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1

Particle Swarm Optimization with Quantum Infusion for the design of digital filters  

Microsoft Academic Search

In this paper, particle swarm optimization with quantum infusion (PSO-QI) has been applied for the design of digital filters. In PSO-QI, Global best (gbest) particle (in PSO star topology) obtained from particle swarm optimization is enhanced by doing a tournament with an offspring produced by quantum behaved PSO, and selecting the winner as the new gbest. Filters are designed based

Bipul Luitel; Ganesh Kumar Venayagamoorthy

2008-01-01

2

An input-balanced realization based adaptive IIR filter using particle swarm optimization  

Microsoft Academic Search

In this paper, based on input-balanced realizations (IBR) and the particle swarm optimization (PSO) technique a novel adaptive IIR filter is proposed. This filter is derived from the input-balanced realization (IBR) that yields an excellent per- formance against finite precision errors. With such a realization, the stability of the adaptive filter can be ensured easily. As well known, the traditional

Yue Wang; Gang Li; Liping Chang

2011-01-01

3

Particle Swarm Optimization Aided Kalman Filter for Object Tracking  

Microsoft Academic Search

Object tracking aims to detect the path of objects moving randomly by obtaining input from a series of images. Automatic detection and tracking of object is an interesting area of research for defence related applications like missile tracking, security systems and commercial fields like virtual reality interfaces, robot vision etc., Kalman filter tracks the object by assuming the initial state

Nimmakayala Ramakoti; Ari Vinay; Ravi Kumar Jatoth

2009-01-01

4

Designing Linear Phase FIR Filters with Particle Swarm Optimization and Harmony Search  

NASA Astrophysics Data System (ADS)

In recent years, evolutionary methods have shown great success in solving many combinatorial optimization problems such as FIR (Finite Impulse Response) filter design. An ordinary method in FIR filter design problem is Parks-McClellan, which is both difficult to implement and computationally expensive. The goal of this paper is to design a near optimal linear phase FIR filter using two recent evolutionary approaches; Particle Swarm Optimization (PSO) and Harmony Search (HS). These methods are robust, easy to implement, and they would not trap in local optima due to their stochastic behavior. In addition, they have distinguishing features such as less variance error and smaller overshoots in both stop and pass bands. To prove these benefits, two case studies are presented and obtained results are compared with previous implementations. In both cases, better and reliable results are achieved.

Shirvani, Abdolreza; Khezri, Kaveh; Razzazi, Farbod; Lucas, Caro

5

Design of reflective color filters with high angular tolerance by particle swarm optimization method.  

PubMed

We propose three color filters (red, green, blue) based on a two-dimensional (2D) grating, which maintain the same perceived specular colors for a broad range of incident angles with the average polarization. Particle swarm optimization (PSO) method is employed to design these filters for the first time to our knowledge. Two merit functions involving the reflectance curves and color difference in CIEDE2000 formula are respectively constructed to adjust the structural parameters during the optimization procedure. Three primary color filters located at 637nm, 530nm and 446nm with high saturation are obtained with the peak reflectance of 89%, 83%, 66%. The reflectance curves at different incident angles are coincident and the color difference is less than 8 for the incident angle up to 45°. The electric field distribution of the structure is finally studied to analyze the optical property. PMID:23609642

Yang, Chenying; Hong, Liang; Shen, Weidong; Zhang, Yueguang; Liu, Xu; Zhen, Hongyu

2013-04-22

6

Gaussian particle filtering  

Microsoft Academic Search

Sequential Bayesian estimation for dynamic state space models involves recursive estimation of hidden states based on noisy observations. The update of filtering and predictive densities for nonlinear models with non-Gaussian noise using Monte Carlo particle filtering methods is considered. The Gaussian particle filter (GPF) is introduced, where densities are approximated as a single Gaussian, an assumption which is also made

Jayesh H. Kotecha; Petar M. Djuric

2001-01-01

7

Limited memory optimal filtering  

Microsoft Academic Search

Linear and nonlinear optimal filters with limited memory length are developed. The filter output is the conditional probability density function and, in the linear Gaussian case, is the conditional mean and covariance matrix where the conditioning is only on a fixed amount of most recent data. This is related to maximum-likelihood least-squares estimation. These filters have application in problems where

A. Jazwinski

1968-01-01

8

Using of Intelligent Particle Swarm Optimization Algorithm to Synthesis the Index Modulation Profile of Narrow Ban Fiber Bragg Grating Filter  

Microsoft Academic Search

A new method for synthesis of fiber Bragg gratings based filter is proposed. By combining the transmission matrix method and\\u000a the particles swarm optimization algorithm, we obtain a novel method for the inverse problem of the synthesizing fiber gratings.\\u000a With adjusting the parameters of the PSO algorithm we can get the demand index modulation for the target reflection spectrums\\u000a including

Yumin Liu; Zhongyuan Yu

2006-01-01

9

Optimal nonlinear filtering in GPS\\/INS integration  

Microsoft Academic Search

The application of optimal nonlinear\\/non-Gaussian filtering to the problem of INS\\/GPS integration in critical situations is described. This approach is made possible by a new technique called particle filtering, and exhibits superior performance when compared with classical suboptimal techniques such as extended Kalman filtering. Particle filtering theory is introduced and GPS\\/INS integration simulation results are discussed.

H. Carvalho; P. Del Moral; A. Monin; G. Salut

1997-01-01

10

Optimal Phase-Only Filters.  

National Technical Information Service (NTIS)

This report summarizes the results obtained during the contract No. F 19628-88-K-0018 entitled 'Optimal Phase-only Filters'. This research was focused on Phase-only Filters (POFs) and Binary Phase-only Filters (BPOFs). We prove in this report that the con...

B. V. Kumar Z. Bahri

1990-01-01

11

Optimal filtering for patterned displays  

Microsoft Academic Search

Displays with repeating patterns of colored subpixels gain spatial resolution by setting individual subpixels rather than by setting entire pixels. This paper describes optimal filtering that produces subpixel values from a high-resolution input image. The optimal filtering is based on an error metric inspired by psychophysical experiments. Minimizing the error metric yields a linear system of equations, which can be

John C. Platt

2000-01-01

12

Synthetic approach to optimal filtering  

Microsoft Academic Search

As opposed to the analytic approach used in the modern theory of optimal filtering, a synthetic approach is presented. The signal\\/sensor data, which are generated by either computer simulation or actual experiments, are synthesized into a filter by training a recurrent multilayer perceptron (RMLP) with at least one hidden layer of fully or partially interconnected neurons and with or without

James Ting-Ho Lo

1994-01-01

13

Quasi-Gaussian Particle Filtering  

Microsoft Academic Search

\\u000a The recently-raised Gaussian particle filtering (GPF) introduced the idea of Bayesian sampling into Gaussian filters. This\\u000a note proposes to generalize the GPF by further relaxing the Gaussian restriction on the prior probability. Allowing the non-Gaussianity\\u000a of the prior probability, the generalized GPF is provably superior to the original one. Numerical results show that better\\u000a performance is obtained with considerably reduced

Yuanxin Wu; Dewen Hu; Meiping Wu; Xiaoping Hu

2006-01-01

14

Design of Optimal Digital Filters  

NASA Astrophysics Data System (ADS)

Four methods for designing digital filters optimal in the Chebyshev sense are developed. The properties of these filters are investigated and compared. An analytic method for designing narrow-band FIR filters using Zolotarev polynomials, which are extensions of Chebyshev polynomials, is proposed. Bandpass and bandstop narrow-band filters as well as lowpass and highpass filters can be designed by this method. The design procedure, related formulae and examples are presented. An improved method of designing optimal minimum phase FIR filters by directly finding zeros is proposed. The zeros off the unit circle are found by an efficient special purpose root-finding algorithm without deflation. The proposed algorithm utilizes the passband minimum ripple frequencies to establish the initial points, and employs a modified Newton's iteration to find the accurate initial points for a standard Newton's iteration. The proposed algorithm can be used to design very long filters (L = 325) with very high stopband attenuations. The design of FIR digital filters in the complex domain is investigated. The complex approximation problem is converted into a near equivalent real approximation problem. A standard linear programming algorithm is used to solve the real approximation problem. Additional constraints are introduced which allow weighting of the phase and/or group delay of the approximation. Digital filters are designed which have nearly constant group delay in the passbands. The desired constant group delay which gives the minimum Chebyshev error is found to be smaller than that of a linear phase filter of the same length. These filters, in addition to having a smaller, approximately constant group delay, have better magnitude characteristics than exactly linear phase filters with the same length. The filters have nearly equiripple magnitude and group delay. The problem of IIR digital filter design in the complex domain is formulated such that the existence of best approximation is guaranteed. An efficient and numerically stable algorithm for the design is proposed. The methods to establish a good initial point are investigated. Digital filters are designed which have nearly constant group delay in the passbands. The magnitudes of the filter poles near the passband edge are larger than of those far from the passband edge. A delay overshooting may occur in the transition band (don't care region), and it can be reduced by decreasing the maximum allowed pole magnitude of the design problem at the expense of increasing the approximation error.

Chen, Xiangkun

15

Fault detection via optimally robust detection filters  

Microsoft Academic Search

An approach is presented for using optimally robust detection filters to generate analytic redundancy. By introducing an appropriate criterion the design of the filter is formulated as an optimization problem. Its solution shows that the optimally robust detection filter consists of a bandpass filter and a linear system which is obtained by solving a general eigenvalue problem. The algorithm for

X. Ding; P. M. Frank

1989-01-01

16

Particle flow for nonlinear filters with log-homotopy  

NASA Astrophysics Data System (ADS)

We describe a new nonlinear filter that is vastly superior to the classic particle filter. In particular, the computational complexity of the new filter is many orders of magnitude less than the classic particle filter with optimal estimation accuracy for problems with dimension greater than 2 or 3. We consider nonlinear estimation problems with dimensions varying from 1 to 20 that are smooth and fully coupled (i.e. dense not sparse). The new filter implements Bayes' rule using particle flow rather than with a pointwise multiplication of two functions; this avoids one of the fundamental and well known problems in particle filters, namely "particle collapse" as a result of Bayes' rule. We use a log-homotopy to derive the ODE that describes particle flow. This paper was written for normal engineers, who do not have homotopy for breakfast.

Daum, Fred; Huang, Jim

2008-05-01

17

State estimation in large-scale open channel networks using sequential Monte Carlo methods: Optimal sampling importance resampling and implicit particle filters  

NASA Astrophysics Data System (ADS)

This article investigates the performance of Monte Carlo-based estimation methods for estimation of flow state in large-scale open channel networks. After constructing a state space model of the flow based on the Saint-Venant equations, we implement the optimal sampling importance resampling filter to perform state estimation in a case in which measurements are available at every time step. Considering a case in which measurements become available intermittently, a random-map implementation of the implicit particle filter is applied to estimate the state trajectory in the interval between the measurements. Finally, some heuristics are proposed, which are shown to improve the estimation results and lower the computational cost. In the first heuristics, considering the case in which measurements are available at every time step, we apply the implicit particle filter over time intervals of a desired size while incorporating all the available measurements over the corresponding time interval. As a second heuristic method, we introduce a maximum a posteriori (MAP) method, which does not require sampling. It will be seen, through implementation, that the MAP method provides more accurate results in the case of our application while having a smaller computational cost. All estimation methods are tested on a network of 19 tidally forced subchannels and 1 reservoir, Clifton Court Forebay, in Sacramento-San Joaquin Delta in California, and numerical results are presented.

Rafiee, Mohammad; Barrau, Axel; Bayen, Alexandre M.

2013-06-01

18

Design and optimization of nanostructured optical filters  

NASA Astrophysics Data System (ADS)

Optical filters encompass a vast array of devices and structures for a wide variety of applications. Generally speaking, an optical filter is some structure that applies a designed amplitude and phase transform to an incident signal. Different classes of filters have vastly divergent characteristics, and one of the challenges in the optical design process is identifying the ideal filter for a given application and optimizing it to obtain a specific response. In particular, it is highly advantageous to obtain a filter that can be seamlessly integrated into an overall device package without requiring exotic fabrication steps, extremely sensitive alignments, or complicated conversions between optical and electrical signals. This dissertation explores three classes of nano-scale optical filters in an effort to obtain different types of dispersive response functions. First, dispersive waveguides are designed using a sub-wavelength periodic structure to transmit a single TE propagating mode with very high second order dispersion. Next, an innovative approach for decoupling waveguide trajectories from Bragg gratings is outlined and used to obtain a uniform second-order dispersion response while minimizing fabrication limitations. Finally, high Q-factor microcavities are coupled into axisymmetric pillar structures that offer extremely high group delay over very narrow transmission bandwidths. While these three novel filters are quite diverse in their operation and target applications, they offer extremely compact structures given the magnitude of the dispersion or group delay they introduce to an incident signal. They are also designed and structured as to be formed on an optical wafer scale using standard integrated circuit fabrication techniques. A number of frequency-domain numerical simulation methods are developed to fully characterize and model each of the different filters. The complete filter response, which includes the dispersion and delay characteristics and optical coupling, is used to evaluate each filter design concept. However, due to the complex nature of the structure geometries and electromagnetic interactions, an iterative optimization approach is required to improve the structure designs and obtain a suitable response. To this end, a Particle Swarm Optimization algorithm is developed and applied to the simulated filter responses to generate optimal filter designs.

Brown, Jeremiah Daniel

19

A Hybrid Computer Optimal Filter.  

National Technical Information Service (NTIS)

In 1971 a hybrid computer algorithm for implementation of an optimal nonlinear one-step predictor by applying Bayes' Rule to sequentially update the conditional probability density function from the latest data was presented in a paper. Such a filter has ...

L. Basanez P. Brunet R. S. Bucy R. Huber D. S. Miller

1975-01-01

20

Approximations to optimal nonlinear filters  

Microsoft Academic Search

Let the signal and noise processes be given as solutions to nonlinear stochastic differential equations. The optimal filter for the problem, derived elsewhere, is usually infinite dimensional. Several methods of obtaining possibly useful finite dimensional approximations are considered here, and some of the special problems of simulation are discussed. The numerical results indicate a number of useful features of the

H. Kushner

1967-01-01

21

Ascent Particle Filter Molecular Conductance Study.  

National Technical Information Service (NTIS)

Ascent particle filters on enclosures containing space hardware, such as electronics boxes, regulate venting of these enclosures during launch and ascent. While allowing venting to occur, these filters prevent the transport of particles into and out of th...

K. A. Folgner K. R. Olson R. M. Villahermosa

2009-01-01

22

Particle Swarm Optimization.  

National Technical Information Service (NTIS)

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The pa...

G. Venter

2002-01-01

23

Optimal unbiased filtering via linear matrix inequalities  

Microsoft Academic Search

Solutions to the optimal H? and L2?L? unbiased reduced-order filtering problems are obtained in terms of linear matrix inequalities (LMIs). The order of the optimal filter is equal to the number of measurements. Both continuous- and discrete-time results are presented. An explicit parametrization of all optimal unbiased filters is provided in terms of a free contractive matrix.

Karolos M. Grigoriadis

1998-01-01

24

Real-time hand tracking using a mean shift embedded particle filter  

Microsoft Academic Search

Particle filtering and mean shift (MS) are two successful approaches to visual tracking. Both have their respective strengths and weaknesses. In this paper, we propose to integrate advantages of the two approaches for improved tracking. By incorporating the MS optimization into particle filtering to move particles to local peaks in the likelihood, the proposed mean shift embedded particle filter (MSEPF)

Caifeng Shan; Tieniu Tan; Yucheng Wei

2007-01-01

25

Particle filter tracking for long range radars  

NASA Astrophysics Data System (ADS)

In this paper we present an approach for tracking in long range radar scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems, and that particle filters may suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and the divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter and the Gaussian Mixture Sigma-Point Particle Filter are shown to avoid this diversity problem while producing consistent results.

Romeo, Kevin; Willett, Peter; Bar-Shalom, Yaakov

2012-05-01

26

Westinghouse Advanced Particle Filter System  

SciTech Connect

Integrated Gasification Combined Cycles (IGCC) and Pressurized Fluidized Bed Combustion (PFBC) are being developed and demonstrated for commercial, power generation application. Hot gas particulate filters are key components for the successful implementation of IGCC and PFBC in power generation gas turbine cycles. The objective of this work is to develop and qualify through analysis and testing a practical hot gas ceramic barrier filter system that meets the performance and operational requirements of PFBC and IGCC systems. This paper reports on the development and status of testing of the Westinghouse Advanced Hot Gas Particle Filter (W-APF) including: W-APF integrated operation with the American Electric Power, 70 MW PFBC clean coal facility--approximately 6000 test hours completed; approximately 2500 hours of testing at the Hans Ahlstrom 10 MW PCFB facility located in Karhula, Finland; over 700 hours of operation at the Foster Wheeler 2 MW 2nd generation PFBC facility located in Livingston, New Jersey; status of Westinghouse HGF supply for the DOE Southern Company Services Power System Development Facility (PSDF) located in Wilsonville, Alabama; the status of the Westinghouse development and testing of HGF`s for Biomass Power Generation; and the status of the design and supply of the HGF unit for the 95 MW Pinon Pine IGCC Clean Coal Demonstration.

Lippert, T.E.; Bruck, G.J.; Sanjana, Z.N.; Newby, R.A.; Bachovchin, D.M. [Westinghouse Electric Corp., Pittsburgh, PA (United States). Science and Technology Center

1996-12-31

27

Heterogeneous particle swarm optimizers  

Microsoft Academic Search

Particle swarm optimization (PSO) is a swarm intelligence technique originally inspired by models of flocking and of social influence that assumed homogeneous individuals. During its evolution to become a practical optimization tool, some heterogeneous variants have been proposed. However, heterogeneity in PSO algorithms has never been explicitly studied and some of its potential effects have therefore been overlooked. In this

Marco Antonio Montes de Oca; Jorge Peńa; Thomas Stützle; Carlo Pinciroli; Marco Dorigo

2009-01-01

28

Direct electromagnetic optimization of microwave filters  

Microsoft Academic Search

This article explores an optimization procedure for microwave filters and multiplexers. The procedure is initialized by a classical filter synthesis based on a segmented electromagnetic synthesis that provides the basic dimensions of the structure. The optimization loop, which combines a global electromagnetic analysis and a coupling identification, improves the structure response compared to an empirical optimization

S. Bila; D. Baillargeat; M. Aubourg; S. Verdeyme; P. Guillon; F. Seyfert; J. Grimm; L. Baratchart; C. Zanchi; J. Sombrin

2001-01-01

29

Particle swarm optimization  

Microsoft Academic Search

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. As researchers have learned about\\u000a the technique, they have derived new versions, developed new applications, and published theoretical studies of the effects\\u000a of the various parameters and aspects of the algorithm. This paper comprises a snapshot of particle swarming from the authors’\\u000a perspective, including variations in the

Riccardo Poli; James Kennedy; Tim Blackwell

2007-01-01

30

Particle filter tracking for the banana problem  

NASA Astrophysics Data System (ADS)

In this paper we present an approach for tracking with a high-bandwidth active sensor in very long range scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems; and most flavors of particle filter suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and the divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter is shown to avoid this diversity problem while producing consistent results. The regularization is accomplished using a modified version of the Epanechnikov kernel.

Romeo, Kevin; Willett, Peter; Bar-Shalom, Yaakov

2013-09-01

31

Gaussian particle filtering for tracking maneuvering targets  

Microsoft Academic Search

Tracking for maneuvering targets in the presence of clutter is a challenging problem. In this paper, we present an algorithm for reliable tracking of maneuvering targets based on Gaussian particle filtering (GPF) techniques. It has been shown that sequential Monte Carlo (SMC) methods outperform the various Kalman filter based algorithms for nonlinear tracking models. The SMC, also known as particle

Tadesse Ghirmai

2007-01-01

32

Angle only tracking with particle flow filters  

NASA Astrophysics Data System (ADS)

We show the results of numerical experiments for tracking ballistic missiles using only angle measurements. We compare the performance of an extended Kalman filter with a new nonlinear filter using particle flow to compute Bayes' rule. For certain difficult geometries, the particle flow filter is an order of magnitude more accurate than the EKF. Angle only tracking is of interest in several different sensors; for example, passive optics and radars in which range and Doppler data are spoiled by jamming.

Daum, Fred; Huang, Jim

2011-09-01

33

Optimal weighted median filtering under structural constraints  

Microsoft Academic Search

A new expression for the output moments of weighted median filtered data is derived. The noise attenuation capability of a weighted median filter can now be assessed using the L-vector and M-vector parameters in the new expression. The second major contribution of the paper is the development of a new optimality theory for weighted median filters. This theory is based

Ruikang Yang; Lin Yin; Moncef Gabbouj; Jaakko Astola; Yrjo Neuvo

1995-01-01

34

Improving particle filters in rainfall-runoff models: Application of the resample-move step and the ensemble Gaussian particle filter  

NASA Astrophysics Data System (ADS)

The objective of this paper is to analyze the improvement in the performance of the particle filter by including a resample-move step or by using a modified Gaussian particle filter. Specifically, the standard particle filter structure is altered by the inclusion of the Markov chain Monte Carlo move step. The second choice adopted in this study uses the moments of an ensemble Kalman filter analysis to define the importance density function within the Gaussian particle filter structure. Both variants of the standard particle filter are used in the assimilation of densely sampled discharge records into a conceptual rainfall-runoff model. The results indicate that the inclusion of the resample-move step in the standard particle filter and the use of an optimal importance density function in the Gaussian particle filter improve the effectiveness of particle filters. Moreover, an optimization of the forecast ensemble used in this study allowed for a better performance of the modified Gaussian particle filter compared to the particle filter with resample-move step.

Plaza Guingla, Douglas A.; Keyser, Robin; Lannoy, GabriëLle J. M.; Giustarini, Laura; Matgen, Patrick; Pauwels, Valentijn R. N.

2013-07-01

35

Optimal weighted median filters under structural constraints  

Microsoft Academic Search

An algorithm is developed for finding optimal weighted median (WM) filters which minimize noise subject to a predetermined set of structural constraints on the filter's behavior. Based on the derivation of the output moments of weighted medians, it is shown that optimal weighted medians with structural constraints may be found by solving a group of linear inequalities. One-dimensional applications are

Ruikang Yang; Lin Yin; Moncef Gabbouj; Jaakko Astola; Yrjö Neuvo

1993-01-01

36

Optimal filtering for systems with unknown inputs  

Microsoft Academic Search

An optimal filtering formula is derived for linear time-varying discrete systems with unknown inputs. By making use of the well-known innovations filtering technique, the derivation is an extension of a new observer design method for time-invariant deterministic systems with unknown inputs. The systems under consideration have the most general form. The derived optimal filter has a similar form to the

M. Hou; R. J. Patton

1998-01-01

37

Optimal power flow using particle swarm optimization  

Microsoft Academic Search

This paper presents an efficient and reliable evolutionary-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs particle swarm optimization (PSO) algorithm for optimal settings of OPF problem control variables. Incorporation of PSO as a derivative-free optimization technique in solving OPF problem significantly relieves the assumptions imposed on the optimized objective functions. The proposed approach has

M. A. Abido

2002-01-01

38

A New Approximate Solution of the Optimal Nonlinear Filter for Data Assimilation in Meteorology and Oceanography  

Microsoft Academic Search

This paper introduces a new approximate solution of the optimal nonlinear filter suitable for nonlinear oceanic and atmospheric data assimilation problems. The method is based on a local linearization in a low-rank kernel representation of the state's probability density function. In the resulting low-rank kernel particle Kalman (LRKPK) filter, the standard (weight type) particle filter correction is complemented by a

I. Hoteit; D.-T. Pham; G. Triantafyllou; G. Korres

2008-01-01

39

Particle Filter-based Policy Gradient in POMDPs  

Microsoft Academic Search

Our setting is a Partially Observable Markov Decision Process with continuous state, observation and action spaces. Decisions are based on a Particle Filter for estimating the belief state given past observations. We consider a policy gradient approach for parameterized policy optimization. For that purpose, we investigate sensitivity analysis of the performance measure with respect to the parameters of the policy,

Pierre-arnaud Coquelin; Romain Deguest; Rémi Munos

2008-01-01

40

Westinghouse advanced particle filter system  

SciTech Connect

Integrated Gasification Combined Cycles (IGCC), Pressurized Fluidized Bed Combustion (PFBC) and Advanced PFBC (APFB) are being developed and demonstrated for commercial power generation application. Hot gas particulate filters are key components for the successful implementation of IGCC, PFBC and APFB in power generation gas turbine cycles. The objective of this work is to develop and qualify through analysis and testing a practical hot gas ceramic barrier filter system that meets the performance and operational requirements of these advanced, solid fuel power generation cycles.

