the robot tracks the 3D natural point landmarks, which are structured with matching image feature pairs extracted through Scale Invariant Feature Transform (SIFT. The matching for multi-dimension SIFT features which are highly distinctive due to a special descriptor is implemented with a KD-Tree in the time cost of O(log2N. Experiments on the robot Pioneer3 in our real indoor environment show that our method is of high precision and stability.
Novel Mobile Robot Simultaneous Localization and Mapping Using Rao-Blackwellised Particle Filter
Directory of Open Access Journals (Sweden)
Hong Bingrong
2008-11-01
Full Text Available This paper presents the novel method of mobile robot simultaneous localization and mapping (SLAM, which is implemented by using the Rao-Blackwellised particle filter (RBPF for monocular vision-based autonomous robot in unknown indoor environment. The particle filter is combined with unscented Kalman filter (UKF to extending the path posterior by sampling new poses that integrate the current observation. The landmark position estimation and update is implemented through the unscented transform (UT. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem. Monocular CCD camera mounted on the robot tracks the 3D natural point landmarks, which are structured with matching image feature pairs extracted through Scale Invariant Feature Transform (SIFT. The matching for multi-dimension SIFT features which are highly distinctive due to a special descriptor is implemented with a KDTree in the time cost of O(log2N. Experiments on the robot Pioneer3 in our real indoor environment show that our method is of high precision and stability.
A New Mutated Quantum-Behaved Particle Swarm Optimizer for Digital IIR Filter Design
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Wenbo Xu
2009-01-01
Full Text Available Adaptive infinite impulse response (IIR filters have shown their worth in a wide range of practical applications. Because the error surface of IIR filters is multimodal in most cases, global optimization techniques are required for avoiding local minima. In this paper, we employ a global optimization algorithm, Quantum-behaved particle swarm optimization (QPSO that was proposed by us previously, and its mutated version in the design of digital IIR filter. The mechanism in QPSO is based on the quantum behaviour of particles in a potential well and particle swarm optimization (PSO algorithm. QPSO is characterized by fast convergence, good search ability, and easy implementation. The mutated QPSO (MuQPSO is proposed in this paper by using a random vector in QPSO to increase the randomness and to enhance the global search ability. Experimental results on three examples show that QPSO and MuQPSO are superior to genetic algorithm (GA, differential evolution (DE algorithm, and PSO algorithm in quality, convergence speed, and robustness.
Robust dead reckoning system for mobile robots based on particle filter and raw range scan.
Duan, Zhuohua; Cai, Zixing; Min, Huaqing
2014-09-04
Robust dead reckoning is a complicated problem for wheeled mobile robots (WMRs), where the robots are faulty, such as the sticking of sensors or the slippage of wheels, for the discrete fault models and the continuous states have to be estimated simultaneously to reach a reliable fault diagnosis and accurate dead reckoning. Particle filters are one of the most promising approaches to handle hybrid system estimation problems, and they have also been widely used in many WMRs applications, such as pose tracking, SLAM, video tracking, fault identification, etc. In this paper, the readings of a laser range finder, which may be also interfered with by noises, are used to reach accurate dead reckoning. The main contribution is that a systematic method to implement fault diagnosis and dead reckoning in a particle filter framework concurrently is proposed. Firstly, the perception model of a laser range finder is given, where the raw scan may be faulty. Secondly, the kinematics of the normal model and different fault models for WMRs are given. Thirdly, the particle filter for fault diagnosis and dead reckoning is discussed. At last, experiments and analyses are reported to show the accuracy and efficiency of the presented method.
3D head pose estimation and tracking using particle filtering and ICP algorithm
Ben Ghorbel, Mahdi
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.
Energy Technology Data Exchange (ETDEWEB)
Lee, Jong Chan; Jung, Woo Young; Lee, Hyun Chul; Lee, Doo Young [FNC TECH., Yongin (Korea, Republic of)
2016-05-15
Optical Particle Counter (OPC) is used to provide real-time measurement of aerosol concentration and size distribution. Glass fiber membrane filter also be used to measure average mass concentration. Three tests (MTA-1, 2 and 3) have been conducted to study thermal-hydraulic effect, a filtering tendency at given SiO{sub 2} particles. Based on the experimental results, the experiment will be carried out further with a main carrier gas of steam and different aerosol size. The test results will provide representative behavior of the aerosols under various conditions. The aim of the tests, MTA 1, 2 and 3, are to be able to 1) establish the test manuals for aerosol generation, mixing, sampling and measurement system, which defines aerosol preparation, calibration, operating and evaluation method under high pressure and high temperature 2) develop commercial aerosol test modules applicable to the thermal power plant, environmental industry, automobile exhaust gas, chemical plant, HVAC system including nuclear power plant. Based on the test results, sampled aerosol particles in the filter indicate that important parameters affecting aerosol behavior aerosols are 1) system temperature to keep above a evaporation temperature of ethanol and 2) aerosol losses due to the settling by ethanol liquid droplet.
Robust Dead Reckoning System for Mobile Robots Based on Particle Filter and Raw Range Scan
Directory of Open Access Journals (Sweden)
Zhuohua Duan
2014-09-01
Full Text Available Robust dead reckoning is a complicated problem for wheeled mobile robots (WMRs, where the robots are faulty, such as the sticking of sensors or the slippage of wheels, for the discrete fault models and the continuous states have to be estimated simultaneously to reach a reliable fault diagnosis and accurate dead reckoning. Particle filters are one of the most promising approaches to handle hybrid system estimation problems, and they have also been widely used in many WMRs applications, such as pose tracking, SLAM, video tracking, fault identification, etc. In this paper, the readings of a laser range finder, which may be also interfered with by noises, are used to reach accurate dead reckoning. The main contribution is that a systematic method to implement fault diagnosis and dead reckoning in a particle filter framework concurrently is proposed. Firstly, the perception model of a laser range finder is given, where the raw scan may be faulty. Secondly, the kinematics of the normal model and different fault models for WMRs are given. Thirdly, the particle filter for fault diagnosis and dead reckoning is discussed. At last, experiments and analyses are reported to show the accuracy and efficiency of the presented method.
Directory of Open Access Journals (Sweden)
Askar Wesam
2017-01-01
Full Text Available Vision based object tracking problem still a hot and important area of research specially when the tracking algorithms are performed by the aircraft unmanned vehicle (UAV. Tracking with the UAV requires special considerations due to the flight maneuvers, environmental conditions and aircraft moving camera. The ego motion calculations can compensate the effect of the moving background resulted from the moving camera. In this paper an optimized object tracking framework is introduced to tackle this problem based on particle filter. It integrates the calculated ego motion transformation matrix with the dynamic model of the particle filter during the prediction stage. Then apply the correction stage on the particle filter observation model which based on two kinds of features includes Haar-like Rectangles and edge orientation histogram (EOH features. The Gentle AdaBoost classifier is used to select the most informative features as a preliminary step. The experimental results achieved more than 94.6% rate of successful tracking during different scenarios of the VIVID database in real time tracking speed.
The use of GPS for Handling Lack of Indoor Constraints in Particle Filter-based Inertial Positioning
DEFF Research Database (Denmark)
Toftkjær, Thomas; Kjærgaard, Mikkel Baun
Particle filter-based inertial positioning promises infrastructure-less positioning, but previous research have not provided an understanding of, how the positioning accuracy of such systems depends on the layout of building structures. This poster presents initial result for the impact...... of the layout of building structures on the positioning accuracy using a particle filter-based inertial positioning system named Pro-Position. We also consider methods for using GPS positioning with particle filter-based inertial positioningto improve accuracy in areas, where positioning is poor because of lack...
Calibration of micromechanical parameters for DEM simulations by using the particle filter
Cheng, Hongyang; Shuku, Takayuki; Thoeni, Klaus; Yamamoto, Haruyuki
2017-06-01
The calibration of DEM models is typically accomplished by trail and error. However, the procedure lacks of objectivity and has several uncertainties. To deal with these issues, the particle filter is employed as a novel approach to calibrate DEM models of granular soils. The posterior probability distribution of the microparameters that give numerical results in good agreement with the experimental response of a Toyoura sand specimen is approximated by independent model trajectories, referred as `particles', based on Monte Carlo sampling. The soil specimen is modeled by polydisperse packings with different numbers of spherical grains. Prepared in `stress-free' states, the packings are subjected to triaxial quasistatic loading. Given the experimental data, the posterior probability distribution is incrementally updated, until convergence is reached. The resulting `particles' with higher weights are identified as the calibration results. The evolutions of the weighted averages and posterior probability distribution of the micro-parameters are plotted to show the advantage of using a particle filter, i.e., multiple solutions are identified for each parameter with known probabilities of reproducing the experimental response.
Energy Technology Data Exchange (ETDEWEB)
Jaeschke, B.C., E-mail: Ben.Jaeschke@gmail.com [Department of Ecology Environment and Plant Sciences, Stockholm University, SE-106 91 Stockholm (Sweden); CERAD CoE, Department of Environmental Sciences, Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås (Norway); Lind, O.C. [CERAD CoE, Department of Environmental Sciences, Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås (Norway); Bradshaw, C. [Department of Ecology Environment and Plant Sciences, Stockholm University, SE-106 91 Stockholm (Sweden); Salbu, B. [CERAD CoE, Department of Environmental Sciences, Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås (Norway)
2015-01-01
Radioactive particles are aggregates of radioactive atoms that may contain significant activity concentrations. They have been released into the environment from nuclear weapons tests, and from accidents and effluents associated with the nuclear fuel cycle. Aquatic filter-feeders can capture and potentially retain radioactive particles, which could then provide concentrated doses to nearby tissues. This study experimentally investigated the retention and effects of radioactive particles in the blue mussel, Mytilus edulis. Spent fuel particles originating from the Dounreay nuclear establishment, and collected in the field, comprised a U and Al alloy containing fission products such as {sup 137}Cs and {sup 90}Sr/{sup 90}Y. Particles were introduced into mussels in suspension with plankton-food or through implantation in the extrapallial cavity. Of the particles introduced with food, 37% were retained for 70 h, and were found on the siphon or gills, with the notable exception of one particle that was ingested and found in the stomach. Particles not retained seemed to have been actively rejected and expelled by the mussels. The largest and most radioactive particle (estimated dose rate 3.18 ± 0.06 Gy h{sup −1}) induced a significant increase in Comet tail-DNA %. In one case this particle caused a large white mark (suggesting necrosis) in the mantle tissue with a simultaneous increase in micronucleus frequency observed in the haemolymph collected from the muscle, implying that non-targeted effects of radiation were induced by radiation from the retained particle. White marks found in the tissue were attributed to ionising radiation and physical irritation. The results indicate that current methods used for risk assessment, based upon the absorbed dose equivalent limit and estimating the “no-effect dose” are inadequate for radioactive particle exposures. Knowledge is lacking about the ecological implications of radioactive particles released into the environment
Huang, R; Agranovski, I; Pyankov, O; Grinshpun, S
2008-04-01
Continuous emission of unipolar ions has been shown to improve the performance of respirators and stationary filters challenged with non-biological particles. In this study, we investigated the ion-induced enhancement effect while challenging a low-efficiency heating, ventilation and air-conditioning (HVAC) filter with viable bacterial cells, bacterial and fungal spores, and viruses. The aerosol concentration was measured in real time. Samples were also collected with a bioaerosol sampler for viable microbial analysis. The removal efficiency of the filter was determined, respectively, with and without an ion emitter. The ionization was found to significantly enhance the filter efficiency in removing viable biological particles from the airflow. For example, when challenged with viable bacteria, the filter efficiency increased as much as four- to fivefold. For viable fungal spores, the ion-induced enhancement improved the efficiency by a factor of approximately 2. When testing with virus-carrying liquid droplets, the original removal efficiency provided by the filter was rather low: 9.09 +/- 4.84%. While the ion emission increased collection about fourfold, the efficiency did not reach 75-100% observed with bacteria and fungi. These findings, together with our previously published results for non-biological particles, demonstrate the feasibility of a new approach for reducing aerosol particles in HVAC systems used for indoor air quality control. Recirculated air in HVAC systems used for indoor air quality control in buildings often contains considerable number of viable bioaerosol particles because of limited efficiency of the filters installed in these systems. In the present study, we investigated - using aerosolized bacterial cells, bacterial and fungal spores, and virus-carrying particles - a novel idea of enhancing the performance of a low-efficiency HVAC filter utilizing continuous emission of unipolar ions in the filter vicinity. The findings described in
Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin
2014-03-01
Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.
A particle filter to reconstruct a free-surface flow from a depth camera
Energy Technology Data Exchange (ETDEWEB)
Combés, Benoit; Heitz, Dominique; Guibert, Anthony [IRSTEA, UR TERE, 17 avenue de Cucillé, F-35044 Rennes Cedex (France); Mémin, Etienne, E-mail: dominique.heitz@irstea.fr, E-mail: etienne.memin@inria.fr [INRIA, Fluminance group, Campus universitaire de Beaulieu, F-35042 Rennes Cedex (France)
2015-10-15
We investigate the combined use of a kinect depth sensor and of a stochastic data assimilation (DA) method to recover free-surface flows. More specifically, we use a weighted ensemble Kalman filter method to reconstruct the complete state of free-surface flows from a sequence of depth images only. This particle filter accounts for model and observations errors. This DA scheme is enhanced with the use of two observations instead of one classically. We evaluate the developed approach on two numerical test cases: a collapse of a water column as a toy-example and a flow in an suddenly expanding flume as a more realistic flow. The robustness of the method to depth data errors and also to initial and inflow conditions is considered. We illustrate the interest of using two observations instead of one observation into the correction step, especially for unknown inflow boundary conditions. Then, the performance of the Kinect sensor in capturing the temporal sequences of depth observations is investigated. Finally, the efficiency of the algorithm is qualified for a wave in a real rectangular flat bottomed tank. It is shown that for basic initial conditions, the particle filter rapidly and remarkably reconstructs the velocity and height of the free surface flow based on noisy measurements of the elevation alone. (paper)
A particle filter to reconstruct a free-surface flow from a depth camera
Combés, Benoit; Heitz, Dominique; Guibert, Anthony; Mémin, Etienne
2015-10-01
We investigate the combined use of a kinect depth sensor and of a stochastic data assimilation (DA) method to recover free-surface flows. More specifically, we use a weighted ensemble Kalman filter method to reconstruct the complete state of free-surface flows from a sequence of depth images only. This particle filter accounts for model and observations errors. This DA scheme is enhanced with the use of two observations instead of one classically. We evaluate the developed approach on two numerical test cases: a collapse of a water column as a toy-example and a flow in an suddenly expanding flume as a more realistic flow. The robustness of the method to depth data errors and also to initial and inflow conditions is considered. We illustrate the interest of using two observations instead of one observation into the correction step, especially for unknown inflow boundary conditions. Then, the performance of the Kinect sensor in capturing the temporal sequences of depth observations is investigated. Finally, the efficiency of the algorithm is qualified for a wave in a real rectangular flat bottomed tank. It is shown that for basic initial conditions, the particle filter rapidly and remarkably reconstructs the velocity and height of the free surface flow based on noisy measurements of the elevation alone.
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.
Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs
Directory of Open Access Journals (Sweden)
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.
Eftekhar Azam, Saeed
2014-01-01
This monograph assesses in depth the application of recursive Bayesian filters in structural health monitoring. Although the methods and algorithms used here are well established in the field of automatic control, their application in the realm of civil engineering has to date been limited. The monograph is therefore intended as a reference for structural and civil engineers who wish to conduct research in this field. To this end, the main notions underlying the families of Kalman and particle filters are scrutinized through explanations within the text and numerous numerical examples. The main limitations to their application in monitoring of high-rise buildings are discussed, and a remedy based on a synergy of reduced order modeling (based on proper orthogonal decomposition) and Bayesian estimation is proposed. The performance and effectiveness of the proposed algorithm is demonstrated via pseudo-experimental evaluations.
Modified particle filtering algorithm for single acoustic vector sensor DOA tracking.
Li, Xinbo; Sun, Haixin; Jiang, Liangxu; Shi, Yaowu; Wu, Yue
2015-10-16
The conventional direction of arrival (DOA) estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF) algorithm is proposed with state space model of single acoustic vector sensor. Although the particle filtering (PF) algorithm has been introduced for acoustic vector sensor applications, it is not suitable for the case that one dimension angle of source is estimated with large deviation, the two dimension angles (pitch angle and azimuth angle) cannot be simultaneously employed to update the state through resampling processing of PF algorithm. To solve the problems mentioned above, the MPF algorithm is proposed in which the state estimation of previous moment is introduced to the particle sampling of present moment to improve the importance function. Moreover, the independent relationship of pitch angle and azimuth angle is considered and the two dimension angles are sampled and evaluated, respectively. Then, the MUSIC spectrum function is used as the "likehood" function of the MPF algorithm, and the modified PF-MUSIC (MPF-MUSIC) algorithm is proposed to improve the root mean square error (RMSE) and the probability of convergence. The theoretical analysis and the simulation results validate the effectiveness and feasibility of the two proposed algorithms.
Modified Particle Filtering Algorithm for Single Acoustic Vector Sensor DOA Tracking
Directory of Open Access Journals (Sweden)
Xinbo Li
2015-10-01
Full Text Available The conventional direction of arrival (DOA estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF algorithm is proposed with state space model of single acoustic vector sensor. Although the particle filtering (PF algorithm has been introduced for acoustic vector sensor applications, it is not suitable for the case that one dimension angle of source is estimated with large deviation, the two dimension angles (pitch angle and azimuth angle cannot be simultaneously employed to update the state through resampling processing of PF algorithm. To solve the problems mentioned above, the MPF algorithm is proposed in which the state estimation of previous moment is introduced to the particle sampling of present moment to improve the importance function. Moreover, the independent relationship of pitch angle and azimuth angle is considered and the two dimension angles are sampled and evaluated, respectively. Then, the MUSIC spectrum function is used as the “likehood” function of the MPF algorithm, and the modified PF-MUSIC (MPF-MUSIC algorithm is proposed to improve the root mean square error (RMSE and the probability of convergence. The theoretical analysis and the simulation results validate the effectiveness and feasibility of the two proposed algorithms.
Representation of Probability Density Functions from Orbit Determination using the Particle Filter
Mashiku, Alinda K.; Garrison, James; Carpenter, J. Russell
2012-01-01
Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.
Improved near surface heavy impurity detection by a novel charged particle energy filter technique
Energy Technology Data Exchange (ETDEWEB)
Ishibashi, K.; Patnaik, B.K.; Parikh, N.R.; Tateno, H. [North Carolina Univ., Chapel Hill, NC (United States). Dept. of Physics and Astronomy; Hunn, J.D. [Oak Ridge National Lab., TN (United States)
1994-12-31
As the typical feature size of silicon integrated circuits, such as in VLSI technology, has become smaller, the surface cleanliness of silicon wafers has become more important. Hence, detection of trace impurities introduced during the processing steps is essential. A novel technique, consisting of a ``Charged Particle Energy Filter (CPEF)`` used in the path of the scattered helium ions in the conventional Rutherford Backscattering geometry, is proposed and its merits and limitations are discussed. In this technique, an electric field is applied across a pair of plates placed before the detector so that backscattered particles of only a selected energy range go through slits to strike the detector. This can be used to filter out particles from the lighter substrate atoms and thus reduce pulse pileup in the region of the impurity signal. The feasibility of this scheme was studied with silicon wafers implanted with 1{times}10{sup 14} and 1{times}10{sup 13} {sup 54}Fe/cm{sup 2} at an energy of 35 keV, and a 0.5 MeV He{sup +} analysis beam. It was found that the backscattered ion signals from the Si atoms can be reduced by more than three orders of magnitude. This suggests the detection limit for contaminants can be improved by at least two orders of magnitude compared to the conventional Rutherford Backscattering technique. This technique can be incorporated in 200--300 kV ion implanters for monitoring of surface contaminants in samples prior to implantation.
Onur Karslıoǧlu, Mahmut; Aghakarimi, Armin
2013-04-01
Ionosphere modeling is an important field of current studies because of its influences on the propagation of the electromagnetic signals. Among the various methods of obtaining ionospheric information, Global Positioning System (GPS) is the most prominent one because of extensive stations which are distributed all over the world. There are several studies in the literature related to the modeling of the ionosphere in terms of Total Electron Content (TEC). However, most of these studies investigate the ionosphere in the global and regional scales. On the other hand, complex dynamic of the ionosphere requires further studies in the local structure of the TEC distribution. In this work, Particle filter has been used for the investigation of the local character of the ionospheric Vertical Total Electron Content (VTEC). The GPS data of 29 ground based GPS stations, belonging to International GNSS Service (IGS) and Reference Frame Sub-commission for Europe (EUREF), for Europe have been used in this study. The data acquisition time is 18 February 2011 and the data is affected by the 15 February geomagnetic storm. In the preprocessing step, the observations of each satellite are examined for any possible cycle slip and also geometry-free linear combination of the observables are calculated for each continuous arc. Then, Pseudorange observations smoothed with the carrier to code leveling method. Particle filter is used for near-real time estimation of the VTEC and of the combined satellite and receiver biases. The Particle filter is implemented by recursively generating a set of weighted samples of the state variables. This filter has a flexible nature which can be more adaptive to some characteristics of the high dynamic systems. Besides, standard Kalman filter as an effective method for optimal state estimation is applied to the same data sets to compare the corresponding results with results of Particle filter. The comparison shows that Particle filter indicates better
Sen, Subhamoy; Crinière, Antoine; Mevel, Laurent; Cerou, Frederic; Dumoulin, Jean
2017-04-01
Keywords: Parameter estimation; Kalman filter; Particle filter; Particle-Kalman filter; Correlated noise Although Kalman filter (KF) was originally proposed for system control i.e. steering a system as desired by monitoring the system states, its application for parameter estimation problems is widespread because of the excellent similarity between these two apparently different problem types in state space description. In standard Kalman filter, system dynamics is described through the dynamics of certain internal variable, termed as states, evolving over time as defined by an assumed process model, while a measurement model maps these states to measurements. In some parameter estimation problems, the system is replaced by a state space formulation of the dynamic model with parameters appended in the unobserved states and collectively observed through the response measurements. Filtering based parameter estimation problems are thus inherently nonlinear due to the required nonlinear mapping of parameters to the corresponding observations. Being a linear estimator, Kalman Filter (KF) cannot be employed for such nonlinear system estimation and alternative filtering algorithms (eg. Particle filter) are therefore generally used. However, being model based, these filters optimally estimate the parameters of a quasi-static model of the real dynamic system. Consequently, any time variation in the system dynamics may completely diverge the estimation yielding a false or infeasible solution. By decoupling the estimation of system states and parameters, and applying concurrent filtering strategy that attempts conditional estimation of states based on parameters and vice versa, time varying systems can be estimated. This article attempts to combine KF with Particle filter (PF) and apply them for estimation of states and system parameters respectively on a system with correlated noise in process and measurement. The idea is to nest a bank of linear KFs for state estimation
Enhancing hydrologic data assimilation by evolutionary Particle Filter and Markov Chain Monte Carlo
Abbaszadeh, Peyman; Moradkhani, Hamid; Yan, Hongxiang
2018-01-01
Particle Filters (PFs) have received increasing attention by researchers from different disciplines including the hydro-geosciences, as an effective tool to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation using the PFs in hydrology has evolved since 2005 from the PF-SIR (sampling importance resampling) to PF-MCMC (Markov Chain Monte Carlo), and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and MCMC, the so-called EPFM. In this framework, the prior distribution undergoes an evolutionary process based on the designed mutation and crossover operators of GA. The merit of this approach is that the particles move to an appropriate position by using the GA optimization and then the number of effective particles is increased by means of MCMC, whereby the particle degeneracy is avoided and the particle diversity is improved. In this study, the usefulness and effectiveness of the proposed EPFM is investigated by applying the technique on a conceptual and highly nonlinear hydrologic model over four river basins located in different climate and geographical regions of the United States. Both synthetic and real case studies demonstrate that the EPFM improves both the state and parameter estimation more effectively and reliably as compared with the PF-MCMC.
Directory of Open Access Journals (Sweden)
Khanagha Ali
2010-01-01
Full Text Available Blind identification of MIMO FIR systems has widely received attentions in various fields of wireless data communications. Here, we use Particle Swarm Optimization (PSO as the update mechanism of the well-known inverse filtering approach and we show its good performance compared to original method. Specially, the proposed method is shown to be more robust against lower SNR scenarios or in cases with smaller lengths of available data records. Also, a modified version of PSO is presented which further improves the robustness and preciseness of PSO algorithm. However the most important promise of the modified version is its drastically faster convergence compared to standard implementation of PSO.
Modelling and measurement of wear particle flow in a dual oil filter system for condition monitoring
DEFF Research Database (Denmark)
Henneberg, Morten; Eriksen, René Lynge; Fich, Jens
2016-01-01
Wear debris is an indicator of the health of machinery, and the availability of accurate methods for characterising debris is important. In this work, a dual filter model for a gear oil system is used in conjunction with operational data to indicate three different system operating states....... The quantity of wear particles in gear oil is analysed with respect to system running conditions. It is shown that the model fits the data in terms of startup “particle burst” phenomenon, quasi-stationary conditions during operation, and clean-up filtration when placed out of operation. In order to establish...... oil. Using this model it is possible to draw conclusions on the filtration system performance and wear generation in the gears. Limitations of the proposed model are the lack of ability to describe noise and random burst spikes attributed to measurement error distributions. Trending of gear wear...
Heeb, Norbert V; Rey, Maria Dolores; Zennegg, Markus; Haag, Regula; Wichser, Adrian; Schmid, Peter; Seiler, Cornelia; Honegger, Peter; Zeyer, Kerstin; Mohn, Joachim; Bürki, Samuel; Zimmerli, Yan; Czerwinski, Jan; Mayer, Andreas
2015-08-04
Iron-catalyzed diesel particle filters (DPFs) are widely used for particle abatement. Active catalyst particles, so-called fuel-borne catalysts (FBCs), are formed in situ, in the engine, when combusting precursors, which were premixed with the fuel. The obtained iron oxide particles catalyze soot oxidation in filters. Iron-catalyzed DPFs are considered as safe with respect to their potential to form polychlorinated dibenzodioxins/furans (PCDD/Fs). We reported that a bimetallic potassium/iron FBC supported an intense PCDD/F formation in a DPF. Here, we discuss the impact of fatty acid methyl ester (FAME) biofuel on PCDD/F emissions. The iron-catalyzed DPF indeed supported a PCDD/F formation with biofuel but remained inactive with petroleum-derived diesel fuel. PCDD/F emissions (I-TEQ) increased 23-fold when comparing biofuel and diesel data. Emissions of 2,3,7,8-TCDD, the most toxic congener [toxicity equivalence factor (TEF) = 1.0], increased 90-fold, and those of 2,3,7,8-TCDF (TEF = 0.1) increased 170-fold. Congener patterns also changed, indicating a preferential formation of tetra- and penta-chlorodibenzofurans. Thus, an inactive iron-catalyzed DPF becomes active, supporting a PCDD/F formation, when operated with biofuel containing impurities of potassium. Alkali metals are inherent constituents of biofuels. According to the current European Union (EU) legislation, levels of 5 μg/g are accepted. We conclude that risks for a secondary PCDD/F formation in iron-catalyzed DPFs increase when combusting potassium-containing biofuels.
A Beamformer-Particle Filter Framework for Localization of Correlated EEG Sources.
Georgieva, Petia; Bouaynaya, Nidhal; Silva, Filipe; Mihaylova, Lyudmila; Jain, Lakhmi C
2016-05-01
Electroencephalography (EEG)-based brain computer interface (BCI) is the most studied noninvasive interface to build a direct communication pathway between the brain and an external device. However, correlated noises in EEG measurements still constitute a significant challenge. Alternatively, building BCIs based on filtered brain activity source signals instead of using their surface projections, obtained from the noisy EEG signals, is a promising and not well-explored direction. In this context, finding the locations and waveforms of inner brain sources represents a crucial task for advancing source-based noninvasive BCI technologies. In this paper, we propose a novel multicore beamformer particle filter (multicore BPF) to estimate the EEG brain source spatial locations and their corresponding waveforms. In contrast to conventional (single-core) beamforming spatial filters, the developed multicore BPF considers explicitly temporal correlation among the estimated brain sources by suppressing activation from regions with interfering coherent sources. The hybrid multicore BPF brings together the advantages of both deterministic and Bayesian inverse problem algorithms in order to improve the estimation accuracy. It solves the brain activity localization problem without prior information about approximate areas of source locations. Moreover, the multicore BPF reduces the dimensionality of the problem to half compared with the PF solution, thus alleviating the curse of dimensionality problem. The results, based on generated and real EEG data, show that the proposed framework recovers correctly the dominant sources of brain activity.
Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures
Energy Technology Data Exchange (ETDEWEB)
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.
Applying a particle filtering technique for canola crop growth stage estimation in Canada
Sinha, Abhijit; Tan, Weikai; Li, Yifeng; McNairn, Heather; Jiao, Xianfeng; Hosseini, Mehdi
2017-10-01
Accurate crop growth stage estimation is important in precision agriculture as it facilitates improved crop management, pest and disease mitigation and resource planning. Earth observation imagery, specifically Synthetic Aperture Radar (SAR) data, can provide field level growth estimates while covering regional scales. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization SAR data and ground truth growth stage data are used to model the influence of canola growth stages on SAR imagery extracted parameters. The details of the growth stage modeling work are provided, including a) the development of a new crop growth stage indicator that is continuous and suitable as the state variable in the dynamic estimation procedure; b) a selection procedure for SAR polarimetric parameters that is sensitive to both linear and nonlinear dependency between variables; and c) procedures for compensation of SAR polarimetric parameters for different beam modes. The data was collected over three crop growth seasons in Manitoba, Canada, and the growth model provides the foundation of a novel dynamic filtering framework for real-time estimation of canola growth stages using the multi-sensor and multi-mode SAR data. A description of the dynamic filtering framework that uses particle filter as the estimator is also provided in this paper.
Estimation of state-of-charge of Li-ion batteries in EV using the genetic particle filter
Bi, Jun; Gao, Hang; Wang, Yongxing; Zhao, Xiaomei
2017-08-01
Estimating the state of charge (SOC) of electric vehicle (EV) batteries accurately and timely is of great significance to the safe trip of pure EV. Based on the nonlinear properties of the battery, and the standard particle filter (PF) has certain adaptability for this feature, so it can be used to accurately estimate the SOC of the batteries. However, the standard PF has particle degeneracy phenomenon, which will make the accuracy of prediction lower. Therefore, in this paper, the genetic algorithm is applied to the standard PF, and the estimation of SOC is optimized, which makes the improved filter algorithm more accurate. Based on the measured data of Beijing pure electric sanitation vehicle, an experiment is defined to verify the algorithm. The experimental results show that the genetic particle filter (GPF) can increase the diversity of particles and has better prediction accuracy and timeliness than the PF.