Lippert, T.E.; Bruck, G.J.; Sanjana, Z.N.; Newby, R.A.

1995-11-01

41

An optimal Bloom filter replacement  

Microsoft Academic Search

This paper considers space-efficient data structures for storing an approximation S' to a set S such that S ? S' and any element not in S belongs to S' with probability at most ?. The Bloom filter data structure, solving this problem, has found widespread use. Our main result is a new RAM data structure that improves Bloom filters in

Anna Pagh; Rasmus Pagh; S. Srinivasa Rao

2005-01-01

42

STABILITY AND UNIFORM APPROXIMATION OF NONLINEAR FILTERS USING THE HILBERT METRIC AND APPLICATION TO PARTICLE FILTERS1  

Microsoft Academic Search

We study the stability of the optimal filter w.r.t. its initial condition and w.r.t. the model for the hidden state and the observations in a general hidden Markov model, using the Hilbert projective metric. These stability results are then used to prove, under some mixing assumption, the uniform convergence to the optimal filter of several particle filters, such as the

FRANÇOIS LE GLAND; NADIA OUDJANE

2002-01-01

43

Distributed Gaussian particle filtering using likelihood consensus  

Microsoft Academic Search

We propose a distributed implementation of the Gaussian particle filter (GPF) for use in a wireless sensor network. Each sensor runs a local GPF that computes a global state estimate. The updating of the particle weights at each sensor uses the joint likelihood function, which is calculated in a distributed way, using only local communications, via the recently proposed likelihood

Ondrej Hlinka; Ondrej Sluciak; Franz Hlawatsch; Petar M. Djuric; Markus Rupp

2011-01-01

44

Optimal network localization by particle swarm optimization  

Microsoft Academic Search

The practical and theoretical importance of net- work localization has determined a great focus from the scientific community. In recent years several schemes have been proposed to solve the localization problem under certain constraints. Here, we apply the particle swarm optimization (PSO) paradigm to the problem of constructing optimally localizable networks. Alternative solutions which yield non- optimal solutions are also

Catalin V. Rusu; Hyo-Sung Ahn

2011-01-01

45

Optimal multiobjective design of digital filters using spiral optimization technique.  

PubMed

The multiobjective design of digital filters using spiral optimization technique is considered in this paper. This new optimization tool is a metaheuristic technique inspired by the dynamics of spirals. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the spiral optimization technique produced filters which fulfill the desired characteristics and are of practical use. PMID:24083108

Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid

2013-09-13

46

Optimal filtering for multirate systems  

Microsoft Academic Search

For a multirate system where the output sampling is slower than the input updating, this brief aims at designing filters for fast state estimation in the H2 and H? settings. Because of the multirate nature, linear matrix inequality solutions to the design problems involve a nonconvex constraint, which is numerically tackled by the product reduction algorithm. Finally, a design example

Jie Sheng; Tongwen Chen; Sirish L. Shah

2005-01-01

47

Optimal filtering in fractional Fourier domains  

Microsoft Academic Search

For time-invariant degradation models and stationary signals and noise, the classical Fourier domain Wiener filter, which can be implemented in O(N log N) time, gives the minimum mean-square-error estimate of the original undistorted signal. For time-varying degradations and nonstationary processes, however, the optimal linear estimate requires O(N2) time for implementation. We consider filtering in fractional Fourier domains, which enables significant

A. Kutay; Haldun M. Ozaktas; O. Ankan; L. Onural

1997-01-01

48

Application of Particle Filtering to Image Enhancement  

Microsoft Academic Search

Abstract In this report we propose a novel - assumption-free on the noise model - technique based on random,walks for image enhancement. Our method explores multiple neighbors sets (or hypotheses) that can be used for pixel denoising, through a particle filtering approach. This approach associates weights for each hypotheses according to its relevance and its contribution in the denoising process.

Noura Azzabou; Nikos Paragios; Frederic Guichard

49

A modified PSO based particle filter algorithm for object tracking  

NASA Astrophysics Data System (ADS)

In this paper, a modified particle swarm optimization (PSO) approach, particle swarm optimization with ?- greedy exploration ?PSO), is used to tackle the object tracking. In the modified ?PSO algorithm, the cooperative learning mechanism among individuals has been introduced, namely, particles not only adjust its own flying speed according to itself and the best individual of the swarm but also learn from other best individuals according to certain probability. This kind of biologically-inspired mutual-learning behavior can help to find the global optimum solution with better convergence speed and accuracy. The ?PSO algorithm has been tested on benchmark function and demonstrated its effectiveness in high-dimension multi-modal optimization. In addition to the standard benchmark study, we also combined our new ?PSO approach with the traditional particle filter (PF) algorithm on the object tracking task, such as car tracking in complex environment. Comparative studies between our ?PSO combined PF algorithm with those of existing techniques, such as the particle filter (PF) and classic PSO combined PF will be used to verify and validate the performance of our approach.

Tang, Yufei; Fu, Siyao; Tang, Bo; He, Haibo

2013-05-01

50

Interactive Particle Swarm Optimization  

Microsoft Academic Search

It is often desirable to simultaneously handle several objectives and constraints in practical optimization problems. In some cases, these objectives and constraints are non-commensurable and they are not explicitly\\/mathematically available. For this kind of problems, interactive optimization may be a good approach. Interactive optimization means that a human user evaluates the potential solutions in qualitative way. In recent years evolutionary

Janos Madar; János Abonyi; Ferenc Szeifert

2005-01-01

51

Optimal design of active EMC filters  

NASA Astrophysics Data System (ADS)

A recent trend in automotive industry is adding electrical drive systems to conventional drives. The electrification allows an expansion of energy sources and provides great opportunities for environmental friendly mobility. The electrical powertrain and its components can also cause disturbances which couple into nearby electronic control units and communication cables. Therefore the communication can be degraded or even permanently disrupted. To minimize these interferences, different approaches are possible. One possibility is to use EMC filters. However, the diversity of filters is very large and the determination of an appropriate filter for each application is time-consuming. Therefore, the filter design is determined by using a simulation tool including an effective optimization algorithm. This method leads to improvements in terms of weight, volume and cost.

Chand, B.; Kut, T.; Dickmann, S.

2013-07-01

52

Optimal filtering techniques for analytical streamflow forecasting  

Microsoft Academic Search

This paper describes the development of a streamflow forecasting model based on the Sacramento soil moisture accounting model and applies optimal filtering techniques to sequentially update watershed-scale soil moisture state values, to improve streamflow predictions. In general hydrology is the study of the waters of the Earth, especially with relation to the effects of precipitation and evaporation upon the occurrence

D. Kantamneni; Dan Simon; Stuart Schwartz

2005-01-01

53

Small curvature particle flow for nonlinear filters  

NASA Astrophysics Data System (ADS)

We derive five new particle flow algorithms for nonlinear filters based on the small curvature approximation inspired by fluid dynamics. We find it extremely interesting that this physically motivated approximation generalizes two of our previous exact flow algorithms, namely incompressible flow and Gaussian flow. We derive a new algorithm to compute the inverse of the sum of two linear differential operators using a second homotopy, similar to Feynman's perturbation theory for quantum electrodynamics as well as Gromov's h-principle.

Daum, Fred; Huang, Jim

2012-05-01

54

Zero curvature particle flow for nonlinear filters  

NASA Astrophysics Data System (ADS)

We derive a new algorithm for computing Bayes' rule using particle flow that has zero curvature. The flow is computed by solving a vector Riccati equation exactly in closed form rather than solving a PDE, with a significant reduction in computational complexity. Our theory is valid for any smooth nowhere vanishing probability densities, including highly multimodal non-Gaussian densities. We show that this new flow is similar to the extended Kalman filter in the special case of nonlinear measurements with Gaussian noise. We also outline more general particle flows, including: constant curvature, geodesic flow, non-constant curvature, piece-wise constant curvature, etc.

Daum, Fred; Huang, Jim

2013-05-01

55

The Dolph Chebyshev Window: A Simple Optimal Filter  

Microsoft Academic Search

Analyzed data for numerical prediction can be effectively initialized by means of a digital filter. Computation time is reduced by using an optimal filter. The construction of optimal filters involves the solution of a nonlinear minimization problem using an iterative procedure. In this paper a simple filter based on the Dolph-Chebyshev window, which has properties similar to those of an

Peter Lynch

1997-01-01

56

On the optimality of nonunitary filter banks in subband coders  

Microsoft Academic Search

This paper investigates the energy compaction capabilities of nonunitary filter banks in subband coding. It is shown that nonunitary filter banks have larger coding gain than unitary filter banks because of the possibility of performing half-whitening in each channel. For long filter unit pulse responses, optimization of subband coding gain for stationary input signals results in a filter bank decomposition,

Sven Ole Aase; Tor A. Ramstad

1995-01-01

57

H(infty) -Optimal Fractional Delay Filters  

NASA Astrophysics Data System (ADS)

Fractional delay filters are digital filters to delay discrete-time signals by a fraction of the sampling period. Since the delay is fractional, the intersample behavior of the original analog signal becomes crucial. In contrast to the conventional designs based on the Shannon sampling theorem with the band-limiting hypothesis, the present paper proposes a new approach based on the modern sampled-data H-infinity optimization that aims at restoring the intersample behavior beyond the Nyquist frequency. By using the lifting transform or continuous-time blocking the design problem is equivalently reduced to a discrete-time H-infinity optimization, which can be effectively solved by numerical computation softwares. Moreover, a closed-form solution is obtained under an assumption on the original analog signals. Design examples are given to illustrate the advantage of the proposed method.

Nagahara, Masaaki; Yamamoto, Yutaka

2013-09-01

58

Optimal filtering with linear canonical transformations  

Microsoft Academic Search

Optimal filtering with linear canonical transformations allows smaller mean-square errors in restoring signals degraded by linear time- or space-variant distortions and non-stationary noise. This reduction in error comes at no additional computational cost. This is made possible by the additional flexibility that comes with the three free parameters of linear canonical transformations, as opposed to the fractional Fourier transform which

Billur Barshan; M. Alper Kutay; Haldun M. Ozalctas

1997-01-01

59

Point set registration via particle filtering and stochastic dynamics.  

PubMed

In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms compute the transformation parameters by maximizing a metric given an estimate of the correspondence between points across the two sets of interest. This can be viewed as a posterior estimation problem, in which the corresponding distribution can naturally be estimated using a particle filter. In this work, we treat motion as a local variation in pose parameters obtained by running a few iterations of a certain local optimizer. Employing this idea, we introduce stochastic motion dynamics to widen the narrow band of convergence often found in local optimizer approaches for registration. Thus, the novelty of our method is threefold: First, we employ a particle filtering scheme to drive the point set registration process. Second, we present a local optimizer that is motivated by the correlation measure. Third, we increase the robustness of the registration performance by introducing a dynamic model of uncertainty for the transformation parameters. In contrast with other techniques, our approach requires no annealing schedule, which results in a reduction in computational complexity (with respect to particle size) as well as maintains the temporal coherency of the state (no loss of information). Also unlike some alternative approaches for point set registration, we make no geometric assumptions on the two data sets. Experimental results are provided that demonstrate the robustness of the algorithm to initialization, noise, missing structures, and/or differing point densities in each set, on several challenging 2D and 3D registration scenarios. PMID:20558877

Sandhu, Romeil; Dambreville, Samuel; Tannenbaum, Allen

2010-08-01

60

Point Set Registration via Particle Filtering and Stochastic Dynamics  

PubMed Central

In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms compute the transformation parameters by maximizing a metric given an estimate of the correspondence between points across the two sets of interest. This can be viewed as a posterior estimation problem, in which the corresponding distribution can naturally be estimated using a particle filter. In this work, we treat motion as a local variation in pose parameters obtained by running a few iterations of a certain local optimizer. Employing this idea, we introduce stochastic motion dynamics to widen the narrow band of convergence often found in local optimizer approaches for registration. Thus, the novelty of our method is threefold: First, we employ a particle filtering scheme to drive the point set registration process. Second, we present a local optimizer that is motivated by the correlation measure. Third, we increase the robustness of the registration performance by introducing a dynamic model of uncertainty for the transformation parameters. In contrast with other techniques, our approach requires no annealing schedule, which results in a reduction in computational complexity (with respect to particle size) as well as maintains the temporal coherency of the state (no loss of information). Also unlike some alternative approaches for point set registration, we make no geometric assumptions on the two data sets. Experimental results are provided that demonstrate the robustness of the algorithm to initialization, noise, missing structures, and/or differing point densities in each set, on several challenging 2D and 3D registration scenarios.

Sandhu, Romeil; Dambreville, Samuel; Tannenbaum, Allen

2013-01-01

61

Customized optimal filter for eliminating operator's tremor  

NASA Astrophysics Data System (ADS)

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate signal which is transmitted to the controlled subsystem (robot arm, virtual environment or cursor). When man-machine movements are distorted by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel filtering framework in which digital equalizers are optimally designed after pursuit tracking task experiments. Due to inherent properties of the man-machine system, the design of tremor suppression equalizers presents two serious problems: (1) performance criteria leading to optimizations that minimize mean-squared error are not efficient for tremor elimination, and (2) movement signals show highly ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. A new performance indicator is introduced, namely the F-MSEd, and the optimal equalizer according to this new criterion is developed. Ill-condition of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with both a person with tremor disability, and a vibration inducing device, show significant results.

Gonzalez, Juan G.; Heredia, Edwin A.; Rahman, Tariq; Barner, Kenneth E.; Arce, Gonzalo R.

1995-12-01

62

An Improved Particle Filter for Non-linear Problems  

Microsoft Academic Search

The Kalman filter provides an effective solution to the linear-Gaussian fil tering problem. How- ever, where there is nonlinearity, either in the model specification or the observation process, other methods are required. We consider methods known generically as particle filters, which include the condensation algorithm and the Bayesian bootstrap or sampling importance resampling (SIR) filter. These filters represent the posterior

James Carpenter; Peter Clifford; Paul Fearnhead

1999-01-01

63

Tracking Deforming Objects using Particle Filtering for Geometric Active Contours.  

National Technical Information Service (NTIS)

Tracking deforming objects involves estimating the global motion of the object and its local deformations as a function of time. Tracking algorithms using Kalman filters or particle filters have been proposed for finite dimensional representations of shap...

A. Tannenbaum A. Yezzi N. Vaswani Y. Rathi

2007-01-01

64

Design of multirate filter banks by ℋ? optimization  

Microsoft Academic Search

A procedure is developed to design IIR synthesis filters in a multirate filter bank. The filters minimize the l2-induced norm of the error system between the multirate filter bank and a desired pure time-delay system. This criterion is reduced to one of ℋ? optimization, for which there is ready-made software

Tongwen Chen; Bruce A. Francis

1995-01-01

65

Minimum Euclidean distance optimal filter (MEDOF): version 2.0  

Microsoft Academic Search

We previously reported computer code designed to generate optical correlator filters by putting our optimization algorithm into practice. This code is MEDOF: Minimum Euclidean Distance Optimal Filter. MEDOF's version 1.0 demonstrated filters which maximize correlation peak intensity (INT). We also gave some discussion to the quadratic ratio metrics of signal to noise ratio (SNR) and peak to correlation energy ratio

R. Shane Barton; Richard D. Juday

1995-01-01

66

Multisensor particle filter cloud fusion for multitarget tracking  

Microsoft Academic Search

Within the area of target tracking particle filters are the subject of consistent research and continuous improvement. The purpose of this paper is to present a novel method of fusing the information from multiple particle filters tracking in a multisensor multitarget scenario. Data considered for fusion is under the form of labeled particle clouds, obtained in the simulation from two

Daniel Danu; Thia Kirubarajan; Thomas Lang; Michael McDonald

2008-01-01

67

Simultaneous Eye Tracking and Blink Detection with Interactive Particle Filters  

Microsoft Academic Search

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

Junwen Wu; Mohan M. Trivedi

2008-01-01

68

Optimal filters with heuristic 1-norm sparsity constraints  

NASA Astrophysics Data System (ADS)

We present a design method for sparse optimal Finite Impulse Response (FIR) filters that improve the visibility of a desired stochastic signal corrupted with white Gaussian noise. We emphasize that the filters we seek are of high-order but sparse, thus significantly reducing computational complexity. An optimal FIR filter for the estimation of a desired signal corrupted with white noise can be designed by maximizing the signal-to-noise ratio (SNR) of the filter output with the constraint that the magnitude (in 2-norm) of the FIR filter coefficients are set to unity.1, 2 This optimization problem is in essence maximizing the Rayleigh quotient and is thus equivalent to finding the eigenvector with the largest eigenvalue.3 While such filters are optimal, they are rarely sparse. To ensure sparsity, one must introduce a cardinality constraint in the optimization procedure. For high order filters such constraints are computationally burdensome due to the combinatorial search space. We relax the cardinality constraint by using the 1-norm approximation of the cardinality function. This is a relaxation heuristic similar to the recent sparse filter design work of Baran, Wei, and Oppenheim.4 The advantage of this relaxation heuristic is that the solutions tend to be sparse and the optimization procedure reduces to a convex program, thus ensuring global optimality. In addition to our proposed optimization procedure for deriving sparse FIR filters, we show examples where sparse high-order filters significantly perform better than low-order filters, whereas complexity is reduced by a factor of 10.

Yazdani, Mehrdad; Hecht-Nielsen, Robert

2011-09-01

69

Online maintaining appearance model using particle filter  

NASA Astrophysics Data System (ADS)

Tracking by foreground matching heavily depends on the appearance model to establish object correspondences among frames and essentially, the appearance model should encode both the difference part between the object and background to guarantee the robustness and the stable part to ensure tracking consistency. This paper provides a solution for online maintaining appearance models by adjusting features in the model. Object appearance is co-modeled by a subset of Haar features selected from the over-complete feature dictionary which encodes the discriminative part of object appearance and the color histogram which describes the stable appearance. During the particle filtering process, feature values both from background patches and object observations are sampled efficiently by the aid of "foreground" and "background" particles respectively. Based on these sampled values, top-ranked discriminative features are added and invalid features are removed out to ensure the object being distinguishable from current background according to the evolving appearance model. The tracker based on this online appearance model maintaining technique has been tested on people and car tracking tasks and promising experimental results are obtained.

Chen, Siying; Lan, Tian; Wang, Jianyu; Ni, Guoqiang

2008-03-01

70

Metal finishing wastewater pressure filter optimization  

SciTech Connect

The 300-M Area Liquid Effluent Treatment Facility (LETF) of the Savannah River Site (SRS) is an end-of-pipe industrial wastewater treatment facility, that uses precipitation and filtration which is the EPA Best Available Technology economically achievable for a Metal Finishing and Aluminum Form Industries. The LETF consists of three close-coupled treatment facilities: the Dilute Effluent Treatment Facility (DETF), which uses wastewater equalization, physical/chemical precipitation, flocculation, and filtration; the Chemical Treatment Facility (CTF), which slurries the filter cake generated from the DETF and pumps it to interim-StatuS RCRA storage tanks; and the Interim Treatment/Storage Facility (IT/SF) which stores the waste from the CTF until the waste is stabilized/solidified for permanent disposal, 85% of the stored waste is from past nickel plating and aluminum canning of depleted uranium targets for the SRS nuclear reactors. Waste minimization and filtration efficiency are key to cost effective treatment of the supernate, because the waste filter cake generated is returned to the IT/SF. The DETF has been successfully optimized to achieve maximum efficiency and to minimize waste generation.

Norford, S.W.; Diener, G.A.; Martin, H.L.

1992-12-31

71

Metal finishing wastewater pressure filter optimization  

SciTech Connect

The 300-M Area Liquid Effluent Treatment Facility (LETF) of the Savannah River Site (SRS) is an end-of-pipe industrial wastewater treatment facility, that uses precipitation and filtration which is the EPA Best Available Technology economically achievable for a Metal Finishing and Aluminum Form Industries. The LETF consists of three close-coupled treatment facilities: the Dilute Effluent Treatment Facility (DETF), which uses wastewater equalization, physical/chemical precipitation, flocculation, and filtration; the Chemical Treatment Facility (CTF), which slurries the filter cake generated from the DETF and pumps it to interim-StatuS RCRA storage tanks; and the Interim Treatment/Storage Facility (IT/SF) which stores the waste from the CTF until the waste is stabilized/solidified for permanent disposal, 85% of the stored waste is from past nickel plating and aluminum canning of depleted uranium targets for the SRS nuclear reactors. Waste minimization and filtration efficiency are key to cost effective treatment of the supernate, because the waste filter cake generated is returned to the IT/SF. The DETF has been successfully optimized to achieve maximum efficiency and to minimize waste generation.

Norford, S.W.; Diener, G.A.; Martin, H.L.

1992-01-01

72

Real time face tracking by genetic particle filter  

Microsoft Academic Search

There are a great variety of human faces tracking methods based on particle filter. However, most tracking algorithms, so far, are unable to meet the demands for both precise and fast tracking. A real-time algorithm, based on genetic particle filter (GPF) for human faces tracking is presented in this paper. The crossover and mutation operations in evolutionary computation are introduced

Liu Yanli; Zhang Heng

2009-01-01

73

A novel backtracking particle filter for pattern matching indoor localization  

Microsoft Academic Search

Particle Filter (PF) techniques has been widely used in in- door localization systems. They are often used in conjunc- tion with pattern matching based on Received Signal Strength Indication (RSSI) fingerprinting. Several variants of the particle filter within a generic framework of the Sequential Importance Sampling (SIS) algorithm have been described. The purpose of this paper is to show how

Widyawan; Martin Klepal; Stéphane Beauregard

2008-01-01

74

Study of Algorithmic and Architectural Characteristics of Gaussian Particle Filters  

Microsoft Academic Search

In this paper, we analyze algorithmic and architectural characteristics of a class of particle filters known as Gaussian Particle\\u000a Filters (GPFs). GPFs approximate the posterior density of the unknowns with a Gaussian distribution which limits the scope\\u000a of their applications in comparison with the universally applied sample-importance resampling filters (SIRFs) but allows for\\u000a their implementation without the classical resampling procedure.

Miodrag Bolic; Akshay Athalye; Sangjin Hong; Petar M. Djuric

2010-01-01

75

Effects of the particle penetration inside the filter medium on the Hepa filter pressure drop.  

National Technical Information Service (NTIS)

Filter pressure drop modelization as a function of the deposited aerosols mass requires to know the penetration profile of the particles inside the filter medium and to take into account the evolution of the internal structure of the filter. These two par...