Directory of Open Access Journals (Sweden)
Milan Kalas
2013-11-01
Full Text Available Snow is an important component of the water cycle, and its estimation in hydrological models is of great significance concerning the simulation and forecasting of flood events due to snow-melt. The assimilation of Snow Cover Area (SCA in physical distributed hydrological models is a possible source of improvement of snowmelt-related floods. In this study, the assimilation in the LISFLOOD model of the MODIS sensor SCA has been evaluated, in order to improve the streamflow simulations of the model. This work is realized with the final scope of improving the European Flood Awareness System (EFAS pan-European flood forecasts in the future. For this purpose daily 500 m resolution MODIS satellite SCA data have been used. Tests were performed in the Morava basin, a tributary of the Danube, for three years. The particle filter method has been chosen for assimilating the MODIS SCA data with different frequencies. Synthetic experiments were first performed to validate the assimilation schemes, before assimilating MODIS SCA data. Results of the synthetic experiments could improve modelled SCA and discharges in all cases. The assimilation of MODIS SCA data with the particle filter shows a net improvement of SCA. The Nash of resulting discharge is consequently increased in many cases.
PP and PS joint inversion with a posterior constraint and with particle filtering
Tang, Jing; Wang, Yanfei
2017-12-01
The Bayesian framework works well in amplitude versus offset (AVO) inversion, which merges multi-information together to generate posterior distributions of P-wave velocity, S-wave velocity and density. Most existing AVO inversion methods utilize PP reflection seismic data to predict the three elastic parameters. These methods are not usually sensitive to S-wave velocity and density, which make the inversion methods inaccurate and unstable. One way of solving these problems is to perform PP and PS joint inversion by incorporating PS seismic data. Another way is to provide a relatively accurate prior model. In this paper, we apply a particle filtering technique to produce a prior model for the PP and PS joint inversion. In the Bayesian inversion setting, the prior model works as the regularization term. Particle filtering is a Bayesian recursive method that combines prior information with observed data to provide a posterior constraint to reduce the joint inversion’s uncertainty. We generate synthetic models with different signal-to-noise ratios to validate our new method. Comparisons are provided with the traditional joint inversion, which adopts the Gaussian prior model. The inversion results show that the three elastic parameters are retrieved well when the signal-to-noise ratios are high. As the signal-to-noise ratio reduces, our new method can depict more detailed changes than the traditional inversion method, and improves the inversion accuracy apparent in the target layers.
Ikeda, Takeshi; Kawamoto, Mitsuru; Sashima, Akio; Suzuki, Keiji; Kurumatani, Koichi
In the field of the ubiquitous computing, positioning systems which can provide users' location information have paid attention as an important technical element which can be applied to various services, for example, indoor navigation services, evacuation services, market research services, guidance services, and so on. A lot of researchers have proposed various outdoor and indoor positioning systems. In this paper, we deal with indoor positioning systems. Many conventional indoor positioning systems use expensive infrastructures, because the propagated times of radio waves are used to measure users' positions with high accuracy. In this paper, we propose an indoor autonomous positioning system using radio signal strengths (RSSs) based on ISM band communications. In order to estimate users' positions, the proposed system utilizes a particle filter that is one of the Monte Carlo methods. Because the RSS information is used in the proposed system, the equipments configuring the system are not expensive compared with the conventional indoor positioning systems and it can be installed easily. Moreover, because the particle filter is used to estimate user's position, even if the RSS fluctuates due to, for example, multi-paths, the system can carry out position estimation robustly. We install the proposed system in one floor of a building and carry out some experiments in order to verify the validity of the proposed system. As a result, we confirmed that the average of the estimation errors of the proposed system was about 1.8 m, where the result is enough accuracy for achieving the services mentioned above.
Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines
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Boming Song
2017-01-01
Full Text Available Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non-line of sight (NLOS propagation error of the localization signal between the access point (AP and the target node (Tag. In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR method or received signal strength indication (RSSI based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.
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Huan Ma
2016-01-01
Full Text Available Size- and time-dependent aerodynamic behaviors of indoor particles, including PM1.0, were evaluated in a school office in order to test the performance of air-cleaning devices using different filters. In-situ real-time measurements were taken using an optical particle counter. The filtration characteristics of filter media, including single-pass efficiency, volume and effectiveness, were evaluated and analyzed. The electret filter (EE medium shows better initial removal efficiency than the high efficiency (HE medium in the 0.3–3.5 μm particle size range, while under the same face velocity, the filtration resistance of the HE medium is several times higher than that of the EE medium. During service life testing, the efficiency of the EE medium decreased to 60% with a total purifying air flow of 25 × 104 m3/m2. The resistance curve rose slightly before the efficiency reached the bottom, and then increased almost exponentially. The single-pass efficiency of portable air cleaner (PAC with the pre-filter (PR or the active carbon granule filter (CF was relatively poor. While PAC with the pre-filter and the high efficiency filter (PR&HE showed maximum single-pass efficiency for PM1.0 (88.6%, PAC with the HE was the most effective at removing PM1.0. The enhancement of PR with HE and electret filters augmented the single-pass efficiency, but lessened the airflow rate and effectiveness. Combined with PR, the decay constant of large-sized particles could be greater than for PACs without PR. Without regard to the lifetime, the electret filters performed better with respect to resource saving and purification improvement. A most penetrating particle size range (MPPS: 0.4–0.65 μm exists in both HE and electret filters; the MPPS tends to become larger after HE and electret filters are combined with PR. These results serve to provide a better understanding of the indoor particle removal performance of PACs when combined with different kinds of filters in
Rudell, B; Blomberg, A; Helleday, R; Ledin, M C; Lundbäck, B; Stjernberg, N; Hörstedt, P; Sandström, T
1999-08-01
Air pollution particulates have been identified as having adverse effects on respiratory health. The present study was undertaken to further clarify the effects of diesel exhaust on bronchoalveolar cells and soluble components in normal healthy subjects. The study was also designed to evaluate whether a ceramic particle trap at the end of the tail pipe, from an idling engine, would reduce indices of airway inflammation. The study comprised three exposures in all 10 healthy never smoking subjects; air, diluted diesel exhaust, and diluted diesel exhaust filtered with a ceramic particle trap. The exposures were given for 1 hour in randomised order about 3 weeks apart. The diesel exhaust exposure apperatus has previously been carefully developed and evaluated. Bronchoalveolar lavage was performed 24 hours after exposures and the lavage fluids from the bronchial and bronchoalveolar region were analysed for cells and soluble components. The particle trap reduced the mean steady state number of particles by 50%, but the concentrations of the other measured compounds were almost unchanged. It was found that diesel exhaust caused an increase in neutrophils in airway lavage, together with an adverse influence on the phagocytosis by alveolar macrophages in vitro. Furthermore, the diesel exhaust was found to be able to induce a migration of alveolar macrophages into the airspaces, together with reduction in CD3+CD25+ cells. (CD = cluster of differentiation) The use of the specific ceramic particle trap at the end of the tail pipe was not sufficient to completely abolish these effects when interacting with the exhaust from an idling vehicle. The current study showed that exposure to diesel exhaust may induce neutrophil and alveolar macrophage recruitment into the airways and suppress alveolar macrophage function. The particle trap did not cause significant reduction of effects induced by diesel exhaust compared with unfiltered diesel exhaust. Further studies are warranted to
3D Shape-Encoded Particle Filter for Object Tracking and Its Application to Human Body Tracking
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R. Chellappa
2008-03-01
Full Text Available We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The Ã¢Â€Âœshape filterÃ¢Â€Â has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measures to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.
3D Shape-Encoded Particle Filter for Object Tracking and Its Application to Human Body Tracking
Directory of Open Access Journals (Sweden)
Chellappa R
2008-01-01
Full Text Available Abstract We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The "shape filter" has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measures to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.
Templeton, Michael R; Andrews, Robert C; Hofmann, Ron
2007-06-01
This bench-scale study investigated the passage of particle-associated bacteriophage through a dual-media (anthracite-sand) filter over a complete filter cycle and the effect on subsequent ultraviolet (UV) disinfection. Two model viruses, bacteriophages MS2 and T4, were considered. The water matrix was de-chlorinated tap water with either kaolin or Aldrich humic acid (AHA) added and coagulated with alum to form floc before filtration. The turbidity of the influent flocculated water was 6.4+/-1.5 NTU. Influent and filter effluent turbidity and particle counts were measured as well as headloss across the filter media. Filter effluent samples were collected for phage enumeration during three filter cycle stages: (i) filter ripening; (ii) stable operation; and (iii) end of filter cycle. Stable filter operation was defined according to a filter effluent turbidity goal of filtration. There was reduced UV disinfection efficiency due to the presence of particle-associated phage in the filter effluent in trials with bacteriophage MS2 and humic acid floc. Unfiltered influent water samples also resulted in reduced UV inactivation of phage relative to particle-free control conditions for both phages. Trends in filter effluent turbidity corresponded with breakthrough of particle-associated phage in the filter effluent. The results therefore suggest that maintenance of optimum filtration conditions upstream of UV disinfection is a critical barrier to particle-associated viruses.
A radiative transfer scheme that considers absorption, scattering, and distribution of light-absorbing elemental carbon (EC) particles collected on a quartz-fiber filter was developed to explain simultaneous filter reflectance and transmittance observations prior to and during...
Zhu, Zhiliang; Meng, Zhiqiang; Cao, Tingting; Zhang, Zhengjiang; Dai, Yuxing
2017-06-01
State and parameter estimation (SPE) plays an important role in process monitoring, online optimization, and process control. The estimation of states and parameters is generally solved simultaneously in the SPE problem, where the parameters to be estimated are specified as augmented states. When state and/or measurement equations are highly nonlinear and the posterior probability of the state is non-Gaussian, particle filter (PF) is commonly used for SPE. However, when the parameters switch with the operating conditions, the change of parameters cannot be detected and tracked by the conventional SPE method. This paper proposes a PF-based robust SPE method for a nonlinear process system with variable parameters. The measurement test criterion based on observation error is introduced to indirectly identify whether the parameters are changed. Based on the result of identification, the variances of the particles are modified adaptively for the tracking of the changed parameters. Finally, reliable SPE can be derived through iterative particles. The proposed PF-based robust SPE method is applied to two nonlinear process systems. The results demonstrate the effectiveness and robustness of the proposed method.
Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol
2017-06-01
We introduce a sequential importance sampling particle filter (PF)-based multisensor multivariate nonlinear estimator for estimating the in-core neutron flux distribution for pressurized heavy water reactor core. Many critical applications such as reactor protection and control rely upon neutron flux information, and thus their reliability is of utmost importance. The point kinetic model based on neutron transport conveniently explains the dynamics of nuclear reactor. The neutron flux in the large core loosely coupled reactor is sensed by multiple sensors measuring point fluxes located at various locations inside the reactor core. The flux values are coupled to each other through diffusion equation. The coupling facilitates redundancy in the information. It is shown that multiple independent data about the localized flux can be fused together to enhance the estimation accuracy to a great extent. We also propose the sensor anomaly handling feature in multisensor PF to maintain the estimation process even when the sensor is faulty or generates data anomaly.
A Particle Filter Approach to Respiratory Motion Estimation in Nuclear Medicine Imaging
Rahni, A. A. Abd.; Lewis, E.; Guy, M. J.; Goswami, B.; Wells, K.
2011-10-01
With the continual improvement in spatial resolution of Nuclear Medicine (NM) scanners, it has become increasingly important to accurately compensate for patient motion during image acquisition. Respiratory motion produced by normal lung ventilation is a major source of artefacts in NM emission imaging that can affect large parts of the abdominal thoracic cavity. As such, a particle filter (PF) is proposed as a powerful method for motion correction in emission imaging which can successfully account for previously unseen motion. This paper explores a basic PF approach and demonstrates that it is possible to estimate temporally non-stationary motion using training data consisting of only a single respiratory cycle. Evaluation using the XCAT phantom suggests that the PF is a highly promising approach, and can appropriately handle the complex data that arises in clinical situations.
An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm
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Kai Hu
2015-01-01
Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.
Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V
2015-04-30
In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time.
Guitarist Fingertip Tracking by Integrating a Bayesian Classifier into Particle Filters
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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.
Ryu, Duchwan
2013-03-01
The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle filter to estimate the parameters of the dynamic model. We analyze the SST observed in the Caribbean Islands area after a hurricane using the proposed dynamic model. Comparing to the traditional grid-based approach that requires a supercomputer due to its high computational demand, our approach requires much less CPU time and makes real-time forecasting of SST doable on a personal computer. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V.
2015-01-01
In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time. PMID:25942641
Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar
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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.
Particle tracking with iterated Kalman filters and smoothers the PMHT algorithm
Strandlie, A
1999-01-01
We introduce the Probabilistic Multi-Hypothesis Tracking (PMHT) algorithm for particle tracking in high-energy physics detectors. This algorithm has been developed recently for tracking multiple targets in clutter, and it is based on maximum likelihood estimation with help of the EM algorithm. The resulting algorithm basically consists of running several iterated and coupled Kalman filters and smoothers in parallel. It is similar to the Elastic Arms algorithm, but it possesses the additional feature of being able to take process noise into account, as for instance multiple Coulomb scattering. Herein, we review its basic properties and derive a generalized version of the algorithm by including a deterministic annealing scheme. Further developments of the algorithm in order to improve the performance are also discussed. In particular, we propose to modify the hit-to-track assignment probabilities in order to obtain competition between hits in the same detector layer. Finally, we present results of an implementa...
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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.
Particle velocity estimation based on a two-microphone array and Kalman filter.
Bai, Mingsian R; Juan, Shen-Wei; Chen, Ching-Cheng
2013-03-01
A traditional method to measure particle velocity is based on the finite difference (FD) approximation of pressure gradient by using a pair of well matched pressure microphones. This approach is known to be sensitive to sensor noise and mismatch. Recently, a double hot-wire sensor termed Microflown became available in light of micro-electro-mechanical system technology. This sensor eliminates the robustness issue of the conventional FD-based methods. In this paper, an alternative two-microphone approach termed the u-sensor is developed from the perspective of robust adaptive filtering. With two ordinary microphones, the proposed u-sensor does not require novel fabrication technology. In the method, plane wave and spherical wave models are employed in the formulation of a Kalman filter with process and measurement noise taken into account. Both numerical and experimental investigations were undertaken to validate the proposed u-sensor technique. The results have shown that the proposed approach attained better performance than the FD method, and comparable performance to a Microflown sensor.
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Tao Li
2016-03-01
Full Text Available The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF and Kalman filter (KF. The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.
Kim, R. S.; Durand, M. T.
2016-12-01
This paper presents and illustrates improved retrieval method of snow water equivalent (SWE) from airborne passive microwave (PM) measurements. A particle filter approach is proposed to assimilate PM brightness temperature (Tb) data in order to update snowpack states in a land surface model and demonstrates compared to ensemble Kalman filter (EnKF) method. The methods were applied over the Yampa river basin in the Colorado Rockies within the NASA Cold Land Processes Experiment (CLPX) area of 2002-2003. Forcing data is derived from the North American Land Data Assimilation v2 (NLDAS-2) dataset and Microwave Emission Model of Layered Snowpacks (MEMLS) is used to convert the snow state variables to Tb. The effects of vegetation and atmosphere are included in the radiative transfer model (RTM). Multifrequency measurements of PSR (Polarimetric Scanning Radiometer) are used and assimilated into model predictions of SWE at 120-m spatial resolution. The contributions of each channel to recover the true SWE are computed and analyzed. The SWE estimation is validated against SNOTEL and snow course observations.
Assessment of lumen degradation and remaining useful life of LEDs using particle filter
Energy Technology Data Exchange (ETDEWEB)
Lall, Pradeep [Auburn Univ., AL (United States); Zhang, Hao [Auburn Univ., AL (United States); Davis, Lynn [Auburn Univ., AL (United States)
2013-07-16
With the development of light-emitting diode (LED) technology, light emitting diodes system is becoming a popular light source in daily life and industry area. It has shown that Led from same factory and work under same working condition, may have significantly different behavior. Therefore, it is very important to learn the fail mechanisms, especially in the case of safety critical and harsh environment application. This paper focus on a prognostic health management (PHM) method based on the measurement of forward voltage and forward current of bare LED under harsh environment. In this paper, experiment has been done with ten samples. Ten pristine bare LEDs have been tested at 85°C while simultaneously being subjected to 85% humid environment. Pulse width modulation (PWM) control method has been employed to drive the bare LED in order to reduce the heat effect caused by forward current and high frequency (300HZ) data acquisition has been used to measure the peak forward voltage and forward current. Test to failure (lumen drops to 70 percent) data has been measured to study the effects of high temperature and humid environment loadings on the bare LED. Also, solid state cooling method with peltier cooler has been used to control the temperature of LED in the integrating sphere when take the measurement of lumen flux. The shift of forward voltage forward current curve and lumen degradation has been recorded to help build the fail model and predicted the remaining useful life. In this method, particle filter has been employed to predict the remaining useful life (RUL) of the bare LED and give us a whole picture how Led system fails. Result shows that predication of remaining useful life of Led, made by the particle filter model works under reasonable limit, and hence this method can be employed to predict the failure of Led caused by thermal and humid stress under harsh environment.
Energy Technology Data Exchange (ETDEWEB)
Hirota, Noriyuki, E-mail: hirota.noriyuki@nims.go.jp [Fine Particle Engineering Group, National Institute for Materials Science, 3-13 Sakura, Tsukuba (Japan); Ando, Tsutomu; Takano, Tadamitsu [Department of Mechanical Engineering, Nihon University, 1-2-1 Izumicho, Narashino 275-8575 (Japan); Okada, Hidehiko [Fine Particle Engineering Group, National Institute for Materials Science, 3-13 Sakura, Tsukuba (Japan)
2017-04-01
Abstracts: In-situ observations of particles deposition process on a ferromagnetic filter in high gradient magnetic separation were carried out under high magnetic fields to obtain information for the optimization of separation condition. The spike-like deposition structure was observed on the upper stream of the magnetic filter, different from the conventional deposition image obtained for paramagnetic particles. The length of the spike structure tends to be long with lower flow velocity and lower applied magnetic field. It was also observed that the chain structure or the bundle of such chaines were formed on the way to the filter under the condition of the low applied magnetic field and low flow rates. Results obtained here indicate that the effect of deposited particles on the spatial distribution of the magnetic field and the hydrodynamics, they are often ignored in the simulation so far, should be considered appropriately. - Highlights: • In-situ observation of particles deposition process on a ferromagnetic filter in HGMS. • The spike-like deposition structure was observed on the upper stream. • Longer spike structure formed under lower magnetic fields and lower flow rates. • Effect of the magnetization of deposited particles should be considered appropriately.
Energy Technology Data Exchange (ETDEWEB)
Hemmer, G.; Umhauer, H.; Kasper, G. [Univ. Karlsruhe, Inst. fuer Mechanische Verfahrenstechnik und Mechanik, Karlsruhe (Germany); Berbner, S. [Freudenberg Nonwovens, Filtration Div., Hopkinsville, KY (United States)
1999-07-01
Based on the experiences of earlier investigations a special optical particle counter was developed capable of recording size and quantity (concentration) of the particles directly within a given gas particle stream under the prevailing conditions (true in-situ measurements at high temperatures). In addition to earlier investigations [1], a second type of ceramic filter media with much smaller porosity and a membrane layer on the filtration side was tested. The candles with a length of 1.5 m which are used in industrial applications were mounted in the same hot gas filtration unit already used before. Measurements on the clean gas side at temperatures of up to 1000 C have been conducted using a fraction of quartz particles as test dust. The particle size ranged between 0.3 {mu}m and 10 {mu}m. Filtration velocity (1.5 cm/s) and final pressure drop of dust cake {delta}p (1000 Pa) were kept constant. As a main result the fractional efficiency as function of temperature is discussed and compared with that obtained before for a filter media of type I: The fractional efficiency values of filter type II are at least 100 times higher than that of filter type I. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Shafiee, Sara; Zarrebini, Mohammad; Naghashzargar, Elham, E-mail: e.naghashzargar@tx.iut.ac.ir; Semnani, Dariush, E-mail: d-semnani@cc.iut.ac.ir [Isfahan University of Technology, Department of Textile Engineering (Iran, Islamic Republic of)
2015-10-15
Disinfection and elimination of pathogenic microorganisms from liquid can be achieved by filtration process using antibacterial filter media. The advent of nanotechnology has facilitated the introduction of membranes consisting of nano-fiber in filtration operations. The melt electro-spun fibers due to their extremely small diameters are used in the production of this particular filtration medium. In this work, antibacterial polypropylene filter medium containing clay particles and nano-TiO{sub 2} were made using melt electro-spun technology. Antibacterial performance of polypropylene nano-filters was evaluated using E. coli bacteria. Additionally, filtration efficiency of the samples in terms fiber diameter, filter porosity, and fiber distribution using image processing technique was determined. Air permeability and dust aerosol tests were conducted to establish the suitability of the samples as a filter medium. It was concluded that as far as antibacterial property is concerned, nano-fibers filter media containing clay particles are preferential to similar media containing TiO{sub 2} nanoparticles.
Energy Technology Data Exchange (ETDEWEB)
Rodriguez, J.M.; Macias-Machin, A. [ETSII de Las Palmas (Spain); Alvaro, A.; Sanchez, J.R.; Estevez, A.M. [Univ. de Salamanca (Spain). Dept. de Ingenieria Quimica y Textil
1999-01-01
The present study deals with the influence of diverse operating variables such as gas velocity, height of the bed, magnetic field strength, and particle bounce on separation of fine dust particles (iron oxide) in magnetically stabilized granular filters (MSF). The collection results are more effective when the height of the MSF and dust sizes increase. Investigations concerning the magnetic field behavior have shown that the collection efficiency increases when the magnetic field also increases. And the increase of the magnetic field strength has shown that particle bounce significantly decreases and the adhesion probability of the MSF improves.
Epileptic Seizure Prediction by a System of Particle Filter Associated with a Neural Network
Liu, Derong; Pang, Zhongyu; Wang, Zhuo
2009-12-01
None of the current epileptic seizure prediction methods can widely be accepted, due to their poor consistency in performance. In this work, we have developed a novel approach to analyze intracranial EEG data. The energy of the frequency band of 4-12 Hz is obtained by wavelet transform. A dynamic model is introduced to describe the process and a hidden variable is included. The hidden variable can be considered as indicator of seizure activities. The method of particle filter associated with a neural network is used to calculate the hidden variable. Six patients' intracranial EEG data are used to test our algorithm including 39 hours of ictal EEG with 22 seizures and 70 hours of normal EEG recordings. The minimum least square error algorithm is applied to determine optimal parameters in the model adaptively. The results show that our algorithm can successfully predict 15 out of 16 seizures and the average prediction time is 38.5 minutes before seizure onset. The sensitivity is about 93.75% and the specificity (false prediction rate) is approximately 0.09 FP/h. A random predictor is used to calculate the sensitivity under significance level of 5%. Compared to the random predictor, our method achieved much better performance.
Particle Filter with Integrated Voice Activity Detection for Acoustic Source Tracking
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Lehmann Eric A
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.
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.
Epileptic Seizure Prediction by a System of Particle Filter Associated with a Neural Network
Directory of Open Access Journals (Sweden)
Derong Liu
2009-01-01
Full Text Available None of the current epileptic seizure prediction methods can widely be accepted, due to their poor consistency in performance. In this work, we have developed a novel approach to analyze intracranial EEG data. The energy of the frequency band of 4–12 Hz is obtained by wavelet transform. A dynamic model is introduced to describe the process and a hidden variable is included. The hidden variable can be considered as indicator of seizure activities. The method of particle filter associated with a neural network is used to calculate the hidden variable. Six patients' intracranial EEG data are used to test our algorithm including 39 hours of ictal EEG with 22 seizures and 70 hours of normal EEG recordings. The minimum least square error algorithm is applied to determine optimal parameters in the model adaptively. The results show that our algorithm can successfully predict 15 out of 16 seizures and the average prediction time is 38.5 minutes before seizure onset. The sensitivity is about 93.75% and the specificity (false prediction rate is approximately 0.09 FP/h. A random predictor is used to calculate the sensitivity under significance level of 5%. Compared to the random predictor, our method achieved much better performance.
Incorporating advanced language models into the P300 speller using particle filtering
Speier, W.; Arnold, C. W.; Deshpande, A.; Knall, J.; Pouratian, N.
2015-08-01
Objective. The P300 speller is a common brain-computer interface (BCI) application designed to communicate language by detecting event related potentials in a subject’s electroencephalogram signal. Information about the structure of natural language can be valuable for BCI communication, but attempts to use this information have thus far been limited to rudimentary n-gram models. While more sophisticated language models are prevalent in natural language processing literature, current BCI analysis methods based on dynamic programming cannot handle their complexity. Approach. Sampling methods can overcome this complexity by estimating the posterior distribution without searching the entire state space of the model. In this study, we implement sequential importance resampling, a commonly used particle filtering (PF) algorithm, to integrate a probabilistic automaton language model. Main result. This method was first evaluated offline on a dataset of 15 healthy subjects, which showed significant increases in speed and accuracy when compared to standard classification methods as well as a recently published approach using a hidden Markov model (HMM). An online pilot study verified these results as the average speed and accuracy achieved using the PF method was significantly higher than that using the HMM method. Significance. These findings strongly support the integration of domain-specific knowledge into BCI classification to improve system performance.
Chen, Jian; Yuan, Shenfang; Qiu, Lei; Wang, Hui; Yang, Weibo
2018-01-01
Accurate on-line prognosis of fatigue crack propagation is of great meaning for prognostics and health management (PHM) technologies to ensure structural integrity, which is a challenging task because of uncertainties which arise from sources such as intrinsic material properties, loading, and environmental factors. The particle filter algorithm has been proved to be a powerful tool to deal with prognostic problems those are affected by uncertainties. However, most studies adopted the basic particle filter algorithm, which uses the transition probability density function as the importance density and may suffer from serious particle degeneracy problem. This paper proposes an on-line fatigue crack propagation prognosis method based on a novel Gaussian weight-mixture proposal particle filter and the active guided wave based on-line crack monitoring. Based on the on-line crack measurement, the mixture of the measurement probability density function and the transition probability density function is proposed to be the importance density. In addition, an on-line dynamic update procedure is proposed to adjust the parameter of the state equation. The proposed method is verified on the fatigue test of attachment lugs which are a kind of important joint components in aircraft structures. Copyright © 2017 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Barone, Teresa L [ORNL; Storey, John Morse [ORNL; Domingo, Norberto [ORNL
2010-01-01
A field-aged, passive diesel particulate filter (DPF) employed in a school bus retrofit program was evaluated for emissions of particle mass and number concentration before, during and after regeneration. For the particle mass measurements, filter samples were collected for gravimetric analysis with a partial flow sampling system, which sampled proportionally to the exhaust flow. Total number concentration and number-size distributions were measured by a condensation particle counter and scanning mobility particle sizer, respectively. The results of the evaluation show that the number concentration emissions decreased as the DPF became loaded with soot. However after soot removal by regeneration, the number concentration emissions were approximately 20 times greater, which suggests the importance of the soot layer in helping to trap particles. Contrary to the number concentration results, particle mass emissions decreased from 6 1 mg/hp-hr before regeneration to 3 2 mg/hp-hr after regeneration. This indicates that nanoparticles with diameter less than 50 nm may have been emitted after regeneration since these particles contribute little to the total mass. Overall, average particle emission reductions of 95% by mass and 10,000-fold by number concentration after four years of use provided evidence of the durability of a field-aged DPF. In contrast to previous reports for new DPFs in which elevated number concentrations occurred during the first 200 seconds of a transient cycle, the number concentration emissions were elevated during the second half of the heavy-duty federal test procedure when high speed was sustained. This information is relevant for the analysis of mechanisms by which particles are emitted from field-aged DPFs.
Michenfelder, Maggie M; Bartlett, Lucas J; Mahoney, Douglas W; Herold, Thomas J; Hung, Joseph C
2014-12-01
Sentinel node lymphoscintigraphy using colloidal particles has become common practice at many institutions. The ideal particle size for colloids such as filtered (99m)Tc-sulfur colloid ((99m)Tc-FSC) in sentinel node studies is 15-100 nm. It is reported that the use of a reduced heating time during the reconstitution process results in an increased number of smaller particles (15 nm) would be of benefit in sentinel node studies. This study sought to better define particle size by using electron microscopy, as well as to evaluate the radiochemical purity (RCP) of (99m)Tc-FSC at various time points after filtration. One group of (99m)Tc-sulfur colloid ((99m)Tc-SC) preparations was reconstituted using the standard heating time of 5 min, and another group was prepared using a reduced heating time of 3 min. The (99m)Tc-SC preparations were passed through a 0.2-μm filter, and retained filter activity was measured. RCP values were collected at 0, 1, 3, and 6 h after filtration, and the particle sizes were measured at 0 and 6 h after filtration. Average RCP values (± SD) for (99m)Tc-FSC with 5-min heating were 98.4% ± 3.0% and 98.3% ± 1.8% for 0 h and 6 h, respectively (n = 6). Average RCP values for (99m)Tc-FSC with 3-min heating were 98.4% ± 4.1% and 96.9% ± 3.1% for 0 h and 6 h, respectively (n = 6). Electron microscopy data showed that median particle sizes for the 3-min heating at 0 and 6 h were 24 and 35 nm, respectively. Median particle sizes for the 5-min heating at 0 and 6 h were 29 and 27 nm, respectively. The proportion of particles within the ideal range for sentinel node lymphoscintigraphy was similar between the heating methods (91.1% for 3-min heating at 0 h and 88.8% for 5-min heating at 0 h, P = 0.1851). Our results indicate that although there are slight significant differences in RCP value, particle size, and particle number for (99m)Tc-FSC prepared using either a standard or a reduced heating time, both methods produce particles within the optimum
Directory of Open Access Journals (Sweden)
Yi Zhou
Full Text Available Industrial aquaculture wastewater contains large quantities of suspended particles that can be easily broken down physically. Introduction of macro-bio-filters, such as bivalve filter feeders, may offer the potential for treatment of fine suspended matter in industrial aquaculture wastewater. In this study, we employed two kinds of bivalve filter feeders, the Pacific oyster Crassostrea gigas and the blue mussel Mytilus galloprovincialis, to deposit suspended solids from marine fish aquaculture wastewater in flow-through systems. Results showed that the biodeposition rate of suspended particles by C. gigas (shell height: 8.67 ± 0.99 cm and M. galloprovincialis (shell height: 4.43 ± 0.98 cm was 77.84 ± 7.77 and 6.37 ± 0.67 mg ind(-1 • d(-1, respectively. The total solid suspension (TSS deposition rates of oyster and mussel treatments were 3.73 ± 0.27 and 2.76 ± 0.20 times higher than that of the control treatment without bivalves, respectively. The TSS deposition rates of bivalve treatments were significantly higher than the natural sedimentation rate of the control treatment (P < 0.001. Furthermore, organic matter and C, N in the sediments of bivalve treatments were significantly lower than those in the sediments of the control (P < 0.05. It was suggested that the filter feeders C. gigas and M. galloprovincialis had considerable potential to filter and accelerate the deposition of suspended particles from industrial aquaculture wastewater, and simultaneously yield value-added biological products.
Directory of Open Access Journals (Sweden)
Xueping Fan
2016-05-01
Full Text Available In the long-term service period, the bridge health monitoring system produced a huge amount of monitoring stress data; proper handling of these data is one of the main difficulties in the field of structural health monitoring, especially to predict the structural stress based on the monitored data. The objectives of this article are to present: (1 a nonlinear dynamic model, (2 a nonlinear mixed Gaussian particle filtering algorithm for predicting the monitored data based on the dynamic model, and (3 an approach combining nonlinear mixed Gaussian particle filtering algorithm with structural health monitoring data to predict the structural stress under uncertainty in real time. And an actual example is provided to illustrate the application and feasibility of the proposed models and methods.
Directory of Open Access Journals (Sweden)
Xinlong Jiang
2015-01-01
Full Text Available As the development of Indoor Location Based Service (Indoor LBS, a timely localization and smooth tracking with high accuracy are desperately needed. Unfortunately, any single method cannot meet the requirement of both high accuracy and real-time ability at the same time. In this paper, we propose a fusion location framework with Particle Filter using Wi-Fi signals and motion sensors. In this framework, we use Extreme Learning Machine (ELM regression algorithm to predict position based on motion sensors and use Wi-Fi fingerprint location result to solve the error accumulation of motion sensors based location occasionally with Particle Filter. The experiments show that the trajectory is smoother as the real one than the traditional Wi-Fi fingerprint method.
Energy Technology Data Exchange (ETDEWEB)
Manoli, Gabriele, E-mail: manoli@dmsa.unipd.it [Department of Mathematics, University of Padova, Via Trieste 63, 35121 Padova (Italy); Nicholas School of the Environment, Duke University, Durham, NC 27708 (United States); Rossi, Matteo [Department of Geosciences, University of Padova, Via Gradenigo 6, 35131 Padova (Italy); Pasetto, Damiano [Department of Mathematics, University of Padova, Via Trieste 63, 35121 Padova (Italy); Deiana, Rita [Dipartimento dei Beni Culturali, University of Padova, Piazza Capitaniato 7, 35139 Padova (Italy); Ferraris, Stefano [Interuniversity Department of Regional and Urban Studies and Planning, Politecnico and University of Torino, Viale Mattioli 39, 10125 Torino (Italy); Cassiani, Giorgio [Department of Geosciences, University of Padova, Via Gradenigo 6, 35131 Padova (Italy); Putti, Mario [Department of Mathematics, University of Padova, Via Trieste 63, 35121 Padova (Italy)
2015-02-15
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequential inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.
Chen, Fang; Liu, Jia; Liao, Hongen
2017-03-01
In endovascular catheter interventions, the determination of the three-dimensional (3D) catheter shape can increase navigation information and help reduce trauma. This study describes a shape determination method for a flexible interventional catheter using ultrasound scanning and a two-step particle filter without X-ray fluoroscopy. First, we propose a multi-feature, multi-template particle filter algorithm for accurate catheter tracking from ultrasound images. Second, we model the mechanical behavior of the catheter and apply a particle filter shape optimization algorithm to refine the results from the first step. Finally, the acquired catheter's 3D shapes are displayed together with the preoperative 3D images of the cardiac structures to provide intuitive endovascular navigation. We validated our method using ultrasound scanning of the straight and curved catheters in a water tank, and the shape determination errors were 1.44 ± 0.38 mm and 1.95 ± 0.46 mm, respectively. Further, endovascular catheter shape determination was validated in a catheter intervention experiment with a heart phantom. The error of the acquired endovascular catheter shape was 2.23 ± 0.87 mm. These results demonstrate that our two-step method is both accurate and effective. Using ultrasound scanning for shape determination of a flexible catheter will be helpful in endovascular interventions, reducing exposure to radiation and providing rich navigation information.
Decentralized Riemannian Particle Filtering with Applications to Multi-Agent Localization
2012-06-14
will be defined for all p ∈ S and τ ∈ Tp(S). Geodesic completeness is a natural segway to the Hopf-Rinow- De Rham Theorem [166], which is both...approaches provides a natural segway into the defining of the filtering manifold used for algorithm development, along with the filter- ing tools made
Combined Particle Filter and Selective Catalytic Reduction Catalyst for Diesel Engines
DEFF Research Database (Denmark)
Hvam, Jeanette
them ideal for multiple applications like high power electronic devices, heating elements, abrasive materials and cutting tools. Porous silicon carbide is suitable for electrode and catalyst support material as well as hot gas filter units or a combination of these. The automotive industry demands new...... for exhaust gas purification. By combining the particulate filtration application with the application as catalyst support for NOx reduction, the low emissions standards can be met. This project was initiated as a result of the need for new and improved filters with characteristics making it suitable...... here. A new and improved filter was developed on the basis of the research results concerning copper as partner additive. In comparison to filters produced with aluminium as sole additive, these new filters exhibit enhanced mechanical stability, enhanced microstructure and controllable surface...
Directory of Open Access Journals (Sweden)
J. E. Engström
2011-08-01
Full Text Available The presented filter-based optical method for determination of soot (light absorbing carbon or Black Carbon, BC can be implemented in the field under primitive conditions and at low cost. This enables researchers with small economical means to perform monitoring at remote locations, especially in the Asia where it is much needed.
One concern when applying filter-based optical measurements of BC is that they suffer from systematic errors due to the light scattering of non-absorbing particles co-deposited on the filter, such as inorganic salts and mineral dust. In addition to an optical correction of the non-absorbing material this study provides a protocol for correction of light scattering based on the chemical quantification of the material, which is a novelty. A newly designed photometer was implemented to measure light transmission on particle accumulating filters, which includes an additional sensor recording backscattered light. The choice of polycarbonate membrane filters avoided high chemical blank values and reduced errors associated with length of the light path through the filter.
Two protocols for corrections were applied to aerosol samples collected at the Maldives Climate Observatory Hanimaadhoo during episodes with either continentally influenced air from the Indian/Arabian subcontinents (winter season or pristine air from the Southern Indian Ocean (summer monsoon. The two ways of correction (optical and chemical lowered the particle light absorption of BC by 63 to 61 %, respectively, for data from the Arabian Sea sourced group, resulting in median BC absorption coefficients of 4.2 and 3.5 Mm^{−1}. Corresponding values for the South Indian Ocean data were 69 and 97 % (0.38 and 0.02 Mm^{−1}. A comparison with other studies in the area indicated an overestimation of their BC levels, by up to two orders of magnitude. This raises the necessity for chemical correction protocols on optical filter
Dettmer, J.; Quijano, J. E.; Dosso, S. E.; Holland, C. W.; Mandolesi, E.
2016-12-01
Geophysical seabed properties are important for the detection and classification of unexploded ordnance. However, current surveying methods such as vertical seismic profiling, coring, or inversion are of limited use when surveying large areas with high spatial sampling density. We consider surveys based on a source and receiver array towed by an autonomous vehicle which produce large volumes of seabed reflectivity data that contain unprecedented and detailed seabed information. The data are analyzed with a particle filter, which requires efficient reflection-coefficient computation, efficient inversion algorithms and efficient use of computer resources. The filter quantifies information content of multiple sequential data sets by considering results from previous data along the survey track to inform the importance sampling at the current point. Challenges arise from environmental changes along the track where the number of sediment layers and their properties change. This is addressed by a trans-dimensional model in the filter which allows layering complexity to change along a track. Efficiency is improved by likelihood tempering of various particle subsets and including exchange moves (parallel tempering). The filter is implemented on a hybrid computer that combines central processing units (CPUs) and graphics processing units (GPUs) to exploit three levels of parallelism: (1) fine-grained parallel computation of spherical reflection coefficients with a GPU implementation of Levin integration; (2) updating particles by concurrent CPU processes which exchange information using automatic load balancing (coarse grained parallelism); (3) overlapping CPU-GPU communication (a major bottleneck) with GPU computation by staggering CPU access to the multiple GPUs. The algorithm is applied to spherical reflection coefficients for data sets along a 14-km track on the Malta Plateau, Mediterranean Sea. We demonstrate substantial efficiency gains over previous methods. [This
Directory of Open Access Journals (Sweden)
Park Wha Me
2016-01-01
Full Text Available When the one-pass collection efficiency of each size of particles of the sound pressure machine equipped with a glass fiber HEPA filter to get rid of friable asbestos at the asbestos elimination field was evaluated, the collection efficiency of those with the size of 0.3um was examined to be 98.91%. That of the particles of 0.5um size was proved to be 99.21% on average, which is a little bit higher than that of 0.3um size. The 1.0um particles showed 100% of efficiency, and the collection efficiency of each size had statistically meaningful differences.
National Research Council Canada - National Science Library
Birmania Heredia Rivera; Martín Gerardo Rodriguez
2016-01-01
Particulate matter accumulated on car engine air-filters (CAFs) was examined in order to investigate the potential use of these devices as efficient samplers for collecting street level air that people are exposed...
National Research Council Canada - National Science Library
Heredia Rivera, Birmania; Gerardo Rodriguez, Martín
2016-01-01
Particulate matter accumulated on car engine air-filters (CAFs) was examined in order to investigate the potential use of these devices as efficient samplers for collecting street level air that people are exposed...
National Research Council Canada - National Science Library
George P Kouropoulos
2014-01-01
At this study, an attempt for the theoretical approach of the Reynolds number effect of air flow to the particle collection efficiency of a fibrous filter, with cylindrical section, will be made...
Zhou, Yi; Zhang, Shaojun; Liu, Ying; Yang, Hongsheng
2014-01-01
Industrial aquaculture wastewater contains large quantities of suspended particles that can be easily broken down physically. Introduction of macro-bio-filters, such as bivalve filter feeders, may offer the potential for treatment of fine suspended matter in industrial aquaculture wastewater. In this study, we employed two kinds of bivalve filter feeders, the Pacific oyster Crassostrea gigas and the blue mussel Mytilus galloprovincialis, to deposit suspended solids from marine fish aquaculture wastewater in flow-through systems. Results showed that the biodeposition rate of suspended particles by C. gigas (shell height: 8.67±0.99 cm) and M. galloprovincialis (shell height: 4.43±0.98 cm) was 77.84±7.77 and 6.37±0.67 mg ind−1•d−1, respectively. The total solid suspension (TSS) deposition rates of oyster and mussel treatments were 3.73±0.27 and 2.76±0.20 times higher than that of the control treatment without bivalves, respectively. The TSS deposition rates of bivalve treatments were significantly higher than the natural sedimentation rate of the control treatment (Paquaculture wastewater, and simultaneously yield value-added biological products. PMID:25250730
Zhou, Yi; Zhang, Shaojun; Liu, Ying; Yang, Hongsheng
2014-01-01
Industrial aquaculture wastewater contains large quantities of suspended particles that can be easily broken down physically. Introduction of macro-bio-filters, such as bivalve filter feeders, may offer the potential for treatment of fine suspended matter in industrial aquaculture wastewater. In this study, we employed two kinds of bivalve filter feeders, the Pacific oyster Crassostrea gigas and the blue mussel Mytilus galloprovincialis, to deposit suspended solids from marine fish aquaculture wastewater in flow-through systems. Results showed that the biodeposition rate of suspended particles by C. gigas (shell height: 8.67 ± 0.99 cm) and M. galloprovincialis (shell height: 4.43 ± 0.98 cm) was 77.84 ± 7.77 and 6.37 ± 0.67 mg ind(-1) • d(-1), respectively. The total solid suspension (TSS) deposition rates of oyster and mussel treatments were 3.73 ± 0.27 and 2.76 ± 0.20 times higher than that of the control treatment without bivalves, respectively. The TSS deposition rates of bivalve treatments were significantly higher than the natural sedimentation rate of the control treatment (P treatments were significantly lower than those in the sediments of the control (P aquaculture wastewater, and simultaneously yield value-added biological products.
Gu, Wenjun; Zhang, Weizhi; Wang, Jin; Amini Kashani, M. R.; Kavehrad, Mohsen
2015-01-01
Over the past decade, location based services (LBS) have found their wide applications in indoor environments, such as large shopping malls, hospitals, warehouses, airports, etc. Current technologies provide wide choices of available solutions, which include Radio-frequency identification (RFID), Ultra wideband (UWB), wireless local area network (WLAN) and Bluetooth. With the rapid development of light-emitting-diodes (LED) technology, visible light communications (VLC) also bring a practical approach to LBS. As visible light has a better immunity against multipath effect than radio waves, higher positioning accuracy is achieved. LEDs are utilized both for illumination and positioning purpose to realize relatively lower infrastructure cost. In this paper, an indoor positioning system using VLC is proposed, with LEDs as transmitters and photo diodes as receivers. The algorithm for estimation is based on received-signalstrength (RSS) information collected from photo diodes and trilateration technique. By appropriately making use of the characteristics of receiver movements and the property of trilateration, estimation on three-dimensional (3-D) coordinates is attained. Filtering technique is applied to enable tracking capability of the algorithm, and a higher accuracy is reached compare to raw estimates. Gaussian mixture Sigma-point particle filter (GM-SPPF) is proposed for this 3-D system, which introduces the notion of Gaussian Mixture Model (GMM). The number of particles in the filter is reduced by approximating the probability distribution with Gaussian components.
Nonlinear Bayesian Tracking Loops for Multipath Mitigation
Directory of Open Access Journals (Sweden)
Pau Closas
2012-01-01
Full Text Available This paper studies Bayesian filtering techniques applied to the design of advanced delay tracking loops in GNSS receivers with multipath mitigation capabilities. The analysis includes tradeoff among realistic propagation channel models and the use of a realistic simulation framework. After establishing the mathematical framework for the design and analysis of tracking loops in the context of GNSS receivers, we propose a filtering technique that implements Rao-Blackwellization of linear states and a particle filter for the nonlinear partition and compare it to traditional delay lock loop/phase lock loop-based schemes.
Sampling Jitter mitigation in latency-critical state-estimation applications using particle filters
El Hakim, Viktorio Semir; Bekooij, Marco Jan Gerrit
2017-01-01
State estimation algorithms, such as the Kalman filter, are applied for conditioning and sensor fusion in digital control loops. It is desirable that these algorithms can be executed on embedded multiprocessor systems. However this results in large worst-case execution times with a consequence that
The ensemble particle filter (EnPF) in rainfall-runoff models
Van Delft, G.; El Serafy, G.Y.; Heemink, A.W.
2009-01-01
Rainfall-runoff models play a very important role in flood forecasting. However, these models contain large uncertainties caused by errors in both the model itself and the input data. Data assimilation techniques are being used to reduce these uncertainties. The ensemble Kalman filter (EnKF) and the
Directory of Open Access Journals (Sweden)
George P. Kouropoulos
2014-01-01
Full Text Available At this study an attempt for the theoretical approach of the Re ynolds number effect of air flow to the particle collection efficiency of a fibrous fil ter with cylindrical section will be made. Initially, a report of the air filtration models to fibrous filter media will be presented along with an explanation of both the parameters and the physical quantities which govern the air filtration process. Furthermore, the resul ting equation from the mathematical model will be applied to a real filter medium and the characteristic curves of filter efficiency will be drawn. The change of a filter medi um efficiency with regard to the Reynolds number of air flow that passes through the filt er, derived from the curves, will be studied. The general conclusion that we have is that as the Reynolds number of filtered air increases, the collection efficiency of the filter decreases.
DEFF Research Database (Denmark)
Riisgård, Hans Ulrik; Okamura, Beth; Funch, Peter
2010-01-01
We studied particle capture using video-microscopy in two gymnolaemates, the marine cheilostome Electra pilosa and the freshwater ctenostome Paludicella articulata, and three phylactolaemates, Fredericella sultana with a circular funnel-shaped lophophore, and Cristatella mucedo and Lophophus...... crystallinus, both with a horseshoe-shaped lophophore. The video-microscope observations along with studies of lophophore morphology and ultrastructure indicated that phylactolaemate and gymnolaemate bryozoans with a diversity of lophophore shapes rely on the same basic structures and mechanisms for particle...... capture. Our study also demonstrates that essential features of the particle capture process resemble one another in bryozoans, brachiopods and phoronids....
Gao, Xiangdong; Mo, Ling; You, Deyong; Li, Zhuman
2017-11-01
It is a challenge to detect the weld position during tight butt joint laser welding in that the tight butt joint is non-grooved and invisible. This paper proposes a novel method for tight butt joint weld detection based on magneto optical imaging. Two pieces of weldment were magnetized by an electromagnet so that they could show magnetic N and S polarity respectively. When a polarized light was projected on a magneto-optical film, it would deflect due to magneto-optical effect. In accordance with magneto field distribution, an image formed on the visual sensor. A transition zone of magnetic field distribution which corresponded to the butt joint could be shown in a magneto optical image of weldment. Variation features of magnetic field distribution were obtained by using image sequence optical flow method, and a particle filter was integrated to make an accurate prediction on weld position. Weld position was obtained by calculating the maximum value of optical flow intensity in the vertical direction, and a particle filter was used to realize the accurate prediction on weld position. Experimental results showed that the proposed method was effective in detection of weld and realizing weld seam tracking.
Sbarufatti, Claudio; Corbetta, Matteo; Giglio, Marco; Cadini, Francesco
2017-03-01
Lithium-Ion rechargeable batteries are widespread power sources with applications to consumer electronics, electrical vehicles, unmanned aerial and spatial vehicles, etc. The failure to supply the required power levels may lead to severe safety and economical consequences. Thus, in view of the implementation of adequate maintenance strategies, the development of diagnostic and prognostic tools for monitoring the state of health of the batteries and predicting their remaining useful life is becoming a crucial task. Here, we propose a method for predicting the end of discharge of Li-Ion batteries, which stems from the combination of particle filters with radial basis function neural networks. The major innovation lies in the fact that the radial basis function model is adaptively trained on-line, i.e., its parameters are identified in real time by the particle filter as new observations of the battery terminal voltage become available. By doing so, the prognostic algorithm achieves the flexibility needed to provide sound end-of-discharge time predictions as the charge-discharge cycles progress, even in presence of anomalous behaviors due to failures or unforeseen operating conditions. The method is demonstrated with reference to actual Li-Ion battery discharge data contained in the prognostics data repository of the NASA Ames Research Center database.
Directory of Open Access Journals (Sweden)
Xinbin Li
2017-12-01
Full Text Available Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs. However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.
Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping
2017-12-21
Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.
Burggraeve, A; Van Den Kerkhof, T; Hellings, M; Remon, J P; Vervaet, C; De Beer, T
2010-09-01
In this study, the feasibility of spatial filter velocimetry (SFV) as process analytical technology tool for the in-line monitoring of the particle size distribution during top spray fluidized bed granulation was examined. The influence of several process (inlet air temperature during spraying and drying) and formulation variables (HPMC and Tween 20 concentration) upon the particle size distribution during processing, and the end product particle size distribution, tapped density and Hausner ratio was examined using a design of experiments (DOE) (2-level full factorial design, 19 experiments). The trend in end granule particle size distributions of all DOE batches measured with in-line SFV was similar to the off-line laser diffraction (LD) data. Analysis of the DOE results showed that mainly the HPMC concentration and slightly the inlet air temperature during drying had a positive effect on the average end granule size. The in-line SFV particle size data, obtained every 10s during processing, further allowed to explain and better understand the (in)significance of the studied DOE variables, which was not possible based on the LD data as this technique only supplied end granule size information. The variation in tapped density and Hausner ratio among the end granules of the different DOE batches could be explained by their difference in average end granule size. Univariate, multivariate PLS and multiway N-PLS models were built to relate these end granule properties to the in-line-measured particle size distribution. The multivariate PLS tapped density model and the multiway N-PLS Hausner ratio model showed the highest R(2) values in combination with the lowest RMSEE values (R(2) of 82% with an RMSEE of 0.0279 for tapped density and an R(2) of 52% with an RMSEE of 0.0268 for Hausner ratio, respectively). 2010 Elsevier B.V. All rights reserved.
Modulation power of porous materials and usage as ripple filter in particle therapy.
Printz Ringbæk, Toke; Simeonov, Yuri; Witt, Matthias; Engenhart-Cabillic, Rita; Kraft, Gerhard; Zink, Klemens; Weber, Uli
2017-04-07
Porous materials with microscopic structures like foam, sponges, lung tissues and lung substitute materials have particular characteristics, which differ from those of solid materials. Ion beams passing through porous materials show much stronger energy straggling than expected for non-porous solid materials of the same thickness. This effect depends on the microscopic fine structure, the density and the thickness of the porous material. The beam-modulating effect from a porous plate enlarges the Bragg peak, yielding similar benefits in irradiation time reduction as a ripple filter. A porous plate can additionally function as a range shifter, which since a higher energy can be selected for the same penetration depth in the body reduces the scattering at the beam line and therefore improves the lateral fall-off. Bragg curve measurements of ion beams passing through different porous materials have been performed in order to determine the beam modulation effect of each. A mathematical model describing the correlation between the mean material density, the porous pore structure size and the strength of the modulation has been developed and a new material parameter called 'modulation power' is defined as the square of the Gaussian sigma divided by the mean water-equivalent thickness of the porous absorber. Monte Carlo simulations have been performed in order to validate the model and to investigate the Bragg peak enlargement, the scattering effects of porosity and the lateral beam width at the end of the beam range. The porosity is found to only influence the lateral scattering in a negligible way. As an example of a practical application, it is found that a 20 mm and 50 mm plate of Gammex LN300 performs similar to a 3 mm and 6 mm ripple filter, respectively, and at the same time can improve the sharpness of the lateral beam due to its multifunctionality as a ripple filter and a range shifter.
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative
2011-06-14
are several ways this might be approached. For example for non-ergodic signals using ideas in Oudjane and Rubenthaler [2005], Heine and Crisan [2008...1− ρ + Cρ n−p−1(n− p), 0 ≤ p ≤ n. Combining this bound with (7.23) will establish the result. References A. Beskos, D. Crisan , and A. Jasra. On the...Radar Sig. Proces., 140:107–113, 1993. K. Heine and D. Crisan . Uniform approximations of discrete-time filters. Adv. in Appl. Probab., 40 (4):979
Adaptively Blocked Particle Filtering with Spatial Smoothing in Large Scale Dynamic Random Fields
2014-07-01
References [1] B.D.O. Anderson and J.B. Moore. Optimal Filtering. Prentice Hall, Englewood Cliffs, N.J., 1979. [2] A. Beskos, D. Crisan , and A. Jasra. On the... Crisan , A. Jasra, and N. Whiteley. Error bounds and normalising constants for sequential Monte Carlo samplers in high dimensions. Advances in Applied...Statistics, 2008. [5] O. Cappé, E. Moulines, and T. Rydén. Inference in Hidden MarkovModels. Springer, New York, N.Y., 2005. [6] D. Crisan and A. Doucet
Kristensen, Kasper; Bilde, Merete; Aalto, Pasi P.; Petäjä, Tuukka; Glasius, Marianne
2016-04-01
Carboxylic acids and organosulfates comprise an important fraction of atmospheric secondary organic aerosols formed from both anthropogenic and biogenic precursors. The partitioning of these compounds between the gas and particle phase is still unclear and further research is warranted to better understand the abundance and effect of organic acids and organosulfates on the formation and properties of atmospheric aerosols. This work compares atmospheric aerosols collected at an urban and a boreal forest site using two side-by-side sampling systems; a high volume sampler (HVS) and a low volume (LVS) denuder/filter sampling system allowing for separate collection of gas- and particle-phase organics. All particle filters and denuder samples were collected at H.C. Andersen Boulevard (HCAB), Copenhagen, Denmark in the summer of 2010, and at the remote boreal forest site at Hyytiälä forestry field station in Finland in the summer of 2012. The chemical composition of gas- and particle-phase secondary organic aerosol was investigated by ultra-high performance liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC/ESI-Q-TOFMS), with a focus on carboxylic acids and organosulfates. Results show gas-phase concentrations higher than those observed in the particle phase by a factor of 5-6 in HCAB 2010 and 50-80 in Hyytiälä 2012. Although abundant in the particle phase, no organosulfates were detected in the gas phase at either site. Through a comparison of samples collected by the HVS and the LVS denuder/filter sampling system we evaluate the potential artifacts associated with sampling of atmospheric aerosols. Such comparison shows that particle phase concentrations of semi-volatile organic acids obtained from the filters collected by HVS are more than two times higher than concentrations obtained from filters collected using LVS denuder/filter system. In most cases, higher concentrations of organosulfates are observed in particles
DEFF Research Database (Denmark)
Ardkapan, Siamak Rahimi; Johnson, Matthew S.; Yazdi, Sadegh
2014-01-01
on the fibers and form chain-like agglomerates known as dendrites. The dendrites themselves contribute in capturing the other particles. Increasing exposure will result in increasing the number of the dendrites because of the static charging and consequently increasing the efficiency. Static electrical charging...
Energy Technology Data Exchange (ETDEWEB)
Alleman, T. L.; Eudy, L.; Miyasato, M.; Oshinuga, A.; Allison, S.; Corcoran, T.; Chatterjee, S.; Jacobs, T.; Cherrillo, R. A.; Clark, R.; Virrels, I.; Nine, R.; Wayne, S.; Lansing, R.
2005-11-01
A fleet of six 2001 International Class 6 trucks operating in southern California was selected for an operability and emissions study using gas-to-liquid (GTL) fuel and catalyzed diesel particle filters (CDPF). Three vehicles were fueled with CARB specification diesel fuel and no emission control devices (current technology), and three vehicles were fueled with GTL fuel and retrofit with Johnson Matthey's CCRT diesel particulate filter. No engine modifications were made.
Heimbuch, B K; Harnish, D A; Balzli, C; Lumley, A; Kinney, K; Wander, J D
2015-06-01
To avoid interference by water-iodine disinfection chemistry and measure directly the effect of iodine, captured from a triiodide complex bound to a filter medium, on viability of penetrating viral particles. Aerosols of MS2 coli phage were passed through control P100 or iodinated High-Efficiency Particulate Air media, collected in plastic bags, incubated for 0-10 min, collected in an impinger containing thiosulphate to consume all unreacted iodine, plated and enumerated. Comparison of viable counts demonstrated antimicrobial activity with an apparent half-life for devitalization in tens of seconds; rate of kill decreased at low humidity and free iodine was captured by the bags. The results support the mechanism of near-contact capture earlier proposed; however, the disinfection chemistry in the aerosol phase is very slow on the time scale of inhalation. This study shows that disinfection by filter-bound iodine in the aerosol phase is too slow to be clinically significant in individual respiratory protection, but that it might be of benefit to limit airborne transmission of infections in enclosed areas. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
Closas, Pau; Guillamon, Antoni
2017-12-01
This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain's connectivity, here we focus on a microscopic vision of the problem, where single neurons (potentially connected to a network of peers) are at the core of our study. The sole observation available are noisy, sampled voltage traces obtained from intracellular recordings. We design algorithms and inference methods using the tools provided by stochastic filtering that allow a probabilistic interpretation and treatment of the problem. Using particle filtering, we are able to reconstruct traces of voltages and estimate the time course of auxiliary variables. By extending the algorithm, through PMCMC methodology, we are able to estimate hidden physiological parameters as well, like intrinsic conductances or reversal potentials. Last, but not least, the method is applied to estimate synaptic conductances arriving at a target cell, thus reconstructing the synaptic excitatory/inhibitory input traces. Notably, the performance of these estimations achieve the theoretical lower bounds even in spiking regimes.
Saturated and unsaturated flow through sloped compost filter beds of different particle sizes.
Petrell, R J; Gumulia, Anastasia
2013-01-01
Little is known about the hydraulics of sloped compost beds having active free and non-flowing zones, and used for runoff erosion and volume control, and heavy metal removal. Water sorption tests on yard waste compost indicated that water transfer between the two zones would be slow (6 hr for a 0.04 m rise). The free flowing zone in ≈1 m long sloped (15°) beds increased in depth (0.01-0.08 m) with decreasing particle size and increasing flow. Particle size and flow (0.08-0.3 L/s/m) affected bed stability. Drainage volume increased with flow while drainage time remained fairly constant. Saturated flow occurred depending on the particle size above 0.02-0.165 L/s/m. Data indicate that sheet runoff from low intensity storms would most likely create unsaturated but stable bed conditions. Concentrated flows as from downspouts would likely create saturated conditions and have to be managed to prevent washout. A model based on porous media theory indicated that flow regime under saturated flow is turbulent. Results can be used to design compost beds for various runoff rates and to develop a heavy metal sorption model.
Wang, Ke; Huang, Zhi; Zhong, Zhihua
2014-11-01
Due to the large variations of environment with ever-changing background and vehicles with different shapes, colors and appearances, to implement a real-time on-board vehicle recognition system with high adaptability, efficiency and robustness in complicated environments, remains challenging. This paper introduces a simultaneous detection and tracking framework for robust on-board vehicle recognition based on monocular vision technology. The framework utilizes a novel layered machine learning and particle filter to build a multi-vehicle detection and tracking system. In the vehicle detection stage, a layered machine learning method is presented, which combines coarse-search and fine-search to obtain the target using the AdaBoost-based training algorithm. The pavement segmentation method based on characteristic similarity is proposed to estimate the most likely pavement area. Efficiency and accuracy are enhanced by restricting vehicle detection within the downsized area of pavement. In vehicle tracking stage, a multi-objective tracking algorithm based on target state management and particle filter is proposed. The proposed system is evaluated by roadway video captured in a variety of traffics, illumination, and weather conditions. The evaluating results show that, under conditions of proper illumination and clear vehicle appearance, the proposed system achieves 91.2% detection rate and 2.6% false detection rate. Experiments compared to typical algorithms show that, the presented algorithm reduces the false detection rate nearly by half at the cost of decreasing 2.7%-8.6% detection rate. This paper proposes a multi-vehicle detection and tracking system, which is promising for implementation in an on-board vehicle recognition system with high precision, strong robustness and low computational cost.
Oladyshkin, S.; Class, H.; Helmig, R.; Nowak, W.
2011-12-01
constructing the response surface depend on the number of parameters and the expansion degree. Step two consists of Bayesian updating in order to match the reduced model to available measurements of state variables or other past or real-time observations of system behavior (e.g. past production data or pressure at monitoring wells during a certain time period). In step 2 we apply particle filtering on the integrative response surface constructed at step one. Particle filtering is a strong technique for Bayesian updating which takes into consideration the nonlinearity of inverse problem in history matching more accurately than Ensemble Kalman filter do. Thanks to the computational efficiency of PCE and integrative response surface, Bayesian updating for history matching becomes an interactive task and can incorporate real time measurements.
Georgy, Jacques; Noureldin, Aboelmagd
2011-01-01
Satellite navigation systems such as the global positioning system (GPS) are currently the most common technique used for land vehicle positioning. However, in GPS-denied environments, there is an interruption in the positioning information. Low-cost micro-electro mechanical system (MEMS)-based inertial sensors can be integrated with GPS and enhance the performance in denied GPS environments. The traditional technique for this integration problem is Kalman filtering (KF). Due to the inherent errors of low-cost MEMS inertial sensors and their large stochastic drifts, KF, with its linearized models, has limited capabilities in providing accurate positioning. Particle filtering (PF) was recently suggested as a nonlinear filtering technique to accommodate for arbitrary inertial sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF called the Mixture PF is utilized in this study to perform tightly coupled integration of a three dimensional (3D) reduced inertial sensors system (RISS) with GPS. In this work, the RISS consists of one single-axis gyroscope and a two-axis accelerometer used together with the vehicle's odometer to obtain 3D navigation states. These sensors are then integrated with GPS in a tightly coupled scheme. In loosely-coupled integration, at least four satellites are needed to provide acceptable GPS position and velocity updates for the integration filter. The advantage of the tightly-coupled integration is that it can provide GPS measurement update(s) even when the number of visible satellites is three or lower, thereby improving the operation of the navigation system in environments with partial blockages by providing continuous aiding to the inertial sensors even during limited GPS satellite availability. To effectively exploit the capabilities of PF, advanced modeling for the stochastic drift of the vertically aligned gyroscope is used. In order to benefit from measurement updates for such drift, which are
Directory of Open Access Journals (Sweden)
Jacques Georgy
2011-04-01
Full Text Available Satellite navigation systems such as the global positioning system (GPS are currently the most common technique used for land vehicle positioning. However, in GPS-denied environments, there is an interruption in the positioning information. Low-cost micro-electro mechanical system (MEMS-based inertial sensors can be integrated with GPS and enhance the performance in denied GPS environments. The traditional technique for this integration problem is Kalman filtering (KF. Due to the inherent errors of low-cost MEMS inertial sensors and their large stochastic drifts, KF, with its linearized models, has limited capabilities in providing accurate positioning. Particle filtering (PF was recently suggested as a nonlinear filtering technique to accommodate for arbitrary inertial sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF called the Mixture PF is utilized in this study to perform tightly coupled integration of a three dimensional (3D reduced inertial sensors system (RISS with GPS. In this work, the RISS consists of one single-axis gyroscope and a two-axis accelerometer used together with the vehicle’s odometer to obtain 3D navigation states. These sensors are then integrated with GPS in a tightly coupled scheme. In loosely-coupled integration, at least four satellites are needed to provide acceptable GPS position and velocity updates for the integration filter. The advantage of the tightly-coupled integration is that it can provide GPS measurement update(s even when the number of visible satellites is three or lower, thereby improving the operation of the navigation system in environments with partial blockages by providing continuous aiding to the inertial sensors even during limited GPS satellite availability. To effectively exploit the capabilities of PF, advanced modeling for the stochastic drift of the vertically aligned gyroscope is used. In order to benefit from measurement updates for such drift
Giffin, Paxton K.; Parsons, Michael S.; Unz, Ronald J.; Waggoner, Charles A.