P. Letourneau J. Vendel V. Renaudin

1992-01-01

76

Application of Particle Filter for Target Tracking in Wireless Sensor Networks  

Microsoft Academic Search

In the application of particle filter algorithm for target tracking in wireless sensor networks, an Auxiliary particle filter (APF) and Gaussian particle filter (GPF) are discussed to solve the particle degradation problem of Particle Filter (PF). By introducing an auxiliary variable and two rounds weighted processes, APF makes the particle weights stable and relaxes particle degradation. GPF uses a Gaussian

Dong Hui-ying; Cao Bin; Yang Yue-ping

2010-01-01

77

Optimal Gabor filters for texture segmentation  

Microsoft Academic Search

Texture segmentation involves subdividing an image into differently textured regions. Many texture segmentation schemes are based on a filter-bank model, where the filters, called Gabor filters, are derived from Gabor elementary functions. The goal is to transform texture differences into detectable filter-output discontinuities at texture boundaries. By locating these discontinuities, one can segment the image into differently textured regions. Distinct

Dennis F. Dunn; William E. Higgins

1995-01-01

78

Optimal peak sidelobe filters for biphase pulse compression  

Microsoft Academic Search

A technique for the generation of mismatched filters that minimize the peak sidelobe in the correlation of a biphase code is developed. The technique is applied to several well-known codes, and the resulting sidelobe performance is compared to that of the matched filter and optimal integrated sidelobe level filter. The theory is shown to be applicable to the generation of

J. M. Baden; M. N. Cohen

1990-01-01

79

Optimal filter banks for signal reconstruction from noisy subband components  

Microsoft Academic Search

Conventional design techniques for analysis and synthesis filters in subband processing applications guarantee perfect reconstruction of the original signal from its subband components. The resulting filters, however, lose their optimality when additive noise due, for example, to signal quantization, disturbs the subband sequences. We propose filter design techniques that minimize the reconstruction mean squared error (MSE) taking into account the

A. N. Delopoulos; S. D. Kollias

1996-01-01

80

Evolutionary Gabor Filter Optimization with Application to Vehicle Detection  

Microsoft Academic Search

Despite the considerable amount of research work on the ap- plication of Gabor filters in pattern classification, their design and selection have been mostly done on a trial and error basis. Existing techniques are either only suitable for a small number of filters or less problem-oriented. A systematic and general evolutionary Gabor filter optimization (EGFO) approach that yields a more

Zehang Sun; George Bebis; Ronald Miller

2003-01-01

81

Multiobjective optimization using dynamic neighborhood particle swarm optimization  

Microsoft Academic Search

This paper presents a particle swarm optimization (PSO) algorithm for multiobjective optimization problems. PSO is modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple objectives. Several benchmark cases were tested and showed that PSO could efficiently find multiple Pareto optimal solutions

Xiaohui Hu; Russell C. Eberhart

2002-01-01

82

A Scalable Coevolutionary Particle Swarm Optimizer  

Microsoft Academic Search

Most existing evolutionary algorithms are only effective for optimization problems with no more than one hundred decision variables. However, many optimization problems involve more than several hundreds decision variables, even one thousand. To deal with these problems, a fast cooperative coevolutionary particle swarm optimizer (FCPSO) is proposed, which is constructed based on cooperative coevolutionary framework and particle swarm optimizer with

Xiangwei Zheng; Hong Liu; Jie Chen

2008-01-01

83

Defect detection in textured materials using optimized filters  

Microsoft Academic Search

The problem of automated defect detection in textured materials is investigated. A new approach for defect detection using linear FIR filters with optimized energy separation is proposed. The performance of different feature separation criteria with reference to fabric defects has been evaluated. The issues relating to the design of optimal filters for supervised and unsupervised web inspection are addressed. A

Ajay Kumar; Grantham K. H. Pang

2002-01-01

84

Polynomial systems approach to optimal linear filtering and prediction  

Microsoft Academic Search

The solution of the optimal linear estimation problem is considered, using a polynomial matrix description for the discrete system. The filter or predictor is given by the solution of two diophantine equations and is equivalent to the state equation form of the steady-state Kalman filter, or the transfer-function matrix form of the Wiener filter. The pole-zero properties of the optimal

M. J. GRIMBLE

1985-01-01

85

Synthesis of general topology multiple coupled resonator filters by optimization  

Microsoft Academic Search

A synthesis procedure, using optimization, for multiple coupled resonator filters having general topology and general response is described. The error function for the optimization is based on the values of the characteristic function at its zeros and poles. The optimization is performed directly on the element values of the coupling matrix. Convergence of the optimization is extremely fast and nearly

Walid A. Atia; Kawthar A. Zaki; A. E. Atia

1998-01-01

86

Speedup and tracking accuracy evaluation of parallel particle filter algorithms implemented on a multicore architecture  

Microsoft Academic Search

Four different parallel particle filters such as globally distributed particle filter (GDPF), resampling with proportional allocation filter (RPA), resampling with non-proportional allocation filter (RNA) and the Gaussian particle filter (GPF), are studied in terms of speedup and tracking accuracy in a bearings-only tracking problem. The filters are implemented on a shared memory multicore computer, where the speedup is measured using

Olov Rosén; Alexander Medvedev; Mats Ekman

2010-01-01

87

Optimal filter-based detection of microcalcifications.  

PubMed

This paper deals with the problem of texture feature extraction in digital mammograms. We use the extracted features to discriminate between texture representing clusters of microcalcifications and texture representing normal tissue. Having a two-class problem, we suggest a texture feature extraction method based on a single filter optimized with respect to the Fisher criterion. The advantage of this criterion is that it uses both the feature mean and the feature variance to achieve good feature separation. Image compression is desirable to facilitate electronic transmission and storage of digitized mammograms. In this paper, we also explore the effects of data compression on the performance of our proposed detection scheme. The mammograms in our test set were compressed at different ratios using the Joint Photographic Experts Group compression method. Results from an experimental study indicate that our scheme is very well suited for detecting clustered microcalcifications in both uncompressed and compressed mammograms. For the uncompressed mammograms, at a rate of 1.5 false positive clusters/image our method reaches a true positive rate of about 95%, which is comparable to the best results achieved so far. The detection performance for images compressed by a factor of about four is very similar to the performance for uncompressed images. PMID:11686626

Gulsrud, T O; Husřy, J H

2001-11-01

88

Parallel asynchronous particle swarm optimization  

PubMed Central

SUMMARY The high computational cost of complex engineering optimization problems has motivated the development of parallel optimization algorithms. A recent example is the parallel particle swarm optimization (PSO) algorithm, which is valuable due to its global search capabilities. Unfortunately, because existing parallel implementations are synchronous (PSPSO), they do not make efficient use of computational resources when a load imbalance exists. In this study, we introduce a parallel asynchronous PSO (PAPSO) algorithm to enhance computational efficiency. The performance of the PAPSO algorithm was compared to that of a PSPSO algorithm in homogeneous and heterogeneous computing environments for small- to medium-scale analytical test problems and a medium-scale biomechanical test problem. For all problems, the robustness and convergence rate of PAPSO were comparable to those of PSPSO. However, the parallel performance of PAPSO was significantly better than that of PSPSO for heterogeneous computing environments or heterogeneous computational tasks. For example, PAPSO was 3.5 times faster than was PSPSO for the biomechanical test problem executed on a heterogeneous cluster with 20 processors. Overall, PAPSO exhibits excellent parallel performance when a large number of processors (more than about 15) is utilized and either (1) heterogeneity exists in the computational task or environment, or (2) the computation-to-communication time ratio is relatively small.

Koh, Byung-Il; George, Alan D.; Haftka, Raphael T.; Fregly, Benjamin J.

2006-01-01

89

Handling Multiple Objectives With Particle Swarm Optimization  

Microsoft Academic Search

This paper presents an approach in which Pareto dominance is incorporated into particle swarm optimization (PSO) in order to allow this heuristic to handle problems with several objective functions. Unlike other current proposals to extend PSO to solve multiobjective optimization problems, our algorithm uses a secondary (i.e., external) repository of particles that is later used by other particles to guide

Carlos A. Coello Coello; Gregorio Toscano Pulido; M. Salazar Lechuga

2004-01-01

90

MRPSO: MapReduce particle swarm optimization  

Microsoft Academic Search

In optimization problems involving large amounts of data, Particle Swarm Optimization (PSO) must be parallelized because individual function evaluations may take minutes or even hours. However, large-scale parallelization is difficult because programs must communicate efficiently, balance workloads and tolerate node failures. To address these issues, we present Map Reduce Particle Swarm Optimization(MRPSO), a PSO implementation based on Google's Map Reduce

Andrew W. Mcnabb; Christopher K. Monson; Kevin D. Seppi

2007-01-01

91

Novel Roughening Method for Reentry Vehicle Tracking Using Particle Filter  

Microsoft Academic Search

An improvement for the generic particle filter (PF) is to add a roughening step in resampling. This paper studied the reentry vehicle tracking problem using PF with roughening. A novel algorithm to calculate the reasonable standard deviation of the roughening jitter is proposed. For comparison, the Unscented Kalman filter, the generic PF and the PF with the typical roughening are

W. Zang; Z. G. Shi; S. C. Du; K. S. Chen

2007-01-01

92

Text Segmentation Approach Based on Recursive Particle Filter  

Microsoft Academic Search

In order to solving segment text accurately and robustly from a video sequences. This paper presents a new approach for text segmentation in video sequences by using recursive particle filter. This approach presents a probabilistic algorithm for segmenting text in video sequences based on adaptive thresholding using a Bayes filtering method. First, we describe adaptive mixture model for video text

Shi Zhen-gang; He Li-li

2009-01-01

93

Multiagent system for optimizing filter coefficients in image compression  

NASA Astrophysics Data System (ADS)

In this paper, we present a new intelligent agent-based method to design filter banks that maximize compression quality. In this method, a multi-agent system containing cooperating intelligent agents with different roles is developed to search for filter banks that improve image compression quality. The multi-agent system consists of one generalization agent, and several problem formulation, optimization, and compression agents. The generalization agent performs problem decomposition and result collection. It distributes optimization tasks to optimization agents, and later collects results and selects one solution that works well on all training images as the final output. Problem formulation agents build optimization models that are used by the optimization agents. The optimization formulation includes both the overall performance of image compression and metrics of individual filters. The compression performance is provided by the image coding agent. Optimization agents apply various optimization methods to find the best filter bank for individual training images. Our method is modular and flexible, and is suitable for distributed processing. In experiments, we applied the proposed method to a set of benchmark images and designed filter banks that improve the compression performance of existing filter banks.

Shang, Yi; Li, Longzhuang

1999-10-01

94

Optimal linear filtering under parameter uncertainty  

Microsoft Academic Search

This paper addresses the problem of designing a guaranteed minimum error variance robust filter for convex bounded parameter uncertainty in the state, output, and input matrices. The design procedure is valid for linear filters that are obtained from the minimization of an upper bound of the error variance holding for all admissible parameter uncertainty. The results provided generalize the ones

Jose C. Geromel

1999-01-01

95

Optimal Filter Design for Annular Imaging.  

National Technical Information Service (NTIS)

The purpose of this paper is the design of spatial filters that maximize the ratio of the energy incident on an annulus of specified radius and infinitely small width in the image plane of a lens-filter combination to the energy incident from a point sour...

A. Fedotowsky K. Lehovec

1973-01-01

96

Tunable UHF TV channel power filter optimization  

Microsoft Academic Search

In this paper the design and realization of a mechanically tunable TEM-mode channel power filter for the UHF TV band are presented. A three-stage coaxial resonator filter was made without tunable capacitors and with minimum necessary adjustment by two inductive couplings. Calculated and experimental results agreed very well

J. R. Bogdanovic; G. M. Donic; MomEilo D. Sarenac; S. M. Milosevic

1998-01-01

97

Optimal Filter Systems for Photometric Redshift Estimation  

NASA Astrophysics Data System (ADS)

In the coming years, several cosmological surveys will rely on imaging data to estimate the redshift of galaxies, using traditional filter systems with 4-5 optical broad bands; narrower filters improve the spectral resolution, but strongly reduce the total system throughput. We explore how photometric redshift performance depends on the number of filters nf , characterizing the survey depth by the fraction of galaxies with unambiguous redshift estimates. For a combination of total exposure time and telescope imaging area of 270 hr m2, 4-5 filter systems perform significantly worse, both in completeness depth and precision, than systems with nf gsim 8 filters. Our results suggest that for low nf the color-redshift degeneracies overwhelm the improvements in photometric depth, and that even at higher nf the effective photometric redshift depth decreases much more slowly with filter width than naively expected from the reduction in the signal-to-noise ratio. Adding near-IR observations improves the performance of low-nf systems, but still the system which maximizes the photometric redshift completeness is formed by nine filters with logarithmically increasing bandwidth (constant resolution) and half-band overlap, reaching ~0.7 mag deeper, with 10% better redshift precision, than 4-5 filter systems. A system with 20 constant-width, nonoverlapping filters reaches only ~0.1 mag shallower than 4-5 filter systems, but has a precision almost three times better, ?z = 0.014(1 + z) versus ?z = 0.042(1 + z). We briefly discuss a practical implementation of such a photometric system: the ALHAMBRA Survey.

Benítez, N.; Moles, M.; Aguerri, J. A. L.; Alfaro, E.; Broadhurst, T.; Cabrera-Cańo, J.; Castander, F. J.; Cepa, J.; Cervińo, M.; Cristóbal-Hornillos, D.; Fernández-Soto, A.; González Delgado, R. M.; Infante, L.; Márquez, I.; Martínez, V. J.; Masegosa, J.; Del Olmo, A.; Perea, J.; Prada, F.; Quintana, J. M.; Sánchez, S. F.

2009-02-01

98

Optimal filtering in linear systems with time delays  

Microsoft Academic Search

The optimal linear filtering theory of Kalman and Bucy is extended to include linear systems with multiple time delays as well as the smoothing problem. The (ordinary) filter differential equation and variance equation of the Kalman-Bucy theory are replaced by partial differential equations. An explicit solution is given of the smoothing problem for systems without time delays.

H. Kwakernaak

1967-01-01

99

Finite-dimensional sensor orbits and optimal nonlinear filtering  

Microsoft Academic Search

The filtering problem of a system with linear dynamics and non-Gaussian a priori distribution is investigated. A closed-form exact solution to the problem is presented along with an approximation scheme. The approximation is made in the construction of a mathematical model. It reduces optimal estimation to a combination of linear estimations. The asymptotic behavior of the filter is examined. The

JAMES TING-HO LO

1972-01-01

100

Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets  

Microsoft Academic Search

The majority of tactical weapons systems require that manned maneuverable vehicles, such as aircraft, ships, and submarines, be tracked accurately. An optimal Kalman filter has been derived for this purpose using a target model that is simple to implement and that represents closely the motions of maneuvering targets. Using this filter, parametric tracking accuracy data have been generated as a

Robert Singer

1970-01-01

101

Optimal Design of Filters with Bounded, Lossy Elements  

Microsoft Academic Search

This paper proposes a solution to the problem of designing a filter of given structure, incorporating nonideal elements, to meet or exceed given insertion loss specifications subject to element value bounds. This problem is reformulated as a nonlinear programming problem, i.e., minimize an objective function subject to inequality constraints, whose solution yields a filter optimal in a min-max sense. To

L. S. LASDON; A. D. WAREN

1966-01-01

102

Optimized and iterative Wiener filter for image restoration  

Microsoft Academic Search

Two new techniques were suggested in this research. The first one is for optimizing image restoration with Wiener filter by suggesting an efficient method for estimating an optimum value for the signal to noise ratio parameter used in Wiener filter restoration formula. The estimated value is different for each segment in frequency domain. Estimation depends on the degraded image only,

A. M. A. Mahmood

2009-01-01

103

Contrasting Particle Clogging in Soils and Granular Media Filters  

NASA Astrophysics Data System (ADS)

Deposition of colloidal particles leads to permeability reduction (or clogging) in the soil geomembrane, which reduces fluxes, alters flow patterns, and limits both colloid-associated contaminant transport and delivery of colloidal reactants for purposes of remediation. Comparison of experimental results for soils and granular media filters reveals qualitatively different clogging phenomena with regard to (1) particle stabilization, (2) fluid velocity, and (3) the fractal dimension of particle deposits. These differences have important implications for contaminant hydrology, because the classical approach for understanding particles in natural environments is taken from the filtration literature, which is based on clean granular media. Accordingly, many of the relevant experiments have been performed with granular filters using media such as glass beads or quartz sand. In such filters, clogging is associated with destabilized particles, slower fluid velocity and deposits with smaller fractal dimensions. In contrast, in soils clogging is associated with stabilized particles, faster fluid velocity and deposits with larger fractal dimensions. With regard to these variables, soils are opposite to filters but identical to cake filtration. Numerous examples will be presented from the filtration literature and the soil science literature to illustrate these differing viewpoints. This analysis demonstrates that experiments on clean granular media filters should not be expected to predict particle clogging in soils, sandstones or other natural porous materials containing more than a few percent fines.

Mays, D. C.

2005-12-01

104

Optimal Switched Dynamic Modulated Power Filter Compensator for Radial Distribution System  

Microsoft Academic Search

This paper presents a novel pulse width switched modulated power filter compensator (MPFC) for the voltage stability enhancement, energy utilization, loss reduction, and power factor correction in a radial distribution network using the Particle Swarm Optimization (PSO) technique. The MPFC is controlled by a novel dynamic tri-loop error driven controller. The dynamic controller is regulated to minimize the switching current

Adel M. Sharaf; Adel A. A. El-gammal

2009-01-01

105

Analysis of video-based microscopic particle trajectories using Kalman filtering.  

PubMed

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

Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P; Tseng, Yiider

2010-06-16

106

Silicon oxide nano-particles doped PQ-PMMA for volume holographic imaging filters  

PubMed Central

Holographic imaging filters are required to have high Bragg selectivity to obtain spatial-spectral information within a three-dimensional object. In this Letter, we present the design of holographic imaging filters formed using silicon oxide nano-particles (nano-SiO2) in PQ-PMMA polymer recording material. This combination offers greater angular and spectral selectivity and increases the diffraction efficiency of holographic filters. The holographic filters with optimized ratio of nano-SiO2 in PQ-PMMA can significantly improve the performance of Bragg selectivity and diffraction efficiency by 53% and 16%, respectively. We present experimental results and data analysis demonstrating this technique in use for holographic spatial-spectral imaging filters.

Luo, Yuan; Russo, Juan M.; Kostuk, Raymond K.; Barbastathis, George

2011-01-01

107

Optimal realizable filters and the minimum Euclidean distance principle.  

PubMed

Minimizing a Euclidean distance in the complex plane optimizes a wide class of correlation metrics for filters implemented on realistic devices. The algorithm searches over no more than two real scalars (gain and phase). It unifies a variety of previous solutions for special cases (e.g., a maximum signal-to-noise ratio with colored noise and a real filter and a maximum correlation intensity with no noise and a coupled filter). It extends optimal partial information filter theory to arbitrary spatial light modulators (fully complex, coupled, discrete, finite contrast ratio, and so forth), additive input noise (white or colored), spatially nonuniform filter modulators, and additive correlation detection noise (including signaldependent noise). An appendix summarizes the algorithm as it is implemented in available computer code. PMID:20856317

Juday, R D

1993-09-10

108

Distributed generation installation using particle swarm optimization  

Microsoft Academic Search

This paper presents a particle swarm optimization approach for the placement of distributed generation (DG) in the distribution system. DG installation in the distribution system is very useful in reducing the line losses, as well as improving the voltage profiles. The proposed method combines particle swarm optimization and the Newton-Raphson load flow method to determine the location and size of

L. Y. Wong; Siti Rafidah Abdul Rahim; Mohd Herwan Sulaiman; O. Aliman

2010-01-01

109

Road-constrained target tracking and identification a particle filter  

NASA Astrophysics Data System (ADS)

Sequential Monte Carlo methods have attracted the attention of the tracking community as a solution to Bayesian estimation particularly for nonlinear problems. Several attributes of particle filters support their use in jointly tracking and identifying ground targets in a road-constrained network. First, since the target dynamics are simulated, propagating a target within a constrained state space is handled quite naturally since the particle filter is not restricted to propagating Gaussian PDFs. Furthermore, a particle filter can approximate a PDF which is a mixture of continuous random variables (the target kinematic state) and discrete random variables (the target ID) which is necessary for the joint tracking and identification problem. Given HRRGMTI measurements of a target, we propose to jointly estimate a target's kinematic state and identification by propagating the joint PDF of the target kinematic state (position and velocity) and target ID. In this way, we capitalize on the inherent coupling between the target's feature measurement (the HRR profile) and the target's kinematic state. In addition to the coupling between a target's feature measurement and the target's kinematic state, there exists a coupling between a target's dynamics and the target's ID which can also be exploited through particle filtering methods. We develop the particle filtering algorithm for tracking and identifying ground targets in a road-constrained environment and present simulation results for a two-class problem.

Agate, Craig S.; Sullivan, Kevin J.

2003-12-01

110

Road-constrained target tracking and identification a particle filter  

NASA Astrophysics Data System (ADS)

Sequential Monte Carlo methods have attracted the attention of the tracking community as a solution to Bayesian estimation particularly for nonlinear problems. Several attributes of particle filters support their use in jointly tracking and identifying ground targets in a road-constrained network. First, since the target dynamics are simulated, propagating a target within a constrained state space is handled quite naturally since the particle filter is not restricted to propagating Gaussian PDFs. Furthermore, a particle filter can approximate a PDF which is a mixture of continuous random variables (the target kinematic state) and discrete random variables (the target ID) which is necessary for the joint tracking and identification problem. Given HRRGMTI measurements of a target, we propose to jointly estimate a target's kinematic state and identification by propagating the joint PDF of the target kinematic state (position and velocity) and target ID. In this way, we capitalize on the inherent coupling between the target's feature measurement (the HRR profile) and the target's kinematic state. In addition to the coupling between a target's feature measurement and the target's kinematic state, there exists a coupling between a target's dynamics and the target's ID which can also be exploited through particle filtering methods. We develop the particle filtering algorithm for tracking and identifying ground targets in a road-constrained environment and present simulation results for a two-class problem.

Agate, Craig S.; Sullivan, Kevin J.

2004-01-01

111

Effect of particle-fiber friction coefficient on ultrafine aerosol particles clogging in nanofiber based filter  

NASA Astrophysics Data System (ADS)

Realistic SEM image based 3D filter model considering transition/free molecular flow regime, Brownian diffusion, aerodynamic slip, particle-fiber and particle-particle interactions together with a novel Euclidian distance map based methodology for the pressure drop calculation has been utilized for a polyurethane nanofiber based filter prepared via electrospinning process in order to more deeply understand the effect of particle-fiber friction coefficient on filter clogging and basic filter characteristics. Based on the performed theoretical analysis, it has been revealed that the increase in the fiber-particle friction coefficient causes, firstly, more weaker particle penetration in the filter, creation of dense top layers and generation of higher pressure drop (surface filtration) in comparison with lower particle-fiber friction coefficient filter for which deeper particle penetration takes place (depth filtration), secondly, higher filtration efficiency, thirdly, higher quality factor and finally, higher quality factor sensitivity to the increased collected particle mass. Moreover, it has been revealed that even if the particle-fiber friction coefficient is different, the cake morphology is very similar.

Sambaer, Wannes; Zatloukal, Martin; Kimmer, Dusan

2013-04-01

112

Square Root Unscented Particle Filtering for Grid Mapping  

NASA Astrophysics Data System (ADS)

In robotics, a key problem is for a robot to explore its environment and use the information gathered by its sensors to jointly produce a map of its environment, together with an estimate of its position: so-called SLAM (Simultaneous Localization and Mapping) [12]. Various filtering methods - Particle Filtering, and derived Kalman Filter methods (Extended, Unscented) - have been applied successfully to SLAM. We present a new algorithm that adapts the Square Root Unscented Transformation [13], previously only applied to feature based maps [5], to grid mapping. We also present a new method for the so-called pose-correction step in the algorithm. Experimental results show improved computational performance on more complex grid maps compared to an existing grid based particle filtering algorithm.

Zandara, Simone; Nicholson, Ann

113

Particle swarm optimization method in multiobjective problems  

Microsoft Academic Search

This paper constitutes a first study of the Particle Swarm Optimization (PSO) method in Multiobjective Optimization (MO) problems. The ability of PSO to detect Pareto Optimal points and capture the shape of the Pareto Front is studied through experiments on well-known non-trivial test functions. The Weighted Aggregation technique with fixed or adaptive weights is considered. Furthermore, critical aspects of the

Konstantinos E. Parsopoulos; Michael N. Vrahatis

2002-01-01

114

On optimal linear filtering for edge detection  

Microsoft Academic Search

In this paper, we revisit the analytical expressions of the three Canny's (1983) criteria for edge detection quality: good detection, good localization, and low multiplicity of false detections. Our work differs from Canny's work on two essential points. Here, the criteria are given for discrete sampled signals, i.e., for the real, implemented filters. Instead of a single-step edge as input

Didier Demigny

2002-01-01

115

Theory of optimal orthonormal filter banks  

Microsoft Academic Search

In a previous paper we derived a set of necessary and sufficient conditions for maximizing the coding gain in an orthonormal filter bank. These are referred to as the decorrelation and majorization conditions. While each of these two conditions is individually only necessary and not sufficient, they together form a set of necessary and sufficient conditions. In this paper we

P. P. Vaidyanathan

1996-01-01

116

Robustness of optimal binary filters for sparse noise  

NASA Astrophysics Data System (ADS)

An optimal binary image filter is an operator defined on an observed random set (image) and the output random set estimates some ideal (uncorrupted) random set with minimal error. Assuming the probability law of the ideal process is determined by a parameter vector, the output law is also determined by a parameter vector, and this latter law is a function of the input law and a degradation operator producing the observed image from the ideal image. The robustness question regards the degree to which performance of an optimal filter degrades when it is applied to an image process whose law differs (not too greatly) form the law of the process for which it is optimal. The present paper examines robustness of the optimal translation-invariant binary filter for restoring images degraded by sparse salt-and-pepper noise. An analytical model is developed in terms of prior probabilities of the signal and this model is used to compute a robustness surface.