2012-05-01
The Institute for Clean Energy Technology (ICET) at Mississippi State University has developed a test stand capable of lifecycle testing of high efficiency particulate air filters and other filters specified in American Society of Mechanical Engineers Code on Nuclear Air and Gas Treatment (AG-1) filters. The test stand is currently equipped to test AG-1 Section FK radial flow filters, and expansion is currently underway to increase testing capabilities for other types of AG-1 filters. The test stand is capable of producing differential pressures of 12.45 kPa (50 in. w.c.) at volumetric air flow rates up to 113.3 m3/min (4000 CFM). Testing is performed at elevated and ambient conditions for temperature and relative humidity. Current testing utilizes three challenge aerosols: carbon black, alumina, and Arizona road dust (A1-Ultrafine). Each aerosol has a different mass median diameter to test loading over a wide range of particles sizes. The test stand is designed to monitor and maintain relative humidity and temperature to required specifications. Instrumentation is implemented on the upstream and downstream sections of the test stand as well as on the filter housing itself. Representative data are presented herein illustrating the test stand's capabilities. Digital images of the filter pack collected during and after testing is displayed after the representative data are discussed. In conclusion, the ICET test stand with AG-1 filter testing capabilities has been developed and hurdles such as test parameter stability and design flexibility overcome.
Zhao, Yaqin; Yue, Qinyan; Li, Renbo; Yue, Min; Han, Shuxin; Gao, Baoyu; Li, Qian; Yu, Hui
2009-11-01
Sludge-fly ash ceramic particles (SFCP) and clay ceramic particles (CCP) were employed in two lab-scale up-flow biological aerated filters (BAF) for wastewater treatment to investigate the availability of SFCP used as biofilm support compared with CCP. For synthetic wastewater, under the selected hydraulic retention times (HRT) of 1.5, 0.75 and 0.37 h, respectively, the removal efficiencies of chemical oxygen demand (COD(Cr)) and ammonium nitrogen (NH(4)(+)-N) in SFCP reactor were all higher than those of CCP reactor all through the media height. Moreover, better capabilities responding to loading shock and faster recovery after short intermittence were observed in the SFCP reactor compared with the CCP reactor. For municipal wastewater treatment, which was carried out under HRT of 0.75 h, air-liquid ratio of 7.5 and backwashing period of 48 h, the SFCP reactor also performed better than the CCP reactor, especially for the removal of NH(4)(+)-N.
Hiemstra, P.H.; Karssenberg, D.J.; Dijk, A. van
2011-01-01
Atmospheric transport models and observations from monitoring networks are commonly used aids for forecasting spatial distribution of contamination in case of a radiological incident. In this study, we assessed the particle filter data-assimilation technique as a tool for ensemble forecasting the
Directory of Open Access Journals (Sweden)
Zutao Zhang
2016-06-01
Full Text Available Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.
Preble, C.; Cados, T.; Harley, R.; Kirchstetter, T.
2016-12-01
Heavy-duty diesel trucks (HDDT) are a major source of nitrogen oxides (NOx) and black carbon (BC) in urban environments, contributing to persistent ozone and particulate matter air quality problems. Diesel particle filters (DPFs) and selective catalytic reduction (SCR) systems that target PM and NOx emissions, respectively, have recently become standard equipment on new HDDT. DPFs can also be installed on older engines as a retrofit device. Previous work has shown that DPF and SCR systems can reduce NOx and BC emissions by up to 70% and 90%, respectively, compared to modern trucks without these after-treatment controls (Preble et al., ES&T 2015). DPFs can have the undesirable side-effect of increasing ultrafine particle (UFP) and nitrogen dioxide (NO2) emissions. While SCR systems can partially mitigate DPF-related NO2 increases, these systems can emit nitrous oxide (N2O), a potent greenhouse gas. We report new results from a study of HDDT emissions conducted in fall 2015 at the Port of Oakland and Caldecott Tunnel in California's San Francisco Bay Area. We report pollutant emission factors (g kg-1) for emitted NOx, NO2, BC, PM2.5, UFP, and N2O on a truck-by-truck basis. Using a roadside license plate recognition system, we categorize each truck by its engine model year and installed after-treatment controls. From this, we develop emissions profiles for trucks with and without DPF and SCR. We evaluate the effectiveness of these devices as a function of their age to determine whether degradation is an issue. We also compare the emission profiles of trucks traveling at low speeds along a level, arterial road en route to the port and at high speeds up a 4% grade highway approaching the tunnel. Given the climate impacts of BC and N2O, we also examine the global warming potential of emissions from trucks with and without DPF and SCR.
Yu, Jianbo
2015-12-01
Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.
Yuan, Shenfang; Chen, Jian; Yang, Weibo; Qiu, Lei
2017-08-01
Fatigue crack growth prognosis is important for prolonging service time, improving safety, and reducing maintenance cost in many safety-critical systems, such as in aircraft, wind turbines, bridges, and nuclear plants. Combining fatigue crack growth models with the particle filter (PF) method has proved promising to deal with the uncertainties during fatigue crack growth and reach a more accurate prognosis. However, research on prognosis methods integrating on-line crack monitoring with the PF method is still lacking, as well as experimental verifications. Besides, the PF methods adopted so far are almost all sequential importance resampling-based PFs, which usually encounter sample impoverishment problems, and hence performs poorly. To solve these problems, in this paper, the piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The deterministic resampling PF (DRPF) is proposed to be used in fatigue crack growth prognosis, which can overcome the sample impoverishment problem. The proposed method is verified through fatigue tests of attachment lugs, which are a kind of important joint component in aerospace systems.
Sun, Kangfeng; Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai; Yang, Shichun
2018-01-01
As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small.
Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You
2017-02-01
Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.
Sau, J.; EL-FAOUZI, NE; BEN-AISSA, A; DE MOUZON, O
2007-01-01
Real-time estimation and short-term prediction of traffic conditions is one of major concern of traffic managers and ITS-oriented systems. Model-based methods appear now as very promising ways in order to reach this purpose. Such methods are already used in process control (Kalman filtering, Luenberger observers). In the application presented in this paper, due to the high non linearity of the traffic models, particle filter (PF) approach is applied in combination with the well-known first or...
Directory of Open Access Journals (Sweden)
Saad Ali
2003-12-01
Full Text Available Abstract Background Images of frozen hydrated [vitrified] virus particles were taken close-to-focus in an electron microscope containing structural signals at high spatial frequencies. These images had very low contrast due to the high levels of noise present in the image. The low contrast made particle selection, classification and orientation determination very difficult. The final purpose of the classification is to improve the signal-to-noise ratio of the particle representing the class, which is usually the average. In this paper, the proposed method is based on wavelet filtering and multi-resolution processing for the classification and reconstruction of this very noisy data. A multivariate statistical analysis (MSA is used for this classification. Results The MSA classification method is noise dependant. A set of 2600 projections from a 3D map of a herpes simplex virus -to which noise was added- was classified by MSA. The classification shows the power of wavelet filtering in enhancing the quality of class averages (used in 3D reconstruction compared to Fourier band pass filtering. A 3D reconstruction of a recombinant virus (VP5-VP19C is presented as an application of multi-resolution processing for classification and reconstruction. Conclusion The wavelet filtering and multi-resolution processing method proposed in this paper offers a new way for processing very noisy images obtained from electron cryo-microscopes. The multi-resolution and filtering improves the speed and accuracy of classification, which is vital for the 3D reconstruction of biological objects. The VP5-VP19C recombinant virus reconstruction presented here is an example, which demonstrates the power of this method. Without this processing, it is not possible to get the correct 3D map of this virus.
Okamoto, Kenta; Miyazaki, Naoyuki; Song, Chihong; Maia, Filipe R N C; Reddy, Hemanth K N; Abergel, Chantal; Claverie, Jean-Michel; Hajdu, Janos; Svenda, Martin; Murata, Kazuyoshi
2017-10-16
The Pithoviridae giant virus family exhibits the largest viral particle known so far, a prolate spheroid up to 2.5 μm in length and 0.9 μm in diameter. These particles show significant variations in size. Little is known about the structure of the intact virion due to technical limitations with conventional electron cryo-microscopy (cryo-EM) when imaging thick specimens. Here we present the intact structure of the giant Pithovirus sibericum particle at near native conditions using high-voltage electron cryo-tomography (cryo-ET) and energy-filtered cryo-EM. We detected a previously undescribed low-density outer layer covering the tegument and a periodical structuring of the fibres in the striated apical cork. Energy-filtered Zernike phase-contrast cryo-EM images show distinct substructures inside the particles, implicating an internal compartmentalisation. The density of the interior volume of Pithovirus particles is three quarters lower than that of the Mimivirus. However, it is remarkably high given that the 600 kbp Pithovirus genome is only half the size of the Mimivirus genome and is packaged in a volume up to 100 times larger. These observations suggest that the interior is densely packed with macromolecules in addition to the genomic nucleic acid.
Chen, Liang; Piché, Robert; Kuusniemi, Heidi; Chen, Ruizhi
2014-12-01
This paper studies the problem of tracking a mobile device in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. NLOS error is assumed to be Gaussian with unknown mean and variance. An adaptive Rao-Blackwellized particle filter (RBPF) is proposed for mobile tracking in such scenarios. An extended Kalman filter is used to approximately estimate the mobile state, and the particle filter is applied to estimate the posterior distribution of sight conditions and the unknown static parameters, the distribution of which is updated by sufficient statistics. To improve the efficiency of the particle filtering, we use the approximate optimal proposal distribution for particle inference. Algorithm performance is investigated in the scenario of mobile tracking using signals of opportunity from digital TV (DTV) network. Simulation results show that the adaptive RBPF method is effective to infer the unknown NLOS parameter and can achieve good tracking accuracy using a small number of particles.
Moving-Target Position Estimation Using GPU-Based Particle Filter for IoT Sensing Applications
Directory of Open Access Journals (Sweden)
Seongseop Kim
2017-11-01
Full Text Available A particle filter (PF has been introduced for effective position estimation of moving targets for non-Gaussian and nonlinear systems. The time difference of arrival (TDOA method using acoustic sensor array has normally been used to for estimation by concealing the location of a moving target, especially underwater. In this paper, we propose a GPU -based acceleration of target position estimation using a PF and propose an efficient system and software architecture. The proposed graphic processing unit (GPU-based algorithm has more advantages in applying PF signal processing to a target system, which consists of large-scale Internet of Things (IoT-driven sensors because of the parallelization which is scalable. For the TDOA measurement from the acoustic sensor array, we use the generalized cross correlation phase transform (GCC-PHAT method to obtain the correlation coefficient of the signal using Fast Fourier Transform (FFT, and we try to accelerate the calculations of GCC-PHAT based TDOA measurements using FFT with GPU compute unified device architecture (CUDA. The proposed approach utilizes a parallelization method in the target position estimation algorithm using GPU-based PF processing. In addition, it could efficiently estimate sudden movement change of the target using GPU-based parallel computing which also can be used for multiple target tracking. It also provides scalability in extending the detection algorithm according to the increase of the number of sensors. Therefore, the proposed architecture can be applied in IoT sensing applications with a large number of sensors. The target estimation algorithm was verified using MATLAB and implemented using GPU CUDA. We implemented the proposed signal processing acceleration system using target GPU to analyze in terms of execution time. The execution time of the algorithm is reduced by 55% from to the CPU standalone operation in target embedded board, NVIDIA Jetson TX1. Also, to apply large
Tansho, R.; Furukawa, T.; Hara, Y.; Mizushima, K.; Saotome, N.; Saraya, Y.; Shirai, T.; Noda, K.
2017-09-01
A ridge filter (RGF), a beam energy modulation device, is usually used for particle radiotherapy with a pencil beam scanning system. The conventional RGF has a one-dimensional (1D) periodic laterally stepped structure in orthogonal plane with a central beam direction. The energy of a beam passing through the different thicknesses of the stepped RGF is modulated. Although the lateral pencil beam size is required to cover the several stepped RGF units to modulate its energy as designed, the current trend is to decrease lateral beam size to improve the scanning system. As a result, the beam size becomes smaller than the size of the individual RGF unit. The aim of this study was to develop a new RGF with two-dimensional (2D) honeycomb geometry to simultaneously achieve both a decrease in lateral beam size and the desired energy modulation. The conventional 1D-RGF and the 2D-RGF with honeycomb geometry were both designed so that the Bragg peak size of a 79 MeV/u carbon ion pencil beam in water was 1 mm RMS in the beam direction. To validate the design of the 2D-RGF, we calculated depth dose distributions in water using a simplified Monte Carlo method. In the calculations, we decreased the lateral pencil beam size at the entrance of the RGF and investigated the threshold of lateral beam size with which the pencil beam can reproduce the desired Bragg peak size for each type of RGF. In addition, we calculated lateral dose distributions in air downstream from the RGF and evaluated the inhomogeneity of the lateral dose distributions. Using the 2D-RGF, the threshold of lateral beam size with which the pencil beam can reproduce the desired Bragg peak size was smaller than that using the 1D-RGF. Moreover, the distance from the RGF at which the lateral dose distribution becomes uniform was shorter using the 2D-RGF than that using the 1D-RGF. These results indicate that when the periodic length of both RGFs is the same, the 2D-RGF allows use of a pencil beam with smaller lateral
Regenerative particulate filter development
Descamp, V. A.; Boex, M. W.; Hussey, M. W.; Larson, T. P.
1972-01-01
Development, design, and fabrication of a prototype filter regeneration unit for regenerating clean fluid particle filter elements by using a backflush/jet impingement technique are reported. Development tests were also conducted on a vortex particle separator designed for use in zero gravity environment. A maintainable filter was designed, fabricated and tested that allows filter element replacement without any leakage or spillage of system fluid. Also described are spacecraft fluid system design and filter maintenance techniques with respect to inflight maintenance for the space shuttle and space station.
Saffaripour, Meghdad; Chan, Tak W; Liu, Fengshan; Thomson, Kevin A; Smallwood, Gregory J; Kubsh, Joseph; Brezny, Rasto
2015-10-06
The size and morphology of particulate matter emitted from a light-duty gasoline-direct-injection (GDI) vehicle, over the FTP-75 and US06 transient drive cycles, have been characterized by transmission-electron-microscope (TEM) image analysis. To investigate the impact of gasoline particulate filters on particulate-matter emission, the results for the stock-GDI vehicle, that is, the vehicle in its original configuration, have been compared to the results for the same vehicle equipped with a catalyzed gasoline particulate filter (GPF). The stock-GDI vehicle emits graphitized fractal-like aggregates over all driving conditions. The mean projected area-equivalent diameter of these aggregates is in the 78.4-88.4 nm range and the mean diameter of primary particles varies between 24.6 and 26.6 nm. Post-GPF particles emitted over the US06 cycle appear to have an amorphous structure, and a large number of nucleation-mode particles, depicted as low-contrast ultrafine droplets, are observed in TEM images. This indicates the emission of a substantial amount of semivolatile material during the US06 cycle, most likely generated by the incomplete combustion of accumulated soot in the GPF during regeneration. The size of primary particles and soot aggregates does not vary significantly by implementing the GPF over the FTP-75 cycle; however, particles emitted by the GPF-equipped vehicle over the US06 cycle are about 20% larger than those emitted by the stock-GDI vehicle. This may be attributed to condensation of large amounts of organic material on soot aggregates. High-contrast spots, most likely solid nonvolatile cores, are observed within many of the nucleation-mode particles emitted over the US06 cycle by the GPF-equipped vehicle. These cores are either generated inside the engine or depict incipient soot particles which are partially carbonized in the exhaust line. The effect of drive cycle and the GPF on the fractal parameters of particles, such as fractal dimension and
Energy Technology Data Exchange (ETDEWEB)
Del Fabbro, L
2002-07-01
The devices of air cleaning against particles are widely spread in various branches of industry: nuclear, motor, food, electronic,...; among these devices, numerous are constituted by pleated porous media to increase the surface of filtration and thus to reduce the pressure drop, for given air flow. The objective of our work is to compensate a lack evident of knowledge on the evolution of the pressure drop of pleated filter during the clogging and to deduct a modelling from it, on the basis of experiments concerning industrial filters of nuclear and car types. The obtained model is a function of characteristics of the filtering medium and pleats, of the characteristics of solid particles deposited on the filter, of the mass of particles and of the aeraulic conditions of air flow. It also depends on data on the clogging of flat filters of equivalent medium. To elaborate this model of pressure drop, an initial stage was carried out in order to characterize, experimentally and numerically, the pressure drop and the distribution of air flow in clean pleated filters of nuclear (high efficiency particulate air filter, in fiberglasses) and car (mean efficiency filter, in fibers of cellulose) types. The numerical model allowed to understand the fundamental role played by the aeraulic resistance of the filtering medium. From an non-dimensional approach, we established a semi-empirical model of pressure drop for a clean pleated filter valid for both studied types of medium; this model is used of first base for the development of the final model of clogging. The study of the clogging of the filters showed the complexity of the phenomenon dependent mainly on a reduction of the surface of filtration. This observation brings us to propose a clogging of pleated filters in three phases. Both first phases are similar in those observed for flat filters, while last phase corresponds to a reduction of the surface of filtration and leads a strong increase of the filter pressure drop
Li, Jingyi; Liu, Qian; Alsamarri, Hussein; Lounsbury, Jenny A; Haversitick, Doris M; Landers, James P
2013-03-07
Reliable measurement of DNA concentration is essential for a broad range of applications in biology and molecular biology, and for many of these, quantifying the nucleic acid content is inextricably linked to obtaining optimal results. In its most simplistic form, quantitative analysis of nucleic acids can be accomplished by UV-Vis absorbance and, in more sophisticated format, by fluorimetry. A recently reported new concept, the 'pinwheel assay', involves a label-free approach for quantifying DNA through aggregation of paramagnetic beads in a rotating magnetic field. Here, we describe a simplified version of that assay adapted for execution using only a pipet and filter paper. The 'pipette, aggregate, and blot' (PAB) approach allows DNA to induce bead aggregation in a pipette tip through exposure to a magnetic field, followed by dispensing (blotting) onto filter paper. The filter paper immortalises the extent of aggregation, and digital images of the immortalized bead conformation, acquired with either a document scanner or a cell phone camera, allows for DNA quantification using a noncomplex algorithm. Human genomic DNA samples extracted from blood are quantified with the PAB approach and the results utilized to define the volume of sample used in a PCR reaction that is sensitive to input mass of template DNA. Integrating the PAB assay with paper-based DNA extraction and detection modalities has the potential to yield 'DNA quant-on-paper' devices that may be useful for point-of-care testing.
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
Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru
2016-04-01
An integrated method consisting of a proper orthogonal decomposition (POD)-based reduced-order model (ROM) and a particle filter (PF) is proposed for real-time prediction of an unsteady flow field. The proposed method is validated using identical twin experiments of an unsteady flow field around a circular cylinder for Reynolds numbers of 100 and 1000. In this study, a PF is employed (ROM-PF) to modify the temporal coefficient of the ROM based on observation data because the prediction capability of the ROM alone is limited due to the stability issue. The proposed method reproduces the unsteady flow field several orders faster than a reference numerical simulation based on Navier-Stokes equations. Furthermore, the effects of parameters, related to observation and simulation, on the prediction accuracy are studied. Most of the energy modes of the unsteady flow field are captured, and it is possible to stably predict the long-term evolution with ROM-PF.
Fiebrandt, Marcel; Hillebrand, Bastian; Lackmann, Jan-Wilm; Raguse, Marina; Moeller, Ralf; Awakowicz, Peter; Stapelmann, Katharina
2018-01-01
Inactivation experiments were performed with Bacillus subtilis spores in a low pressure double inductively coupled plasma (DICP) system. Argon, nitrogen and oxygen at 5 Pa were used as feed gas to change the emission spectrum in the range of 100 nm to 400 nm, as well as between radical and metastable densities. Optical filters were applied, to block particles and selected wavelengths from the spores. By determining absolute photon fluxes, the sporicidal efficiency of various wavelength ranges was evaluated. The results showed good agreement with other plasma experiments, as well as with monochromatic light inactivation experiments from a synchrotron. The findings indicated that the inactivation rate constants of broadband plasma emission and monochromatic light were identical, and that no synergistic effect exists. Furthermore, the influence of radicals, ions and metastables on the inactivation efficiency was of minor importance in the set-up used, and radiation was the main reason for spore inactivation.
DEFF Research Database (Denmark)
Toftkjær, Thomas
Pedestrian positioning with full coverage in urban environments is a long sought after research goal. This thesis proposes new techniques for handling the challenging task of truly pervasive pedestrian positioning. It shows that through sensor fusion one can both improve accuracy and extend...... the coverage of pedestrian positioning, for the professional person, such as rst responders, as well as for the ordinary citizen. Since GNSS alone cannot satisfy the availability and accuracy demands for all indoor settings, this thesis pursues a better understanding of the capabilities of GNSS indoors......, called particle lters, it is possible to use GPS measurements within ProPosition to improve pedestrian positioning accuracy by up to 2.5 meters, from 10 meters accuracy to 7.5 meters accuracy in investigated indoor environments. Secondly, this thesis furthermore proposes ProLoc, a particle lter framework...
Granade, Christopher; Wiebe, Nathan
2017-08-01
A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.
Ceramic fiber filter technology
Energy Technology Data Exchange (ETDEWEB)
Holmes, B.L.; Janney, M.A.
1996-06-01
Fibrous filters have been used for centuries to protect individuals from dust, disease, smoke, and other gases or particulates. In the 1970s and 1980s ceramic filters were developed for filtration of hot exhaust gases from diesel engines. Tubular, or candle, filters have been made to remove particles from gases in pressurized fluidized-bed combustion and gasification-combined-cycle power plants. Very efficient filtration is necessary in power plants to protect the turbine blades. The limited lifespan of ceramic candle filters has been a major obstacle in their development. The present work is focused on forming fibrous ceramic filters using a papermaking technique. These filters are highly porous and therefore very lightweight. The papermaking process consists of filtering a slurry of ceramic fibers through a steel screen to form paper. Papermaking and the selection of materials will be discussed, as well as preliminary results describing the geometry of papers and relative strengths.
Clark, Elizabeth; Wood, Andy; Nijssen, Bart; Mendoza, Pablo; Newman, Andy; Nowak, Kenneth; Arnold, Jeffrey
2017-04-01
In an automated forecast system, hydrologic data assimilation (DA) performs the valuable function of correcting raw simulated watershed model states to better represent external observations, including measurements of streamflow, snow, soil moisture, and the like. Yet the incorporation of automated DA into operational forecasting systems has been a long-standing challenge due to the complexities of the hydrologic system, which include numerous lags between state and output variations. To help demonstrate that such methods can succeed in operational automated implementations, we present results from the real-time application of an ensemble particle filter (PF) for short-range (7 day lead) ensemble flow forecasts in western US river basins. We use the System for Hydromet Applications, Research and Prediction (SHARP), developed by the National Center for Atmospheric Research (NCAR) in collaboration with the University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. SHARP is a fully automated platform for short-term to seasonal hydrologic forecasting applications, incorporating uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions through ensemble methods. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 temperature and precipitation time series through conceptual and physically-oriented models. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. The PF selects and/or weights and resamples the IHCs that are most consistent with external streamflow observations, and uses the particles to initialize a streamflow forecast ensemble driven by ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS). We apply this method in real-time for several basins in the western US that are important for water resources management, and perform a hindcast
Energy Technology Data Exchange (ETDEWEB)
2007-03-01
Presents the results of a 2,000-hour test of an emissions control system consisting of a nitrogen oxides adsorber catalyst in combination with a diesel particle filter, advanced fuels, and advanced engine controls in an SUV/pick-up truck vehicle platform.
Fundamentals of Stochastic Filtering
Crisan, Dan
2008-01-01
The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this book is to provide a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient
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.
Energy Technology Data Exchange (ETDEWEB)
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, NaNO_{2}, and NaNO_{3}) 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.
Sensory pollution from bag filters, carbon filters and combinations.
Bekö, G; Clausen, G; Weschler, C J
2008-02-01
Used ventilation filters are a major source of sensory pollutants in air handling systems. The objective of the present study was to evaluate the net effect that different combinations of filters had on perceived air quality after 5 months of continuous filtration of outdoor suburban air. A panel of 32 subjects assessed different sets of used filters and identical sets consisting of new filters. Additionally, filter weights and pressure drops were measured at the beginning and end of the operation period. The filter sets included single EU5 and EU7 fiberglass filters, an EU7 filter protected 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. Furthermore, its pressure drop changed very little during the 5 months of service, and it had the added benefit of removing a large fraction of ozone from the airstream. If similar results are obtained over a wider variety of soiling conditions, such filters may be a viable solution to a long recognized problem. The present study was designed to address the emission of sensory offending pollutants from loaded ventilation filters. The goal was to find a low-polluting solution from commercially available products. The results indicate that the use of activated carbon (AC) filters downstream of fiberglass bag filters can reduce the degradation of air quality that occurs with increasing particle loading. A more practical solution, yet comparably effective, is a stand-alone particle
Wang, Yujie; Zhang, Chenbin; Chen, Zonghai
2015-04-01
The state-of-charge (SOC) estimation for LiFePO4 batteries is one of the most important issues in battery management system (BMS) on electric vehicles (EVs). Significant temperature changes and drift current noises are inevitable in EVs and cause strong interference in SOC estimation, therefore a SOC-Particle filter (PF) estimator is proposed for SOC estimation. This paper tries to make three contributions: (1) a temperature composed battery model is established based on commercial LiFePO4 cells which can be used for SOC estimation at dynamic temperatures. (2) A capacity retention ratio (CRR) aging model is established based on the real history statistical analysis of the running mileage of the battery on an urban bus. (3) The proposed models are combined with an electrochemical model and the PF method is employed for SOC estimation to eliminate the drift noise effects. Experiments under dynamic current and temperature conditions are designed and performed to verify the accuracy and robustness of the proposed method. The numeral results of the validation experiments have verified that accurate and robust SOC estimation results can be obtained by the proposed method.
Sakurai, Gen; Yonemura, Seiichiro; Kishimoto-Mo, Ayaka W; Murayama, Shohei; Ohtsuka, Toshiyuki; Yokozawa, Masayuki
2015-01-01
Carbon dioxide (CO2) efflux from the soil surface, which is a major source of CO2 from terrestrial ecosystems, represents the total CO2 production at all soil depths. Although many studies have estimated the vertical profile of the CO2 production rate, one of the difficulties in estimating the vertical profile is measuring diffusion coefficients of CO2 at all soil depths in a nondestructive manner. In this study, we estimated the temporal variation in the vertical profile of the CO2 production rate using a data assimilation method, the particle filtering method, in which the diffusion coefficients of CO2 were simultaneously estimated. The CO2 concentrations at several soil depths and CO2 efflux from the soil surface (only during the snow-free period) were measured at two points in a broadleaf forest in Japan, and the data were assimilated into a simple model including a diffusion equation. We found that there were large variations in the pattern of the vertical profile of the CO2 production rate between experiment sites: the peak CO2 production rate was at soil depths around 10 cm during the snow-free period at one site, but the peak was at the soil surface at the other site. Using this method to estimate the CO2 production rate during snow-cover periods allowed us to estimate CO2 efflux during that period as well. We estimated that the CO2 efflux during the snow-cover period (about half the year) accounted for around 13% of the annual CO2 efflux at this site. Although the method proposed in this study does not ensure the validity of the estimated diffusion coefficients and CO2 production rates, the method enables us to more closely approach the "actual" values by decreasing the variance of the posterior distribution of the values.
Zhou, Jiafeng
2010-01-01
The general theory of microwave filter design based on lumped-element circuit is described in this chapter. The lowpass prototype filters with Butterworth, Chebyshev and quasielliptic characteristics are synthesized, and the prototype filters are then transformed to bandpass filters by lowpass to bandpass frequency mapping. By using immitance inverters ( J - or K -inverters), the bandpass filters can be realized by the same type of resonators. One design example is given to verify the theory ...
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.
Hydrodynamics of microbial filter feeding
DEFF Research Database (Denmark)
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...... 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...
Interpolation and Iteration for Nonlinear Filters
Energy Technology Data Exchange (ETDEWEB)
Chorin, Alexandre J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Tu, Xuemin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
2009-10-16
We present a general form of the iteration and interpolation process used in implicit particle filters. Implicit filters are based on a pseudo-Gaussian representation of posterior densities, and are designed to focus the particle paths so as to reduce the number of particles needed in nonlinear data assimilation. Examples are given.
1993-01-01
The Aquaspace H2OME Guardian Water Filter, available through Western Water International, Inc., reduces lead in water supplies. The filter is mounted on the faucet and the filter cartridge is placed in the "dead space" between sink and wall. This filter is one of several new filtration devices using the Aquaspace compound filter media, which combines company developed and NASA technology. Aquaspace filters are used in industrial, commercial, residential, and recreational environments as well as by developing nations where water is highly contaminated.
Flight prototype regenerative particulate filter system development
Green, D. C.; Garber, P. J.
1974-01-01
The effort to design, fabricate, and test a flight prototype Filter Regeneration Unit used to regenerate (clean) fluid particulate filter elements is reported. The design of the filter regeneration unit and the results of tests performed in both one-gravity and zero-gravity are discussed. The filter regeneration unit uses a backflush/jet impingement method of regenerating fluid filter elements that is highly efficient. A vortex particle separator and particle trap were designed for zero-gravity use, and the zero-gravity test results are discussed. The filter regeneration unit was designed for both inflight maintenance and ground refurbishment use on space shuttle and future space missions.
1987-01-01
A compact, lightweight electrolytic water filter generates silver ions in concentrations of 50 to 100 parts per billion in the water flow system. Silver ions serve as effective bactericide/deodorizers. Ray Ward requested and received from NASA a technical information package on the Shuttle filter, and used it as basis for his own initial development, a home use filter.