Dougherty, Edward R.; Grigoryan, Artyom M.

1997-10-01

117

Particle PHD filter multiple target tracking in sonar image  

Microsoft Academic Search

Two contrasting approaches for tracking multiple targets in multi-beam forward-looking sonar images are considered. The first approach is based on assigning a Kalman filter to each target and managing the measurements with gating and a measurement-to-track data association technique. The second approach uses the recently developed particle implementation of the multiple-target probability hypothesis density (PHD) filter and a target state

Daniel Clark; Ioseba Ruiz; Yvan Petillot; Judith Bell

2007-01-01

118

Effects of particle size and velocity on burial depth of airborne particles in glass fiber filters  

SciTech Connect

Air sampling for particulate radioactive material involves collecting airborne particles on a filter and then determining the amount of radioactivity collected per unit volume of air drawn through the filter. The amount of radioactivity collected is frequently determined by directly measuring the radiation emitted from the particles collected on the filter. Counting losses caused by the particle becoming buried in the filter matrix may cause concentrations of airborne particulate radioactive materials to be underestimated by as much as 50%. Furthermore, the dose calculation for inhaled radionuclides will also be affected. The present study was designed to evaluate the extent to which particle size and sampling velocity influence burial depth in glass-fiber filters. Aerosols of high-fired /sup 239/PuO/sub 2/ were collected at various sampling velocities on glass-fiber filters. The fraction of alpha counts lost due to burial was determined as the ratio of activity detected by direct alpha count to the quantity determined by photon spectrometry. The results show that burial of airborne particles collected on glass-fiber filters appears to be a weak function of sampling velocity and particle size. Counting losses ranged from 0 to 25%. A correction that assumes losses of 10 to 15% would ensure that the concentration of airborne alpha-emitting radionuclides would not be underestimated when glass-fiber filters are used. 32 references, 21 figures, 11 tables.

Higby, D.P.

1984-11-01

119

Principal component filter banks for optimal multiresolution analysis  

Microsoft Academic Search

An important issue in multiresolution analysis is that of optimal basis selection. An optimal P-band perfect reconstruction filter bank (PRFB) is derived in this paper, which minimizes the approximation error (in the mean-square sense) between the original signal and its low-resolution version. The resulting PRFB decomposes the input signal into uncorrelated, low-resolution principal components with decreasing variance. Optimality issues are

Michail K. Tsatsanis; Georgios B. Giannakis

1995-01-01

120

Optimal realizable filters and the minimum Euclidean distance principle  

Microsoft Academic Search

Minimizing a Euclidean distance in the complex plane optimizes a wide class of correlation metrics for filters implemented on realistic devices. The algorithm searches over no more than two real scalars (gain and phase). It unifies a variety of previous solutions for special cases (e.g., a maximum signal-to-noise ratio with colored noise and a real filter and a maximum correlation

Richard D. Juday

1993-01-01

121

Convergence results for the particle PHD filter  

Microsoft Academic Search

ó Bayesian single-target tracking techniques can be extended to a multiple-target environment by viewing the multiple-target state as a Random Finite Set, but evaluating the multiple-target posterior distribution is currently computation- ally intractable for real-time applications. A practical alternative to the optimal Bayes multi-target lter is the PHD (Probabil- ity Hypothesis Density) lter , which propagates the rst-order moment of

Daniel Edward Clark; Judith Bell

2006-01-01

122

Optimal tolerance allocation using a multiobjective particle swarm optimizer  

Microsoft Academic Search

Particle swarm optimizers are routinely utilized in engineering design problems, but much work remains to take advantage of\\u000a their full potential in the combined areas of sensitivity analysis and tolerance synthesis. In this paper, a novel Pareto-based\\u000a multiobjective formulation is proposed to enhance the operations of a particle swarm optimizer and systematically distribute\\u000a tolerances among various components of a mechanical

Babak Forouraghi

2009-01-01

123

Nonlinear Statistical Signal Processing: A Particle Filtering Approach  

SciTech Connect

A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations.

Candy, J

2007-09-19

124

Optimization of filtering schemes for broadband astro-combs.  

PubMed

To realize a broadband, large-line-spacing astro-comb, suitable for wavelength calibration of astrophysical spectrographs, from a narrowband, femtosecond laser frequency comb ("source-comb"), one must integrate the source-comb with three additional components: (1) one or more filter cavities to multiply the source-comb's repetition rate and thus line spacing; (2) power amplifiers to boost the power of pulses from the filtered comb; and (3) highly nonlinear optical fiber to spectrally broaden the filtered and amplified narrowband frequency comb. In this paper we analyze the interplay of Fabry-Perot (FP) filter cavities with power amplifiers and nonlinear broadening fiber in the design of astro-combs optimized for radial-velocity (RV) calibration accuracy. We present analytic and numeric models and use them to evaluate a variety of FP filtering schemes (labeled as identical, co-prime, fraction-prime, and conjugate cavities), coupled to chirped-pulse amplification (CPA). We find that even a small nonlinear phase can reduce suppression of filtered comb lines, and increase RV error for spectrograph calibration. In general, filtering with two cavities prior to the CPA fiber amplifier outperforms an amplifier placed between the two cavities. In particular, filtering with conjugate cavities is able to provide <1 cm/s RV calibration error with >300 nm wavelength coverage. Such superior performance will facilitate the search for and characterization of Earth-like exoplanets, which requires <10 cm/s RV calibration error. PMID:23187265

Chang, Guoqing; Li, Chih-Hao; Phillips, David F; Szentgyorgyi, Andrew; Walsworth, Ronald L; Kärtner, Franz X

2012-10-22

125

Accelerating parallel particle swarm optimization via GPU  

Microsoft Academic Search

Particle swarm optimization (PSO) is a population-based stochastic and derivative-free method that has been used to solve various optimization problems due to its simplicity and efficiency. While solving high-dimensional or complicated problems, PSO requires a large number of particles to explore the problem domains and consequently introduces high computational costs. In this paper, we focus on the acceleration of PSO

Yukai Hung; Weichung Wang

2010-01-01

126

Particle Filtering with Factorized Likelihoods for Tracking Facial Features  

Microsoft Academic Search

In the recent years particle filtering has been the dominant paradigm for tracking facial and body features, recogniz- ing temporal events and reasoning in uncertainty. A major problem associated with it is that its performance deterio- rates drastically when the dimensionality of the state space is high. In this paper, we address this problem when the state space can be

Ioannis Patras; Maja Pantic

2004-01-01

127

Particle Filter for INS In-Motion Alignment  

Microsoft Academic Search

This paper presents a nonlinear dynamical model for the in-motion alignment of the inertial navigation system (INS) in the case that the observation variable is the velocity information. It allows the initial misalignment uncertainty. Therefore, this model is also suitable for the transfer alignment based on the velocity matching algorithm. Then the Gaussian particle filter (GPF) is analyzed and utilized

Yanling Hao; Zhilan Xiong; Zaigang Hu

2006-01-01

128

Particle Filtering for Multiple Object Tracking in Molecular Cell Biology  

Microsoft Academic Search

Motion analysis of subcellular structures in living cells is currently a major topic in molecular cell biology, for which computerized methods are desperately needed. In this paper we adopt and tailor particle filtering techniques for this purpose and present the results of robust and accurate tracking of multiple objects in real fluorescence microscopy image data acquired for specific biological studies.

Ihor Smal; Wiro Niessen; Erik Meijering

2006-01-01

129

Real-world particle filtering-based speech enhancement  

Microsoft Academic Search

This paper presents a viable particle filtering (PF) solution for single microphone speech enhancement in real-world conditions, i.e., operating at low SNR in nonstationary noise environments, while remaining computationally tractable. The enhancement takes place in the subband domain with elementary PFs in each band. To efficiently handle complex noise situations, the noise spectrum is modelled in each band as a

Frederic Mustiere; Miodrag Bolic; Martin Bouchard

2010-01-01

130

Fast, parallel implementation of particle filtering on the GPU architecture  

NASA Astrophysics Data System (ADS)

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- ?s 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- ?s 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.

Gelencsér-Horváth, Anna; Tornai, Gábor János; Horváth, András; Cserey, György

2013-12-01

131

State estimation using particle filters in wildfire spread simulation  

Microsoft Academic Search

A fundamental issue in data assimilation of wildfire simulation is to estimate the dynamically changing states, e.g., the fire front position of wildfire, based on observation data of fire sensors. This is a challenging task because of the dynamic and non-linear behavior of fire spread. In this paper, we apply particles filters, also called sequential Monte Carlo methods, to data

Feng Gu; Xuefeng Yan; Xiaolin Hu

2009-01-01

132

Vehicle Detection under Various Lighting Conditions by Incorporating Particle Filter  

Microsoft Academic Search

We propose an automatic system to detect preceding vehicles on the highway under various lighting and different weather conditions based on the computer vision technologies. To adapt to different characteristics of vehicle appearance at daytime and nighttime, four cues including underneath, vertical edge, symmetry and taillight are fused for the preceding vehicle detection. By using particle filter with four cues

Yi-Ming Chan; Shih-Shinh Huang; Li-Chen Fu; Pei-Yung Hsiao

2007-01-01

133

Assessment of optimally filtered recent geodetic mean dynamic topographies  

NASA Astrophysics Data System (ADS)

AbstractRecent geoids from the Gravity Recovery and Climate Experiment (GRACE) and the Gravity field and steady state Ocean Circulation Explorer satellite mission (GOCE) contain useful short-scale information for the construction of a geodetic ocean mean dynamic topography (MDT). The geodetic MDT is obtained from subtracting the geoid from a mean sea surface (MSS) as measured by satellite altimetry. A gainful use of the MDT and an adequate assessment needs an <span class="hlt">optimal</span> <span class="hlt">filtering</span>. This is accomplished here by defining a cutoff length scale dmax for the geoid and applying a Gaussian <span class="hlt">filter</span> with half-width radius r on the MDT. A series of MDTs (GRACE, GOCE, and combined satellite-only (GOCO) solutions) is tested, using different sets of <span class="hlt">filter</span> parameters dmax and r. <span class="hlt">Optimal</span> global and regional dependent <span class="hlt">filter</span> parameters are estimated. To find <span class="hlt">optimal</span> parameters and to assess the resulting MDTs, the geostrophic surface currents induced by the <span class="hlt">filtered</span> geodetic MDT are compared to corrected near-surface currents obtained from the Global Drifter Program (GDP). The global <span class="hlt">optimal</span> cutoff degree and order (d/o) dmax (half-width radius r of the spatial Gaussian <span class="hlt">filter</span>) is 160 (1.1°) for GRACE; 180 (1.1-1.2°) for 1st releases of GOCE (time- and space-wise methods) and GOCO models; and 210 (1.0 degree) for 2nd and 3rd releases of GOCE and GOCO models. The cutoff d/o is generally larger (smaller) and the <span class="hlt">filter</span> length smaller (larger) for regions with strong, small-scale (slow, broad scale) currents. The smallest deviations from the drifter data are obtained with the GOCO03s geoid model, although deviations of other models are only slightly higher.</p> <div class="credits"> <p class="dwt_author">Siegismund, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">134</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/461170"> <span id="translatedtitle">Evolutionary <span class="hlt">Optimization</span> Versus <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span>: Philosophy and Performance Differences</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper investigates the philosophical and performance differences of <span class="hlt">particle</span> swarm and evolutionary <span class="hlt">optimization</span>. The method of processing employed in each technique are first reviewed followed by a summary of their philosophical differences. Comparison experiments involving four non-linear functions well studied in the evolutionary <span class="hlt">optimization</span> literature are used to highlight some performance differences between the techniques.</p> <div class="credits"> <p class="dwt_author">Peter J. Angeline</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">135</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/210366"> <span id="translatedtitle">Limiting performance of <span class="hlt">optimal</span> linear <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We study the lowest achievable mean square estimation error in two limiting <span class="hlt">optimal</span> linearfiltering problems. First, when the intensity of the process noise tends to zero, the lowestachievable mean square estimation error is a function of the unstable poles of the system.Second, when the intensity of the measurement noise tends to zero, the lowest achievablemean square estimation error is a</p> <div class="credits"> <p class="dwt_author">Julio H. Braslavsky; Mar??a M. Seron; David Q. Mayne; Petar V. Kokotovic</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">136</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cc.gatech.edu/fac/Thad.Starner/p/032_20_ARVR/device_synchronization_using_optimal_linear_filter_.pdf"> <span id="translatedtitle">Device synchronization using an <span class="hlt">optimal</span> linear <span class="hlt">filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In order to be convincing and natural, interactive graphics applica- tions must correctly synchronize user motion with rendered graph- ics and sound output. We present a solution to the synchronization problem that is based on <span class="hlt">optimal</span> estimation methods and fixed- lag dataflow techniques. A method for discovering and correcting prediction errors using a generalized likelihood approach is also presented. And</p> <div class="credits"> <p class="dwt_author">Martin Friedmann; Thad Starner; Alex Pentland</p> <p class="dwt_publisher"></p> <p class="publishDate">1992-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">137</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/56942395"> <span id="translatedtitle">Asynchronous <span class="hlt">particle</span> swarm <span class="hlt">optimizer</span> with relearning strategy</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Relearning strategy is a commonly used method to improve human memory or skills. In this work, relearning strategy is adopted in asynchronous <span class="hlt">particle</span> swarm <span class="hlt">optimizer</span> (PSO) to enhance its convergence. Although asynchronous PSO converges faster than synchronous PSO in most cases, it cannot guarantee a high successful rate of reproduction of better offspring in each generation. When a <span class="hlt">particle</span> cannot</p> <div class="credits"> <p class="dwt_author">Bo Jiang; Ning Wang; Xiongxiong He</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">138</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51133999"> <span id="translatedtitle">Development of <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> (PSO) is a new stochastic <span class="hlt">optimization</span> technique based on swarm intelligence. In this paper, we introduce the basic principles of PSO firstly. Then, the research progress on PSO algorithm is summarized in several fields, such as parameter selection and design, population topology, hybrid PSO algorithm etc. Finally, some vital applications and aspects that may be conducted in</p> <div class="credits"> <p class="dwt_author">Yu Chen; Fan Yang; Quan Zou; Chen Lin</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">139</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50293064"> <span id="translatedtitle">Hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimizer</span> with mass extinction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimizer</span> with mass extinction, which has been suggested to be an important mechanism for evolutionary progress in the biological world, is presented to enhance the capacity in reaching an <span class="hlt">optimal</span> solution. The tested results of three benchmark functions indicate this method improves the performance effectively.</p> <div class="credits"> <p class="dwt_author">Xiao-Feng Xie; Wen-Jun Zhang; Zhi-Lian Yang</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">140</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50563593"> <span id="translatedtitle">Defining a Standard for <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> has become a common heuristic technique in the <span class="hlt">optimization</span> community, with many researchers exploring the concepts, issues, and applications of the algorithm. In spite of this attention, there has as yet been no standard definition representing exactly what is involved in modern implementations of the technique. A standard is defined here which is designed to be a</p> <div class="credits"> <p class="dwt_author">Daniel Bratton; James Kennedy</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_6");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return 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<img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">141</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/39257623"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> in High Dimensional Spaces</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a Global <span class="hlt">optimization</span> methods including <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> are usually used to solve <span class="hlt">optimization</span> problems when the\\u000a number of parameters is small (hundreds). In the case of inverse problems the objective (or fitness) function used for sampling\\u000a requires the solution of multiple forward solves. In inverse problems, both a large number of parameters, and very costly\\u000a forward evaluations hamper the use</p> <div class="credits"> <p class="dwt_author">Juan Luis Fernández Martínez; Tapan Mukerji; Esperanza García-Gonzalo</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">142</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/260732"> <span id="translatedtitle">S-procedure in <span class="hlt">optimal</span> non-stochastic <span class="hlt">filtering</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The paper is purposed to extend the field of application of the stan- dard linear-quadratic and H-infinity <span class="hlt">optimization</span>. We consider <span class="hlt">optimal</span> lin- ear <span class="hlt">filtering</span> problem for a class of uncertain systems with non-stochastic exogenous noises and non-linear plant disturbances. The discrete time case is under consideration. However, the results obtained can be ap- plied to continuous-time systems with constant or</p> <div class="credits"> <p class="dwt_author">A. Megretsky</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">143</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010SPIE.7539E...7T"> <span id="translatedtitle">Object tracking by co-trained classifiers and <span class="hlt">particle</span> <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper presents an online object tracking method, in which co-training and <span class="hlt">particle</span> <span class="hlt">filters</span> algorithms cooperate and complement each other for robust and effective tracking. Under framework of <span class="hlt">particle</span> <span class="hlt">filters</span>, the semi-supervised cotraining algorithm is adopted to construct, on-line update, and mutually boost two complementary object classifiers, which consequently improves discriminant ability of <span class="hlt">particles</span> and its adaptability to appearance variants caused by illumination changing, pose verying, camera shaking, and occlusion. Meanwhile, to make sampling procedure more efficient, knowledge from coarse confidence maps and spatial-temporal constraints are introduced by importance sampling. It improves not only the accuracy and efficiency of sampling procedure, but also provides more reliable training samples for co-training. Experimental results verify the effectiveness and robustness of our method.</p> <div class="credits"> <p class="dwt_author">Tang, Liang; Li, Shanqing; Liu, Keyan; Wang, Lei</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">144</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50132550"> <span id="translatedtitle">Matched <span class="hlt">filter</span> bound <span class="hlt">optimization</span> for multiuser downlink transmit beamforming</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper is devoted to the <span class="hlt">optimization</span> of the matched <span class="hlt">filter</span> bounds (MFB) of different co-channel users, using adaptive antenna arrays at base stations for downlink transmit beamforming in cellular mobile communication systems. We mainly consider time division multiple access (TDMA) frequency division duplexing (FDD) based systems. Note that in the case of time division duplexing (TDD), under terrain assumptions</p> <div class="credits"> <p class="dwt_author">Giuseppe Montalbano; D. T. M. Slock</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">145</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=AD485275"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">Filter</span> Design for Sampled Data Systems with Illustrative Examples.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">This paper presents a method of <span class="hlt">optimal</span> <span class="hlt">filter</span> design for sampled data systems, based on the theory originally developed by R. E. Kalman. The first half of the paper deals with the theoretical development of mathematical models for linear, discrete dynami...</p> <div class="credits"> <p class="dwt_author">F. D. Jardine</p> <p class="dwt_publisher"></p> <p class="publishDate">1965-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">146</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/619750"> <span id="translatedtitle">New approaches to constrained <span class="hlt">optimization</span> of digital <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Two algorithms are presented for the design of constrained least-squares digital <span class="hlt">filters</span>. They can bound the error according to user specifications while also minimizing the total weighted squared error (TWSE). Although the two algorithms are very different internally, they produce very similar results. One algorithm produces nearly <span class="hlt">optimal</span> solutions, and the other algorithm produces solutions that are guaranteed to be</p> <div class="credits"> <p class="dwt_author">J. W. Adams; J. L. Sullivan; R. Hashemi; C. Ghadimi; J. Franklin; B. Tucker</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">147</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/40126815"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filtering</span> for Bayesian detection and attribution of climate change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In the conventional approach to the detection of an anthropogenic or other externally forced climate change signal, <span class="hlt">optimal</span> <span class="hlt">filters</span> (fingerprints) are used to maximize the ratio of the observed climate change signal to the natural variability noise. If detection is successful, attribution of the observed climate change to the hypothesized forcing mechanism is carried out in a second step by</p> <div class="credits"> <p class="dwt_author">R. Schnur; Kl. Hasselmann</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">148</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/3489536"> <span id="translatedtitle">On incremental sigma-delta modulation with <span class="hlt">optimal</span> <span class="hlt">filtering</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The paper presents a quantization-theoretic framework for studying incremental sigma-delta (??) data conversion systems. The framework makes it possible to efficiently compute the quantization intervals and hence the transfer function of the quantizer, and to determine the mean square error (MSE) and maximum error for the <span class="hlt">optimal</span> and conventional linear <span class="hlt">filters</span> for first and second order incremental ?? modulators. The</p> <div class="credits"> <p class="dwt_author">Sam Kavusi; Hossein Kakavand; A. E. Gamal</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">149</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009SPIE.7383E..33L"> <span id="translatedtitle">Multi-target track based on mixtures of <span class="hlt">particle</span> <span class="hlt">filtering</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">For the problem of detecting and tracking a varying number of dim small target in IR image sequences, multitarget track-before-detect approach based on mixture models of probability densities is proposed and mixtures of t distribution <span class="hlt">particle</span> <span class="hlt">filters</span> (MTPF) are developed for the implementation of the proposed approach in this paper. The existence of each tracked target is detected by using the sequential likelihood ratio test estimated by the output of component <span class="hlt">particle</span> <span class="hlt">filter</span>. New targets are detected by the appearance probabilities in the discrete occupancy grid in the image frame. The algorithm explicitly handles the instantiation and removal of <span class="hlt">filters</span> in case new objects enter the scene or previously tracked objects are removed. The proposed approach overcomes the curse of dimensionality by estimating each target state independently by using separate <span class="hlt">particle</span> <span class="hlt">filter</span> and avoids the exponential increase in the estimation complexity. Simulation experiments illustrated that the MTPF algorithm can detect and track the variable number of dim small targets in the IR images, and simultaneously detect the disappearance and appearance of targets.</p> <div class="credits"> <p class="dwt_author">Li, Shaojun; Zhu, Zhenfu</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">150</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004JSMEC..47..560J"> <span id="translatedtitle">Acoustic Radiation <span class="hlt">Optimization</span> Using the <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The present paper describes a fundamental study on structural bending design to reduce noise using a new evolutionary population-based heuristic algorithm called the <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm (PSOA). The <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm is a parallel evolutionary computation technique proposed by Kennedy and Eberhart in 1995. This algorithm is based on the social behavior models for bird flocking, fish schooling and other models investigated by zoologists. <span class="hlt">Optimal</span> structural design problems to reduce noise are highly nonlinear, so that most conventional methods are difficult to apply. The present paper investigates the applicability of PSOA to such problems. <span class="hlt">Optimal</span> bending design of a vibrating plate using PSOA is performed in order to minimize noise radiation. PSOA can be effectively applied to such nonlinear acoustic radiation <span class="hlt">optimization</span>.</p> <div class="credits"> <p class="dwt_author">Jeon, Jin-Young; Okuma, Masaaki</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">151</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012MSSP...28...63Z"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">filter</span> based noise removal method for acoustic emission signals</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper discusses the application of a statistical noise removal technique - Rao-Blackwellised <span class="hlt">particle</span> <span class="hlt">filter</span> (RBPF) for signal to noise ratio (SNR) enhancement of acoustic emission (AE) signals. RBPF is a recursive Bayesian method for dynamic system state estimation. Compared with other signal <span class="hlt">filtering</span> methods, RBPF offers the advantage of broad-band signal cleansing by directly modeling the internal dynamics of the concerned physical system and statistical characteristics of the signal noise. In doing so, signal <span class="hlt">filtering</span> can be related to the dynamic characteristics of the underlying physical system, rather than a purely mathematical operation. RBPF also outperforms a few other statistical signal <span class="hlt">filtering</span> methods such as Kalman <span class="hlt">filter</span>, with the ability of handling nonlinear system and non-Gaussian noise problems. Another feature of RBPF is its ability to allow real-time on-board signal processing. In this paper, moment tensor analysis was performed first to generate simulated baseline AE signals. The simulated AE signal was subsequently superimposed with noise to demonstrate the effectiveness of the RBPF method in <span class="hlt">filtering</span> noise in the AE signals. The results show that the performance of the RBPF in SNR enhancement is very promising. Finally, RBPF is also applied to real AE data obtained from experimental tests and apparent improvement to the SNR in AE feature study is observed.</p> <div class="credits"> <p class="dwt_author">Zhou, Changjiang; Zhang, Yunfeng</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">152</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009LNCS.5748....1I"> <span id="translatedtitle">A 3-Component Inverse Depth Parameterization for <span class="hlt">Particle</span> <span class="hlt">Filter</span> SLAM</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The non-Gaussianity of the depth estimate uncertainty degrades the performance of monocular extended Kalman <span class="hlt">filter</span> SLAM (EKF-SLAM) systems employing a 3-component Cartesian landmark parameterization, especially in low-parallax configurations. Even <span class="hlt">particle</span> <span class="hlt">filter</span> SLAM (PF-SLAM) approaches are affected, as they utilize EKF for estimating the map. The inverse depth parameterization (IDP) alleviates this problem through a redundant representation, but at the price of increased computational complexity. The authors show that such a redundancy does not exist in PF-SLAM, hence the performance advantage of the IDP comes almost without an increase in the computational cost.</p> <div class="credits"> <p class="dwt_author">Imre, Evren; Berger, Marie-Odile</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">153</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20837447"> <span id="translatedtitle">Cultural-based multiobjective <span class="hlt">particle</span> swarm <span class="hlt">optimization</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Multiobjective <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (MOPSO) algorithms have been widely used to solve multiobjective <span class="hlt">optimization</span> problems. Most MOPSOs use fixed momentum and acceleration for all <span class="hlt">particles</span> throughout the evolutionary process. In this paper, we introduce a cultural framework to adapt the personalized flight parameters of the mutated <span class="hlt">particles</span> in a MOPSO, namely momentum and personal and global accelerations, for each individual <span class="hlt">particle</span> based upon various types of knowledge in "belief space," specifically situational, normative, and topographical knowledge. A comprehensive comparison of the proposed algorithm with chosen state-of-the-art MOPSOs on benchmark test functions shows that the movement of the individual <span class="hlt">particle</span> using the adapted parameters assists the MOPSO to perform efficiently and effectively in exploring solutions close to the true Pareto front while exploiting a local search to attain diverse solutions. PMID:20837447</p> <div class="credits"> <p class="dwt_author">Daneshyari, Moayed; Yen, Gary G</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-09-09</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">154</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8745E..0PD"> <span id="translatedtitle"><span class="hlt">Particle</span> flow with non-zero diffusion for nonlinear <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We derive several new algorithms for <span class="hlt">particle</span> flow with non-zero diffusion corresponding to Bayes' rule. This is unlike all of our previous <span class="hlt">particle</span> flows, which assumed zero diffusion for the flow corresponding to Bayes' rule. We emphasize, however, that all of our <span class="hlt">particle</span> flows have always assumed non-zero diffusion for the dynamical model of the evolution of the state vector in time. Our new algorithm is simple and fast, and it has an especially nice intuitive formula, which is the same as Newton's method to solve the maximum likelihood estimation (MLE) problem (but for each <span class="hlt">particle</span> rather than only the MLE), and it is also the same as the extended Kalman <span class="hlt">filter</span> for the special case of Gaussian densities (but for each <span class="hlt">particle</span> rather than just the point estimate). All of these new flows apply to arbitrary multimodal densities with smooth nowhere vanishing non-Gaussian densities.</p> <div class="credits"> <p class="dwt_author">Daum, Fred; Huang, Jim</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">155</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=PB93167278"> <span id="translatedtitle">Computations on the Performance of <span class="hlt">Particle</span> <span class="hlt">Filters</span> and Electronic Air Cleaners.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The paper discusses computations on the performance of <span class="hlt">particle</span> <span class="hlt">filters</span> and electronic air cleaners (EACs). The collection efficiency of <span class="hlt">particle</span> <span class="hlt">filters</span> and EACs is calculable if certain factors can be assumed or calibrated. For fibrous particulate filte...</p> <div class="credits"> <p class="dwt_author">P. A. Lawless A. S. Viner D. S. Ensor L. E. Sparks</p> <p class="dwt_publisher"></p> <p class="publishDate">1990-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">156</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23434235"> <span id="translatedtitle">A novel method for retinal vessel tracking using <span class="hlt">particle</span> <span class="hlt">filters</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Extraction of a proper map from the vessel paths in the retinal images is a prerequisite for many applications such as identification. In this paper, we present a new approach based on <span class="hlt">particle</span> <span class="hlt">filtering</span> to determine and locally track the vessel paths in retina. <span class="hlt">Particle</span> <span class="hlt">filter</span> needs to use an acceptable probability density function (PDF) describing the blood vessels which must be provided by the retinal image. For this purpose, the product of the green and blue channels of the RGB retinal images is considered and after a median <span class="hlt">filtering</span> stage, it is used as a PDF for tracking procedure. Then a stage of optic disc localization is performed to localize the starting points around the optic disc. With a proper set of starting points, the iterative tracking procedure initiates. First, a uniform propagation of the <span class="hlt">particles</span> on an annular ring around each point (including starting points or ones determined as central points in the previous iteration) is performed. The <span class="hlt">particle</span> weights are evaluated and accordingly, each <span class="hlt">particle</span> is decided to be inside or outside the vessel. The subsequent stage is to analyze the hypothetical vectors between a central point and each of the inside vessel <span class="hlt">particles</span> to find ones located inside vessel. Afterwards, the <span class="hlt">particles</span> are clustered using quality threshold clustering method. Finally, each cluster introduces a central point for pursuing the tracking procedure in the next iteration. The tracking proceeds towards a bifurcation or the end of the vessels. We introduced two criteria: automatic/manually tracked ratio (AMTR) and false/manually tracked ratio (FMTR) for evaluating the tracking results. Apart from the labeling accuracy, the average values of AMTR and FMTR were 0.7746 and 0.2091, respectively. The proposed method successfully deals with the bifurcations with robustness against noise and tracks the thin vessels. PMID:23434235</p> <div class="credits"> <p class="dwt_author">Nayebifar, B; Abrishami Moghaddam, H</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-02-21</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">157</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20519156"> <span id="translatedtitle">Selection of <span class="hlt">optimal</span> spectral sensitivity functions for color <span class="hlt">filter</span> arrays.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color <span class="hlt">filter</span> array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color <span class="hlt">filters</span> affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually <span class="hlt">optimal</span> color <span class="hlt">filter</span> sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain <span class="hlt">optimal</span> values of color-<span class="hlt">filter</span> sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color <span class="hlt">filters</span> in terms of both the s-CIELAB ?E error metric and a qualitative assessment. PMID:20519156</p> <div class="credits"> <p class="dwt_author">Parmar, Manu; Reeves, Stanley J</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">158</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/971830"> <span id="translatedtitle">A <span class="hlt">filter</span>-based evolutionary algorithm for constrained <span class="hlt">optimization</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We introduce a <span class="hlt">filter</span>-based evolutionary algorithm (FEA) for constrained <span class="hlt">optimization</span>. The <span class="hlt">filter</span> used by an FEA explicitly imposes the concept of dominance on a partially ordered solution set. We show that the algorithm is provably robust for both linear and nonlinear problems and constraints. FEAs use a finite pattern of mutation offsets, and our analysis is closely related to recent convergence results for pattern search methods. We discuss how properties of this pattern impact the ability of an FEA to converge to a constrained local optimum.</p> <div class="credits"> <p class="dwt_author">Clevenger, Lauren M. (University of New Mexico); Hart, William Eugene; Ferguson, Lauren Ann (Texas Tech University)</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">159</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010SPIE.7997E..27D"> <span id="translatedtitle">Machining fixture layout <span class="hlt">optimization</span> using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Optimization</span> of fixture layout (locator and clamp locations) is critical to reduce geometric error of the workpiece during machining process. In this paper, the application of <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm is presented to minimize the workpiece deformation in the machining region. A PSO based approach is developed to <span class="hlt">optimize</span> fixture layout through integrating ANSYS parametric design language (APDL) of finite element analysis to compute the objective function for a given fixture layout. <span class="hlt">Particle</span> library approach is used to decrease the total computation time. The computational experiment of 2D case shows that the numbers of function evaluations are decreased about 96%. Case study illustrates the effectiveness and efficiency of the PSO based <span class="hlt">optimization</span> approach.</p> <div class="credits"> <p class="dwt_author">Dou, Jianping; Wang, Xingsong; Wang, Lei</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">160</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/39230017"> <span id="translatedtitle">A variant of <span class="hlt">particle</span> <span class="hlt">filtering</span> using historic datasets for tracking complex geospatial phenomena</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The paper presents an extension of the <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithm that is applicable when an accurate state prediction model cannot be specified but a database of prior state evolution tracks is available. The conventional <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithm represents the belief state as a collection of <span class="hlt">particles</span>, where each <span class="hlt">particle</span> is a sample from the state space. The <span class="hlt">particles</span> are updated</p> <div class="credits"> <p class="dwt_author">Anand Panangadan; Ashit Talukder</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_7");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return 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<img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">161</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010IEITC..93..336Y"> <span id="translatedtitle">Marginalized <span class="hlt">Particle</span> <span class="hlt">Filter</span> for Blind Signal Detection with Analog Imperfections</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recently, the marginalized <span class="hlt">particle</span> <span class="hlt">filter</span> (MPF) has been applied to blind symbol detection problems over selective fading channels. The MPF can ease the computational burden of the standard <span class="hlt">particle</span> <span class="hlt">filter</span> (PF) while offering better estimates compared with the standard PF. In this paper, we investigate the application of the blind MPF detector to more realistic situations where the systems suffer from analog imperfections which are non-linear signal distortion due to the inaccurate analog circuits in wireless devices. By reformulating the system model using the widely linear representation and employing the auxiliary variable resampling (AVR) technique for estimation of the imperfections, the blind MPF detector is successfully modified to cope with the analog imperfections. The effectiveness of the proposed MPF detector is demonstrated via computer simulations.</p> <div class="credits"> <p class="dwt_author">Yoshida, Yuki; Hayashi, Kazunori; Sakai, Hideaki; Bocquet, Wladimir</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">162</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012ExFl...52.1361H"> <span id="translatedtitle">Spatial <span class="hlt">filter</span> velocimetry based on time-series <span class="hlt">particle</span> images</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">High accuracy and high spatial resolution are required in measurements of fluid velocity for detailed flow diagnostics. In this study, we proposed spatial <span class="hlt">filter</span> velocimetry (SFV) based on a frequency analysis of time-series spatially <span class="hlt">filtered</span> <span class="hlt">particle</span> images. Since this method can measure velocity from one <span class="hlt">particle</span> in a measurement region, it enables us to measure the velocity with high accuracy and high spatial resolution. We developed a SFV system and applied it to laminar and turbulent flows in a duct to examine its performance. Comparisons between the velocities measured by SFV and LDV confirmed that SFV accurately measures the mean velocity and turbulent intensity with spatial and temporal resolutions as high as LDV.