Anderson, Brian D O
1979-01-01
This graduate-level text augments and extends beyond undergraduate studies of signal processing, particularly in regard to communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to students in such diverse areas as statistics, economics, bioengineering, and operations research.Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; time-invariant filters; properties of Kalman filters; computational aspects; and smoothing of discrete-time signals. Additional subjects e
Stelman, David
1989-01-01
A contactor/filter arrangement for removing particulate contaminants from a gaseous stream includes a housing having a substantially vertically oriented granular material retention member with upstream and downstream faces, a substantially vertically oriented microporous gas filter element, wherein the retention member and the filter element are spaced apart to provide a zone for the passage of granular material therethrough. The housing further includes a gas inlet means, a gas outlet means, and means for moving a body of granular material through the zone. A gaseous stream containing particulate contaminants passes through the gas inlet means as well as through the upstream face of the granular material retention member, passing through the retention member, the body of granular material, the microporous gas filter element, exiting out of the gas outlet means. Disposed on the upstream face of the filter element is a cover screen which isolates the filter element from contact with the moving granular bed and collects a portion of the particulates so as to form a dust cake having openings small enough to exclude the granular material, yet large enough to receive the dust particles. In one embodiment, the granular material is comprised of prous alumina impregnated with CuO, with the cover screen cleaned by the action of the moving granular material as well as by backflow pressure pulses.
Bernard, D.; Frosini, M.
2017-10-01
Novel gamma-ray telescope schemes (silicon wafer stacks, emulsions, gas detectors) are being developed so as to bridge the sensitivity gap between Compton and pair-creation telescopes. The lower average density with respect to the tungsten/silicon active target of the Fermi-LAT makes large effective-area telescopes voluminous objects, for which the photon energy measurement by conventional means (calorimeter, magnetic spectrometer, transition radiation detector) is a challenge for the mass budget of the space mission. We present an optimal measurement of track momentum by the multiple measurement of the angular deflections induced by multiple scattering in the active target itself, using a Bayesian analysis of the filtering innovations of a series of Kalman filters applied to the track. For a silicon-wafer-stack telescope, the method yields meaningful results up to a couple of GeV/c.
Rodigues, Jose Eduardo; Santosdealmeida, Wagner
1987-12-01
Some of the main aspects related to photographic filters are examined and prepared as a reference for researchers and students of remote sensing. A large range of information about the filters including their basic fundamentals, classification, and main types is presented. The theme cannot be exhausted in this or any other individual publication because of its great complexity, profound theoretical publication, and dynmaic technological development. The subject does not deal only with filter applications in remote sensing. As much as possible, additional information about the utilization of these products in other professional areas, as pictorial photography, photographic processing, and optical engineering, were included.
Method of treating contaminated HEPA filter media in pulp process
Hu, Jian S.; Argyle, Mark D.; Demmer, Ricky L.; Mondok, Emilio P.
2003-07-29
A method for reducing contamination of HEPA filters with radioactive and/or hazardous materials is described. The method includes pre-processing of the filter for removing loose particles. Next, the filter medium is removed from the housing, and the housing is decontaminated. Finally, the filter medium is processed as pulp for removing contaminated particles by physical and/or chemical methods, including gravity, flotation, and dissolution of the particles. The decontaminated filter medium is then disposed of as non-RCRA waste; the particles are collected, stabilized, and disposed of according to well known methods of handling such materials; and the liquid medium in which the pulp was processed is recycled.
The PC9A Filter Screening Tool
2016-02-01
particles of known size encased in thin plastic straws that can be easily passed through the sensor. The test kit consists of 5 test straws each...patch connect the lower filter patch holder to the upper filter patch holder. 4 Quick test sensor Pass the black test straw down through the sensor...containing a single particle of known size (Figure 27). Table 13 contains the particle size and type for each coloured test straw . Whilst the kit
1988-01-01
Seeking to find a more effective method of filtering potable water that was highly contaminated, Mike Pedersen, founder of Western Water International, learned that NASA had conducted extensive research in methods of purifying water on board manned spacecraft. The key is Aquaspace Compound, a proprietary WWI formula that scientifically blends various types of glandular activated charcoal with other active and inert ingredients. Aquaspace systems remove some substances; chlorine, by atomic adsorption, other types of organic chemicals by mechanical filtration and still others by catalytic reaction. Aquaspace filters are finding wide acceptance in industrial, commercial, residential and recreational applications in the U.S. and abroad.
Kuban, D.P.; Singletary, B.H.; Evans, J.H.
A plurality of holding tubes are respectively mounted in apertures in a partition plate fixed in a housing receiving gas contaminated with particulate material. A filter cartridge is removably held in each holding tube, and the cartridges and holding tubes are arranged so that gas passes through apertures therein and across the the partition plate while particulate material is collected in the cartridges. Replacement filter cartridges are respectively held in holding canisters mounted on a support plate which can be secured to the aforesaid housing, and screws mounted on said canisters are arranged to push replacement cartridges into the cartridge holding tubes and thereby eject used cartridges therefrom.
Energy Technology Data Exchange (ETDEWEB)
Weichert, R.; Rulik, O.
1997-06-01
Filters may be used for reducing emissions of particulate pollutants from processing plants or for air cleaning in ventilation plants. The efficiency of a filter depends on its material, design, and operating conditions, notably the concentration and size of partciles, and on its load, i.e., its working hours. The purpose of the present project was to develop an inexpensive, easy-to-use, practicable measuring method for on-line measurement of the concentration and particle size distribution of dusts upstream (raw gas) and downstream (clean gas) of filters installed in processing plants, thus providing a means of continuously monitoring filter efficiency. The measuring principle of the developed method is based on the light scatter produced by individual particles passing through the measuring zone. The particle size measuring range is from 0.3 to 30 {mu}m, thus providing for the majority of all respirable dusts. The concentration measuring range is from a few mg/m{sup 3} on the clean gas side up to several g/m{sup 3} on the raw gas side. Special measures were needed to accomodate such a wide concentration range in a single measuring device. One of tasks of the study was to develop the technology required for this. (orig./SR) [Deutsch] Zur Minderung von Emissionen partikelfoermiger Schadstoffe aus verfahrenstechnischen Anlagen sowie zur Reinhaltung der Luft in Lueftungsanlagen werden Filter eingesetzt. Die Wirksamkeit dieser Filter haengt ab - von Material und Aufbau des Filters, von den Betriebsbedingungen des Filters, insbesondere von der Konzentration und der Groesse der Partikel und - von der Beladung des Filters, d.h. von seiner Betriebsdauer. Ziel des Vorhabens ist es, ein kostenguenstiges, handliches und feldtaugliches Messgeraet zu entwickeln, mit dem in technischen Anlagen die Konzentration und Groessenverteilung von Staeuben sowohl vor dem Filter (Rohgas) als auch hinter dem Filter (Reingas) on-line gemessen und so die Wirksamkeit des Filters
Ukaji, Emi; Furusawa, Takeshi; Sato, Masahide; Suzuki, Noboru
2007-11-01
The effect of surface modification with 3-aminopropyltriethoxysilane (APTES) and n-propyltriethoxysilane (PTES) on photo-catalytic activity and UV-shielding ability of fine TiO 2 particles were investigated. The number of surface groups ( NR) [nm -2] which shows the density of modifier on TiO 2 surface was calculated from the results of elemental analysis and BET measurement. The modified samples of which NR are different were obtained by changing the concentration of modifier. When the photo-catalytic activity and UV-shielding ability of modified samples were evaluated, it was found that APTES was more effective modifier than PTES to obtained samples with low photo-catalytic activity and high UV-shielding ability. This is probably because the adsorption mechanisms on TiO 2 surface between modifiers were different and NR is a key factor to control the performances of fine TiO 2 particles. The result of zeta potential showed that surface character of modified samples was varied by changing NR. It suggested from these results that NR affected the photo-catalytic activity and UV-shielding ability because NR changed surface character of modified samples.
Directory of Open Access Journals (Sweden)
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. [...
Energy Technology Data Exchange (ETDEWEB)
Horwat, D.; Endrino, J.L.; Boreave, A.; Karoum,R.; Pierson, J.F.; Weber, S.; Anders, A.; Vernoux, Ph.
2008-12-12
Methane conversion tests were performed on Pd, PdOy, Pd0.6Pt0.4Oy and Pd0.4Pt0.6Oy thin films deposited on yttria stabilized zirconia (YSZ) substrates. Pt containing films exhibited poor activity and high reducibility. As-deposited Pd and PdOy films showed good activity and transformed, during the cycling process, to particles dispersed on the YSZ substrates. The higher reaction rate of initially PdOy films was explained by a better dispersion of the catalyst. A drop of the reaction rate was observed when the temperature exceeded 735oC and 725oC for initially Pd and PdOy, respectively, which can be associated with the high-temperature reduction of PdO into Pd.
Nanoparticles filtration by leaked fibrous filters
Energy Technology Data Exchange (ETDEWEB)
Mouret, Guillaume; Calle-Chazelet, Sandrine; Thomas, Dominique; Appert-Collin, Jean-Christophe [Nancy-Universite/LSGC/CNRS - 1 rue Grandville - BP 20451 - F-54001 Nancy Cedex (France)], E-mail: sandrine.calle@ensic.inpl-nancy.fr; Bemer, Denis [INRS - Avenue de Bourgogne - F-54501 Vandoeuvre les Nancy Cedex (France)
2009-05-01
The aim of this work is first to measured nanoparticles penetration through three different fiberglass filters intentionally-pierced with calibrated needles at different filtration velocity. Then a semi-empirical model based on the air flow resistances of the new and perforated filter media and on the mechanism of Brownian diffusion for the collection of ultrafine particles by the media enables to well predict the efficiency observed for all tested operating conditions. Results show that the increase of particles penetration is all the more important that the pinhole is large and that the particle diameter is low. Another result is that the filtration efficiency of the new filter media controlled the penetration. A high efficiency filter with a high resistance to air flow will be more damaged than a low efficiency filter when being perforated.
1982-01-01
A compact, lightweight electrolytic water sterilizer available through Ambassador Marketing, generates silver ions in concentrations of 50 to 100 parts per billion in water flow system. The silver ions serve as an effective bactericide/deodorizer. Tap water passes through filtering element of silver that has been chemically plated onto activated carbon. The silver inhibits bacterial growth and the activated carbon removes objectionable tastes and odors caused by addition of chlorine and other chemicals in municipal water supply. The three models available are a kitchen unit, a "Tourister" unit for portable use while traveling and a refrigerator unit that attaches to the ice cube water line. A filter will treat 5,000 to 10,000 gallons of water.
Nonlinear Kalman filtering in affine term structure models
DEFF Research Database (Denmark)
Christoffersen, Peter; Dorion, Christian; Jacobs, Kris
2014-01-01
The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed-income applications. We investigate whether the unscented Kalman filter should be used to capture nonlinearities and compare the performance of the Kalman filter with...... performs well when compared with the much more computationally intensive particle filter. These findings suggest that the unscented Kalman filter may be a good approach for a variety of problems in fixed-income pricing....
Leaks in nuclear grade high efficiency aerosol filters
Energy Technology Data Exchange (ETDEWEB)
Scripsick, Ronald Clyde [Univ. of California, Davis, CA (United States)
1994-07-01
Nuclear grade high efficiency aerosol filters, also known as high efficiency particulate air (HEPA) filters, are commonly used in air cleaning systems for removal of hazardous aerosols. Performance of the filter units is important in assuring health and environmental protection. The filter units are constructed from pleated packs of fiberglass filter media sealed into rigid frames. Results of previous studies on such filter units indicate that their performance may not be completely predicted by ideal performance of the fibrous filter media. In this study, departure from ideal performance is linked to leaks existing in filter units and overall filter unit performance is derived from independent performance of the individual filter unit components. The performance of 14 nuclear grade HEPA filter units (size 1, 25 cfm) with plywood frames was evaluated with a test system that permitted independent determination of penetration as a function of particle size for the whole filter unit, the filter unit frame, and the filter media pack. Tests were performed using a polydisperse aerosol of di-2-ethylhexyl phthalate with a count median diameter of 0.2 {mu}m and geometric standard deviation of 1.6. Flow rate and differential pressure were controlled from 1% to 100% of design values. Particle counts were made upstream and downstream of the filter unit with an optical particle counter (OPC). The OPC provided count information in 28 size channels over the particle diameter range from 0.1 to 0.7 μm. Results provide evidence for a two component leak model of filler unit performance with: (1) external leaks through filter unit frames, and (2) internal leaks through defects in the media and through the seal between the media pack and frame. For the filter units evaluated, these leaks dominate overall filter unit performance over much of the flow rate and particle size ranges tested.
Ozone Removal by Filters Containing Activated Carbon: A Pilot Study
Energy Technology Data Exchange (ETDEWEB)
Fisk, William; Spears, Mike; Sullivan, Douglas; Mendell, Mark
2009-09-01
This study evaluated the ozone removal performance of moderate-cost particle filters containing activated carbon when installed in a commercial building heating, ventilating, and air conditioning (HVAC) system. Filters containing 300 g of activated carbon per 0.09 m2 of filter face area were installed in two 'experimental' filter banks within an office building located in Sacramento, CA. The ozone removal performance of the filters was assessed through periodic measurements of ozone concentrations in the air upstream and downstream of the filters. Ozone concentrations were also measured upstream and downstream of a 'reference' filter bank containing filters without any activated carbon. The filter banks with prefilters containing activated carbon were removing 60percent to 70percent of the ozone 67 and 81 days after filter installation. In contrast, there was negligible ozone removal by the reference filter bank without activated carbon.
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
Influence of operating parameters on cake formation in pilot scale pulse-jet bag filter
Saleem, Mahmood; Krammer, Gernot; Khan, Rafi Ullah; Tahir, M. Suleman
2012-01-01
Bag filters are commonly used for fine particles removal in off-gas purification. There dust laden gas pervades through permeable filter media starting at a lower pressure drop limit leaving dust (called filter cake) on the filter media. The filter cakeformation is influenced by many factors including filtration velocity, dust concentration, pressure drop limits, and filter media resistance. Effect of the stated parameters is investigated experimentally in a pilot scale pulse-jet bag filter t...
Curry, Ann; Haycock, Ken
2001-01-01
Discusses results of a survey questionnaire of public and school libraries that investigated the use of Internet filtering software. Considers filter alternatives; reasons for filtering or not filtering; brand names; satisfaction with site blocking; satisfaction with the decision to install filter software; and guidelines for considering filters.…
Schuster, B G; Osetek, D J
1978-02-01
Current methods for evaluating the performance and reliability of high-efficiency air cleaning systems use forward light-scattering photometers and DOP aerosol. This method is limited to measuring protection factors of 10(4) or 10(5) and has poor sensitivity to particles less than .3 micron. More accurate determination of system performance could be made by measuring two filter stages with a single test. Because of the large protection factors of a two-stage system, it is necessary to use high challenge aerosol concentrations and long downstream sampling times. Concentrations were measured using an intra-cavity laser light-scattering aerosol spectrometer which is capable of detection of single particles ranging in size from 0.07 to 3.00 micron diameter. The results of several tests with challenge aerosols of both NaCl and DOP yielded protection factors ranging from 1.4 x 10(7) to 3.0 x 10(9) for two HEPA filters in series.
Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) pilot of the Environmental Technology Verification (ETV) Program. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of th...
Microplastic in a macro filter feeder: humpback whale Megaptera novaeangliae
Besseling, E.; Foekema, E.M.; Franeker, van J.A.; Leopold, M.F.; Bravo Rebolledo, E.; Kuehn, S.; Mielke, L.; Heberle-Bors, E.; Ijzer, J.; Kamminga, P.; Koelmans, A.A.
2015-01-01
Marine filter feeders are exposed to microplastic because of their selection of small particles as food source. Baleen whales feed by filtering small particles from large water volumes. Macroplastic was found in baleen whales before. This study is the first to show the presence of microplastic in
Microplastic in a macro filter feeder: Humpback whale Megaptera novaeangliae.
E., Besseling,; E.M., Foekema,; J.A. van, Franeker; Leopold, Mardik F; Kuhn, S.; Bravo Rebolledo, E.L.; Hese, E.; Mielke, L.; IJzer, J.|info:eu-repo/dai/nl/304839663; Kamminga, P.; Koelmans, A.A.
2015-01-01
Marine filter feeders are exposed to microplastic because of their selection of small particles as food source. Baleen whales feed by filtering small particles from large water volumes. Macroplastic was found in baleen whales before. This study is the first to show the presence of microplastic in
Particle collection efficiency of the rotational particle separator
Brouwers, J.J.H.
1997-01-01
The rotational particle separator is a patented technique for separating solid and/or liquid particles of 0.1 m and larger from gases. The core component is the rotating filter element which consists of a multitude of axially oriented channels which rotate as a whole around a common axis. Particles
Directory of Open Access Journals (Sweden)
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.
Particle Filtering Methods for Incorporating Intelligence Updates
2017-03-01
appropriate information-updating mechanism. There exists a variety of ways to incorporate information updating. These methods include simple heuristics , such...threshold is preferable. It produces smoother results that are visibly more tractable. It eliminates a possible source of bias in the model by not
Development of iron-aluminide hot-gas filters
Energy Technology Data Exchange (ETDEWEB)
Tortorelli, P.F.; Wright, I.G.; Judkins, R.R.
1996-06-01
Removal of particles from hot synthesis gas produced by coal gasification is vital to the success of these systems. In Integrated [Coal] Gasification Combined Cycle systems, the synthesis gas is the fuel for gas turbines. To avoid damage to turbine components, it is necessary that particles be removed from the fuel gas prior to combustion and introduction into the turbine. Reliability and durability of the hot-gas filtering devices used to remove the particles is, of course, of special importance. Hot-gas filter materials include both ceramics and metals. Numerous considerations must be made in selecting materials for these filters. Constituents in the hot gases may potentially degrade the properties and performance of the filters to the point that they are ineffective in removing the particles. Very significant efforts have been made by DOE and others to develop effective hot-particle filters and, although improvements have been made, alternative materials and structures are still needed.
Optimal Gaussian Filter for Effective Noise Filtering
Kopparapu, Sunil; Satish, M
2014-01-01
In this paper we show that the knowledge of noise statistics contaminating a signal can be effectively used to choose an optimal Gaussian filter to eliminate noise. Very specifically, we show that the additive white Gaussian noise (AWGN) contaminating a signal can be filtered best by using a Gaussian filter of specific characteristics. The design of the Gaussian filter bears relationship with the noise statistics and also some basic information about the signal. We first derive a relationship...
CSIR Research Space (South Africa)
Du Plessis, WP
2009-10-01
Full Text Available flexible, and allows design tradeoffs to be evaluated in an intuitive way. Keywords: Cavity resonator filters, microwave filters, coupled transmission lines. 1 Introduction Interdigital filters are popular at the higher microwave frequencies for a... number of reasons. Ideal interdigital filters have perfect symmetry which means that they have better phase and delay characteristics than combline filters [1]. The couplings between the resonators of interdigital filters are also lower than those...
Directory of Open Access Journals (Sweden)
Christelle Garnier
2008-05-01
Full Text Available We address the problem of phase noise (PHN and carrier frequency offset (CFO mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE and the intercarrier interference (ICI which severely degrade the accuracy of the symbol detection stage. Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER and mean square error (MSE to illustrate the efficiency and the robustness of the proposed algorithm.
Particles matter: Transformation of suspended particles in constructed wetlands
Mulling, B.T.M.
2013-01-01
This thesis shows that constructed wetlands transform suspended particles in (treated) municipal wastewater through selective precipitation in ponds, biological filtering by plankton communities and physical and biological retention in reed beds. These processes effectively remove faecal indicator
Determination of the filter fabrics’ selectivity
Directory of Open Access Journals (Sweden)
Vyacheslav I. Kovalchuk
2015-03-01
Full Text Available To determine the coincidence between the filter fabric and impurities removed from the treated water, at power plants’ condensate it is necessary to compare the geometric parameters of pore channels and removed particles. Granulometric size distribution of mechanical impurities is investigated. The methodology of filter fabric selectivity calculation using results of fabric pores’ and suspended impurities’ distribution experimental study is exposed. The authors built an integral curve of particles’ size cumulative distribution, with a graphical differentiation of integral dependency serving to calculate the average-weighted size of impurities. The value of selectivity parameter representing the probability of simultaneous occurrence for events: impurities’ “particles size below…” and filter fabrics’ “pore size above…” is obtained. This will allow an evaluation of the feasibility and effectiveness of membrane-type filter fabrics use at standard operation of a powerful unit’ water treatment plants.
Active Optical Lattice Filters
Directory of Open Access Journals (Sweden)
Gary Evans
2005-06-01
Full Text Available Optical lattice filter structures including gains are introduced and analyzed. The photonic realization of the active, adaptive lattice filter is described. The algorithms which map between gains space and filter coefficients space are presented and studied. The sensitivities of filter parameters with respect to gains are derived and calculated. An example which is relevant to adaptive signal processing is also provided.
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.
A Simple Ripple Filter for FLUKA
DEFF Research Database (Denmark)
Bassler, Niels; Herrmann, Rochus
). The ripple filter at GSI and HIT consists of several wedge like structures, which widens the Bragg-peak up to e.g. 3 mm. For Monte Carlo simulations of C-12 therapy, the exact setup, including the ripple filter needs to be simulated. In the Monte Carlo particle transport program FLUKA, the ripple filter can...... be realized in several ways. The most simplistic version is to apply the ripples as simple triangles. More elaborate version would account for the exact structure, but the drawback is that this will bloat the FLUKA input file with vast amounts of bodys which needs to be included in the geometrical setup...
Joint albedo estimation and pose tracking from video.
Taheri, Sima; Sankaranarayanan, Aswin C; Chellappa, Rama
2013-07-01
The albedo of a Lambertian object is a surface property that contributes to an object's appearance under changing illumination. As a signature independent of illumination, the albedo is useful for object recognition. Single image-based albedo estimation algorithms suffer due to shadows and non-Lambertian effects of the image. In this paper, we propose a sequential algorithm to estimate the albedo from a sequence of images of a known 3D object in varying poses and illumination conditions. We first show that by knowing/estimating the pose of the object at each frame of a sequence, the object's albedo can be efficiently estimated using a Kalman filter. We then extend this for the case of unknown pose by simultaneously tracking the pose as well as updating the albedo through a Rao-Blackwellized particle filter (RBPF). More specifically, the albedo is marginalized from the posterior distribution and estimated analytically using the Kalman filter, while the pose parameters are estimated using importance sampling and by minimizing the projection error of the face onto its spherical harmonic subspace, which results in an illumination-insensitive pose tracking algorithm. Illustrations and experiments are provided to validate the effectiveness of the approach using various synthetic and real sequences followed by applications to unconstrained, video-based face recognition.
Sensory Pollution from Bag Filters, Carbon Filters and Combinations
DEFF Research Database (Denmark)
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...
Preparation of Porcelanite Ceramic Filter by Slip Casting Technique
Directory of Open Access Journals (Sweden)
Majid Muhi Shukur
2016-09-01
Full Text Available This work is conducted to study producing solid block porcelanite filter from Iraqi porcelanite rocks and kaolin clay (as binder material by slip casting technique, and investigating its ability of removing contaminant (Pentachlorophenol from water via the adsorption mechanism. Four particle sizes (74, 88, 105 and 125 µm of porcelanite powder were used. Each batch of particle size was mixed with (30 wt. % kaolin as a binding material to improve the mechanical properties. After that, the mixtures were formed by slip casting to disk and cylindrical filter samples, and then fired at 500 and 700 °C to specify the effects of particle size of porcelanite, temperature and formation technique on porcelanite filter properties. Some physical, mechanical and chemical tests have been done on filter samples. Multi-experiments were carried out to evaluate the ability of porcelanite to form the filter. Porosity, permeability and maximum pore diameter were increased with increasing porcelanite particle size and decreased by increasing temperature, whereas the density shows the reverse behavior. In addition, bending, compressive and tensile strength of samples were increased by increasing temperature, and decreased with increasing porcelanite particle size. Efficiency of disk filter sample to remove pentachlorophenol was 95.41% at a temperature of 700°C using 74 µm particle size of porcelanite. While the efficiency of cylindrical filter sample was 97.57% at the same conditions.
Burt, David
1997-01-01
Presents responses to 10 common arguments against the use of Internet filters in libraries. Highlights include keyword blocking; selection of materials; liability of libraries using filters; users' judgments; Constitutional issues, including First Amendment rights; and censorship. (LRW)
HEPA filter monitoring program
Kirchner, K. N.; Johnson, C. M.; Aiken, W. F.; Lucerna, J. J.; Barnett, R. L.; Jensen, R. T.
1986-07-01
The testing and replacement of HEPA filters, widely used in the nuclear industry to purify process air, are costly and labor-intensive. Current methods of testing filter performance, such as differential pressure measurement and scanning air monitoring, allow determination of overall filter performance but preclude detection of incipient filter failure such as small holes in the filters. Using current technology, a continual in-situ monitoring system was designed which provides three major improvements over current methods of filter testing and replacement. The improvements include: cost savings by reducing the number of intact filters which are currently being replaced unnecessarily; more accurate and quantitative measurement of filter performance; and reduced personnel exposure to a radioactive environment by automatically performing most testing operations.
Novel Backup Filter Device for Candle Filters
Energy Technology Data Exchange (ETDEWEB)
Bishop, B.; Goldsmith, R.; Dunham, G.; Henderson, A.
2002-09-18
The currently preferred means of particulate removal from process or combustion gas generated by advanced coal-based power production processes is filtration with candle filters. However, candle filters have not shown the requisite reliability to be commercially viable for hot gas clean up for either integrated gasifier combined cycle (IGCC) or pressurized fluid bed combustion (PFBC) processes. Even a single candle failure can lead to unacceptable ash breakthrough, which can result in (a) damage to highly sensitive and expensive downstream equipment, (b) unacceptably low system on-stream factor, and (c) unplanned outages. The U.S. Department of Energy (DOE) has recognized the need to have fail-safe devices installed within or downstream from candle filters. In addition to CeraMem, DOE has contracted with Siemens-Westinghouse, the Energy & Environmental Research Center (EERC) at the University of North Dakota, and the Southern Research Institute (SRI) to develop novel fail-safe devices. Siemens-Westinghouse is evaluating honeycomb-based filter devices on the clean-side of the candle filter that can operate up to 870 C. The EERC is developing a highly porous ceramic disk with a sticky yet temperature-stable coating that will trap dust in the event of filter failure. SRI is developing the Full-Flow Mechanical Safeguard Device that provides a positive seal for the candle filter. Operation of the SRI device is triggered by the higher-than-normal gas flow from a broken candle. The CeraMem approach is similar to that of Siemens-Westinghouse and involves the development of honeycomb-based filters that operate on the clean-side of a candle filter. The overall objective of this project is to fabricate and test silicon carbide-based honeycomb failsafe filters for protection of downstream equipment in advanced coal conversion processes. The fail-safe filter, installed directly downstream of a candle filter, should have the capability for stopping essentially all particulate
Application of RPF in MEMS gyro random drift filtering
Guowei, GAO; Yan, XIE
2017-08-01
With the development of micro-mechanical inertial technology, how to suppress the MEMS gyro’s random drift increasingly become a hot topic. In order to filter a certain type of MEMS gyro’s random drift, this paper introduces the regularized particle filter algorithm. The derivation of the algorithm and its application in MEMS gyro’s filtering process are described in detail in this paper: First, acquiring MEMS gyro’s static drift data and conducting data pre-treatment; then establishing the AR model by using time series analysis method, and transforming it into the corresponding state space model; finally, executing the estimation and compensation for MEMS gyro’s random drift with regular particle filter algorithm, and comparing it with other common methods in engineering. Tests and simulation results show that the regularized particle filter algorithm could achieve a good effect on the suppression of MEMS gyro’s random drift, it has a higher practical application value.
R. Bharadwaj; A. Patel, S. Chokdeepanich, Ph.D.; G.G. Chase, Ph.D.
2008-01-01
Coalescing filters are widely used throughout industry and improved performance will reduce droplet emissions and operating costs. Experimental observations show orientation of micro fibers in filter media effect the permeability and the separation efficiency of the filter media. In this work two methods are used to align the fibers to alter the filter structure. The results show that axially aligned fiber media improve quality factor on the order of 20% and cutting media on an angle from a t...
Independent Evaluation of Air Filter Media from Chornobyl
Energy Technology Data Exchange (ETDEWEB)
MD Hoover; AF Fencl; GJ Vargo
1999-12-21
An independent evaluation was performed to assess the morphology, pressure drop characteristics, alpha spectroscopy characteristics, and collection efficiency of an air sampling filter media and two types of aerosol face masks provided from Chernobyl by Pacific Northwest National Laboratory. The evaluation included characterizing the filter morphology by scqg electron microscopy; measuring the filter pressure drop as a function of air flowrate; evaluating the spectroscopy characteristics of the filter for alpha-emitting radionuclides by sampling ambient radon progeny aerosols in an Eberline Alpha-6A alpha continuous air monitor; determining the particle collection efficiency of the filter media for 0.3 {micro}m aerodynamic diameter monodisperse particles at 1 and 2 cfm; and comparing the apparent construction, durability, and performance similarities of the filter media to other media commonly used for monitoring airborne alpha-emitting radionuclides.
In-place HEPA filter penetration test
Energy Technology Data Exchange (ETDEWEB)
Bergman, W.; Wilson, K.; Elliott, J. [Lawrence Livermore National Lab., CA (United States)] [and others
1997-08-01
We have demonstrated the feasibility of conducting penetration tests on high efficiency particulate air (HEPA) filters as installed in nuclear ventilation systems. The in-place penetration test, which is designed to yield equivalent penetration measurements as the standard DOP efficiency test, is based on measuring the aerosol penetration of the filter installation as a function of particle size using a portable laser particle counter. This in-place penetration test is compared to the current in-place leak test using light scattering photometers for single HEPA filter installations and for HEPA filter plenums using the shroud method. Test results show the in-place penetration test is more sensitive than the in-place leak test, has a similar operating procedure, but takes longer to conduct. Additional tests are required to confirm that the in-place penetration test yields identical results as the standard dioctyl phthalate (DOP) penetration test for HEPA filters with controlled leaks in the filter and gasket and duct by-pass leaks. Further development of the procedure is also required to reduce the test time before the in-place penetration test is practical. 14 refs., 14 figs., 3 tabs.
Sellers, Cheryl L [Peoria, IL; Nordyke, Daniel S [Arlington Heights, IL; Crandell, Richard A [Morton, IL; Tomlins, Gregory [Peoria, IL; Fei, Dong [Peoria, IL; Panov, Alexander [Dunlap, IL; Lane, William H [Chillicothe, IL; Habeger, Craig F [Chillicothe, IL
2008-12-09
According to an exemplary embodiment of the present disclosure, a system for removing matter from a filtering device includes a gas pressurization assembly. An element of the assembly is removably attachable to a first orifice of the filtering device. The system also includes a vacuum source fluidly connected to a second orifice of the filtering device.
DEFF Research Database (Denmark)
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 sta...
Gates-Anderson, Dianne D.; Kidd, Scott D.; Bowers, John S.; Attebery, Ronald W.
2003-01-01
A low viscosity resin is delivered into a spent HEPA filter or other waste. The resin is introduced into the filter or other waste using a vacuum to assist in the mass transfer of the resin through the filter media or other waste.