</p> <div class="credits"> <p class="dwt_author">Hosokawa, Shigeo; Tomiyama, Akio</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">163</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://nlpr-web.ia.ac.cn/english/irds/papers/sancf/FG2004.pdf"> <span id="translatedtitle">Real Time Hand Tracking by Combining <span class="hlt">Particle</span> <span class="hlt">Filtering</span> and Mean Shift</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Particle</span> <span class="hlt">filter</span> and mean shift are two successful approaches taken in the pursuit of robust tracking. Both of them have their respective strengths and weaknesses. In this paper, we proposed a new tracking algorithm, the Mean Shift Embedded <span class="hlt">Particle</span> <span class="hlt">Filter</span> (MSEPF), to integrate advantages of the two methods. Compared with the conventional <span class="hlt">particle</span> <span class="hlt">filter</span>, the MSEPF leads to more efficient</p> <div class="credits"> <p class="dwt_author">Caifeng Shan; Yucheng Wei; Tieniu Tan; Frédéric Ojardias</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">164</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/6088020"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">Filter</span> SLAM with High Dimensional Vehicle Model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This work presents a <span class="hlt">particle</span> <span class="hlt">filter</span> method closely related to Fastslam for solving the simultaneous localization and mapping (slam) problem. Using the standard Fastslam algorithm, only low-dimensional vehicle models can be handled due to computational constraints. In this work, an extra factorization\\u000a of the problem is introduced that makes high-dimensional vehicle models computationally feasible. Results using experimental\\u000a data from an</p> <div class="credits"> <p class="dwt_author">David Törnqvist; Thomas B. Schön; Rickard Karlsson; Fredrik Gustafsson</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">165</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://orbit.dtu.dk/app;jsessionid=1C89342C4753F4D69005985E883B54AB?cdis=attachment%3B+filename%3D%22particlefiltersinglespaced%5B1%5D.pdf%22&ctyp=application%2Fpdf&downloadOptionName=URL&service=download_records&url=http%3A%2F%2Furbit.cvt.dk%2Fcgi-bin%2Furbit_fulltext%2F209409%2F1%2F1%2F4038a830c4cf63611aaaca6541e9c07e"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">Filter</span> Inference in an Articulatory Based Speech Model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A time-varying auto-regressive speech model pa- rameterized by formant frequencies, formant bandwidths and formant gains is proposed. Inference in the model is made by <span class="hlt">particle</span> <span class="hlt">filtering</span> for the application of speech enhancement. The advantage of the proposed parametrization over existing param- eterizations based on AR coefficients or reflection coefficients is the smooth time-varying behavior of the parameters and their loose</p> <div class="credits"> <p class="dwt_author">Thomas Beierholm; Ole Winther</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">166</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ee.kth.se/php/modules/publications/reports/2005/IR-SB-EX-0518.pdf"> <span id="translatedtitle">Tempo Tracking of Musical Signals with <span class="hlt">Particle</span> <span class="hlt">Filtering</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Abstract Tempo estimation is fundamental in music content analysis. In this thesis, we present a tempo,tracking algorithm,to estimate the beats per minute,for a given musical signal. The algorithm,consists of two stages; an onset detection to extract the time instants where,music,properties change,and a periodicity detection using <span class="hlt">particle</span> <span class="hlt">filter</span> to give a series of estimated,tempos.,The onset detection combines,a high frequency,content (HFC) method,and</p> <div class="credits"> <p class="dwt_author">YUNYI XIAO</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">167</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/58929783"> <span id="translatedtitle"><span class="hlt">OPTIMAL</span> TRANSACTION <span class="hlt">FILTERS</span> UNDER TRANSITORY TRADING OPPORTUNITIES: Theory and Empirical Illustration</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">If transitory profitable trading opportunities exist, <span class="hlt">filter</span> rules are used in practice to mitigate transaction costs. The <span class="hlt">filter</span> size is difficult to determine a priori. Our paper uses a dynamic programming framework to design a <span class="hlt">filter</span> that is <span class="hlt">optimal</span> in the sense of maximizing expected returns after transaction costs. The <span class="hlt">optimal</span> <span class="hlt">filter</span> size depends crucially on the degree of persistence</p> <div class="credits"> <p class="dwt_author">RONALD J. BALVERS; YANGRU WU</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">168</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005SPIE.5809..313C"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">filter</span> with iterative importance sampling for Bayesian networks inference</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Bayesian network has been applied widely in many areas such as multi-sensor fusion, situation assessment, and decision making under uncertainty. It is well known that, in general when dealing with large complex networks, the exact probabilistic inference methods are computationally difficult or impossible. To deal with the difficulty, the "anytime" stochastic simulation methods such as likelihood weighting and importance sampling have become popular. In this paper, we introduce a very efficient iterative importance sampling algorithm for Bayesian network inference. Much like the recently popular sequential simulation method, <span class="hlt">particle</span> <span class="hlt">filter</span>, this algorithm identifies importance function and conducts sampling iteratively. However, <span class="hlt">particle</span> <span class="hlt">filter</span> methods often run into the so called "degeneration" or "impoverishment" problems due to low likely evidence or high dimensional sampling space. To overcome that, this Bayesian network <span class="hlt">particle</span> <span class="hlt">filter</span> (BNPF) algorithm decomposes the global state space into local ones based on the network structure and learns the importance function accordingly in an iterative manner. We used large real world Bayesian network models available in academic community to test the inference method. The preliminary simulation results show that the algorithm is very promising.</p> <div class="credits"> <p class="dwt_author">Chang, K. C.; He, Donghai</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">169</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013InvPr..29h5007A"> <span id="translatedtitle">Linear multistep methods, <span class="hlt">particle</span> <span class="hlt">filtering</span> and sequential Monte Carlo</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Numerical integration is the main bottleneck in <span class="hlt">particle</span> <span class="hlt">filter</span> methodologies for dynamic inverse problems to estimate model parameters, initial values, and non-observable components of an ordinary differential equation (ODE) system from partial, noisy observations, because proposals may result in stiff systems which first slow down or paralyze the time integration process, then end up being discarded. The immediate advantage of formulating the problem in a sequential manner is that the integration is carried out on shorter intervals, thus reducing the risk of long integration processes followed by rejections. We propose to solve the ODE systems within a <span class="hlt">particle</span> <span class="hlt">filter</span> framework with higher order numerical integrators which can handle stiffness and to base the choice of the variance of the innovation on estimates of the discretization errors. The application of linear multistep methods to <span class="hlt">particle</span> <span class="hlt">filters</span> gives a handle on the stability and accuracy of the propagation, and linking the innovation variance to the accuracy estimate helps keep the variance of the estimate as low as possible. The effectiveness of the methodology is demonstrated with a simple ODE system similar to those arising in biochemical applications.</p> <div class="credits"> <p class="dwt_author">Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">170</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.H41I..07H"> <span id="translatedtitle">Ensemble Data Assimilation for Streamflow Forecasting: Experiments with Ensemble Kalman <span class="hlt">Filter</span> and <span class="hlt">Particle</span> <span class="hlt">Filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present results of data assimilation of ground discharge observation and remotely sensed soil moisture observations into Sacramento Soil Moisture Accounting (SACSMA) model in a small watershed (1593 km2) in Minnesota, the Unites States. Specifically, we perform assimilation experiments with Ensemble Kalman <span class="hlt">Filter</span> (EnKF) and <span class="hlt">Particle</span> <span class="hlt">Filter</span> (PF) in order to improve streamflow forecast accuracy at six hourly time step. The EnKF updates the soil moisture states in the SACSMA from the relative errors of the model and observations, while the PF adjust the weights of the state ensemble members based on the likelihood of the forecast. Results of the improvements of each <span class="hlt">filter</span> over the reference model (without data assimilation) will be presented. Finally, the EnKF and PF are coupled together to further improve the streamflow forecast accuracy.</p> <div class="credits"> <p class="dwt_author">Hirpa, F. A.; Gebremichael, M.; Hopson, T. M.; Wojick, R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">171</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1636674"> <span id="translatedtitle"><span class="hlt">Optimal</span> Noise <span class="hlt">Filtering</span> in the Chemotactic Response of Escherichia coli</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Information-carrying signals in the real world are often obscured by noise. A challenge for any system is to <span class="hlt">filter</span> the signal from the corrupting noise. This task is particularly acute for the signal transduction network that mediates bacterial chemotaxis, because the signals are subtle, the noise arising from stochastic fluctuations is substantial, and the system is effectively acting as a differentiator which amplifies noise. Here, we investigated the <span class="hlt">filtering</span> properties of this biological system. Through simulation, we first show that the cutoff frequency has a dramatic effect on the chemotactic efficiency of the cell. Then, using a mathematical model to describe the signal, noise, and system, we formulated and solved an <span class="hlt">optimal</span> <span class="hlt">filtering</span> problem to determine the cutoff frequency that bests separates the low-frequency signal from the high-frequency noise. There was good agreement between the theory, simulations, and published experimental data. Finally, we propose that an elegant implementation of the <span class="hlt">optimal</span> <span class="hlt">filter</span> in combination with a differentiator can be achieved via an integral control system. This paper furnishes a simple quantitative framework for interpreting many of the key notions about bacterial chemotaxis, and, more generally, it highlights the constraints on biological systems imposed by noise.</p> <div class="credits"> <p class="dwt_author">Andrews, Burton W; Yi, Tau-Mu; Iglesias, Pablo A</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">172</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.math.upatras.gr/~kostasp/papers/NatComp.pdf"> <span id="translatedtitle">Recent approaches to global <span class="hlt">optimization</span> problems through <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents an overview of our most recent results concerning the <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) method. Techniques for the alleviation of local minima, and for detecting multiple minimizers are described. Moreover, results on the ability of the PSO in tackling Multiobjective, Minimax, Integer Programming and ? 1 errors-in-variables problems, as well as problems in noisy and continuously changing environments,</p> <div class="credits"> <p class="dwt_author">Konstantinos E. Parsopoulos; Michael N. Vrahatis</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">173</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011NIMPA.645..300L"> <span id="translatedtitle">Design and <span class="hlt">optimization</span> of multipole lens and Wien <span class="hlt">filter</span> systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The differential algebra (DA) method has been employed to compute the optical properties and aberrations up to the fifth order of multipole systems containing electrostatic and magnetic round, quadrupole, hexapole and octopole lenses, and Wien <span class="hlt">filters</span>. A new software package has been developed, which computes the geometrical and chromatic aberrations up to the fifth order by using a single DA ray trace. It also has an <span class="hlt">optimization</span> module where a weighted set of aberrations can be minimized by the automatic adjustment of a set of user-defined system variables. In this paper, we present our new method for designing and <span class="hlt">optimizing</span> multipole systems including Wien <span class="hlt">filters</span>, and illustrate its application with three relevant examples.</p> <div class="credits"> <p class="dwt_author">Liu, Haoning; Wang, Liping; Rouse, John; Munro, Eric</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">174</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1990apcb.conf...73N"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filter</span> techniques for quasi-periodic oscillations.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Optimal</span> <span class="hlt">filter</span> analysis techniques are employed in order to set constraints on the nature of possible relationships between low frequency noise (LFN) and quasiperiodic oscillations (QPOs) in GX 5-1 on timescales near the QPO coherence length. Models are explored in which LFN shots modulate sinusoidal QPOs for shot rates up to 400 Hz and shot clustering fractions up to ?50%. Such models are found to be constrained by comparison with the data.</p> <div class="credits"> <p class="dwt_author">Norris, J. P.; Hertz, P.; Wood, K. S.; Vaughan, B. A.; Michelson, P. F.; Mitsuda, K.; Dotani, T.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">175</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/24290712"> <span id="translatedtitle">AN <span class="hlt">OPTIMAL</span> EXTENDED KALMAN <span class="hlt">FILTER</span> DESIGNED BY GENETIC ALGORITHMS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A Geno-Kalman <span class="hlt">filter</span> is utilized for state estimation of a bench-scale batch reactor that handles an exothermic reaction between H2O2 and Na2S2O3. This reaction system includes three different states including the concentration of reactants as well as the temperature of the reactor. All of the states are measured during the process. The proposed procedure is to run an <span class="hlt">optimal</span> extended</p> <div class="credits"> <p class="dwt_author">N. Rezaei; H. Kordabadi; A. Elkamel; A. Jahanmiri</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">176</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50993739"> <span id="translatedtitle">A Simplified Adaptive <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A new <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm is presented based on three methods of improvement in original PSO. First, the iteration formula of PSO is changed and simplified by removal of velocity parameter that is unnecessary during the course of evolution. Second, the dynamically decreasing inertia weight is employed to enhance the balance of global and local search of algorithm.</p> <div class="credits"> <p class="dwt_author">Zhigang Zhao; Cheng Chang</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">177</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50461411"> <span id="translatedtitle">Congestion management based on <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">After analyzing the regulation of North East China electricity market and the constraint of safe operation of unit and transmission grid, this paper proposes a congestion management model that is appropriate for power pool. PSO (<span class="hlt">particle</span> swarm <span class="hlt">optimizer</span>) is introduced to solve the complex nonlinear model. The results caused by different PSO parameters are analyzed through using IEEE30 bus system.</p> <div class="credits"> <p class="dwt_author">Zhi xu Chen; Li zi Zhang; Jun Shu</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">178</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007LNCS.4682..770C"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> with Dynamic Step Length</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> (PSO) is a robust swarm intelligent technique inspired from birds flocking and fish schooling. Though many effective improvements have been proposed, however, the premature convergence is still its main problem. Because each <span class="hlt">particle</span>'s movement is a continuous process and can be modelled with differential equation groups, a new variant, <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> with dynamic step length (PSO-DSL), with additional control coefficient- step length, is introduced. Then the absolute stability theory is introduced to analyze the stability character of the standard PSO, the theoretical result indicates the PSO with constant step length can not always be stable, this may be one of the reason for premature convergence. Simulation results show the PSO-DSL is effective.</p> <div class="credits"> <p class="dwt_author">Cui, Zhihua; Cai, Xingjuan; Zeng, Jianchao; Sun, Guoji</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">179</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008EnOp...40.1031Z"> <span id="translatedtitle">Solving constrained <span class="hlt">optimization</span> problems with hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Constrained <span class="hlt">optimization</span> problems (COPs) are very important in that they frequently appear in the real world. A COP, in which both the function and constraints may be nonlinear, consists of the <span class="hlt">optimization</span> of a function subject to constraints. Constraint handling is one of the major concerns when solving COPs with <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) combined with the Nelder-Mead simplex search method (NM-PSO). This article proposes embedded constraint handling methods, which include the gradient repair method and constraint fitness priority-based ranking method, as a special operator in NM-PSO for dealing with constraints. Experiments using 13 benchmark problems are explained and the NM-PSO results are compared with the best known solutions reported in the literature. Comparison with three different meta-heuristics demonstrates that NM-PSO with the embedded constraint operator is extremely effective and efficient at locating <span class="hlt">optimal</span> solutions.</p> <div class="credits"> <p class="dwt_author">Zahara, Erwie; Hu, Chia-Hsin</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">180</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57764932"> <span id="translatedtitle">Variation in Penetration of Submicrometric <span class="hlt">Particles</span> Through Electrostatic <span class="hlt">Filtering</span> Facepieces During Exposure to Paraffin Oil Aerosol</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Several studies show the increase of penetration through electrostatic <span class="hlt">filters</span> during the exposure to an aerosol flow because of <span class="hlt">particle</span> deposition on <span class="hlt">filter</span> fibers. We studied the effect of increasing loads of paraffin oil aerosol on the penetration of selected <span class="hlt">particle</span> sizes through a model of electrostatic <span class="hlt">filtering</span> facepiece. FFP2 facepieces were exposed for 8 hr to a flow rate</p> <div class="credits"> <p class="dwt_author">Carmela Plebani; Stefano Listrani; Giovanna Tranfo; Francesca Tombolini</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_8");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' 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showDiv("page_11");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">181</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/672026"> <span id="translatedtitle">A multi-dimensional procedure for BNCT <span class="hlt">filter</span> <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">An initial version of an <span class="hlt">optimization</span> code utilizing two-dimensional radiation transport methods has been completed. This code is capable of predicting material compositions of a beam tube-<span class="hlt">filter</span> geometry which can be used in a boron neutron capture therapy treatment facility to improve the ratio of the average radiation dose in a brain tumor to that in the healthy tissue surrounding the tumor. The <span class="hlt">optimization</span> algorithm employed by the code is very straightforward. After an estimate of the gradient of the dose ratio with respect to the nuclide densities in the beam tube-<span class="hlt">filter</span> geometry is obtained, changes in the nuclide densities are made based on: (1) the magnitude and sign of the components of the dose ratio gradient, (2) the magnitude of the nuclide densities, (3) the upper and lower bound of each nuclide density, and (4) the linear constraint that the sum of the nuclide density fractions in each material zone be less than or equal to 1.0. A local <span class="hlt">optimal</span> solution is assumed to be found when one of the following conditions is satisfied in every material zone: (1) the maximum positive component of the gradient corresponds to a nuclide at its maximum density and the sum of the density fractions equals 1.0 or, and (2) the positive and negative components of the gradient correspond to nuclides densities at their upper and lower bounds, respectively, and the remaining components of the gradient are sufficiently small. The <span class="hlt">optimization</span> procedure has been applied to a beam tube-<span class="hlt">filter</span> geometry coupled to a simple tumor-patient head model and an improvement of 50% in the dose ratio was obtained.</p> <div class="credits"> <p class="dwt_author">Lille, R.A.</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">182</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18681501"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">filtering</span> for dispersion curve tracking in ocean acoustics.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">A <span class="hlt">particle</span> <span class="hlt">filtering</span> method is developed for dispersion curve extraction from spectrograms of broadband acoustic signals propagating in underwater media. The goal is to obtain accurate representation of modal dispersion which can be employed for source localization and geoacoustic inversion. Results are presented from the application of the method to synthetic data, demonstrating the potential of the approach for accurate estimation of waveguide dispersion characteristics. The method outperforms simple time-frequency analysis providing estimates that are very close to numerically calculated dispersion curves. The method also provides uncertainty information on modal arrival time estimates, typically unavailable when traditional methods are used. PMID:18681501</p> <div class="credits"> <p class="dwt_author">Zorych, Ivan; Michalopoulou, Zoi-Heleni</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">183</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012TISCI..24..250M"> <span id="translatedtitle">Parameter Identification of Linear Approximation Models through <span class="hlt">Particle</span> <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper considers system identification for linearly approximated models. Linear approximation models are useful for identification, but their accuracy may not be estimated by the conventional linear identification methods. This paper proposes a method to evaluate not only the system parameters but also the influence of the linear approximation errors in identification. The method is based on <span class="hlt">particle</span> <span class="hlt">filters</span>, which are known for its applicability to a wide class of nonlinear systems. Numerical examples are given to demonstrate the effectiveness of the proposed method in detail. Furthermore, experimental validation is performed for a simple pendulum system.</p> <div class="credits"> <p class="dwt_author">Masuda, Tetsuya; Sugie, Toshiharu</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">184</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/909252"> <span id="translatedtitle">Loss of Fine <span class="hlt">Particle</span> Ammonium from Denuded Nylon <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Ammonium is an important constituent of fine particulate mass in the atmosphere, but can be difficult to quantify due to possible sampling artifacts. Losses of semivolatile species such as NH4NO3 can be particularly problematic. In order to evaluate ammonium losses from aerosol <span class="hlt">particles</span> collected on <span class="hlt">filters</span>, a series of field experiments was conducted using denuded nylon and Teflon <span class="hlt">filters</span> at Bondville, Illinois (February 2003), San Gorgonio, California (April 2003 and July 2004), Grand Canyon National Park, Arizona (May, 2003), Brigantine, New Jersey (November 2003), and Great Smoky Mountains National Park (NP), Tennessee (July–August 2004). Samples were collected over 24-hr periods. Losses from denuded nylon <span class="hlt">filters</span> ranged from 10% (monthly average) in Bondville, Illinois to 28% in San Gorgonio, California in summer. Losses on individual sample days ranged from 1% to 65%. Losses tended to increase with increasing diurnal temperature and relative humidity changes and with the fraction of ambient total N(--III) (particulate NH4+ plus gaseous NH3) present as gaseous NH3. The amount of ammonium lost at most sites could be explained by the amount of NH4NO3 present in the sampled aerosol. Ammonium losses at Great Smoky Mountains NP, however, significantly exceeded the amount of NH4NO3 collected. Ammoniated organic salts are suggested as additional important contributors to observed ammonium loss at this location.</p> <div class="credits"> <p class="dwt_author">Yu, Xiao-Ying; Lee, Taehyoung; Ayres, Benjamin; Kreidenweis, Sonia M.; Malm, William C.; Collett, Jeffrey L.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">185</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005ClDy...24...45S"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filtering</span> for Bayesian detection and attribution of climate change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In the conventional approach to the detection of an anthropogenic or other externally forced climate change signal, <span class="hlt">optimal</span> <span class="hlt">filters</span> (fingerprints) are used to maximize the ratio of the observed climate change signal to the natural variability noise. If detection is successful, attribution of the observed climate change to the hypothesized forcing mechanism is carried out in a second step by comparing the observed and predicted climate change signals. In contrast, the Bayesian approach to detection and attribution makes no distinction between detection and attribution. The purpose of <span class="hlt">filtering</span> in this case is to maximize the impact of the evidence, the observed climate change, on the prior probability that the hypothesis of an anthropogenic origin of the observed signal is true. Whereas in the conventional approach model uncertainties have no direct impact on the definition of the <span class="hlt">optimal</span> detection fingerprint, in <span class="hlt">optimal</span> Bayesian <span class="hlt">filtering</span> they play a central role. The number of patterns retained is governed by the magnitude of the predicted signal relative to the model uncertainties, defined in a pattern space normalized by the natural climate variability. Although this results in some reduction of the original phase space, this is not the primary objective of Bayesian <span class="hlt">filtering</span>, in contrast to the conventional approach, in which dimensional reduction is a necessary prerequisite for enhancing the signal-to-noise ratio. The Bayesian <span class="hlt">filtering</span> method is illustrated for two anthropogenic forcing hypotheses: greenhouse gases alone, and a combination of greenhouse gases plus sulfate aerosols. The hypotheses are tested against 31-year trends for near-surface temperature, summer and winter diurnal temperature range, and precipitation. Between six and thirteen response patterns can be retained, as compared with the one or two response patterns normally used in the conventional approach. Strong evidence is found for the detection of an anthropogenic climate change in temperature, with some preference given to the combined forcing hypothesis. Detection of recent anthropogenic trends in diurnal temperature range and precipitation is not successful, but there remains strong net evidence for anthropogenic climate change if all data are considered jointly.</p> <div class="credits"> <p class="dwt_author">Schnur, R.; Hasselmann, Kl.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">186</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2001SPIE.4512..193V"> <span id="translatedtitle">Emergent system identification using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Complex Adaptive Structures can be viewed as a combination of Complex Adaptive Systems and fully integrated autonomous Smart Structures. Traditionally when designing a structure, one combines rules of thumb with theoretical results to develop an acceptable solution. This methodology will have to be extended for Complex Adaptive Structures, since they, by definition, will participate in their own design. In this paper we introduce a new methodology for Emergent System Identification that is concerned with combining the methodologies of self-organizing functional networks (GMDH - Alexy G. Ivakhnenko), <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO - James Kennedy and Russell C. Eberhart) and Genetic Programming (GP - John Koza). This paper will concentrate on the utilization of <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> in this effort and discuss how <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> relates to our ultimate goal of emergent self-organizing functional networks that can be used to identify overlapping internal structural models. The ability for Complex Adaptive Structures to identify emerging internal models will be a key component for their success.</p> <div class="credits"> <p class="dwt_author">Voss, Mark S.; Feng, Xin</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">187</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1579140"> <span id="translatedtitle">On the <span class="hlt">optimal</span> and suboptimal nonlinear <span class="hlt">filtering</span> problem for discrete-time systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper examines <span class="hlt">optimal</span> and suboptimal algorithms for the state <span class="hlt">filtering</span> problem in discrete-time nonlinear systems. The <span class="hlt">optimal</span> equations of sequential <span class="hlt">filtering</span> are analyzed and conditions are obtained which ensure a multimodal character for the a posteriori densities. This analysis is utilized in the discussion of the performance of suboptimal linearized <span class="hlt">filters</span>, and suggestions are made for their improvement in</p> <div class="credits"> <p class="dwt_author">M. L. ANDRADE NETTO; L. Gimeno; M. J. MENDES</p> <p class="dwt_publisher"></p> <p class="publishDate">1978-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">188</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AIPC.1207..912L"> <span id="translatedtitle">Numerical analysis of <span class="hlt">particle</span> distribution on multi-pipe ceramic candle <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The <span class="hlt">particle</span> distribution on the ceramic <span class="hlt">filter</span> surface has great effect on filtration performance. The numerical simulation method is used to analyze the <span class="hlt">particle</span> distribution near the <span class="hlt">filter</span> surface under different operation conditions. The gas/solid two-phase flow field in the ceramic <span class="hlt">filter</span> vessel was simulated using the Eulerian two-fluid model provided by FLUENT code. The user-defined function was loaded with the FLUTNT solver to define the interaction between the <span class="hlt">particle</span> and the gas near the porous ceramic candle <span class="hlt">filter</span>. The distribution of the <span class="hlt">filter</span> cake along the <span class="hlt">filter</span> length and around the <span class="hlt">filter</span> circumference was analyzed. The simulation results agree well with experimental data. The simulation model can be used to predict the <span class="hlt">particle</span> distribution and provide theory direction for the engineering application of porous ceramic <span class="hlt">filters</span>.</p> <div class="credits"> <p class="dwt_author">Li, H. X.; Gao, B. G.; Tie, Z. X.; Sun, Z. J.; Wang, F. H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">189</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/19884080"> <span id="translatedtitle">Speech enhancement based on nonlinear models using <span class="hlt">particle</span> <span class="hlt">filters</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Motivated by the reportedly strong performance of <span class="hlt">particle</span> <span class="hlt">filters</span> (PFs) for noise reduction on essentially linear speech production models, and the mounting evidence that the introduction of nonlinearities can lead to a refined speech model, this paper presents a study of PF solutions to the problem of speech enhancement in the context of nonlinear, neural-type speech models. Several variations of a global model are presented (single/multiple neurons; bias/no bias), and corresponding PF solutions are derived. Different importance functions are given when beneficial, Rao-Blackwellization is proposed when possible, and dual/nondual versions of each algorithms are presented. The method shown can handle both white and colored noise. Using a variety of speech and noise signals and different objective quality measures, the performance of these algorithms are evaluated against other PF solutions running on linear models, as well as some traditional enhancement algorithms. A certain hierarchy in performance is established between each algorithm in the paper. Depending on the experimental conditions, the best-performing algorithms are a classical Rao-Blackwellized <span class="hlt">particle</span> <span class="hlt">filter</span> (RBPF) running on a linear model, and a proposed PF employing a nondual, nonlinear model with multiple neurons and no biases. With consistence, the neural-network-based PF outperforms RBPF at low signal-to-noise ratio (SNR). PMID:19884080</p> <div class="credits"> <p class="dwt_author">Mustičre, Frédéric; Boli?, Miodrag; Bouchard, Martin</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-30</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">190</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EJASP2012...17A"> <span id="translatedtitle">Proposed hardware architectures of <span class="hlt">particle</span> <span class="hlt">filter</span> for object tracking</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this article, efficient hardware architectures for <span class="hlt">particle</span> <span class="hlt">filter</span> (PF) are presented. We propose three different architectures for Sequential Importance Resampling <span class="hlt">Filter</span> (SIRF) implementation. The first architecture is a two-step sequential PF machine, where <span class="hlt">particle</span> sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.</p> <div class="credits"> <p class="dwt_author">Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">191</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=N20050182658"> <span id="translatedtitle">Parallel <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm Accelerated by Asynchronous Evaluations.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">A parallel <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) algorithm is presented. <span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tie...</p> <div class="credits"> <p class="dwt_author">G. Venter J. Sobieszczanski-Sobieski</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">192</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1773669"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">Filters</span> for Location Estimation in Ubiquitous Computing: A Case Study</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Location estimation is an important part of many ubiquitous computing systems. <span class="hlt">Particle</span> <span class="hlt">filters</span> are simulation-based probabilistic ap- proximations which the robotics community has shown to be eective for tracking robots' positions. This paper presents a case study of applying <span class="hlt">particle</span> <span class="hlt">filters</span> to location estimation for ubiquitous computing. Using trace logs from a deployed multi-sensor location system, we show that <span class="hlt">particle</span></p> <div class="credits"> <p class="dwt_author">Jeffrey Hightower; Gaetano Borriello</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">193</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011EJASP2011...53C"> <span id="translatedtitle">Multi-prediction <span class="hlt">particle</span> <span class="hlt">filter</span> for efficient parallelized implementation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Particle</span> <span class="hlt">filter</span> (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 <span class="hlt">particle</span> 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 <span class="hlt">particle</span> number is usually required to obtain an accurate estimation, and the complexity of the resampling procedure is highly related to the number of <span class="hlt">particles</span>. In this article, we propose a multi-prediction (MP) framework with two selection approaches. The proposed MP framework can reduce the required <span class="hlt">particle</span> 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 <span class="hlt">particles</span>, respectively. Hence, the proposed MP-PF can enhance the efficiency of the parallelization.