Nanofiber filter media for air filtration
Raghavan, Bharath Kumar
Nanofibers have higher capture efficiencies in comparison to microfibers in the submicron particle size range of 100-500 nm because of small fiber diameter and increased surface area of the fibers. Pressure drop across the filter increases tremendously with decrease in fiber diameter in the continuum flow regime. Nanofibers with fiber diameter less than 300 nm are in the slip flow regime as a consequence of which steep increase in pressure drop is considerably reduced due to slip effect. The outlet or inlet gases have broad range of particle size distribution varying from few micrometers to nanometers. The economic benefits include capture of a wide range of particle sizes in the gas streams using compact filters composed of nanofibers and microfibers. Electrospinning technique was used to successfully fabricate polymeric and ceramic nanofibers. The nanofibers were long, continuous, and flexible with diameters in the range of 200--300 nm. Nanofibers were added to the filter medium either by mixing microfibers and nanofibers or by directly electrospinning nanofibers as thin layer on the surface of the microfiber filter medium. Experimental results showed that either by mixing Nylon 6 nanofibers with B glass fibers or by electrospinning Nylon 6 nanofibers as a thin layer on the surface of the microfiber medium in the surface area ratio of 1 which is 0.06 g of nanofibers for 2 g of microfibers performed better than microfiber filter media in air filtration tests. This improved performance is consistent with numerical modeling. The particle loading on a microfibrous filter were studied for air filtration tests. The experimental and modeling results showed that both pressure drop and capture efficiency increased with loading time. Nanofiber filter media has potential applications in many filtration applications and one of them being hot gas filtration. Ceramic nanofibers made of alumina and titania nanofibers can withstand in the range of 1000°C. Ceramic nanofibers
Marginalized approximate filtering of state-space models
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil
2018-01-01
Roč. 32, č. 1 (2018), s. 1-12 ISSN 0890-6327 R&D Projects: GA ČR(CZ) GA16-09848S Institutional support: RVO:67985556 Keywords : approximate filtering * marginalized filters * particle filtering Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.708, year: 2016 http:// library .utia.cas.cz/separaty/2017/AS/dedecius-0478074.pdf
... Your Health Particle Pollution Public Health Issues Particle Pollution Recommend on Facebook Tweet Share Compartir Particle pollution — ... see them in the air. Where does particle pollution come from? Particle pollution can come from two ...
A variance-minimizing filter for large-scale applications
Leeuwen, P.J. van
A data-assimilation method is introduced for large-scale applications in the ocean and the atmosphere that does not rely on Gaussian assumptions, i.e. it is completely general following Bayes theorem. It is a so-called particle filter. A truly variance minimizing filter is introduced and its
Nonlinear Kalman Filtering With Divergence Minimization
Gultekin, San; Paisley, John
2017-12-01
We consider the nonlinear Kalman filtering problem using Kullback-Leibler (KL) and $\\alpha$-divergence measures as optimization criteria. Unlike linear Kalman filters, nonlinear Kalman filters do not have closed form Gaussian posteriors because of a lack of conjugacy due to the nonlinearity in the likelihood. In this paper we propose novel algorithms to optimize the forward and reverse forms of the KL divergence, as well as the alpha-divergence which contains these two as limiting cases. Unlike previous approaches, our algorithms do not make approximations to the divergences being optimized, but use Monte Carlo integration techniques to derive unbiased algorithms for direct optimization. We assess performance on radar and sensor tracking, and options pricing problems, showing general improvement over the UKF and EKF, as well as competitive performance with particle filtering.
Microwave Bandpass Filter Based on Mie-Resonance Extraordinary Transmission.
Directory of Open Access Journals (Sweden)
Xiaolong Pan
Full Text Available Microwave bandpass filter structure has been designed and fabricated by filling the periodically metallic apertures with dielectric particles. The microwave cannot transmit through the metallic subwavelength apertures. By filling the metallic apertures with dielectric particles, a transmission passband with insertion loss 2 dB appears at the frequency of 10-12 GHz. Both simulated and experimental results show that the passband is induced by the Mie resonance of the dielectric particles. In addition, the passband frequency can be tuned by the size and the permittivity of the dielectric particles. This approach is suitable to fabricate the microwave bandpass filters.
Microwave Bandpass Filter Based on Mie-Resonance Extraordinary Transmission.
Pan, Xiaolong; Wang, Haiyan; Zhang, Dezhao; Xun, Shuang; Ouyang, Mengzhu; Fan, Wentao; Guo, Yunsheng; Wu, Ye; Huang, Shanguo; Bi, Ke; Lei, Ming
2016-01-01
Microwave bandpass filter structure has been designed and fabricated by filling the periodically metallic apertures with dielectric particles. The microwave cannot transmit through the metallic subwavelength apertures. By filling the metallic apertures with dielectric particles, a transmission passband with insertion loss 2 dB appears at the frequency of 10-12 GHz. Both simulated and experimental results show that the passband is induced by the Mie resonance of the dielectric particles. In addition, the passband frequency can be tuned by the size and the permittivity of the dielectric particles. This approach is suitable to fabricate the microwave bandpass filters.
Validation of Underwater Sensor Package Using Feature Based SLAM
Directory of Open Access Journals (Sweden)
Christopher Cain
2016-03-01
Full Text Available Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package.
Methodology for modeling the microbial contamination of air filters.
Directory of Open Access Journals (Sweden)
Yun Haeng Joe
Full Text Available In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.
Superposition as a Relativistic Filter
Ord, G. N.
2017-07-01
By associating a binary signal with the relativistic worldline of a particle, a binary form of the phase of non-relativistic wavefunctions is naturally produced by time dilation. An analog of superposition also appears as a Lorentz filtering process, removing paths that are relativistically inequivalent. In a model that includes a stochastic component, the free-particle Schrödinger equation emerges from a completely relativistic context in which its origin and function is known. The result establishes the fact that the phase of wavefunctions in Schrödinger's equation and the attendant superposition principle may both be considered remnants of time dilation. This strongly argues that quantum mechanics has its origins in special relativity.
Compact planar microwave blocking filters
U-Yen, Kongpop (Inventor); Wollack, Edward J. (Inventor)
2012-01-01
A compact planar microwave blocking filter includes a dielectric substrate and a plurality of filter unit elements disposed on the substrate. The filter unit elements are interconnected in a symmetrical series cascade with filter unit elements being organized in the series based on physical size. In the filter, a first filter unit element of the plurality of filter unit elements includes a low impedance open-ended line configured to reduce the shunt capacitance of the filter.
Comparison of Three Nonlinear Filters for Fault Detection in Continuous Glucose Monitors
DEFF Research Database (Denmark)
Mahmoudi, Zeinab; Wendt, Sabrina Lyngbye; Boiroux, Dimitri
2016-01-01
model of the glucose-insulin dynamics in people with type 1 diabetes. Drift is modelled by a Gaussian random walk and is detected based on the statistical tests of the 90-min prediction residuals of the filters. The unscented Kalman filter had the highest average F score of 85.9%, and the smallest......The purpose of this study is to compare the performance of three nonlinear filters in online drift detection of continuous glucose monitors. The nonlinear filters are the extended Kalman filter (EKF), the unscented Kalman filter (UKF), and the particle filter (PF). They are all based on a nonlinear...
ADVANCED HOT GAS FILTER DEVELOPMENT
Energy Technology Data Exchange (ETDEWEB)
E.S. Connolly; G.D. Forsythe
1998-12-22
Advanced, coal-based power plants will require durable and reliable hot gas filtration systems to remove particulate contaminants from the gas streams to protect downstream components such as turbine blades from erosion damage. It is expected that the filter elements in these systems will have to be made of ceramic materials to withstand goal service temperatures of 1600 F or higher. Recent demonstration projects and pilot plant tests have indicated that the current generation of ceramic hot gas filters (cross-flow and candle configurations) are failing prematurely. Two of the most promising materials that have been extensively evaluated are clay-bonded silicon carbide and alumina-mullite porous monoliths. These candidates, however, have been found to suffer progressive thermal shock fatigue damage, as a result of rapid cooling/heating cycles. Such temperature changes occur when the hot filters are back-pulsed with cooler gas to clean them, or in process upset conditions, where even larger gas temperature changes may occur quickly and unpredictably. In addition, the clay-bonded silicon carbide materials are susceptible to chemical attack of the glassy binder phase that holds the SiC particles together, resulting in softening, strength loss, creep, and eventual failure.
Directory of Open Access Journals (Sweden)
X. Yang
2009-07-01
Full Text Available A new class of ensemble filters, called the Diffuse Ensemble Filter (DEnF, is proposed in this paper. The DEnF assumes that the forecast errors orthogonal to the first guess ensemble are uncorrelated with the latter ensemble and have infinite variance. The assumption of infinite variance corresponds to the limit of "complete lack of knowledge" and differs dramatically from the implicit assumption made in most other ensemble filters, which is that the forecast errors orthogonal to the first guess ensemble have vanishing errors. The DEnF is independent of the detailed covariances assumed in the space orthogonal to the ensemble space, and reduces to conventional ensemble square root filters when the number of ensembles exceeds the model dimension. The DEnF is well defined only in data rich regimes and involves the inversion of relatively large matrices, although this barrier might be circumvented by variational methods. Two algorithms for solving the DEnF, namely the Diffuse Ensemble Kalman Filter (DEnKF and the Diffuse Ensemble Transform Kalman Filter (DETKF, are proposed and found to give comparable results. These filters generally converge to the traditional EnKF and ETKF, respectively, when the ensemble size exceeds the model dimension. Numerical experiments demonstrate that the DEnF eliminates filter collapse, which occurs in ensemble Kalman filters for small ensemble sizes. Also, the use of the DEnF to initialize a conventional square root filter dramatically accelerates the spin-up time for convergence. However, in a perfect model scenario, the DEnF produces larger errors than ensemble square root filters that have covariance localization and inflation. For imperfect forecast models, the DEnF produces smaller errors than the ensemble square root filter with inflation. These experiments suggest that the DEnF has some advantages relative to the ensemble square root filters in the regime of small ensemble size, imperfect model, and copious
Generic Kalman Filter Software
Lisano, Michael E., II; Crues, Edwin Z.
2005-01-01
The Generic Kalman Filter (GKF) software provides a standard basis for the development of application-specific Kalman-filter programs. Historically, Kalman filters have been implemented by customized programs that must be written, coded, and debugged anew for each unique application, then tested and tuned with simulated or actual measurement data. Total development times for typical Kalman-filter application programs have ranged from months to weeks. The GKF software can simplify the development process and reduce the development time by eliminating the need to re-create the fundamental implementation of the Kalman filter for each new application. The GKF software is written in the ANSI C programming language. It contains a generic Kalman-filter-development directory that, in turn, contains a code for a generic Kalman filter function; more specifically, it contains a generically designed and generically coded implementation of linear, linearized, and extended Kalman filtering algorithms, including algorithms for state- and covariance-update and -propagation functions. The mathematical theory that underlies the algorithms is well known and has been reported extensively in the open technical literature. Also contained in the directory are a header file that defines generic Kalman-filter data structures and prototype functions and template versions of application-specific subfunction and calling navigation/estimation routine code and headers. Once the user has provided a calling routine and the required application-specific subfunctions, the application-specific Kalman-filter software can be compiled and executed immediately. During execution, the generic Kalman-filter function is called from a higher-level navigation or estimation routine that preprocesses measurement data and post-processes output data. The generic Kalman-filter function uses the aforementioned data structures and five implementation- specific subfunctions, which have been developed by the user on
Arathy Rajagopal; B. Geethanjali; Arulprakash P
2015-01-01
A major security challenge on the Internet is the existence of the large number of compromised machines. Such machines have been increasingly used to launch various security attacks including spamming and spreading malware, DDoS, and identity theft. These compromised machines are called "Zombies". In general E-mail applications and providers uses spam filters to filter the spam messages. Spam filtering is a technique for discriminating the genuine message from the spam messages. The attackers...
Zakharov, Alexander V.; Ilchenko, Mykhailo Ye.; Trubarov, Igor V.; Pinchuk, Ludmila S.
2016-01-01
There are considered constructions of microsized stripe delay filters, which are realized on a basis of ceramic materials with high dielectric permittivity. Delay time of non-minimal phase filters is 7–12 ns at frequencies of 1900 MHz with relative bandwidth of 3.6–3.85%. Filters dimensions are comparable with ones used in portable communication devices. Dimensions of researched three-resonator filter at frequency of 1900 MHz are 8.4×5×2 mm with material dielectric permittivity εr = 92, and 5...
Oxygen activity changing when simulating silicon filtering process
Directory of Open Access Journals (Sweden)
A. D. Mekhtiyev
2016-07-01
Full Text Available In the article there is considered the efficiency of using filters for the refinement of metal melts, the use of filters in metallurgical practice and research of the inoculating mechanism of filter refinement of a metal melt from the dissolved impurities. In the inoculating mechanism the surface of the filter serves as a substrate for separation on it the nonmetallic phase directly from the melt, passing the stage of its separation into an isolated particle. This is proved experimentally, by monitoring the change of the deleted impurity activity by the EMF (electromotive force method.
Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms
Aman, Beshir M.
2012-12-01
This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation. Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.
Prokaryotic communities in drinking water biofilters using alternative filter medium
DEFF Research Database (Denmark)
Breda, Inês Lousinha Ribeiro; Roslev, Peter; Ramsay, Loren
in an alternative filter medium during the start-up of manganese removal. Filter media properties were measured using gravimetric methods and a photometric particle analyzer. Physical, chemical and microbial analyses were used to follow the manganese ripening. Microbial analyses of both inlet water and filter...... medium samples detected the presence of commonly reported prokaryotic groups: Alphaproteobacteria, Betaprotobacteria, Nitrospirae and Gammaproteobacteria. MnOB's were already attached to the medium grains by day 30 of the start-up when removal of manganese was still low. Knowledge of the microbial...... community in alternative filter medium can have great impact on start-up of biofilters....
Volatilization of PM2.5 Inorganic Ions in a Filter Pack System with Backup Filter and Denuders
Kim, C.; Choi, Y.; Ghim, Y.
2012-12-01
Concentrations of PM2.5 inorganic ions were measured at the rooftop of the 5-story building on the hill (37.02oN, 127.16oE, 167 m above sea level) in the Global Campus of Hankuk University of Foreign Studies, about 35 km southeast of downtown Seoul, Korea. The measurements were made four times during one-year span between 2011 and 2012 by considering the climate of Korea with distinct seasonal variations: July 29 to August 26 (summer); September 14 to October 13 (fall); November 28 to January 4 (winter); February 14 to May 31 (spring). A filter pack system was composed of PM2.5 cyclone, two annular denuders, Teflon filter, nylon filter, and an annular denuder, in series. Two annular denuders were to remove acidic and basic gases prior to collecting particles on the Teflon filter. Nylon filter and an annular denuder were to back up the Teflon filter by absorbing acidic and basic gases, respectively, which were volatilized from collected particles on the Teflon filter. Samplings were made for 24 hours every day. Extracts from filters and denuders were analyzed by ion chromatography to measure concentrations of anions (SO42-, NO3-, Cl-) and cations (Ca2+, Mg2+, NH4+, Na+, K+). The amounts of ionic species absorbed at the backup nylon filter and denuder were examined in terms of meteorological parameters, the amounts of gases removed in front of the Teflon filter, and the amounts of particulate ions collected on the Teflon filter. Major factors to affect the volatilization from particles collected on the Teflon filter were discussed.
Energy Technology Data Exchange (ETDEWEB)
Alvin, M.A.
1993-04-05
(1) After 500 hours of operation in the pressurized fluidized-bed combustion gas environment, the fibrous outer membrane along the clay bonded silicon carbide Schumacher Dia Schumalith candles remained intact. The fibrous outer membrane did not permit penetration of fines through the filter wall. (2) An approximate 10-15% loss of material strength occurred within the intact candle clay bonded silicon carbide matrix after 500 hours of exposure to the PFBC gas environment. A relatively uniform strength change resulted within the intact candles throughout the vessel (i.e., top to bottom plenums), as well as within the various cluster ring positions (i.e., outer versus inner ring candle filters). A somewhat higher loss of material strength, i.e., 25% was detected in fractured candle segments removed from the W-APF ash hopper. (3) Sulfur which is present in the pressurized fluidized-bed combustion gas system induced phase changes along the surface of the binder which coats the silicon carbide grains in the Schumacher Dia Schumalith candle filter matrix.
Weighted Ensemble Square Root Filters for Non-linear, Non-Gaussian, Data Assimilation
Livings, D. M.; van Leeuwen, P.
2012-12-01
In recent years the Ensemble Kalman Filter (EnKF) has become widely-used in both operational and research data assimilation systems. The particle filter is an alternative ensemble-based algorithm that offers the possibility of improved performance in non-linear and non-Gaussian problems. Papadakis et al (2010) introduced the Weighted Ensemble Kalman Filter (WEnKF) as a combination of the best features of the EnKF and the particle filter. Published work on the WEnKF has so far concentrated on the formulation of the EnKF in which observations are perturbed; no satisfactory general framework has been given for particle filters based on the alternative formulation of the EnKF known as the ensemble square root filter. This presentation will provide such a framework and show how several popular ensemble square root filters fit into it. No linear or Gaussian assumptions about the dynamical or observational models will be necessary. By examining the algorithms closely, shortcuts will be identified that increase both the simplicity and the efficiency of the resulting particle filter in comparison with a naive implementation. A procedure will be given for simply converting an existing ensemble square root filter into a particle filter. The procedure will not be limited to basic ensemble square root filters, but will be able to incorporate common variations such as covariance inflation without making any approximations.
Bonded carbon or ceramic fiber composite filter vent for radioactive waste
Brassell, Gilbert W.; Brugger, Ronald P.
1985-02-19
Carbon bonded carbon fiber composites as well as ceramic or carbon bonded ceramic fiber composites are very useful as filters which can separate particulate matter from gas streams entraining the same. These filters have particular application to the filtering of radioactive particles, e.g., they can act as vents for containers of radioactive waste material.
Energy Technology Data Exchange (ETDEWEB)
Destaillats, Hugo; Chen, Wenhao; Apte, Michael; Li, Nuan; Spears, Michael; Almosni, Jérémie; Brunner, Gregory; Zhang, Jianshun (Jensen); Fisk, William J.
2011-05-01
Prior research suggests that chemical processes taking place on the surface of particle filters employed in buildings may lead to the formation of harmful secondary byproducts. We investigated ozone reactions with fiberglass, polyester, cotton/polyester and polyolefin filter media, as well as hydrolysis of filter media additives. Studies were carried out on unused media, and on filters that were installed for 3 months in buildings at two different locations in the San Francisco Bay Area. Specimens from each filter media were exposed to {approx}150 ppbv ozone in a flow tube under a constant flow of dry or humidified air (50percent RH). Ozone breakthrough was recorded for each sample over periods of {approx}1000 min; the ozone uptake rate was calculated for an initial transient period and for steady-state conditions. While ozone uptake was observed in all cases, we did not observe significant differences in the uptake rate and capacity for the various types of filter media tested. Most experiments were performed at an airflow rate of 1.3 L/min (face velocity = 0.013 m/s), and a few tests were also run at higher rates (8 to 10 L/min). Formaldehyde and acetaldehyde, two oxidation byproducts, were quantified downstream of each sample. Those aldehydes (m/z 31 and 45) and other volatile byproducts (m/z 57, 59, 61 and 101) were also detected in real-time using Proton-Transfer Reaction - Mass Spectrometry (PTR-MS). Low-ppbv byproduct emissions were consistently higher under humidified air than under dry conditions, and were higher when the filters were loaded with particles, as compared with unused filters. No significant differences were observed when ozone reacted over various types of filter media. Fiberglass filters heavily coated with impaction oil (tackifier) showed higher formaldehyde emissions than other samples. Those emissions were particularly high in the case of used filters, and were observed even in the absence of ozone, suggesting that hydrolysis of additives
Filtration device for rapid separation of biological particles from complex matrices
Energy Technology Data Exchange (ETDEWEB)
Kim, Sangil; Naraghi-Arani, Pejman; Liou, Megan
2018-01-09
Methods and systems for filtering of biological particles are disclosed. Filtering membranes separate adjacent chambers. Through osmotic or electrokinetic processes, flow of particles is carried out through the filtering membranes. Cells, viruses and cell waste can be filtered depending on the size of the pores of the membrane. A polymer brush can be applied to a surface of the membrane to enhance filtering and prevent fouling.
Assessment of high-temperature filtering elements
Energy Technology Data Exchange (ETDEWEB)
Monica Lupion; Francisco J. Gutierrez Ortiz; Benito Navarrete; Vicente J. Cortes [University of Seville, Seville (Spain). E.T.S. Ingenieros
2008-07-01
A complete experimental campaign has been carried out in a hot gas filtration test facility so as to test several filtering elements and configurations, particularly, three different types of bag filters and one ceramic candle. The facility was designed to operate under a wide range of conditions, thus providing an excellent tool for the investigation of hot gas filtration applications for the advanced electrical power generation industry such as IGCC, PFBC or fuel cell technologies. Relevant parameters for the characterization and optimization of the performance of the filters have been studied for a variety of operation conditions such as filtration velocity, particle concentration, pressure and temperature among others. Pressure drop across the filter, cleaning pulse interval, baseline pressure drop, filtration efficiency and durability of the filter have been investigated for each type considered and dependences on parameters have been established. On top of that, optimal operating conditions and cleaning strategies were determined. The tests results show that bag filters are a suitable alternative for the hot gas filtration due to the better performance and the high efficiency observed, which makes them suitable for industrial applications operating under high temperature high pressure conditions considered within the study (200-370{degree}C and 4-7.5 barg respectively). 7 refs., 7 figs., 10 tabs.
Lagrangian multi-particle statistics
DEFF Research Database (Denmark)
Lüthi, Beat; Berg, Jacob; Ott, Søren
2007-01-01
. Based on an analytical result and on a sensitivity analysis, both presented here, we estimate the accuracy for filtered strain, (s) over tilde (2), and enstrophy, (omega) over tilde (2), at around 30%. The accuracy improves with higher tracer seeding density and with smaller filter scale Delta. We...... obtain good scaling with t* = root 2r(2)/15S(2)(r) for filtered strain and vorticity and present filtered R-Q invariant maps with the typical 'tear drop' shape that is known from velocity gradients at viscous scales. Lagrangian results are given for the growth of particle pairs, triangles and tetrahedra...... that the contribution from the coarse-grained strain field, r(i)r(j)(s) over tilde (ij) filtered at scale Delta = r, is responsible for roughly 2/3 of the separation rate, while 1/3 stems from scales Delta r....
Directory of Open Access Journals (Sweden)
N. L de Freitas
2004-12-01
Full Text Available Neste trabalho foram utilizados filtros cerâmicos para filtração de aerossóis, constituídos por dupla camada, onde a primeira camada é formada por um suporte celular de elevada porosidade com diâmetro de poro controlado e a segunda formada por uma película filtrante. A camada suporte foi obtida pela técnica de replicação cerâmica de espuma poliuretânica, por meio da impregnação de uma suspensão aquosa de Al2O3. Foram utilizados suportes de 45 e 75 poros/polegada. A membrana filtrante (Al2O3 e argila foi a mesma para ambos os suportes, sendo composta por uma massa granular cerâmica de baixa porosidade. Os experimentos de filtração foram realizados em temperaturas de 25 a 700 ºC onde mediu-se a capacidade dos filtros de limpar um aerossol de partículas finas polidispersas (diâmetro mediano de 4,6 µm e calculou-se a eficiência de coleta para diâmetros de partícula entre 0,4 e 8,5 µm. Os resultados mostraram que a eficiência diminuiu com o aumento da temperatura e aumentou com o diâmetro da partícula.In this work, ceramic filters were used for aerosol filtration. The filters were constituted by two layers, where the first layer was formed by of a highly porous ceramic support with controlled pore size and the second layer constituted by a fine membrane. The ceramic support was obtained from polymeric foams utilizing a technique of alumina impregnation. The supports had 45 and 75 pores per inch (ppi. The membrane (a mixture of alumina and clay was the same for the two supports, with much smaller pore sizes. The filtration experiments were accomplished at temperatures varying from 25 to 700 ºC, where the ability of the filters for cleaning an aerosol constituted by fine particles (median diameter of 4.6 µm was measured. The collection efficiency was calculated for particle diameters between 0.4 and 8.5 µm. The results showed that the collection efficiency decreased with the increase of the temperature and increased
Randomized Filtering Algorithms
DEFF Research Database (Denmark)
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...
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.
DEFF Research Database (Denmark)
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 inter...
Fast Anisotropic Gauss Filtering
Geusebroek, J.M.; Smeulders, A.W.M.; van de Weijer, J.; Heyden, A.; Sparr, G.; Nielsen, M.; Johansen, P.
2002-01-01
We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x-direction followed by a one dimensional filter in a non-orthogonal direction phi. So also the anisotropic Gaussian can be decomposed by dimension. This appears to be extremely efficient from a
Vena cava filter; Vena-cava-Filter
Energy Technology Data Exchange (ETDEWEB)
Helmberger, T. [Klinikum Bogenhausen, Institut fuer Diagnostische und Interventionelle Radiologie und Nuklearmedizin, Muenchen (Germany)
2007-05-15
Fulminant pulmonary embolism is one of the major causes of death in the Western World. In most cases, deep leg and pelvic venous thrombosis are the cause. If an anticoagulant/thrombotic therapy is no longer possible or ineffective, a vena cava filter implant may be indicated if an embolism is threatening. Implantation of the filter is a simple and safe intervention. Nevertheless, it is necessary to take into consideration that the data base for determining the indications for this treatment are very limited. Currently, a reduction in the risk of thromboembolism with the use of filters of about 30%, of recurrences of almost 5% and fatal pulmonary embolism of 1% has been reported, with a risk of up to 20% of filter induced vena cava thrombosis. (orig.) [German] Die fulminante Lungenembolie zaehlt zu den Haupttodesursachen in der westlichen Welt. In der Mehrzahl der Faelle sind tiefe Bein- und Beckenvenenthrombosen ursaechlich verantwortlich. Ist eine antikoagulative/-thrombotische Therapie nicht (mehr) moeglich oder unwirksam, kann bei drohender Emboliegefahr die Vena-cava-Filterimplantation indiziert sein. Die Filterimplantation ist eine einfache und sehr sichere Intervention. Dennoch muss bei der Indikationsstellung beruecksichtigt werden, dass die Datenlage zur Wirksamkeit sehr limitiert ist. So wird aktuell ueber eine Reduktion des Thrombembolierisikos um 30% bei Embolierezidiven von knapp 5% und fatalen Lungenembolien von 1% unter Filterprophylaxe berichtet, bei einem Risiko von bis zu 20% fuer die filterinduzierte Vena-cava-Thrombose. (orig.)
de Vries, AJ; Vermeijden, WJ; Gu, YJ; Hagenaars, JAM; van Oeveren, W
Activated leukocytes and fat particles are associated with organ injury after a cardiac surgery. Filters are currently used to remove either leukocytes or fat particles. A novel approach with a filter that combines leukocyte and fat removal might be clinically useful. As it is not known which type
André, V; Barraud, C; Capron, D; Preterre, D; Keravec, V; Vendeville, C; Cazier, F; Pottier, D; Morin, J P; Sichel, F
2015-01-01
Diesel exhausts are partly responsible for the deleterious effects on human health associated with urban pollution, including cardiovascular diseases, asthma, COPD, and possibly lung cancer. Particulate fraction has been incriminated and thus largely investigated for its genotoxic properties, based on exposure conditions that are, however, not relevant for human risk assessment. In this paper, original and more realistic protocols were used to investigate the hazards induced by exhausts emitted by the combustion of standard (DF0) vs. bio-diesel fuels (DF7 and DF30) and to assess the impact of exhaust treatment devices (DOC and DPF). Mutagenicity and genotoxicity were evaluated for (1) resuspended particles ("off line" exposure that takes into account the bioavailability of adsorbed chemicals) and for (2) the whole aerosols (particles+gas phase components) under continuous flow exposure ("on line" exposure). Native particles displayed mutagenic properties associated with nitroaromatic profiles (YG1041), whereas PAHs did not seem to be involved. After DOC treatment, the mutagenicity of particles was fully abolished. In contrast, the level of particle deposition was low under continuous flow exposure, and the observed mutagenicity in TA98 and TA102 was thus attributable to the gas phase. A bactericidal effect was also observed in TA102 after DOC treatment, and a weak but significant mutagenicity persisted after DPF treatment for bio-diesel fuels. No formation of bulky DNA-adducts was observed on A549 cells exposed to diesel exhaust, even in very drastic conditions (organic extracts corresponding to 500 μg equivalent particule/mL, 48 h exposure). Taken together, these data indicate that the exhausts issued from the bio-diesel fuels supplemented with rapseed methyl ester (RME), and generated by current diesel engines equipped with after treatment devices are less mutagenic than older ones. The residual mutagenicity is linked to the gas phase and could be due to pro
Ghausi, M. S.
1984-01-01
The evolution of active filters during the time from 1920 to 1980 is considered, taking into account the hardware used to implement a filtering network for voice frequency over 60 years. From 1920 to 1960 the majority of voice-frequency filters was realized as discrete RLC networks. After the development of transistors, it was realized that size and cost reductions could be achieved by replacing the inductors with active networks. In the early 1970's, batch-processed thin-film hybrid integrated circuits began to be employed. The synthesis of transfer functions which are predominantly input/output types is considered. Attention is given to direct realizations, synthesis using component simulation, cascade synthesis, multiple-loop feedback design, active-R and active-C filters, aspects of sensitivity, and switched-capacitor filters.
Sironi, Amos; Tekin, Bugra; Rigamonti, Roberto; Lepetit, Vincent; Fua, Pascal
2015-01-01
Learning filters to produce sparse image representations in terms of over-complete dictionaries has emerged as a powerful way to create image features for many different purposes. Unfortunately, these filters are usually both numerous and non-separable, making their use computationally expensive. In this paper, we show that such filters can be computed as linear combinations of a smaller number of separable ones, thus greatly reducing the computational complexity at no cost in terms of performance. This makes filter learning approaches practical even for large images or 3D volumes, and we show that we significantly outperform state-of-the-art methods on the curvilinear structure extraction task, in terms of both accuracy and speed. Moreover, our approach is general and can be used on generic convolutional filter banks to reduce the complexity of the feature extraction step.
Validation of the integrity of a HEPA filter system.
Wang, Wei-Hsung
2003-11-01
The objective of this study was to establish a delayed air sampling method to verify the integrity of an existing HEPA filter system in a ventilated fume hood. (238U,232Th)O2 microspheres were generated to fabricate cement nuclear fuel pellets in a HEPA-filtered hood. To comply with the air effluent concentration limits by NRC, the capture efficiency of the HEPA filter was examined. An in-line isokinetic air sampling system was installed downstream of the HEPA filter. Utilizing a gas flow proportional counter, 212Pb was used as a surrogate to indicate any possible penetration of the (238U,232Th)O2 particles through the HEPA filter. Based on the experimental results, this delayed sampling method proved to be an easy and effective way to validate the integrity of the HEPA filter.
Outlier Detection in GNSS Pseudo-Range/Doppler Measurements for Robust Localization.
Zair, Salim; Le Hégarat-Mascle, Sylvie; Seignez, Emmanuel
2016-04-22
In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS) data is hindered by Non-Line Of Sight (NLOS) and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR) and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF) or a Rao-Blackwellization (RB) approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the 'outliers' in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation.
Outlier Detection in GNSS Pseudo-Range/Doppler Measurements for Robust Localization
Directory of Open Access Journals (Sweden)
Salim Zair
2016-04-01
Full Text Available In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS data is hindered by Non-Line Of Sight (NLOS and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF or a Rao-Blackwellization (RB approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the ‘outliers’ in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation.
An Anchor-Based Pedestrian Navigation Approach Using Only Inertial Sensors
Gu, Yang; Song, Qian; Li, Yanghuan; Ma, Ming; Zhou, Zhimin
2016-01-01
In inertial-based pedestrian navigation, anchors can effectively compensate the positioning errors originating from deviations of Inertial Measurement Units (IMUs), by putting constraints on pedestrians’ motions. However, these anchors often need to be deployed beforehand, which can greatly increase system complexity, rendering it unsuitable for emergency response missions. In this paper, we propose an anchor-based pedestrian navigation approach without any additional sensors. The anchors are defined as the intersection points of perpendicular corridors and are considered characteristics of building structures. In contrast to these real anchors, virtual anchors are extracted from the pedestrian’s trajectory and are considered as observations of real anchors, which can accordingly be regarded as inferred building structure characteristics. Then a Rao-Blackwellized particle filter (RBPF) is used to solve the joint estimation of positions (trajectory) and maps (anchors) problem. Compared with other building structure-based methods, our method has two advantages. The assumption on building structure is minimum and valid in most cases. Even if the assumption does not stand, the method will not lead to positioning failure. Several real-scenario experiments are conducted to validate the effectiveness and robustness of the proposed method. PMID:26959031
Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors
Directory of Open Access Journals (Sweden)
Arturo Gil
2010-05-01
Full Text Available In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.
Filter-Feeding Zoobenthos and Hydrodynamics
DEFF Research Database (Denmark)
Riisgård, Hans Ulrik; Larsen, Poul Scheel
2017-01-01
interplay between benthic filter feeders and hydrodynamics. Starting from the general concept of grazing potential and typical data on benthic population densities its realization is considered, first at the level of the individual organism through the processes of pumping and trapping of food particles...... for ingestion which relies on hydrodynamics. Studies have shown the importance of biomixing giving increased vertical seston flux due to mixing induced by exhalant jets of filter feeders, particularly in stagnant water but likely also in benthic boundary layers over mussel beds at moderate flow velocities......This chapter summarizes recent years’ studies on zoobenthic filter feeding in the sea. General principles are extracted based on experiments and mathematical modeling, mainly from own studies in shallow temperate Danish waters, in order to present primary characteristics of the sophisticated...
Glass particle contamination of parenteral preparations of ...
African Journals Online (AJOL)
This was a prospective, randomised, single-blinded comparative study to assess the amount of glass particle contamination in single-use drug ampoules, and to compare the differences between the filter straw (B Braun Filter Straw® 5 micron), 23G hypodermic needles and 18G drawing-up needles in reducing ...
Real-time evaluation of ventilation filter-bank systems.
Moyer, Ernest S; Commodore, Michael A; Hayes, Jeffrey L; Fotta, Steven A; Berardinelli, Stephen P
2007-01-01
This study evaluated two government facility ventilation systems. One was a metropolitan government office complex with a recirculation system where outside air was the makeup air; the other was a NIOSH facility that used 100% outside air with no recirculation. The methodology employed was a modified American Society of Agricultural Engineers standard (S525) for testing total enclosure filtration efficiency, in agricultural tractor cabs, with optical particle counters (OPC). The low-efficiency bag filters were tested when new and after being in the ventilation system for 3 months. The replacement medium-efficiency filters were evaluated for 6 months (the manufacturer's suggested change-out schedule). These eight-chamber, medium-efficiency filters had an increased filter surface area that resulted in increased airflow through the system. Unfortunately, these filters contained electrostatic filter media and lost filtration efficiency rapidly, which was subsequently confirmed in a 30-day study conducted to determine an appropriate change-out schedule for the eight-chamber bag filters. The study determined that less than 6 months' use was justified due to the reduced efficiency of the electrostatic filter media. The NIOSH facility's air handler #8 (100% outside air unit) was upgraded from electrostatic bag filters, which had a suggested 9-month change-out schedule, to V Bank mechanical, wet-laid, glass fiber filters. The results of a 3-year evaluation showed that the V Bank filters had better filter efficiency after 3 years of service than the electrostatic filters had at 9 months. Both studies employed matched OPC instruments to reduce instrument-to-instrument bias. The methodology is adaptable to monitoring the total efficiency of most air filtration systems, and results can help make decisions about upgrading filter performance.
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.
Far infrared interference filters.
Varma, S P; Möller, K D
1969-08-01
Capacitive meshes for far ir, low pass filters are prepared from Cu layers on 2.5 micro plastic film. The properties of these meshes of different mesh constants g with their different combinations in two-mesh, fourmesh, and eight-mesh filters are studied in the spectral region 160 cm(-1) to 10 cm(-1) by the use of a grating spectrometer. The applications of these meshes as low pass filters in the far ir spectral region in a grating spectrometer are described.
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
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
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.
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).
DEFF Research Database (Denmark)
D'Agostino, Maria-Antonietta; Boers, Maarten; Kirwan, John
2014-01-01
OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Filter provides a framework for the validation of outcome measures for use in rheumatology clinical research. However, imaging and biochemical measures may face additional validation challenges because of their technical nature. The Imagin...
Ke, Yougang; Liu, Zhenxing; Liu, Yachao; Zhou, Junxiao; Shu, Weixing; Luo, Hailu; Wen, Shuangchun
2016-10-01
In this letter, we propose and experimentally demonstrate a compact photonic spin filter formed by integrating a Pancharatnam-Berry phase lens (focal length of ±f ) into a conventional plano-concave lens (focal length of -f). By choosing the input port of the filter, photons with a desired spin state, such as the right-handed component or the left-handed one, propagate alone its original propagation direction, while the unwanted spin component is quickly diverged after passing through the filter. One application of the filter, sorting the spin-dependent components of vector vortex beams on higher-order Poincaré sphere, is also demonstrated. Our scheme provides a simple method to manipulate light, and thereby enables potential applications for photonic devices.
Lenczewski, Romuald
2001-01-01
By introducing a color filtration to the multiplicity space, we extend the quantum Ito calculus on multiple symmetric Fock space to the framework of filtered adapted biprocesses. In this new notion of adaptedness,``classical'' time filtration makes the integrands similar to adapted processes, whereas ``quantum'' color filtration produces their deviations from adaptedness. An important feature of this calculus, which we call filtered stochastic calculus, is that it provides an explicit interpo...
Wu, Kun-Ta; Feng, Lang; Sha, Ruojie; Dreyfus, Rémi; Grosberg, Alexander Y.; Seeman, Nadrian C.; Chaikin, Paul M.
2012-01-01
DNA is increasingly used as an important tool in programming the self-assembly of micrometer- and nanometer-scale particles. This is largely due to the highly specific thermoreversible interaction of cDNA strands, which, when placed on different particles, have been used to bind precise pairs in aggregates and crystals. However, DNA functionalized particles will only reach their true potential for particle assembly when each particle can address and bind to many different kinds of particles. ...
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
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
Filter Media Tests Under Simulated Martian Atmospheric Conditions
Agui, Juan H.
2016-01-01
Human exploration of Mars will require the optimal utilization of planetary resources. One of its abundant resources is the Martian atmosphere that can be harvested through filtration and chemical processes that purify and separate it into its gaseous and elemental constituents. Effective filtration needs to be part of the suite of resource utilization technologies. A unique testing platform is being used which provides the relevant operational and instrumental capabilities to test articles under the proper simulated Martian conditions. A series of tests were conducted to assess the performance of filter media. Light sheet imaging of the particle flow provided a means of detecting and quantifying particle concentrations to determine capturing efficiencies. The media's efficiency was also evaluated by gravimetric means through a by-layer filter media configuration. These tests will help to establish techniques and methods for measuring capturing efficiency and arrestance of conventional fibrous filter media. This paper will describe initial test results on different filter media.
Microplastic in a macro filter feeder: Humpback whale Megaptera novaeangliae.
Besseling, E; Foekema, E M; Van Franeker, J A; Leopold, M F; Kühn, S; Bravo Rebolledo, E L; Heße, E; Mielke, L; IJzer, J; Kamminga, P; Koelmans, A A
2015-06-15
Marine filter feeders are exposed to microplastic because of their selection of small particles as food source. Baleen whales feed by filtering small particles from large water volumes. Macroplastic was found in baleen whales before. This study is the first to show the presence of microplastic in intestines of a baleen whale (Megaptera novaeangliae). Contents of its gastrointestinal tract were sieved, dissolved in 10% potassium hydroxide and washed. From the remaining dried material, potential synthetic polymer particles were selected based on density and appearance, and analysed by Fourier transform infrared (FTIR) spectroscopy. Several polymer types (polyethylene, polypropylene, polyvinylchloride, polyethylene terephthalate, nylon) were found, in varying particle shapes: sheets, fragments and threads with a size of 1mm to 17cm. This diversity in polymer types and particle shapes, can be interpreted as a representation of the varying characteristics of marine plastic and the unselective way of ingestion by M. novaeangliae. Copyright © 2015 Elsevier Ltd. All rights reserved.
On a multiscale approach for filter efficiency simulations
Iliev, Oleg
2014-07-01
Filtration in general, and the dead end depth filtration of solid particles out of fluid in particular, is intrinsic multiscale problem. The deposition (capturing of particles) essentially depends on local velocity, on microgeometry (pore scale geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences the velocity field and pressure distribution inside the filter element. To close the loop, we mention that the velocity influences the transport and deposition of particles. In certain cases one can evaluate the filtration efficiency considering only microscale or only macroscale models, but in general an accurate prediction of the filtration efficiency requires multiscale models and algorithms. This paper discusses the single scale and the multiscale models, and presents a fractional time step discretization algorithm for the multiscale problem. The velocity within the filter element is computed at macroscale, and is used as input for the solution of microscale problems at selected locations of the porous medium. The microscale problem is solved with respect to transport and capturing of individual particles, and its solution is postprocessed to provide permeability values for macroscale computations. Results from computational experiments with an oil filter are presented and discussed.
Gravimetric Measurements of Filtering Facepiece Respirators Challenged With Diesel Exhaust.
Satish, Swathi; Swanson, Jacob J; Xiao, Kai; Viner, Andrew S; Kittelson, David B; Pui, David Y H
2017-07-01
Elevated concentrations of diesel exhaust have been linked to adverse health effects. Filtering facepiece respirators (FFRs) are widely used as a form of respiratory protection against diesel particulate matter (DPM) in occupational settings. Previous results (Penconek A, Drążyk P, Moskal A. (2013) Penetration of diesel exhaust particles through commercially available dust half masks. Ann Occup Hyg; 57: 360-73.) have suggested that common FFRs are less efficient than would be expected for this purpose based on their certification approvals. The objective of this study was to measure the penetration of DPM through NIOSH-certified R95 and P95 electret respirators to verify this result. Gravimetric-based penetration measurements conducted using polytetrafluoroethylene (PTFE) and polypropylene (PP) filters were compared with penetration measurements made with a Scanning Mobility Particle Sizer (SMPS, TSI Inc.), which measures the particle size distribution. Gravimetric measurements using PP filters were variable compared to SMPS measurements and biased high due to adsorption of gas phase organic material. Relatively inert PTFE filters adsorbed less gas phase organic material resulting in measurements that were more accurate. To attempt to correct for artifacts associated with adsorption of gas phase organic material, primary and secondary filters were used in series upstream and downstream of the FFR. Correcting for adsorption by subtracting the secondary mass from the primary mass improved the result for both PTFE and PP filters but this correction is subject to 'equilibrium' conditions that depend on sampling time and the concentration of particles and gas phase hydrocarbons. Overall, the results demonstrate that the use of filters to determine filtration efficiency of FFRs challenged with diesel exhaust produces erroneous results due to the presence of gas phase hydrocarbons in diesel exhaust and the tendency of filters to adsorb organic material. Published by
Investigation of Locally Made Ceramic Filter for Household Water Treatment
Directory of Open Access Journals (Sweden)
Awaluddin Nurmiyanto
2012-06-01
Full Text Available This research have objective to develop and evaluate the performance of ceramic filter in using locally available material at Yogyakarta. Ceramic filter are made by pressing a mixture of clay, discarded pottery (grog and combustible material (coconut fiber into the molder. Curving processes are then applied to form tubular shape before firing it using kiln (1005°C. Filtration test were performed gravitationally by flowing well water into ceramic filter. Filtered water quality was complying with Indonesia drinking water quality standard (E.Coli and turbidity although it has low filtration rate (0,461 L/Hr. The most optimum ceramic filter in turbidity and bacterial removal was composition number 10 {clay+coconut fiber 4,5%(w/w+grog 5%(w/w} that have average turbidity removal 88,2%, and average E. Coli removal 100%. N2 adsorption-desorption result on ceramic filter number 10 showed 0,04μm pore size, and 4,32m2/g pore surface area. The result from the XRD (X-ray diffractometer indicates crystal structure of calcite and quartz on ceramic filter surface. Energy Dispersive X-ray (EDX analysis showed Carbon compound as the most material constituent within the filter. Whereas micro’s photo using SEM (scanning electron microscopic and TEM (transmitted electron microscopic showed filter surface consists of stacked aggregates, separated by more randomly oriented particles.
Visualization of flow during cleaning process on a liquid nanofibrous filter
Bílek, P.
2017-10-01
This paper deals with visualization of flow during cleaning process on a nanofibrous filter. Cleaning of a filter is very important part of the filtration process which extends lifetime of the filter and improve filtration properties. Cleaning is carried out on flat-sheet filters, where particles are deposited on the filter surface and form a filtration cake. The cleaning process dislodges the deposited filtration cake, which is loose from the membrane surface to the retentate flow. The blocked pores in the filter are opened again and hydrodynamic properties are restored. The presented optical method enables to see flow behaviour in a thin laser sheet on the inlet side of a tested filter during the cleaning process. The local concentration of solid particles is possible to estimate and achieve new information about the cleaning process. In the article is described the cleaning process on nanofibrous membranes for waste water treatment. The hydrodynamic data were compared to the images of the cleaning process.
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
IIR Filter Modeling Using an Algorithm Inspired on Electromagnetism
Directory of Open Access Journals (Sweden)
Cuevas-Jiménez E.
2013-01-01
Full Text Available Infinite-impulse-response (IIR filtering provides a powerful approach for solving a variety of problems. However, its design represents a very complicated task, since the error surface of IIR filters is generally multimodal, global optimization techniques are required in order to avoid local minima. In this paper, a new method based on the Electromagnetism-Like Optimization Algorithm (EMO is proposed for IIR filter modeling. EMO originates from the electro-magnetism theory of physics by assuming potential solutions as electrically charged particles which spread around the solution space. The charge of each particle depends on its objective function value. This algorithm employs a collective attraction-repulsion mechanism to move the particles towards optimality. The experimental results confirm the high performance of the proposed method in solving various benchmark identification problems.
Filters for cathodic arc plasmas
Anders, Andre; MacGill, Robert A.; Bilek, Marcela M. M.; Brown, Ian G.
2002-01-01
Cathodic arc plasmas are contaminated with macroparticles. A variety of magnetic plasma filters has been used with various success in removing the macroparticles from the plasma. An open-architecture, bent solenoid filter, with additional field coils at the filter entrance and exit, improves macroparticle filtering. In particular, a double-bent filter that is twisted out of plane forms a very compact and efficient filter. The coil turns further have a flat cross-section to promote macroparticle reflection out of the filter volume. An output conditioning system formed of an expander coil, a straightener coil, and a homogenizer, may be used with the magnetic filter for expanding the filtered plasma beam to cover a larger area of the target. A cathodic arc plasma deposition system using this filter can be used for the deposition of ultrathin amorphous hard carbon (a-C) films for the magnetic storage industry.
Multilevel Mixture Kalman Filter
Directory of Open Access Journals (Sweden)
Xiaodong Wang
2004-11-01
Full Text Available The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.
Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception.
Kutschireiter, Anna; Surace, Simone Carlo; Sprekeler, Henning; Pfister, Jean-Pascal
2017-08-18
The robust estimation of dynamical hidden features, such as the position of prey, based on sensory inputs is one of the hallmarks of perception. This dynamical estimation can be rigorously formulated by nonlinear Bayesian filtering theory. Recent experimental and behavioral studies have shown that animals' performance in many tasks is consistent with such a Bayesian statistical interpretation. However, it is presently unclear how a nonlinear Bayesian filter can be efficiently implemented in a network of neurons that satisfies some minimum constraints of biological plausibility. Here, we propose the Neural Particle Filter (NPF), a sampling-based nonlinear Bayesian filter, which does not rely on importance weights. We show that this filter can be interpreted as the neuronal dynamics of a recurrently connected rate-based neural network receiving feed-forward input from sensory neurons. Further, it captures properties of temporal and multi-sensory integration that are crucial for perception, and it allows for online parameter learning with a maximum likelihood approach. The NPF holds the promise to avoid the 'curse of dimensionality', and we demonstrate numerically its capability to outperform weighted particle filters in higher dimensions and when the number of particles is limited.
Filters for Submillimeter Electromagnetic Waves
Berdahl, C. M.
1986-01-01
New manufacturing process produces filters strong, yet have small, precise dimensions and smooth surface finish essential for dichroic filtering at submillimeter wavelengths. Many filters, each one essentially wafer containing fine metal grid made at same time. Stacked square wires plated, fused, and etched to form arrays of holes. Grid of nickel and tin held in brass ring. Wall thickness, thickness of filter (hole depth) and lateral hole dimensions all depend upon operating frequency and filter characteristics.
Directory of Open Access Journals (Sweden)
Wan Yang
2014-04-01
Full Text Available A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.. Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters--a basic particle filter (PF with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF, and particle Markov chain Monte Carlo (pMCMC--and three ensemble filters--the ensemble Kalman filter (EnKF, the ensemble adjustment Kalman filter (EAKF, and the rank histogram filter (RHF--were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003-2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable; the three particle filters perform slightly better predicting peaks 1-5 weeks in the future; the ensemble filters are more accurate predicting peaks in
Interaction of Burning Metal Particles
Dreizin, Edward L.; Berman, Charles H.; Hoffmann, Vern K.
1999-01-01
Physical characteristics of the combustion of metal particle groups have been addressed in this research. The combustion behavior and interaction effects of multiple metal particles has been studied using a microgravity environment, which presents a unique opportunity to create an "aerosol" consisting of relatively large particles, i.e., 50-300 m diameter. Combustion behavior of such an aerosol could be examined using methods adopted from well-developed single particle combustion research. The experiment included fluidizing relatively large (order of 100 m diameter) uniform metal particles under microgravity and igniting such an "aerosol" using a hot wire igniter. The flame propagation and details of individual particle combustion and particle interaction have been studied using a high speed movie and video-imaging with cameras coupled with microscope lenses to resolve individual particles. Interference filters were used to separate characteristic metal and metal oxide radiation bands from the thermal black body radiation. Recorded flame images were digitized and various image processing techniques including flame position tracking, color separation, and pixel by pixel image comparison were employed to understand the processes occurring in the burning aerosol. The development of individual particle flames, merging or separation, and extinguishment as well as induced particle motion have been analyzed to identify the mechanisms governing these processes. Size distribution, morphology, and elemental compositions of combustion products were characterized and used to link the observed in this project aerosol combustion phenomena with the recently expanded mechanism of single metal particle combustion.
Condensation Particle Counter Instrument Handbook
Energy Technology Data Exchange (ETDEWEB)
Kuang, C. [Brookhaven National Lab. (BNL), Upton, NY (United States)
2016-02-01
The Model 3772 CPC is a compact, rugged, and full-featured instrument that detects airborne particles down to 10 nm in diameter, at an aerosol flow rate of 1.0 lpm, over a concentration range from 0 to 1x104 #/cc. This CPC is ideally suited for applications without high concentration measurements, such as basic aerosol research, filter and air-cleaner testing, particle counter calibrations, environmental monitoring, mobile aerosol studies, particle shedding and component testing, and atmospheric and climate studies.
Cigarette Smoke Cadmium Breakthrough from Traditional Filters: Implications for Exposure
Pappas, R. Steven; Fresquez, Mark R.; Watson, Clifford H.
2015-01-01
Cadmium, a carcinogenic metal, is highly toxic to renal, skeletal, nervous, respiratory, and cardiovascular systems. Accurate and precise quantification of mainstream smoke cadmium levels in cigarette smoke is important because of exposure concerns. The two most common trapping techniques for collecting mainstream tobacco smoke particulate for analysis are glass fiber filters and electrostatic precipitators. We observed that a significant portion of total cadmium passed through standard glass fiber filters that are used to trap particulate matter. We therefore developed platinum traps to collect the cadmium that passed through the filters and tested a variety of cigarettes with different physical parameters for quantities of cadmium that passed though the filters. We found less than 1% cadmium passed through electrostatic precipitators. In contrast, cadmium that passed through 92 mm glass fiber filters on a rotary smoking machine was significantly higher, ranging from 3.5% to 22.9% of total smoke cadmium deliveries. Cadmium passed through 44 mm filters typically used on linear smoking machines to an even greater degree, ranging from 13.6% to 30.4% of the total smoke cadmium deliveries. Differences in the cadmium that passed through from the glass fiber filters and electrostatic precipitator could be explained in part if cadmium resides in the smaller mainstream smoke aerosol particle sizes. Differences in particle size distribution could have toxicological implications and could help explain the pulmonary and cardiovascular cadmium uptake in smokers. PMID:25313385
Kovačević, Branko; Milosavljević, Milan
2013-01-01
“Adaptive Digital Filters” presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms. The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in m...
Energy Technology Data Exchange (ETDEWEB)
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.
Automated electronic filter design
Banerjee, Amal
2017-01-01
This book describes a novel, efficient and powerful scheme for designing and evaluating the performance characteristics of any electronic filter designed with predefined specifications. The author explains techniques that enable readers to eliminate complicated manual, and thus error-prone and time-consuming, steps of traditional design techniques. The presentation includes demonstration of efficient automation, using an ANSI C language program, which accepts any filter design specification (e.g. Chebyschev low-pass filter, cut-off frequency, pass-band ripple etc.) as input and generates as output a SPICE(Simulation Program with Integrated Circuit Emphasis) format netlist. Readers then can use this netlist to run simulations with any version of the popular SPICE simulator, increasing accuracy of the final results, without violating any of the key principles of the traditional design scheme.
Filters in topology optimization
DEFF Research Database (Denmark)
Bourdin, Blaise
1999-01-01
In this article, a modified (``filtered'') version of the minimum compliance topology optimization problem is studied. The direct dependence of the material properties on its pointwise density is replaced by a regularization of the density field using a convolution operator. In this setting...... it is possible to establish the existence of solutions. Moreover, convergence of an approximation by means of finite elements can be obtained. This is illustrated through some numerical experiments. The ``filtering'' technique is also shown to cope with two important numerical problems in topology optimization...
Directory of Open Access Journals (Sweden)
M. Van Looy
1998-12-01
Full Text Available In this paper we present a switched capacitor filter design using the SC22324 1C, which is fitted with an E2PROM. It contains four digitally programmable switched-capacitor filter sections, in order to obtain different responses. The SC22324 also contains the on-chip RAM. We'd like to explain, how could the on-chip RAM controlled via a PC. In this way the chip may be used afterwards with a menu where the user may select the wanted parameters.
Removing Pathogens Using Nano-Ceramic-Fiber Filters
Tepper, Frederick; Kaledin, Leonid
2005-01-01
A nano-aluminum-oxide fiber of only 2 nanometers in diameter was used to develop a ceramic-fiber filter. The fibers are electropositive and, when formulated into a filter material (NanoCeram(TradeMark)), would attract electro-negative particles such as bacteria and viruses. The ability to detect and then remove viruses as well as bacteria is of concern in space cabins since they may be carried onboard by space crews. Moreover, an improved filter was desired that would polish the effluent from condensed moisture and wastewater, producing potable drinking water. A laboratory- size filter was developed that was capable of removing greater than 99.9999 percent of bacteria and virus. Such a removal was achieved at flow rates hundreds of times greater than those through ultraporous membranes that remove particles by sieving. Because the pore size of the new filter was rather large as compared to ultraporous membranes, it was found to be more resistant to clogging. Additionally, a full-size cartridge is being developed that is capable of serving a full space crew. During this ongoing effort, research demonstrated that the filter media was a very efficient adsorbent for DNA (deoxyribonucleic acid), RNA (ribonucleic acid), and endotoxins. Since the adsorption is based on the charge of the macromolecules, there is also a potential for separating proteins and other particulates on the basis of their charge differences. The separation of specific proteins is a major new thrust of biotechnology. The principal application of NanoCeram filters is based on their ability to remove viruses from water. The removal of more than 99.9999 percent of viruses was achieved by a NanoCeram polishing filter added to the effluent of an existing filtration device. NanoCeram is commercially available in laboratory-size filter discs and in the form of a syringe filter. The unique characteristic of the filter can be demonstrated by its ability to remove particulate dyes such as Metanyl yellow. Its
DEFF Research Database (Denmark)
Lee, Carson; Albrechtsen, Hans-Jørgen; Smets, Barth F.
studies to determine how operating conditions affect the performance of the filters. Substrate concentrations, particle/precipitate accumulation, and biomass kinetics are monitored throughout the depth of the filter and over the operational cycle of the filter. Tracer tests, using a conservative salt...
Enhanced Optical Filter Design
Cushing, David
2011-01-01
This book serves as a supplement to the classic texts by Angus Macleod and Philip Baumeister, taking an intuitive approach to the enhancement of optical coating (or filter) performance. Drawing from 40 years of experience in thin film design, Cushing introduces the basics of thin films, the commonly used materials and their deposition, the major coatings and their applications, and improvement methods for each.
Beck, H P; Boissat, C; Davis, R; Duval, P Y; Etienne, F; Fede, E; Francis, D; Green, P; Hemmer, F; Jones, R; MacKinnon, J; Mapelli, Livio P; Meessen, C; Mommsen, R K; Mornacchi, Giuseppe; Nacasch, R; Negri, A; Pinfold, James L; Polesello, G; Qian, Z; Rafflin, C; Scannicchio, D A; Stanescu, C; Touchard, F; Vercesi, V
1999-01-01
An overview of the studies for the ATLAS Event Filter is given. The architecture and the high level design of the DAQ-1 prototype is presented. The current status if the prototypes is briefly given. Finally, future plans and milestones are given. (11 refs).
2016-08-01
EXWC) performed the evaluation at the Naval Air Station Lemoore, CA . The two year evaluation period began with one year of sand filter operation...appear dirty? If you answered “ yes ” to the first question and “ yes ” to either of the other questions, investigate this technology for your
Fast Anisotropic Gauss Filters
Geusebroek, J.M.; Smeulders, A.W.M.; van de Weijer, J.
2003-01-01
We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x-direction phi. So also the anisotropic Gaussian can be decomposed by dimension. This appears to be extremely efficient from a computing perspective. An implementation scheme for normal covolution and
Energy Technology Data Exchange (ETDEWEB)
Mitchell, M A; Bergman, W; Haslam, J; Brown, E P; Sawyer, S; Beaulieu, R; Althouse, P; Meike, A
2012-04-30
Potential benefits of ceramic filters in nuclear facilities: (1) Short term benefit for DOE, NRC, and industry - (a) CalPoly HTTU provides unique testing capability to answer questions for DOE - High temperature testing of materials, components, filter, (b) Several DNFSB correspondences and presentations by DNFSB members have highlighted the need for HEPA filter R and D - DNFSB Recommendation 2009-2 highlighted a nuclear facility response to an evaluation basis earthquake followed by a fire (aka shake-n-bake) and CalPoly has capability for a shake-n-bake test; (2) Intermediate term benefit for DOE and industry - (a) Filtration for specialty applications, e.g., explosive applications at Nevada, (b) Spin-off technologies applicable to other commercial industries; and (3) Long term benefit for DOE, NRC, and industry - (a) Across industry, strong desire for better performance filter, (b) Engineering solution to safety problem will improve facility safety and decrease dependence on associated support systems, (c) Large potential life-cycle cost savings, and (d) Facilitates development and deployment of LLNL process innovations to allow continuous ventilation system operation during a fire.
Rutger van Aalst; Ines Simic
2015-01-01
This paper describes a possible solution to the underwater sound filtering problem, using Blind Source Separation. The problem regards splitting sound from a boat engine and the water waves to prove the possibility to extract one sound fragment from the other on the open sea. The illustrations shown
DEFF Research Database (Denmark)
Bekö, Gabriel; Clausen, Geo; Weschler, Charles J.
2007-01-01
efficiencies than an identical filter not protected from ozone during the same 9 weeks of service filtering the same air. This result indicates that a filter's exposure history subsequently influences the quantity of oxidation products generated when ozone-containing air flows through it. (c) 2007 Elsevier Ltd......The sensory pollutants emitted by loaded ventilation filters are assumed to include products formed via oxidation of organics associated with captured particles. In this study, experiments were performed that used either particle production or ozone removal as probes to further improve our...... understanding of such processes. The measured ratio of downstream to upstream submicron particle concentrations increased when ozone was added to air passing through samples from loaded particle filters. Such an observation is consistent with low volatility oxidation products desorbing from the filter...
DEMONSTRATION BULLETIN: COLLOID POLISHING FILTER METHOD - FILTER FLOW TECHNOLOGY, INC.
The Filter Flow Technology, Inc. (FFT) Colloid Polishing Filter Method (CPFM) was tested as a transportable, trailer mounted, system that uses sorption and chemical complexing phenomena to remove heavy metals and nontritium radionuclides from water. Contaminated waters can be pro...
DEVELOPMENT OF AN ADHESIVE CANDLE FILTER SAFEGUARD DEVICE
Energy Technology Data Exchange (ETDEWEB)
John P. Hurley; Ann K. Henderson; Jan W. Nowok; Michael L. Swanson
2002-01-01
device at high temperatures in a dusty gas stream is difficult because of problems with materials corrosion, dust leakage, and detection of filter failure. Therefore, the Energy & Environmental Research Center is using its knowledge of the factors that make filter dust sticky at gas filtration temperatures to make a simple and inexpensive SGD that employs an adhesive yet thermodynamically stable coating on a highly porous ceramic substrate. The SGDs are placed on top of individual candle filters at the filtered gas exit. Upon failure of the filter, the dirty gas flows through the SGD where the adhesive surface rapidly and permanently traps dust particles, causing the device to plug and prevent the dust from reaching the turbine.
CERN. Geneva
1999-01-01
Introduction, interaction of radiation with matter measurement of momentum of charged particles, of energy of e/gamma, hadrons, identification of particles. Design of HEP detectors. Principle of operation and performance of tracking sub-detectors, calorimeters and muon system.
Numerical study of canister filters with alternatives filter cap configurations
Mohammed, A. N.; Daud, A. R.; Abdullah, K.; Seri, S. M.; Razali, M. A.; Hushim, M. F.; Khalid, A.