</p> <div class="credits"> <p class="dwt_author">Chu, Chun-Yuan; Chao, Chih-Hao; Chao, Min-An; Wu, An-Yeu Andy</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">194</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/17357741"> <span id="translatedtitle">Adaptive Rao-Blackwellized <span class="hlt">particle</span> <span class="hlt">filter</span> and its evaluation for tracking in surveillance.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary"><span class="hlt">Particle</span> <span class="hlt">filters</span> can become quite inefficient when being applied to a high-dimensional state space since a prohibitively large number of samples may be required to approximate the underlying density functions with desired accuracy. In this paper, by proposing an adaptive Rao-Blackwellized <span class="hlt">particle</span> <span class="hlt">filter</span> for tracking in surveillance, we show how to exploit the analytical relationship among state variables to improve the efficiency and accuracy of a regular <span class="hlt">particle</span> <span class="hlt">filter</span>. Essentially, the distributions of the linear variables are updated analytically using a Kalman <span class="hlt">filter</span> which is associated with each <span class="hlt">particle</span> in a <span class="hlt">particle</span> <span class="hlt">filtering</span> framework. Experiments and detailed performance analysis using both simulated data and real video sequences reveal that the proposed method results in more accurate tracking than a regular <span class="hlt">particle</span> <span class="hlt">filter</span>. PMID:17357741</p> <div class="credits"> <p class="dwt_author">Xu, Xinyu; Li, Baoxin</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">195</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50242310"> <span id="translatedtitle">Integration of <span class="hlt">optimized</span> low-pass <span class="hlt">filters</span> in band-pass <span class="hlt">filters</span> for out-of-band improvement</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose an original structure for the design of high performance <span class="hlt">filters</span> with simultaneously controlled band-pass and band-reject responses. The band-reject response is controlled due to the integration of low-pass structure. Thus, the spurious resonances of the band-pass <span class="hlt">filter</span> are rejected up to the low-pass <span class="hlt">filter</span> ones. In this way, we have to <span class="hlt">optimize</span> the response of the low-pass structure</p> <div class="credits"> <p class="dwt_author">CCdric QUENDO; C. Person; E. Rius; M. Ney</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">196</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57013967"> <span id="translatedtitle">Bernoulli <span class="hlt">Particle\\/Box-Particle</span> <span class="hlt">Filters</span> for Detection and Tracking in the Presence of Triple Measurement Uncertainty</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This work presents sequential Bayesian detection and estimation methods for nonlinear dynamic stochastic systems using measurements affected by three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. Following Mahler's framework for information fusion, the paper develops the <span class="hlt">optimal</span> Bayes <span class="hlt">filter</span> for this problem in the form of the Bernoulli <span class="hlt">filter</span> for interval measurements. Two numerical implementations of the <span class="hlt">optimal</span></p> <div class="credits"> <p class="dwt_author">Amadou Gning; Branko Ristic; Lyudmila Mihaylova</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">197</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8768E..1AZ"> <span id="translatedtitle">Adaptive mean shift and <span class="hlt">particle</span> <span class="hlt">filter</span> tracking method based on joint feature</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In the object tracking area, both <span class="hlt">particle</span> <span class="hlt">filter</span> and mean shift algorithm have proven successful approaches. However, both of them have notable weakness. In this paper, we present a new algorithm which combined the two algorithms to track the target. First, the mean shift algorithm is employed to search an object candidate near the target state. Then, if the candidate is good enough, it will be used to adapt the <span class="hlt">particle</span> <span class="hlt">filter</span> parameters, including the number of <span class="hlt">particle</span> <span class="hlt">filter</span>, and etc. Finally, the <span class="hlt">particle</span> <span class="hlt">filter</span> will estimate the target state based on these new parameters. Further, the paper introduces the color-texture combined feature instead of color feature.</p> <div class="credits"> <p class="dwt_author">Zhang, La; Yang, Yingyun; Wang, Huabing; Yang, Yansi; Liu, Bo</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">198</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1497668"> <span id="translatedtitle">Simple and effective EM-based <span class="hlt">optimization</span> procedure for microwave <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A simple and effective computerized <span class="hlt">optimization</span> procedure for microwave <span class="hlt">filters</span> is discussed. The basic idea is to integrate a fast and accurate electromagnetic (EM) solver, a <span class="hlt">filter</span> design strategy, and two different <span class="hlt">optimization</span> algorithms. The structural parameters to be modified are then chosen with the objective of improving the interaction between the EM solver and the <span class="hlt">optimization</span> process. A simple</p> <div class="credits"> <p class="dwt_author">J. T. Alos; M. Guglielmi</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">199</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EPJWC..2501046L"> <span id="translatedtitle">Numerical simulation of DPF <span class="hlt">filter</span> for selected regimes with deposited soot <span class="hlt">particles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">For the purpose of accumulation of particulate matter from Diesel engine exhaust gas, <span class="hlt">particle</span> <span class="hlt">filters</span> are used (referred to as DPF or FAP <span class="hlt">filters</span> in the automotive industry). However, the cost of these <span class="hlt">filters</span> 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 <span class="hlt">particle</span> <span class="hlt">filter</span> behavior under various operating modes. The simulations were especially focused on selected critical states of <span class="hlt">particle</span> <span class="hlt">filter</span>, when engine is switched to emergency regime. The aim was to prevent and avoid critical situations due the <span class="hlt">filter</span> behavior understanding. The numerical simulations were based on experimental analysis of used diesel <span class="hlt">particle</span> <span class="hlt">filters</span>.</p> <div class="credits"> <p class="dwt_author">Lávi?ka, David; Kova?ík, Petr</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">200</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1847839"> <span id="translatedtitle">A near <span class="hlt">optimal</span> deblocking <span class="hlt">filter</span> for H.264 advanced video coding</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose a near <span class="hlt">optimal</span> hardware architecture for deblocking <span class="hlt">filter</span> in H.264\\/MPEG-4 AVC. We propose a novel <span class="hlt">filtering</span> order and a data reuse strategy that result in significant saving in <span class="hlt">filtering</span> time, local memory usage, and memory traffic. Every 16x16 macroblock requires 192 <span class="hlt">filtering</span> operations. After a few initialization cycles, our 5-stage pipelined architecture is able to perform one <span class="hlt">filtering</span></p> <div class="credits"> <p class="dwt_author">Shen-yu Shih; Cheng-ru Chang; Youn-long Lin</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_9");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> 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showDiv("page_12");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">201</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/952810"> <span id="translatedtitle">Using triaxial magnetic fields to create <span class="hlt">optimal</span> <span class="hlt">particle</span> composites.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The properties of a <span class="hlt">particle</span> composite can be controlled by organizing the <span class="hlt">particles</span> into assemblies. The properties of the composite will depend on the structure of the <span class="hlt">particle</span> assemblies, and for any give property there is some <span class="hlt">optimal</span> structure. Through simulation and experiment we show that the application of heterodyned triaxial magnetic or electric fields generates structures that <span class="hlt">optimize</span> the magnetic and dielectric properties of <span class="hlt">particle</span> composites. We suggest that <span class="hlt">optimizing</span> these properties <span class="hlt">optimizes</span> other properties, such as transport properties, and we give as one example of this <span class="hlt">optimization</span> the magnetostriction of magnetic <span class="hlt">particle</span> composites formed in a silicone elastomer.</p> <div class="credits"> <p class="dwt_author">Martin, James Ellis</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">202</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22997266"> <span id="translatedtitle">Spatio-temporal auxiliary <span class="hlt">particle</span> <span class="hlt">filtering</span> with l1-norm-based appearance model learning for robust visual tracking.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">In this paper, we propose an efficient and accurate visual tracker equipped with a new <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithm and robust subspace learning-based appearance model. The proposed visual tracker avoids drifting problems caused by abrupt motion changes and severe appearance variations that are well-known difficulties in visual tracking. The proposed algorithm is based on a type of auxiliary <span class="hlt">particle</span> <span class="hlt">filtering</span> that uses a spatio-temporal sliding window. Compared to conventional <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithms, spatio-temporal auxiliary <span class="hlt">particle</span> <span class="hlt">filtering</span> is computationally efficient and successfully implemented in visual tracking. In addition, a real-time robust principal component pursuit (RRPCP) equipped with l(1)-norm <span class="hlt">optimization</span> has been utilized to obtain a new appearance model learning block for reliable visual tracking especially for occlusions in object appearance. The overall tracking framework based on the dual ideas is robust against occlusions and out-of-plane motions because of the proposed spatio-temporal <span class="hlt">filtering</span> and recursive form of RRPCP. The designed tracker has been evaluated using challenging video sequences, and the results confirm the advantage of using this tracker. PMID:22997266</p> <div class="credits"> <p class="dwt_author">Kim, Du Yong; Jeon, Moongu</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-09-13</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">203</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009JEI....18d3009A"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filtering</span> of polyphase-downsampling-based multiple description coded video</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We combine an <span class="hlt">optimal</span> <span class="hlt">filtering</span> approach with a multiple description coding (MDC) approach to enhance the quality of video at the receiver. <span class="hlt">Optimal</span> <span class="hlt">filter</span> coefficients are computed at the encoder and added to each description. At the decoder, <span class="hlt">optimal</span> <span class="hlt">filter</span> coefficients are obtained directly from the bit stream and employed to improve the quality. Experimental results show that the proposed approach enables better MDC performance for video in case of packet losses.</p> <div class="credits"> <p class="dwt_author">Ate?, Ça?lar; Urhan, O?uzhan; Ertürk, Sarp</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">204</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/19571861"> <span id="translatedtitle">Digital convolution <span class="hlt">filtering</span> techniques on an array processor for <span class="hlt">particle</span> image velocimetry</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The use of digital, convolution <span class="hlt">filtering</span> techniques in <span class="hlt">particle</span> image velocimetry is described. The technique is illustrated by considering its application to real and synthetic <span class="hlt">particle</span> image velocimetry images using a dedicated array processor.</p> <div class="credits"> <p class="dwt_author">Ian Grant; Jian Hang Qiu</p> <p class="dwt_publisher"></p> <p class="publishDate">1990-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">205</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=ADP010172"> <span id="translatedtitle">Evaluation of Various Methods to Detect Metallic Wear <span class="hlt">Particles</span> in Lube Oil <span class="hlt">Filter</span> Debris.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">Studies were conducted to evaluate methods of detecting metallic wear <span class="hlt">particles</span> in lube oil <span class="hlt">filter</span> debris. The methods studied were low temperature oxidation of the organic constituents in the debris, separation of ferromagnetic <span class="hlt">particles</span> by passage throu...</p> <div class="credits"> <p class="dwt_author">G. C. Fisher</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">206</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1998JaJAP..37.1010K"> <span id="translatedtitle">Polymer <span class="hlt">Optimization</span> of Pigmented Photoresists for Color <span class="hlt">Filter</span> Production</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The lithographic performance of pigmented photoresists for color <span class="hlt">filter</span> production is affected by the structure of the employed polymer. Four polymers with acrylate backbones and pendant reactive acrylate/methacrylate groups were prepared, and the effects of their molecular weights and acid values on the pixel pattern quality, development time, sensitivity and development mode were elucidated. ECHIPTM, a statistical experimental design program was used for <span class="hlt">optimization</span> studies revealing that the red resist performs best, when polymers with relatively low acid values (<40 mg KOH/g polymer) and high molecular weights >50,000 are used. The green and the blue resists yielded <span class="hlt">optimal</span> patterns at molecular weights in the range of 20,000 30,000 with acid values of about 50 60 mg KOH/g polymer. The sensitivity of resists containing polymers with pendant acryloyl groups is in general higher than that of the corresponding methacryloyl derivatives. Polymers having butyl acrylate-methacrylic acid backbone units showed the highest sensitivity among the polymers investigated. When developed with an <span class="hlt">optimized</span> tetramethyl ammonium hydroxide (TMAH) based developer, resists using polymers with methyl methacrylate units showed peeling type development, while butyl acrylate copolymers effected homogeneous dissolution yielding higher resolution.</p> <div class="credits"> <p class="dwt_author">Kudo, Takanori; Nanjo, Yuki; Nozaki, Yuko; Yamaguchi, Hidemasa; Kang, Wen-Bing; Pawlowski, Georg</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">207</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://users.ece.gatech.edu/%7Elanterma/pcl/papers/IAC_paper_386_v2.pdf"> <span id="translatedtitle">A <span class="hlt">particle</span> <span class="hlt">filtering</span> approach to FM-band passive radar tracking and automatic target recognition</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present two stochastic <span class="hlt">filters</span> for an FM-band passive air surveillance radar. The first system uses an extended Kalman <span class="hlt">filter</span> and delay-Doppler measurements to track targets. The second system uses a <span class="hlt">particle</span> <span class="hlt">filter</span> to simultaneously track and classify targets. Automatic target recognition is made possible by the inclusion of radar cross section (RCS) in the measurement vector. The extended Kalman</p> <div class="credits"> <p class="dwt_author">Shawn Herman; Pierre Moulin</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">208</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/22840706"> <span id="translatedtitle">Clogging of fibrous <span class="hlt">filters</span> by liquid aerosol <span class="hlt">particles</span>: Experimental and phenomenological modelling study</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Fibrous <span class="hlt">filters</span> are the most common means used to separate liquid aerosol <span class="hlt">particles</span> from an industrial gas stream. The pressure drop and penetration (=1-efficiency) are the most important performance criteria of the <span class="hlt">filter</span>. In this study, experimental and modelling results describing the pressure drop and penetration evolution of a glass microfibre HEPA <span class="hlt">filter</span> are presented. For the experimental part, the</p> <div class="credits"> <p class="dwt_author">Tom Frising; Dominique Thomas; Denis Bémer; Patrick Contal</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">209</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51081163"> <span id="translatedtitle">Gesture Analysis Using 3D Camera, Shape Features and <span class="hlt">Particle</span> <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a framework of gesture recognition and tracking using 3D camera, edge features and <span class="hlt">particle</span> <span class="hlt">filters</span>. A target gesture is modeled with perceptual shape features qualitatively. The perceptual model is used to guide tracking based on a <span class="hlt">particle</span> <span class="hlt">filtering</span> method to achieve reliable results. The system has been applied to a video game control application, Interactive Dart Game,</p> <div class="credits"> <p class="dwt_author">Gang Hu; Qigang Gao</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">210</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/3202469"> <span id="translatedtitle">Hybrid <span class="hlt">Particle</span> <span class="hlt">Filter</span> and Mean Shift tracker with adaptive transition model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose a tracking algorithm based on a combination of <span class="hlt">Particle</span> <span class="hlt">Filter</span> and Mean Shift, and enhanced with a new adaptive state transition model. <span class="hlt">Particle</span> <span class="hlt">Filter</span> is robust to partial and total occlusions, can deal with multi-modal pdf s and can recover lost tracks. However, its complexity dramatically increases with the dimensionality of the sampled pdf. Mean Shift has a</p> <div class="credits"> <p class="dwt_author">Emilio Maggio; Andrea Cavallaro</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">211</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/26580326"> <span id="translatedtitle">A semi-analytical <span class="hlt">particle</span> <span class="hlt">filter</span> for identification of nonlinear oscillators</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Particle</span> <span class="hlt">filters</span> find important applications in the problems of state and parameter estimations of dynamical systems of engineering interest. Since a typical <span class="hlt">filtering</span> algorithm involves Monte Carlo simulations of the process equations, sample variance of the estimator is inversely proportional to the number of <span class="hlt">particles</span>. The sample variance may be reduced if one uses a Rao–Blackwell marginalization of states and</p> <div class="credits"> <p class="dwt_author">R. Sajeeb; C. S. Manohar; D. Roy</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">212</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.washington.edu/ai/Mobile_Robotics/projects/mcl/postscripts/adaptive-ijrr-2003.pdf"> <span id="translatedtitle">Adapting the Sample Size in <span class="hlt">Particle</span> <span class="hlt">Filters</span> Through KLD-Sampling</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Over the last years, <span class="hlt">particle</span> <span class="hlt">filters</span> have been applied with great success to a variety of state estimation problems. In this paper we present a statistical approach to increasing the efficiency of <span class="hlt">particle</span> <span class="hlt">filters</span> by adapting the size of sample sets during the estimation pro- cess. The key idea of the KLD-sampling method is to bound the approximation error intro-</p> <div class="credits"> <p class="dwt_author">Dieter Fox</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">213</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/49829688"> <span id="translatedtitle"><span class="hlt">Optimizing</span> LPC <span class="hlt">filter</span> parameters for multi-pulse excitation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Present LPC analysis procedures assume that the input to the all-pole <span class="hlt">filter</span> is white; the <span class="hlt">filter</span> parameters are obtained by minimizing the mean-squared error between the <span class="hlt">filter</span> output samples and their values obtained by linear prediction on the basis of past output samples. It is well known that these procedures often do not yield accurate <span class="hlt">filter</span> parameters for periodic (or</p> <div class="credits"> <p class="dwt_author">Sharad Singhal; Bishnu S. Atal</p> <p class="dwt_publisher"></p> <p class="publishDate">1983-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">214</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51081468"> <span id="translatedtitle">The Random Wander Ant <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> and Random Benchmarks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">To solve the problem that the swarm was trapped by local <span class="hlt">optimization</span> in searching process, the random wander ant <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span>(called RWA-PSO) was pro- posed. The algorithm applied the mechanism of ant randomly wandering to find the food, and introduced it into the velocity updating process of <span class="hlt">particle</span>. The probability that <span class="hlt">particle</span> flied out the range of initialization increased.</p> <div class="credits"> <p class="dwt_author">Jihong Shen; Yan Li</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">215</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/56967632"> <span id="translatedtitle">An improved path planning approach based on <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, an improved path planning scheme based on <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> and Ferguson Splines is proposed. Firstly, a string of Ferguson Splines are used to describe a path for a mobile robot, and the path planning problem is then equivalent to the <span class="hlt">optimization</span> of parameters of particular cubic Ferguson splines. Secondly, an improved <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm, which</p> <div class="credits"> <p class="dwt_author">Wu Xianxiang; Ming Yan; Wang Juan</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">216</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50217662"> <span id="translatedtitle"><span class="hlt">Optimal</span> design of wide band low loss SAW <span class="hlt">filters</span>, using slanted interdigital transducers</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Slanted finger SAW transducers allow one to design wide band <span class="hlt">filters</span> with excellent characteristics. One of the most interesting modifications of such a <span class="hlt">filter</span> is the slanted SPUDT. We present an approach to the analysis of such <span class="hlt">filters</span> based on consistent use of the Y-matrix instead of the conventional P-matrix. Conditions of <span class="hlt">optimal</span> matching of such SPUDT are obtained and</p> <div class="credits"> <p class="dwt_author">S. M. Balashov; K. H. Baek</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">217</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/66222"> <span id="translatedtitle">FIR <span class="hlt">Filter</span> Design via Spectral Factorization and Convex <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">udio, spectrum shaping, ... ) upper bounds are convex in h; lower bounds are notMagnitude <span class="hlt">filter</span> design problem involves magnitude specsClassical example: lowpass <span class="hlt">filter</span> designlowpass <span class="hlt">filter</span> with maximum stopband attenuation:521\\/51IS()l variables: h C R (<span class="hlt">filter</span> coefficients),52 G R (stopband attenuation) parameters: 51 ( R (logarithmic passband ripple), n (order),Op (passband frequency), Os (stopband frequency)magnitude <span class="hlt">filter</span> design problems are nonconvex can</p> <div class="credits"> <p class="dwt_author">Lieven Vandenberghe; Shao-po Wu; Stephen Boyd</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">218</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22674153"> <span id="translatedtitle"><span class="hlt">Particles</span> shed from syringe <span class="hlt">filters</span> and their effects on agitation-induced protein aggregation.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We tested the hypothesis that foreign <span class="hlt">particles</span> shed from <span class="hlt">filters</span> can accelerate the rate of protein aggregation and <span class="hlt">particle</span> formation during agitation stress. Various types and brands of syringe <span class="hlt">filters</span> were tested. <span class="hlt">Particle</span> counts and size distribution (?1 µm) in buffer alone or in solutions of keratinocyte growth factor 2 (KGF-2) were determined with a micro-flow imaging. Submicron <span class="hlt">particle</span> populations were characterized by dynamic light scattering. Loss of soluble protein during filtration or postfiltration incubation was determined by ultraviolet spectroscopy and bicinchoninic acid protein assay. There was a wide range (from essentially none to >100,000/mL) in the counts for at least 1 µm <span class="hlt">particles</span> shed into buffer or KGF-2 solution from the different syringe <span class="hlt">filters</span> (with or without borosilicate glass microfibers). Filtration of KGF-2 with units containing glass microfibers above the membrane resulted in 20%-80% loss of protein due to adsorption to <span class="hlt">filter</span> components. Filtration with systems containing a membrane alone resulted in 0%-20% loss of KGF-2. Effects of 24-h postfiltration incubation were tested on KGF-2 solution <span class="hlt">filtered</span> with polyether sulfone membrane <span class="hlt">filters</span>. Loss of soluble protein and formation of <span class="hlt">particles</span> during agitation were much greater than that in control, unfiltered KGF-2 solutions. Similar acceleration of protein aggregation and <span class="hlt">particle</span> formation was observed when unfiltered KGF-2 solution was mixed with <span class="hlt">filtered</span> buffer and agitated. <span class="hlt">Particle</span> shedding from syringe <span class="hlt">filters</span>--and the resulting acceleration of protein aggregation during agitation--varied greatly among the different syringe <span class="hlt">filters</span> and individual units of a given <span class="hlt">filter</span> type. Our results demonstrate that nanoparticles and microparticles shed from the <span class="hlt">filters</span> can accelerate protein aggregation and <span class="hlt">particle</span> formation, especially during agitation. PMID:22674153</p> <div class="credits"> <p class="dwt_author">Liu, Lu; Randolph, Theodore W; Carpenter, John F</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-06-06</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">219</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1993STIN...9418278D"> <span id="translatedtitle"><span class="hlt">Optimal</span> design of binary phase-only <span class="hlt">filters</span> using genetic algorithms</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The genetic algorithm is a mathematical <span class="hlt">optimization</span> technique which has generally been applied to one-dimensional problems. In this work, the genetic algorithm was applied to a two-dimensional problem--the construction of binary phase-only spatial <span class="hlt">filters</span> for optical pattern recognition. Spatial <span class="hlt">filters</span> that are invariant to range and aspect changes are required for robust pattern recognition. Construction of invariant <span class="hlt">filters</span> is an <span class="hlt">optimization</span> problem where the correlation is the objective function for the genetic algorithm. Results are presented for correlation of a genetic algorithm-constructed <span class="hlt">filter</span> with a multiple aspect angle target set. <span class="hlt">Filters</span> using a hill-climber algorithm were also constructed and tested.</p> <div class="credits"> <p class="dwt_author">Deb, Kalyanmoy</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">220</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=129164"> <span id="translatedtitle"><span class="hlt">PARTICLE</span> REMOVAL AND HEAD LOSS DEVELOPMENT IN BIOLOGICAL <span class="hlt">FILTERS</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">The physical performance of granular media <span class="hlt">filters</span> was studied under pre-chlorinated, backwash-chlorinated, and nonchlorinated conditions. Overall, biological <span class="hlt">filteration</span> produced a high-quality water. Although effluent turbidities showed littleer difference between the perform...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_10");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">221</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhFl...24d5103B"> <span id="translatedtitle">Intrinsic <span class="hlt">filtering</span> errors of Lagrangian <span class="hlt">particle</span> tracking in LES flow fields</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Large-eddy simulation (LES) of two-phase turbulent flows exhibits quantitative differences in <span class="hlt">particle</span> statistics if compared to direct numerical simulation (DNS) which, in the context of the present study, is considered the exact reference case. Differences are primarily due to <span class="hlt">filtering</span>, a fundamental intrinsic feature of LES. <span class="hlt">Filtering</span> the fluid velocity field yields approximate computation of the forces acting on <span class="hlt">particles</span> and, in turn, trajectories that are inaccurate when compared to those of DNS. In this paper, we focus precisely on the <span class="hlt">filtering</span> error for which we quantify a lower bound. To this aim, we use a DNS database of inertial <span class="hlt">particle</span> dispersion in turbulent channel flow and we perform a priori tests in which the error purely due to <span class="hlt">filtering</span> is singled out removing error accumulation effects, which would otherwise lead to progressive divergence between DNS and LES <span class="hlt">particle</span> trajectories. By applying <span class="hlt">filters</span> of different type and width at varying <span class="hlt">particle</span> inertia, we characterize the statistical properties of the <span class="hlt">filtering</span> error as a function of the wall distance. Results show that <span class="hlt">filtering</span> error is stochastic and has a non-Gaussian distribution. In addition, the distribution of the <span class="hlt">filtering</span> error depends strongly on the wall-normal coordinate being maximum in the buffer region. Our findings provide insight on the effect of sub-grid scale velocity field on the force driving the <span class="hlt">particles</span>, and establish the requirements that any closure model aimed at recovering sub-grid scale effects on the dynamics of inertial <span class="hlt">particles</span> must satisfy.</p> <div class="credits"> <p class="dwt_author">Bianco, F.; Chibbaro, S.; Marchioli, C.; Salvetti, M. V.; Soldati, A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">222</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/6574741"> <span id="translatedtitle">Computations on the performance of <span class="hlt">particle</span> <span class="hlt">filters</span> and electronic air cleaners</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The paper discusses computations on the performance of <span class="hlt">particle</span> <span class="hlt">filters</span> and electronic air cleaners (EACs). The collection efficiency of <span class="hlt">particle</span> <span class="hlt">filters</span> and EACs is calculable if certain factors can be assumed or calibrated. For fibrous particulate <span class="hlt">filters</span>, measurement of collection performance at one <span class="hlt">particle</span> size can allow the performance for other <span class="hlt">particle</span> sizes to be inferred, within limits, by using the established collection mechanisms of interception and diffusion. For EACs, standard electrostatic precipitator models can be used, if the fraction of flow by-passing the collection zone can be determined. The calculations of these models are demonstrated and compared with experimental results.</p> <div class="credits"> <p class="dwt_author">Lawless, P.A.; Viner, A.S.; Ensor, D.S.; Sparks, L.E.</p> <p class="dwt_publisher"></p> <p class="publishDate">1990-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">223</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013CNSNS..18..327G"> <span id="translatedtitle">Chaos-enhanced accelerated <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">There are more than two dozen variants of <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithms in the literature. Recently, a new variant, called accelerated PSO (APSO), shows some extra advantages in convergence for global search. In the present study, we will introduce chaos into the APSO in order to further enhance its global search ability. Firstly, detailed studies are carried out on benchmark problems with twelve different chaotic maps to find out the most efficient one. Then the chaotic APSO (CAPSO) will be compared with some other chaotic PSO algorithms presented in the literature. The performance of the CAPSO algorithm is also validated using three engineering problems. The results show that the CAPSO with an appropriate chaotic map can clearly outperform standard APSO, with very good performance in comparison with other algorithms and in application to a complex problem.