2017-09-01
Air filtration system and filter play an important role in getting a good quality air into turbo machinery such as gas turbine. The filtration system and filter has improved the quality of air and protect the gas turbine part from contaminants which could bring damage. During separation of contaminants from the air, pressure drop cannot be avoided but it can be minimized thus helps to reduce the intake losses of the engine [1]. This study is focused on the configuration of the filter in order to obtain the minimal pressure drop along the filter. The configuration used is the basic filter geometry provided by Salutary Avenue Manufacturing Sdn Bhd. and two modified canister filter cap which is designed based on the basic filter model. The geometries of the filter are generated by using SOLIDWORKS software and Computational Fluid Dynamics (CFD) software is used to analyse and simulates the flow through the filter. In this study, the parameters of the inlet velocity are 0.032 m/s, 0.063 m/s, 0.094 m/s and 0.126 m/s. The total pressure drop produce by basic, modified filter 1 and 2 is 292.3 Pa, 251.11 Pa and 274.7 Pa. The pressure drop reduction for the modified filter 1 is 41.19 Pa and 14.1% lower compared to basic filter and the pressure drop reduction for modified filter 2 is 17.6 Pa and 6.02% lower compared to the basic filter. The pressure drops for the basic filter are slightly different with the Salutary Avenue filter due to limited data and experiment details. CFD software are very reliable in running a simulation rather than produces the prototypes and conduct the experiment thus reducing overall time and cost in this study.
FPGA implementation of filtered image using 2D Gaussian filter
Leila kabbai; Anissa Sghaier; Ali Douik; Mohsen Machhout
2016-01-01
Image filtering is one of the very useful techniques in image processing and computer vision. It is used to eliminate useless details and noise from an image. In this paper, a hardware implementation of image filtered using 2D Gaussian Filter will be present. The Gaussian filter architecture will be described using a different way to implement convolution module. Thus, multiplication is in the heart of convolution module, for this reason, three different ways to implement multiplication opera...
Generalized Selection Weighted Vector Filters
Directory of Open Access Journals (Sweden)
Rastislav Lukac
2004-09-01
Full Text Available This paper introduces a class of nonlinear multichannel filters capable of removing impulsive noise in color images. The here-proposed generalized selection weighted vector filter class constitutes a powerful filtering framework for multichannel signal processing. Previously defined multichannel filters such as vector median filter, basic vector directional filter, directional-distance filter, weighted vector median filters, and weighted vector directional filters are treated from a global viewpoint using the proposed framework. Robust order-statistic concepts and increased degree of freedom in filter design make the proposed method attractive for a variety of applications. Introduced multichannel sigmoidal adaptation of the filter parameters and its modifications allow to accommodate the filter parameters to varying signal and noise statistics. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, yields excellent performance, and is able to preserve fine details and color information while efficiently suppressing impulsive noise. This paper is an extended version of the paper by Lukac et al. presented at the 2003 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03 in Grado, Italy.
Visual SLAM Using Variance Grid Maps
Howard, Andrew B.; Marks, Tim K.
2011-01-01
An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance
Median filtering algorithms for multichannel detectors
Hovhannisyan, A.; Chilingarian, A.
2011-05-01
Particle detectors of worldwide networks are continuously measuring various secondary particle fluxes incident on Earth surface. At the Aragats Space Environmental Center (ASEC), the data of 12 cosmic ray particle detectors with a total of ˜280 measuring channels (count rates of electrons, muons and neutrons channels) are sent each minute via wireless bridges to a MySQL database. These time series are used for the different tasks of off-line physical analysis and for online forewarning services. Usually long time series contain several types of errors (gaps due to failures of high or low voltage power supply, spurious spikes due to radio interferences, abrupt changes of mean values of several channels or/and slowly trends in mean values due to aging of electronics components, etc.). To avoid erroneous physical inference and false alarms of alerting systems we introduce offline and online filters to "purify" multiple time-series. In the presented paper we classify possible mistakes in time series and introduce median filtering algorithms for online and off-line "purification" of multiple time-series.
Analog filters in nanometer CMOS
Uhrmann, Heimo; Zimmermann, Horst
2014-01-01
Starting from the basics of analog filters and the poor transistor characteristics in nanometer CMOS 10 high-performance analog filters developed by the authors in 120 nm and 65 nm CMOS are described extensively. Among them are gm-C filters, current-mode filters, and active filters for system-on-chip realization for Bluetooth, WCDMA, UWB, DVB-H, and LTE applications. For the active filters several operational amplifier designs are described. The book, furthermore, contains a review of the newest state of research on low-voltage low-power analog filters. To cover the topic of the book comprehensively, linearization issues and measurement methods for the characterization of advanced analog filters are introduced in addition. Numerous elaborate illustrations promote an easy comprehension. This book will be of value to engineers and researchers in industry as well as scientists and Ph.D students at universities. The book is also recommendable to graduate students specializing on nanoelectronics, microelectronics ...
Sim, Kyoung Mi; Park, Hyun-Seol; Bae, Gwi-Nam; Jung, Jae Hee
2015-11-15
In this study, we demonstrated an antimicrobial nanoparticle-coated electrostatic (ES) air filter. Antimicrobial natural-product Sophora flavescens nanoparticles were produced using an aerosol process, and were continuously deposited onto the surface of air filter media. For the electrostatic activation of the filter medium, a corona discharge electrification system was used before and after antimicrobial treatment of the filter. In the antimicrobial treatment process, the deposition efficiency of S. flavescens nanoparticles on the ES filter was ~12% higher than that on the pristine (Non-ES) filter. In the evaluation of filtration performance using test particles (a nanosized KCl aerosol and submicron-sized Staphylococcus epidermidis bioaerosol), the ES filter showed better filtration efficiency than the Non-ES filter. However, antimicrobial treatment with S. flavescens nanoparticles affected the filtration efficiency of the filter differently depending on the size of the test particles. While the filtration efficiency of the KCl nanoparticles was reduced on the ES filter after the antimicrobial treatment, the filtration efficiency was improved after the recharging process. In summary, we prepared an antimicrobial ES air filter with >99% antimicrobial activity, ~92.5% filtration efficiency (for a 300-nm KCl aerosol), and a ~0.8 mmAq pressure drop (at 13 cm/s). This study provides valuable information for the development of a hybrid air purification system that can serve various functions and be used in an indoor environment. Copyright © 2015 Elsevier B.V. All rights reserved.
Manipulation Robustness of Collaborative Filtering
Benjamin Van Roy; Xiang Yan
2010-01-01
A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions and hence have become targets of manipulation by unscrupulous vendors. We demonstrate that nearest neighbors algorithms, which are widely used in commercial systems, are highly susceptible to manipulation and introduce new collaborative filtering algorithms that are relatively robust.
Hughes, Katie; Cronin, G; Welch, L
2017-01-01
So-called “fake news” is everywhere and is having a major impact on daily life from politics to education. The rapid growth of information and the numbers of people who can create it means that we need more sophisticated tools to process the news we receive. Join us to learn about different methods you can use to be your own fact checker and pop your filter bubble.
Offsetting the Affective Filter
Directory of Open Access Journals (Sweden)
Barry Chametzky, PhD
2017-06-01
Full Text Available When forced to deal with a stressful, unfamiliar situation, how do people react? People are familiar, in a traditional setting, with sensory overload. But in an online environment, when learners are anxious, they exhibit different behaviors to help mediate their anxiety. Additionally, in an online environment, since visual clues are often lacking, how do these behaviors manifest themselves? People navigate stressful and/or unfamiliar situations by offsetting their affective filter.
Chebira, Amina; Fickus, Matthew; Mixon, Dustin G.
2010-01-01
In this paper we characterize and construct novel oversampled filter banks implementing fusion frames. A fusion frame is a sequence of orthogonal projection operators whose sum can be inverted in a numerically stable way. When properly designed, fusion frames can provide redundant encodings of signals which are optimally robust against certain types of noise and erasures. However, up to this point, few implementable constructions of such frames were known; we show how to construct them using ...
In Situ Solid Particle Generator
Agui, Juan H.; Vijayakumar, R.
2013-01-01
Particle seeding is a key diagnostic component of filter testing and flow imaging techniques. Typical particle generators rely on pressurized air or gas sources to propel the particles into the flow field. Other techniques involve liquid droplet atomizers. These conventional techniques have drawbacks that include challenging access to the flow field, flow and pressure disturbances to the investigated flow, and they are prohibitive in high-temperature, non-standard, extreme, and closed-system flow conditions and environments. In this concept, the particles are supplied directly within a flow environment. A particle sample cartridge containing the particles is positioned somewhere inside the flow field. The particles are ejected into the flow by mechanical brush/wiper feeding and sieving that takes place within the cartridge chamber. Some aspects of this concept are based on established material handling techniques, but they have not been used previously in the current configuration, in combination with flow seeding concepts, and in the current operational mode. Unlike other particle generation methods, this concept has control over the particle size range ejected, breaks up agglomerates, and is gravity-independent. This makes this device useful for testing in microgravity environments.
Misty Paig-Tran, E W; Summers, A P
2014-04-01
The four, evolutionarily independent, lineages of suspension feeding elasmobranchs have two types of branchial filters. The first is a robust, flattened filter pad akin to a colander (e.g., whale sharks, mantas and devil rays) while the second more closely resembles the comb-like gill raker structure found in bony fishes (e.g., basking and megamouth sharks). The structure and the presence of mucus on the filter elements will determine the mechanical function of the filter and subsequent particle transport. Using histology and scanning electron microscopy, we investigated the anatomy of the branchial filters in 12 of the 14 species of Chondrichthyian filter-feeding fishes. We hypothesized that mucus producing cells would be abundant along the filter epithelium and perform as a sticky mechanism to retain and transport particles; however, we found that only three species had mucus producing goblet cells. Two of these (Mobula kuhlii and Mobula tarapacana) also had branchial cilia, indicating sticky retention and transport. The remaining filter-feeding elasmobranchs did not have a sticky surface along the filter for particles to collect and instead must employ alternative mechanisms of filtration (e.g., direct sieving, inertial impaction or cross-flow). With the exception of basking sharks, the branchial filter is composed of a hyaline cartilage skeleton surrounded by a layer of highly organized connective tissue that may function as a support. Megamouth sharks and most of the mobulid rays have denticles along the surface of the filter, presumably to protect against damage from large particle impactions. Basking sharks have branchial filters that lack a cartilaginous core; instead they are composed entirely of smooth keratin. Copyright © 2014 Wiley Periodicals, Inc.
DETERMINATION OF KEY PARAMETERS OF A FILTER FAST FROM DRINKING WATER TREATMENT PLANT
Directory of Open Access Journals (Sweden)
RADU Ionuţ Valentin
2012-11-01
Full Text Available This paper presents an algorithm based on quick sand filter. Using the computer and specialized software that can allow quick and easy determination of filtration parameters quickly, allowing them to find optimal values by studying several options. Filtration through a layer of sand is a mechanical process that allows removal of solid particles (small size of water. As the flow rate of water through the filter bed is less filtering process is even better.
Filtering in hybrid dynamic Bayesian networks (left)
DEFF Research Database (Denmark)
Andersen, Morten Nonboe; Andersen, Rasmus Ørum; Wheeler, Kevin
We demonstrate experimentally that inference in a complex hybrid Dynamic Bayesian Network (DBN) is possible using the 2-Time Slice DBN (2T-DBN) from (Koller & Lerner, 2000) to model fault detection in a watertank system. In (Koller & Lerner, 2000) a generic Particle Filter (PF) is used...... that the choice of network structure is very important for the performance of the generic PF and the EKF algorithms, but not for the UKF algorithms. Furthermore, we investigate the influence of data noise in the watertank simulation. Theory and implementation is based on the theory presented in (v.d. Merwe et al...
Filtering in hybrid dynamic Bayesian networks
DEFF Research Database (Denmark)
Andersen, Morten Nonboe; Andersen, Rasmus Ørum; Wheeler, Kevin
2004-01-01
We demonstrate experimentally that inference in a complex hybrid Dynamic Bayesian Network (DBN) is possible using the 2-Time Slice DBN (2T-DBN) from (Koller & Lerner, 2000) to model fault detection in a watertank system. In (Koller & Lerner, 2000) a generic Particle Filter (PF) is used...... that the choice of network structure is very important for the performance of the generic PF and the EKF algorithms, but not for the UKF algorithms. Furthermore, we investigate the influence of data noise in the watertank simulation. Theory and implementation is based on the theory presented in (v.d. Merwe et al...
Filtering in hybrid dynamic Bayesian networks (center)
DEFF Research Database (Denmark)
Andersen, Morten Nonboe; Andersen, Rasmus Ørum; Wheeler, Kevin
We demonstrate experimentally that inference in a complex hybrid Dynamic Bayesian Network (DBN) is possible using the 2-Time Slice DBN (2T-DBN) from (Koller & Lerner, 2000) to model fault detection in a watertank system. In (Koller & Lerner, 2000) a generic Particle Filter (PF) is used...... that the choice of network structure is very important for the performance of the generic PF and the EKF algorithms, but not for the UKF algorithms. Furthermore, we investigate the influence of data noise in the watertank simulation. Theory and implementation is based on the theory presented in (v.d. Merwe et al...
Adaptive filtering for stochastic volatility by using exact sampling
Aihara, ShinIchi; Bagchi, Arunabha; Saha, S.
2013-01-01
We study the sequential identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility is constructed. The systems parameters are sequentially
Carbon flux bias estimation employing Maximum Likelihood Ensemble Filter (MLEF)
Zupanski, Dusanka; Denning, A. Scott; Uliasz, Marek; Zupanski, Milija; Schuh, Andrew E.; Rayner, Peter J.; Peters, Wouter; Corbin, Katherine D.
2007-01-01
We evaluate the capability of an ensemble based data assimilation approach, referred to as Maximum Likelihood Ensemble Filter (MLEF), to estimate biases in the CO2 photosynthesis and respiration fluxes. We employ an off-line Lagrangian Particle Dispersion Model (LPDM), which is driven by the carbon
Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) pilot of the Environmental Technology Verification (ETV) Program. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of th...
High Efficiency Particulate Air (HEPA) filters from polyester and polypropylene fibre nonwovens
CSIR Research Space (South Africa)
Boguslavsky, L
2010-10-01
Full Text Available In this work, High Efficiency Particulate Air (HEPA) Filters are designed to keep small harmful particles from entering a control environment or to prevent them from escaping. Nonwoven fabrics for filtration application were produced from...
Advances in Intelligent Signal Processing and Data Mining Theory and Applications
Mihaylova, Lyudmila; Jain, Lakhmi
2013-01-01
The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.
Wu, Kun-Ta; Feng, Lang; Sha, Ruojie; Dreyfus, Rémi; Grosberg, Alexander Y; Seeman, Nadrian C; Chaikin, Paul M
2012-11-13
DNA is increasingly used as an important tool in programming the self-assembly of micrometer- and nanometer-scale particles. This is largely due to the highly specific thermoreversible interaction of cDNA strands, which, when placed on different particles, have been used to bind precise pairs in aggregates and crystals. However, DNA functionalized particles will only reach their true potential for particle assembly when each particle can address and bind to many different kinds of particles. Indeed, specifying all bonds can force a particular designed structure. In this paper, we present the design rules for multiflavored particles and show that a single particle, DNA functionalized with many different "flavors," can recognize and bind specifically to many different partners. We investigate the cost of increasing the number of flavors in terms of the reduction in binding energy and melting temperature. We find that a single 2-μm colloidal particle can bind to 40 different types of particles in an easily accessible time and temperature regime. The practical limit of ∼100 is set by entropic costs for particles to align complementary pairs and, surprisingly, by the limited number of distinct "useful" DNA sequences that prohibit subunits with nonspecific binding. For our 11 base "sticky ends," the limit is 73 distinct sequences with no unwanted overlaps of 5 bp or more. As an example of phenomena enabled by polygamous particles, we demonstrate a three-particle system that forms a fluid of isolated clusters when cooled slowly and an elastic gel network when quenched.
Amanda L. Fox; Dean E. Eisenhauer; Michael G. Dosskey
2005-01-01
Vegetated filters (buffers) are used to intercept overland runoff and reduce sediment and other contaminant loads to streams (Dosskey, 2001). Filters function by reducing runoff velocity and volume, thus enhancing sedimentation and infiltration. lnfiltration is the main mechanism for soluble contaminant removal, but it also plays a role in suspended particle removal....
Air-sampled Filter Analysis for Endotoxins and DNA Content.
Lang-Yona, Naama; Mazar, Yinon; Pardo, Michal; Rudich, Yinon
2016-03-07
Outdoor aerosol research commonly uses particulate matter sampled on filters. This procedure enables various characterizations of the collected particles to be performed in parallel. The purpose of the method presented here is to obtain a highly accurate and reliable analysis of the endotoxin and DNA content of bio-aerosols extracted from filters. The extraction of high molecular weight organic molecules, such as lipopolysaccharides, from sampled filters involves shaking the sample in a pyrogen-free water-based medium. The subsequent analysis is based on an enzymatic reaction that can be detected using a turbidimetric measurement. As a result of the high organic content on the sampled filters, the extraction of DNA from the samples is performed using a commercial DNA extraction kit that was originally designed for soils and modified to improve the DNA yield. The detection and quantification of specific microbial species using quantitative polymerase chain reaction (q-PCR) analysis are described and compared with other available methods.
Monolithic integrated filters - An overview
Entenmann, W.
1981-04-01
An overview of the state of the art in monolithic integrated filter design is given. The close mutual influence of technology and network theory and the continuing development of filter designs with higher integration, higher reliability, lower costs and lower space demands are examined. The fundamental concepts of circuit theory and MOS technology are described and the principal construction of the components of the three major classes of MOS filter circuits examined, namely the change-transfer filter, the switched-capacitor filter and the digital filter. The most important properties, such as the periodicity of the spectra, the impulse response, as well as recursive, nonrecursive, linear and minimal phase filters are covered. Some methods for calculating filter circuits by using classical reactance filter synthesis with the aid of suitable transformations from analog time-continuous reference circuits are discussed. The obtainable signal frequency ranges and filter grades are shown in order to compare the efficiency and operating range of monolithic integrated filter circuits with each other and with other concepts.
Wiener filter for filtered back projection in digital breast tomosynthesis
Wang, Xinying; Mainprize, James G.; Wu, Gang; Yaffe, Martin J.
2012-03-01
Conventional filtered back projection (FBP) reconstruction for digital breast tomosynthesis (DBT) can suffer from a low signal to noise ratio. Because of the strong amplification by the reconstruction filters (ramp, apodization and slice thickness), noise at high spatial frequencies can be greatly increased. Image enhancement by Wiener filtering is investigated as a possible method to improve image quality. A neighborhood wavelet coefficient window technique is used to estimate the noise content of projection images and a Wiener filter is applied to the projection images. The neighborhood wavelet coefficient window is a non-linear technique, which may cause the Wiener filters estimated before and after the application of the reconstruction filters to be different. Image quality of a FBP reconstruction with and without Wiener filtering is investigated using a Fourier-based observer detectability metric ( d' ) for evaluation. Simulations of tomosynthesis are performed in both homogeneous and anatomic textured backgrounds containing lowcontrast masses or small microcalcifications. Initial results suggest that improvements in detectability can be achieved when the Wiener filter is applied, especially when the Wiener filter is estimated for the reconstruction filtered projections.
CERN. Geneva
2007-01-01
The understanding of the Universe at the largest and smallest scales traditionally has been the subject of cosmology and particle physics, respectively. Studying the evolution of the Universe connects today's large scales with the tiny scales in the very early Universe and provides the link between the physics of particles and of the cosmos. This series of five lectures aims at a modern and critical presentation of the basic ideas, methods, models and observations in today's particle cosmology.
Multi-Target Detection from Full-Waveform Airborne Laser Scanner Using Phd Filter
Fuse, T.; Hiramatsu, D.; Nakanishi, W.
2016-06-01
We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD) filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions simultaneously. PHD filter overcomes some limitations of conventional Gaussian decomposition method; PHD filter doesn't require a priori knowledge on the number of targets, assumption of parametric form of the intensity distribution. In addition, it can take a similarity between successive irradiations into account by modelling relative positions of the same targets spatially. Firstly we explain PHD filter and particle filter implementation to it. Secondly we formulate the multi-target detection problem on PHD filter by modelling components and parameters within it. At last we conducted the experiment on real data of forest and vegetation, and confirmed its ability and accuracy.
MULTI-TARGET DETECTION FROM FULL-WAVEFORM AIRBORNE LASER SCANNER USING PHD FILTER
Directory of Open Access Journals (Sweden)
T. Fuse
2016-06-01
Full Text Available We propose a new technique to detect multiple targets from full-waveform airborne laser scanner. We introduce probability hypothesis density (PHD filter, a type of Bayesian filtering, by which we can estimate the number of targets and their positions simultaneously. PHD filter overcomes some limitations of conventional Gaussian decomposition method; PHD filter doesn’t require a priori knowledge on the number of targets, assumption of parametric form of the intensity distribution. In addition, it can take a similarity between successive irradiations into account by modelling relative positions of the same targets spatially. Firstly we explain PHD filter and particle filter implementation to it. Secondly we formulate the multi-target detection problem on PHD filter by modelling components and parameters within it. At last we conducted the experiment on real data of forest and vegetation, and confirmed its ability and accuracy.
Martin, B R
2008-01-01
An essential introduction to particle physics, with coverage ranging from the basics through to the very latest developments, in an accessible and carefully structured text. Particle Physics: Third Edition is a revision of a highly regarded introduction to particle physics. In its two previous editions this book has proved to be an accessible and balanced introduction to modern particle physics, suitable for those students needed a more comprehensive introduction to the subject than provided by the 'compendium' style physics books. In the Third Edition the standard mod
Energy Technology Data Exchange (ETDEWEB)
Pang, C S; Falco, C M; Kampwirth, R T; Schuller, I K; Hudak, J J; Anastasio, T A
1979-01-01
Results of a preliminary investigation of a superconducting notch filter for possible application in the 2 to 30 MHz high frequency (HF) communication band are presented. The circuit was successfully implemented using planar geometry so that closed cycle refrigeration could be used to cool circuits fabricated from high T/sub c/ Nb/sub 3/Sn or Nb/sub 3/Ge thin films. In the present design, circuit Q's of about 2 x 10/sup 3/ were obtained with 50-ohm source and output impedance. (TFD)
Spindoktorer et politisk filter
Talic, Elvedin; Bernt, Rune; Mortensen, Mass Holmegård
2015-01-01
Through the TV and other media, many rumors about what a spin-doctor does and the nature of his services have spread. We would like to clarify the function; role and influence the spin-doctor have on Danish politics. We will look specifically at the relationship of power between the Ministers and spin-doctors, and the spin-doctors and media, as some believe that the spin-doctor sometimes will rise to power. We will also take look at the filter function between spin-doctors and media, as it is...
Advances in Collaborative Filtering
Koren, Yehuda; Bell, Robert
The collaborative filtering (CF) approach to recommenders has recently enjoyed much interest and progress. The fact that it played a central role within the recently completed Netflix competition has contributed to its popularity. This chapter surveys the recent progress in the field. Matrix factorization techniques, which became a first choice for implementing CF, are described together with recent innovations. We also describe several extensions that bring competitive accuracy into neighborhood methods, which used to dominate the field. The chapter demonstrates how to utilize temporal models and implicit feedback to extend models accuracy. In passing, we include detailed descriptions of some the central methods developed for tackling the challenge of the Netflix Prize competition.
Multilevel ensemble Kalman filtering
Hoel, Hakon
2016-06-14
This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Energy Technology Data Exchange (ETDEWEB)
Lyons, J. [Nuclear Regulatory Commission, Washington, DC (United States)
1997-08-01
In this very brief, informal presentation, a representative of the US Nuclear Regulatory Commission outlines some problems with charcoal filter testing procedures and actions being taken to correct the problems. Two primary concerns are addressed: (1) the process to find the test method is confusing, and (2) the requirements of the reference test procedures result in condensation on the charcoal and causes the test to fail. To address these problems, emergency technical specifications were processed for three nuclear plants. A generic or an administrative letter is proposed as a more permanent solution. 1 fig.
Soederberg, Per G.; Michael, Ralph; Ayala, Marcelo; Wu, Jiangmei; Loefgren, Stefan; Merriam, John; Chen, Enping
1999-06-01
It is concluded that sunglasses shall block UVR and toxic blue light, allow transmittance of signal light and bring luminous intensity behind the filters to a comfortable level. It was found that some commercially available sunglasses, apart from one pair of photochromatic dark state lenses tested, block ultraviolet radiation (UVR) adequately. Further, it was found that it is possible to block the toxic blue radiation without interfering substantially on blue signal light perception. However, none of the sunglasses tested blocked the toxic blue light enough.
Biofouling reduction for improvement of depth water filtration. Filter production and testing
Directory of Open Access Journals (Sweden)
Sztuk - Sikorska Ewa
2016-09-01
Full Text Available Water is a strategic material. Recycling is an important component of balancing its use. Deep-bed filtration is an inexpensive purification method and seems to be very effective in spreading water recovery. Good filter designs, such as the fibrous filter, have high separation efficiency, low resistance for the up-flowing fluid and high retention capacity. However, one of the substantial problems of this process is the biofouling of the filter. Biofouling causes clogging and greatly reduces the life of the filter. Therefore, the melt-blown technique was used for the formation of novel antibacterial fibrous filters. Such filters are made of polypropylene composites with zinc oxide and silver nanoparticles on the fiber surface. These components act as inhibitors of bacterial growth in the filter and were tested in laboratory and full scale experiments. Antibacterial/bacteriostatic tests were performed on Petri dishes with E. coli and B. subtilis. Full scale experiments were performed on natural river water, which contained abiotic particles and mutualistic bacteria. The filter performance at industrial scale conditions was measured using a particle counter, a flow cytometer and a confocal microscope. The results of the experiments indicate a significant improvement of the composite filter performance compared to the regular fibrous filter. The differences were mostly due to a reduction in the biofouling effect.
Digital Filters for Low Frequency Equalization
DEFF Research Database (Denmark)
Tyril, Marni; Abildgaard, J.; Rubak, Per
2001-01-01
Digital filters with high resolution in the low-frequency range are studied. Specifically, for a given computational power, traditional IIR filters are compared with warped FIR filters, warped IIR filters, and modified warped FIR filters termed warped individual z FIR filters (WizFIR). The results...
Selective particle capture by asynchronously beating cilia
Ding, Yang; Kanso, Eva
2015-12-01
Selective particle filtration is fundamental in many engineering and biological systems. For example, many aquatic microorganisms use filter feeding to capture food particles from the surrounding fluid, using motile cilia. One of the capture strategies is to use the same cilia to generate feeding currents and to intercept particles when the particles are on the downstream side of the cilia. Here, we develop a 3D computational model of ciliary bands interacting with flow suspended particles and calculate particle trajectories for a range of particle sizes. Consistent with experimental observations, we find optimal particle sizes that maximize capture rate. The optimal size depends nonlinearly on cilia spacing and cilia coordination, synchronous vs. asynchronous. These parameters affect the cilia-generated flow field, which in turn affects particle trajectories. The low capture rate of smaller particles is due to the particles' inability to cross the flow streamlines of neighboring cilia. Meanwhile, large particles have difficulty entering the sub-ciliary region once advected downstream, also resulting in low capture rates. The optimal range of particle sizes is enhanced when cilia beat asynchronously. These findings have potentially important implications on the design and use of biomimetic cilia in processes such as particle sorting in microfluidic devices.
Horak, F
1995-01-01
The faeces of the dust mite are the most significant source of allergy for those allergic to the dust mite. During vacuum cleaning, faecal particles are emitted from the cleaner and into the air to form pathological concentrations. The aim of the study was to discover if these extreme concentrations could be prevented by the use of appropriate filters. As the allergen source, dust mite faeces were used. A Miele vacuum cleaner type S424i was used without filter, with S-Class filter, and with Super Air Clean Filter. In the first test 1 g, and in the second test 2 g of dust mite faecal particles were evenly spread and then vacumed up. While using each filter in turn, the expelled air was measured for faecal concentrations. The analysis was performed by counting the number of faecal particles, and determining the content of major allergen Der p I in the expelled air. Without a filter there was a massive concentration of faecal particles in the expelled air. The simple filter Type (S-class-filter) achieved a significant reduction on the emission of allergens. The more complex special filter (Super air clean filter), was able to remove all traces of allergens from the expelled air.
High flow ceramic pot filters.
van Halem, D; van der Laan, H; Soppe, A I A; Heijman, S G J
2017-11-01
Ceramic pot filters are considered safe, robust and appropriate technologies, but there is a general consensus that water revenues are limited due to clogging of the ceramic element. The objective of this study was to investigate the potential of high flow ceramic pot filters to produce more water without sacrificing their microbial removal efficacy. High flow pot filters, produced by increasing the rice husk content, had a higher initial flow rate (6-19 L h-1), but initial LRVs for E. coli of high flow filters was slightly lower than for regular ceramic pot filters. This disadvantage was, however, only temporarily as the clogging in high flow filters had a positive effect on the LRV for E. coli (from below 1 to 2-3 after clogging). Therefore, it can be carefully concluded that regular ceramic pot filters perform better initially, but after clogging, the high flow filters have a higher flow rate as well as a higher LRV for E. coli. To improve the initial performance of new high flow filters, it is recommended to further utilize residence time of the water in the receptacle, since additional E. coli inactivation was observed during overnight storage. Although a relationship was observed between flow rate and LRV of MS2 bacteriophages, both regular and high flow filters were unable to reach over 2 LRV. Copyright © 2017 Elsevier Ltd. All rights reserved.
From Microwave Filter to Digital Filter and Back Again
DEFF Research Database (Denmark)
Dalby, Arne Brejning
1989-01-01
A new very simple state variable flow graph representation for interdigital transmission line bandpass filters is presented, which has led to two important results: 1) A new type of digital filter with properties, that surpass the properties of most other (all pole) digital filtertypes. 2......) The study of the new digital filtertype has led to design formulas for interdigital transmission line filters that are very simple compared to the hitherto known formulas. The accuracy is the same or better....
DSP Control of Line Hybrid Active Filter
DEFF Research Database (Denmark)
Dan, Stan George; Benjamin, Doniga Daniel; Magureanu, R.
2005-01-01
Active Power Filters have been intensively explored in the past decade. Hybrid active filters inherit the efficiency of passive filters and the improved performance of active filters, and thus constitute a viable improved approach for harmonic compensation. In this paper a parallel hybrid filter ...... active filter. Simulation and experimental results obtained in laboratory confirmed the validity and effectiveness of the control.......Active Power Filters have been intensively explored in the past decade. Hybrid active filters inherit the efficiency of passive filters and the improved performance of active filters, and thus constitute a viable improved approach for harmonic compensation. In this paper a parallel hybrid filter...... is studied for current harmonic compensation. The hybrid filter is formed by a single tuned Le filter and a small-rated power active filter, which are directly connected in series without any matching transformer. Thus the required rating of the active filter is much smaller than a conventional standalone...
Carlsmith, Duncan
2012-01-01
Particle Physics is the first book to connect theory and experiment in particle physics. Duncan Carlsmith provides the first accessible exposition of the standard model with sufficient mathematical depth to demystify the language of gauge theory and Feynman diagrams used by researchers in the field. Carlsmith also connects theories to past, present, and future experiments.
Particle filtering in the Hough space for instrument tracking.
Climent, Joan; Hexsel, Roberto A
2012-05-01
In this paper we present a real-time tracking system of surgical instruments in laparoscopic operations. We combine Condensation tracking, with the Hough Transform in order to obtain an efficient and accurate tracking. The Condensation algorithm performs well in heavy clutter, and the Hough Transform is robust under illumination changes, occlusion and distractions. The Hough array is computed using the gradient direction image obtained by means of a Principal Component Analysis. This improves accuracy in the determination of edge orientation and speeds up computation of the Hough Transform. The experiments on image sequences of actual laparoscopic surgical operations show that the instrument tip is located even in the presence of smoke, occlusions or motion blurring. Copyright © 2012 Elsevier Ltd. All rights reserved.