</p> <div class="credits"> <p class="dwt_author">Gandomi, Amir Hossein; Yun, Gun Jin; Yang, Xin-She; Talatahari, Siamak</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">224</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50581355"> <span id="translatedtitle">An <span class="hlt">Optimal</span> FIR <span class="hlt">Filter</span> for Linear TIE Models of Local Clocks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, we present an <span class="hlt">optimal</span> finite impulse response (FIR) <span class="hlt">filter</span> for linear TIE models of local clocks. A comparison with the unbiased FIR <span class="hlt">filter</span> is provided. Estimations are carried out for a local crystal clock using GPS-based sawtooth measurements. As a main conclusion, we notice that an <span class="hlt">optimal</span> solution does not contribute too much to estimation accuracy and</p> <div class="credits"> <p class="dwt_author">Yuriy S. Shmaliy</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">225</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ajith.softcomputing.net/nabic09_9.pdf"> <span id="translatedtitle">Design of <span class="hlt">Optimal</span> Digital IIR <span class="hlt">Filters</span> by using a Bandwidth Adaptive Harmony Search Algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Evolutionary <span class="hlt">optimization</span> algorithms have been recently applied to <span class="hlt">optimal</span> digital IIR <span class="hlt">filter</span> design. In this paper, we apply a Bandwidth Adaptive Harmony Search (BAHS) algorithm to the design of 1- dimensional IIR <span class="hlt">filters</span>. Harmony Search is an evolutionary algorithm, which emulates the improvisation process of musicians. We have modified the algorithm by setting the bandwidth equal to the standard deviation</p> <div class="credits"> <p class="dwt_author">Sayan Ghosh; Debarati Kundu; Kaushik Suresh; Swagatam Das; Ajith Abraham</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">226</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1580960"> <span id="translatedtitle">A direct derivation of the <span class="hlt">optimal</span> linear <span class="hlt">filter</span> using the maximum principle</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The purpose of this paper is to present an alternate derivation of <span class="hlt">optimal</span> linear <span class="hlt">filters</span>. The basic technique is the use of a matrix version of the maximum principle of Pontryagin coupled with the use of gradient matrices to derive the <span class="hlt">optimal</span> values of the <span class="hlt">filter</span> coefficients for minimum variance estimation under the requirement that the estimates be unbiased. The</p> <div class="credits"> <p class="dwt_author">M. Athans; E. Tse</p> <p class="dwt_publisher"></p> <p class="publishDate">1967-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">227</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1581200"> <span id="translatedtitle"><span class="hlt">Optimal</span> adaptive <span class="hlt">filter</span> realizations for sample stochastic processes with an unknown parameter</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Techniques are given for realizing <span class="hlt">optimal</span> learning systems for <span class="hlt">filtering</span> a sampled stochastic process in the presence of an unknown constant or time-varying parameter. It is shown how the nonlinear Bayes <span class="hlt">optimal</span> (quadratic sense) adaptive <span class="hlt">filters</span> can be directly realized for continuous parameter spaces by real-time analog systems. Examples are given for both constant and time-varying unknown parameters.</p> <div class="credits"> <p class="dwt_author">C. Hilborn; D. Lainiotis</p> <p class="dwt_publisher"></p> <p class="publishDate">1969-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">228</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/26957168"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filtering</span> with random sensor delay, multiple packet dropout and uncertain observations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper studies the problem of <span class="hlt">optimal</span> <span class="hlt">filtering</span> of discrete-time systems with random sensor delay, multiple packet dropout and uncertain observation. The random sensor delay, multiple packet dropout or uncertainty in observation is transformed to a stochastic parameter in the system representation. A new formulation enables us to design an <span class="hlt">optimal</span> <span class="hlt">filter</span> for a system with multiple packet dropout in</p> <div class="credits"> <p class="dwt_author">M. Sahebsara; T. Chen; S. L. Shah</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">229</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1638130"> <span id="translatedtitle">Continuous-time envelope-constrained <span class="hlt">filter</span> design via Laguerre <span class="hlt">filters</span> and ℋ? <span class="hlt">optimization</span> methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The envelope-constrained <span class="hlt">filtering</span> problem is concerned with the design of a time-invariant <span class="hlt">filter</span> to process a given input signal such that the noiseless output of the <span class="hlt">filter</span> is guaranteed to lie within a specified output mask while minimizing the noise gain of the <span class="hlt">filter</span>. An algorithm is developed to solve the continuous-time envelope-constrained <span class="hlt">filter</span> design problem with the ℋ? norm</p> <div class="credits"> <p class="dwt_author">Zhuquan Zang; Antoni Cantoni; Kok Lay Teo</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">230</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4297560"> <span id="translatedtitle"><span class="hlt">Optimal</span> HMM <span class="hlt">filtering</span> and decision feedback equalisation for differential encoded transmission systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper conditional hidden Markov model (HMM) <span class="hlt">filters</span> and conditional Kalman <span class="hlt">filters</span> (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the <span class="hlt">optimal</span> HMM <span class="hlt">filter</span> for demodulation. The <span class="hlt">filter</span> requires O(N<sup>3<\\/sup>) calculations per time iteration, where N is the number of message</p> <div class="credits"> <p class="dwt_author">Jason Ford; John Moore</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">231</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22714295"> <span id="translatedtitle">Improved <span class="hlt">particle</span> size estimation in digital holography via sign matched <span class="hlt">filtering</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">A matched <span class="hlt">filter</span> method is provided for obtaining improved <span class="hlt">particle</span> size estimates from digital in-line holograms. This improvement is relative to conventional reconstruction and pixel counting methods for <span class="hlt">particle</span> size estimation, which is greatly limited by the CCD camera pixel size. The proposed method is based on iterative application of a sign matched <span class="hlt">filter</span> in the Fourier domain, with sign meaning the matched <span class="hlt">filter</span> takes values of ±1 depending on the sign of the angular spectrum of the <span class="hlt">particle</span> aperture function. Using simulated data the method is demonstrated to work for <span class="hlt">particle</span> diameters several times the pixel size. Holograms of piezoelectrically generated water droplets taken in the laboratory show greatly improved <span class="hlt">particle</span> size measurements. The method is robust to additive noise and can be applied to real holograms over a wide range of matched-<span class="hlt">filter</span> <span class="hlt">particle</span> sizes. PMID:22714295</p> <div class="credits"> <p class="dwt_author">Lu, Jiang; Shaw, Raymond A; Yang, Weidong</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">232</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50669715"> <span id="translatedtitle">A Cooperative Parallel mechanism based Multi-<span class="hlt">Particle</span>-Swarm <span class="hlt">Optimizer</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">An evolutionary mechanism of local-competing and global-cooperating is presented for cooperative parallel mechanism based multi-<span class="hlt">particle</span>-swarm <span class="hlt">optimizer</span> (CP-MPSO), the competitive relationship between the <span class="hlt">particles</span> of the traditional serial <span class="hlt">particle</span> swarm <span class="hlt">optimizer</span> is analyzed. A weighted-best-information based the PSO with cooperation-characteristic is proposed. Finally, the implementation of CP-MPSO is showed and its time-complexity is analyzed. The experiment results show that the <span class="hlt">optimizer</span></p> <div class="credits"> <p class="dwt_author">Fayong Guo; Yong Zhang; Dunwei Gong; Wei Wang</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">233</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013MNRAS.428..195A"> <span id="translatedtitle">Constraining clumpy dusty torus models using <span class="hlt">optimized</span> <span class="hlt">filter</span> sets</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recent success in explaining several properties of the dusty torus around the central engine of active galactic nuclei has been gathered with the assumption of clumpiness. The properties of such clumpy dusty tori can be inferred by analysing spectral energy distributions (SEDs), sometimes with scarce sampling given that large aperture telescopes and long integration times are needed to get good spatial resolution and signal. We aim at using the information already present in the data and the assumption of clumpy dusty torus, in particular, the CLUMPY models of Nenkova et al., to evaluate the optimum next observation such that we maximize the constraining power of the new observed photometric point. To this end, we use the existing and barely applied idea of Bayesian adaptive exploration, a mixture of Bayesian inference, prediction and decision theories. The result is that the new photometric <span class="hlt">filter</span> we use is the one that maximizes the expected utility, which we approximate with the entropy of the predictive distribution. In other words, we have to sample where there is larger variability in the SEDs compatible with the data with what we know of the model parameters. We show that Bayesian adaptive exploration can be used to suggest new observations, and ultimately <span class="hlt">optimal</span> <span class="hlt">filter</span> sets, to better constrain the parameters of the clumpy dusty torus models. In general, we find that the region between 10 and 200 ?m produces the largest increase in the expected utility, although sub-mm data from Atacama Large Millimeter Array also prove to be useful. It is important to note that here we are not considering the angular resolution of the data, which is key when constraining torus parameters. Therefore, the expected utilities derived from this methodology must be weighted with the spatial resolution of the data.</p> <div class="credits"> <p class="dwt_author">Asensio Ramos, A.; Ramos Almeida, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">234</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4275144"> <span id="translatedtitle">Research on Sampling Methods in <span class="hlt">Particle</span> <span class="hlt">Filtering</span> Based upon Microstructure of State Variable</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">With the purpose of decreasing the number of <span class="hlt">particles</span> needed to be sampled stochastically in <span class="hlt">particle</span> <span class="hlt">filtering</span>, a new sampling\\u000a method used in <span class="hlt">particle</span> <span class="hlt">filtering</span> is put forward in this paper. First of all, under specific human-computer conditions, both\\u000a cognitive psychology features of operators and motion features of the operators’ hands are studied, upon which a novel concept,\\u000a microstructure of</p> <div class="credits"> <p class="dwt_author">Zhiquan Feng; Bo Yang; Yuehui Chen; Yanwei Zheng; Yi Li; Zhonghua Wang</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">235</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011JEPT...84.1267K"> <span id="translatedtitle">Evaporation of suspensions to form an incompressible cake and to fill <span class="hlt">filter</span> pores with solid <span class="hlt">particles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Equations of filtration of suspensions to form an incompressible cake of <span class="hlt">particles</span> on the surface of the <span class="hlt">filter</span> with simultaneous passage of a certain share of the <span class="hlt">particles</span> from the cake to the <span class="hlt">filter</span>'s pore space and next to the region of a <span class="hlt">filtered</span> liquid are derived from the principles of the mechanics of multiphase media. The influence of the travel of the <span class="hlt">particles</span> in the region of the cake and the <span class="hlt">filter</span> on the dynamics of growth of the cake bed is investigated. An analysis of the derived dynamic filtration equations shows that allowance for the factors of travel and accumulation of <span class="hlt">particles</span> in the cake and the <span class="hlt">filter</span> causes their total filtration resistance, in particular the resistance in the inertial component of the filtration law, to decrease.</p> <div class="credits"> <p class="dwt_author">Khuzhayorov, B. Kh.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">236</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21308091"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">filtering</span> with path sampling and an application to a bimodal ocean current model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">This paper introduces a recursive <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithm designed to <span class="hlt">filter</span> 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 <span class="hlt">particle</span> <span class="hlt">filters</span>. 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 <span class="hlt">particle</span> <span class="hlt">filter</span> but have been inaccessible due to the limitations of standard <span class="hlt">particle</span> <span class="hlt">filtering</span> strategies.</p> <div class="credits"> <p class="dwt_author">Weare, Jonathan [Courant Institute, New York University, 251 Mercer Street, New York, NY 10012 (United States)], E-mail: weare@cims.nyu.edu</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">237</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50546396"> <span id="translatedtitle">An <span class="hlt">Optimal</span> Structure for Implementation of Digital <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, different structures for an elliptic <span class="hlt">filter</span> with fixed point arithmetic are implemented and compared. The <span class="hlt">filter</span> must be quantized for hardware implementation. This quantization is done in two steps. First the coefficients of <span class="hlt">filter</span> are quantized and then the accuracy of internal nodes are limited. According to the simulation results, lattice and DF2- parallel structures have minimal</p> <div class="credits"> <p class="dwt_author">S. Rahmanian; E. Rahmani; A. N. Avanaki; S. M. Fakhraie</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">238</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/27047918"> <span id="translatedtitle">Entropy-Based <span class="hlt">Optimization</span> of Wavelet Spatial <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A new class of spatial <span class="hlt">filters</span> for surface electromyographic (EMG) signal detection is proposed. These <span class="hlt">filters</span> are based on the 2-D spatial wavelet decomposition of the surface EMG recorded with a grid of electrodes and inverse transformation after zeroing a subset of the transformation coefficients. The <span class="hlt">filter</span> transfer function depends on the selected mother wavelet in the two spatial directions.</p> <div class="credits"> <p class="dwt_author">Dario Farina; Ernest Nlandu Kamavuako; Jian Wu; Francesco Naddeo</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">239</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/11931302"> <span id="translatedtitle">Single half-wavelength ultrasonic <span class="hlt">particle</span> <span class="hlt">filter</span>: predictions of the transfer matrix multilayer resonator model and experimental filtration results.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The quantitative performance of a "single half-wavelength" acoustic resonator operated at frequencies around 3 MHz as a continuous flow microparticle <span class="hlt">filter</span> has been investigated. Standing wave acoustic radiation pressure on suspended <span class="hlt">particles</span> (5-microm latex) drives them towards the center of the half-wavelength separation channel. Clarified suspending phase from the region closest to the <span class="hlt">filter</span> wall is drawn away through a downstream outlet. The filtration efficiency of the device was established from continuous turbidity measurements at the <span class="hlt">filter</span> outlet. The frequency dependence of the acoustic energy density in the aqueous <span class="hlt">particle</span> suspension layer of the <span class="hlt">filter</span> system was obtained by application of the transfer matrix model [H. Nowotny and E. Benes, J. Acoust. Soc. Am. 82, 513-521 (1987)]. Both the measured clearances and the calculated energy density distributions showed a maximum at the fundamental of the piezoceramic transducer and a second, significantly larger, maximum at another system's resonance not coinciding with any of the transducer or empty chamber resonances. The calculated frequency of this principal energy density maximum was in excellent agreement with the <span class="hlt">optimal</span> clearance frequency for the four tested channel widths. The high-resolution measurements of <span class="hlt">filter</span> performance provide, for the first time, direct verification of the matrix model predictions of the frequency dependence of acoustic energy density in the water layer. PMID:11931302</p> <div class="credits"> <p class="dwt_author">Hawkes, Jeremy J; Coakley, W Terence; Gröschl, Martin; Benes, Ewald; Armstrong, Sian; Tasker, Paul J; Nowotny, Helmut</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">240</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/21682358"> <span id="translatedtitle">A <span class="hlt">particle</span> <span class="hlt">filtering</span> approach for spatial arrival time tracking in ocean acoustics.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The focus of this work is on arrival time and amplitude estimation from acoustic signals recorded at spatially separated hydrophones in the ocean. A <span class="hlt">particle</span> <span class="hlt">filtering</span> 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 <span class="hlt">particle</span> <span class="hlt">filter</span>. It is also shown that posterior probability density functions of times and amplitudes become readily available with <span class="hlt">particle</span> <span class="hlt">filtering</span>. PMID:21682358</p> <div class="credits"> <p class="dwt_author">Jain, Rashi; Michalopoulou, Zoi-Heleni</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-06-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_11");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a 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href="#">10</a> <a onClick='return showDiv("page_11");' href="#">11</a> <a onClick='return showDiv("page_12");' href="#">12</a> <a style="font-weight: bold;">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a onClick='return showDiv("page_16");' href="#">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_14");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">241</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/496uv0ldbrca51wu.pdf"> <span id="translatedtitle">A Non-dominated Sorting <span class="hlt">Particle</span> Swarm <span class="hlt">Optimizer</span> for Multiobjective <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper introduces a modified PSO, Non-dominated Sorting <span class="hlt">Particle</span> Swarm <span class="hlt">Optimizer</span> (NSPSO), for better multiobjective <span class="hlt">optimization</span>.\\u000a NSPSO extends the basic form of PSO by making a better use of <span class="hlt">particles</span>’ personal bests and offspring for more effective nondomination\\u000a comparisons. Instead of a single comparison between a <span class="hlt">particle’s</span> personal best and its offspring, NSPSO compares all <span class="hlt">particles</span>’\\u000a personal bests and their</p> <div class="credits"> <p class="dwt_author">Xiaodong Li</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">242</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JGRC..118.2746M"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">filter</span>-based data assimilation for a three-dimensional biological ocean model and satellite observations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We assimilate satellite observations of surface chlorophyll into a three-dimensional biological ocean model in order to improve its state estimates using a <span class="hlt">particle</span> <span class="hlt">filter</span> referred to as sequential importance resampling (SIR). <span class="hlt">Particle</span> <span class="hlt">Filters</span> represent an alternative to other, more commonly used ensemble-based state estimation techniques like the ensemble Kalman <span class="hlt">filter</span> (EnKF). Unlike the EnKF, <span class="hlt">Particle</span> <span class="hlt">Filters</span> do not require normality assumptions about the model error structure and are thus suitable for highly nonlinear applications. However, their application in oceanographic contexts is typically hampered by the high dimensionality of the model's state space. We apply SIR to a high-dimensional model with a small ensemble size (20) and modify the standard SIR procedure to avoid complications posed by the high dimensionality of the model state. Two extensions to the SIR include a simple smoother to deal with outliers in the observations, and state-augmentation which provides the SIR with parameter memory. Our goal is to test the feasibility of biological state estimation with SIR for realistic models. For this purpose we compare the SIR results to a model simulation with <span class="hlt">optimal</span> parameters with respect to the same set of observations. By running replicates of our main experiments, we assess the robustness of our SIR implementation. We show that SIR is suitable for satellite data assimilation into biological models and that both extensions, the smoother and state-augmentation, are required for robust results and improved fit to the observations.</p> <div class="credits"> <p class="dwt_author">Mattern, Jann Paul; Dowd, Michael; Fennel, Katja</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">243</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51017788"> <span id="translatedtitle">A new Gaussian mixture <span class="hlt">particle</span> CPHD <span class="hlt">filter</span> for multitarget tracking</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">When the number of targets is unknown or varies with time, multitarget state and measurements are represented as random sets and the multitarget tracking problem is addressed by calculating the first moment of the joint distribution, the probability hypothesis density (PHD), recursively. The PHD <span class="hlt">filter</span> has been generalized to the cardinalized PHD (CPHD) <span class="hlt">filter</span>, which propagates not only the PHD</p> <div class="credits"> <p class="dwt_author">Jungen Zhang; Hongbing Ji; Cheng Ouyang</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">244</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/r6713048w49x86v5.pdf"> <span id="translatedtitle">An Estimation of Distribution <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper we present an estimation of distribution par- ticle swarm <span class="hlt">optimization</span> algorithm that borrows ideas from recent de- velopments in ant colony <span class="hlt">optimization</span> which can be considered an es- timation of distribution algorithm. In the classical <span class="hlt">particle</span> swarm opti- mization algorithm, <span class="hlt">particles</span> exploit their individual memory to explore the search space. However, the swarm as a whole has</p> <div class="credits"> <p class="dwt_author">Mudassar Iqbal; Marco Antonio Montes De Oca</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">245</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/14372417"> <span id="translatedtitle">Coevolutionary <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Using Gaussian Distribution for Solving Constrained <span class="hlt">Optimization</span> Problems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this correspondence, an approach based on coevolutionary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> to solve constrained <span class="hlt">optimization</span> problems formulated as min-max problems is presented. In standard or canonical <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO), a uniform probability distribution is used to generate random numbers for the accelerating coefficients of the local and global s. We propose a Gaussian probability distribution to generate the accelerating</p> <div class="credits"> <p class="dwt_author">Renato A. Krohling; Leandro dos Santos Coelho</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">246</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42330188"> <span id="translatedtitle">The Effects of <span class="hlt">Particle</span> Charge on the Performance of a <span class="hlt">Filtering</span> Facepiece</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This study quantitatively determined the effect of electrostatic charge on the performance of an electret <span class="hlt">filtering</span> 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 <span class="hlt">filter</span> were measured using an aerodynamic <span class="hlt">particle</span> sizer, an Aerosizer, and a scanning</p> <div class="credits"> <p class="dwt_author">Chih-Chieh Chen; Sheng-Hsiu Huang</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">247</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.aws.cit.ie/personnel/papers/paper312.pdf"> <span id="translatedtitle">A Backtracking <span class="hlt">Particle</span> <span class="hlt">Filter</span> for fusing building plans with PDR displacement estimates</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">It is known that <span class="hlt">Particle</span> <span class="hlt">Filter</span> and Map <span class="hlt">Filtering</span> techniques can be used to improve the performance of positioning systems, such as Pedestrian Dead Reckoning (PDR). In previous research on indoor navigation, it was generally assumed that detailed building plans were available. However, in many emer gency \\/ rescue scenarios, there may be only limited building plan information on hand.</p> <div class="credits"> <p class="dwt_author">Widyawan; M. Klepal; S. Beauregard</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">248</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=ADA455225"> <span id="translatedtitle">Recovering Sample Diversity in Rao-Blackwellized <span class="hlt">Particle</span> <span class="hlt">Filters</span> for Simultaneous Localization and Mapping.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">This thesis considers possible solutions to sample impoverishment, a well-known failure mode of the Rao-Blackwellized <span class="hlt">particle</span> <span class="hlt">filter</span> (RBPF) in simultaneous localization and mapping (SLAM) situations that arises when precise feature measurements yield a l...</p> <div class="credits"> <p class="dwt_author">A. D. Anderson</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">249</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3087503"> <span id="translatedtitle">An adaptive non-local means <span class="hlt">filter</span> for denoising live-cell images and improving <span class="hlt">particle</span> detection</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and <span class="hlt">particle</span> detection. The commonly used non-local means <span class="hlt">filter</span> is not <span class="hlt">optimal</span> for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a <span class="hlt">particle</span> feature probability image, which is based on Haar-like feature extraction. The <span class="hlt">particle</span> probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this <span class="hlt">filter</span> achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak <span class="hlt">particles</span> when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means <span class="hlt">filter</span> can reduce the threshold of imaging conditions required to obtain meaningful data.</p> <div class="credits"> <p class="dwt_author">Yang, Lei; Parton, Richard; Ball, Graeme; Qiu, Zhen; Greenaway, Alan H.; Davis, Ilan; Lu, Weiping</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">250</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20599512"> <span id="translatedtitle">An adaptive non-local means <span class="hlt">filter</span> for denoising live-cell images and improving <span class="hlt">particle</span> detection.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Fluorescence imaging of dynamical processes in live cells often results in a low signal-to-noise ratio. We present a novel feature-preserving non-local means approach to denoise such images to improve feature recovery and <span class="hlt">particle</span> detection. The commonly used non-local means <span class="hlt">filter</span> is not <span class="hlt">optimal</span> for noisy biological images containing small features of interest because image noise prevents accurate determination of the correct coefficients for averaging, leading to over-smoothing and other artifacts. Our adaptive method addresses this problem by constructing a <span class="hlt">particle</span> feature probability image, which is based on Haar-like feature extraction. The <span class="hlt">particle</span> probability image is then used to improve the estimation of the correct coefficients for averaging. We show that this <span class="hlt">filter</span> achieves higher peak signal-to-noise ratio in denoised images and has a greater capability in identifying weak <span class="hlt">particles</span> when applied to synthetic data. We have applied this approach to live-cell images resulting in enhanced detection of end-binding-protein 1 foci on dynamically extending microtubules in photo-sensitive Drosophila tissues. We show that our feature-preserving non-local means <span class="hlt">filter</span> can reduce the threshold of imaging conditions required to obtain meaningful data. PMID:20599512</p> <div class="credits"> <p class="dwt_author">Yang, Lei; Parton, Richard; Ball, Graeme; Qiu, Zhen; Greenaway, Alan H; Davis, Ilan; Lu, Weiping</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-07-03</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">251</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50602742"> <span id="translatedtitle">Fractional Order Dynamics in a <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This article reports the study of fractional dynamics during the evolution of a <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm. Some initial swarm <span class="hlt">particles</span> are randomly changed, for stimulating the system response, and its effect is compared with a non-perturbed reference. The perturbation effect in the PSO evolution is observed in the perspective of the fitness time behavior of the best <span class="hlt">particle</span>.</p> <div class="credits"> <p class="dwt_author">E. J. Solteiro Pires; P. B. de Oliveira; J. A. T. Machado; I. S. Jesus</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">252</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50704319"> <span id="translatedtitle">Robot Path Planning in Unknown Environments Using <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose a method of robot path planning in unknown environments based on <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> in this paper. We firstly transform the problem of robot path planning into a minimization one, and then define the fitness of a <span class="hlt">particle</span> based on the positions of the target and the obstacles in the environment. The positions of globally best <span class="hlt">particle</span> in</p> <div class="credits"> <p class="dwt_author">Li Lu; Dunwei Gong</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">253</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1483500"> <span id="translatedtitle"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> - mass-spring system analogon</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A concept for the <span class="hlt">optimization</span> of nonlinear cost functionals, occurring in electrical engineering applications, using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) is proposed. PSO is a stochastic <span class="hlt">optimization</span> technique, whose stochastic behavior can be controlled very easily by one single factor. Additionally, this factor can be chosen to end up with a deterministic strategy, that does not need gradient information. The PSO</p> <div class="credits"> <p class="dwt_author">Bernhard Brandstätter; Ulrike Baumgartner</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">254</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/14382421"> <span id="translatedtitle">The Asymptotic <span class="hlt">Optimal</span> Frequency Domain <span class="hlt">Filter</span> for Edge Detection</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In an earlier paper by Shanmugam, Dickey, and Green, an edge detection <span class="hlt">filter</span> was derived which maximized the energy within a specified interval about an edge feature. The initial expression of this <span class="hlt">filter</span> involved a prolate spheroidal wave function. However, a careful analysis of the application of an asymptotic approximation to this function uncovered a major dimensional error. The corrected</p> <div class="credits"> <p class="dwt_author">W. H. H. J. Lunscher</p> <p class="dwt_publisher"></p> <p class="publishDate">1983-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">255</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1613888"> <span id="translatedtitle"><span class="hlt">Optimization</span> of digital <span class="hlt">filters</span> for low roundoff noise</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper treats the problem of minimizing the roundoff noise in digital <span class="hlt">filters</span> using fixed-point arithmetic under sinusoidal input. A basic assumption made is that of representing the roundoff error as white noise that is independent from sample to sample and from source to source. The minimax noise principle is introduced to serve as a guide in the <span class="hlt">filter</span> design</p> <div class="credits"> <p class="dwt_author">W. Lee</p> <p class="dwt_publisher"></p> <p class="publishDate">1974-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">256</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1681492"> <span id="translatedtitle"><span class="hlt">Optimal</span> color <span class="hlt">filters</span> in the presence of noise</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The effect of noise on the number of effective channels (color <span class="hlt">filters</span>) used to record a color image is investigated. Transmittances of color <span class="hlt">filters</span> are calculated that minimize the mean square error that occurs when estimating, from the recorded data, the colors in the image under a collection of viewing illuminants. Since the results indicate that a significant improvement in</p> <div class="credits"> <p class="dwt_author">Michael J. Vrhel; H. Joel Trussell</p> <p class="dwt_publisher"></p> <p class="publishDate">1995-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">257</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18579949"> <span id="translatedtitle">Spectral <span class="hlt">filter</span> <span class="hlt">optimization</span> for the recovery of parameters which describe human skin.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This paper presents a method for finding spectral <span class="hlt">filters</span> that minimize the error associated with histological parameters characterizing normal skin tissue. These parameters can be recovered from digital images of the skin using a physics-based model of skin coloration. The relationship between the image data and histological parameter values is defined as a mapping function from the image space to the parameter space. The accuracy of this function is determined by the choice of optical <span class="hlt">filters</span>. An <span class="hlt">optimization</span> criterion for finding the <span class="hlt">optimal</span> <span class="hlt">filters</span> is defined by combing methodology from differential geometry with statistical error analysis. It is shown that the magnitude of errors associated with the <span class="hlt">optimal</span> <span class="hlt">filters</span> is typically half of that for typical RGB <span class="hlt">filters</span> on a three-parameter model of human skin coloration. Finally, other medical image applications are identified to which this generic methodology could be applied. PMID:18579949</p> <div class="credits"> <p class="dwt_author">Preece, Stephen J; Claridge, Ela</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">258</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011JCMSI...3..315W"> <span id="translatedtitle">Modified Multi-Objective <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span>: Application to <span class="hlt">Optimization</span> of Diesel Engine Control Parameter</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this paper, <span class="hlt">optimization</span> of diesel engine control parameters using a modified multi-objective <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (MOPSO) method is considered. This problem is formulized as a multi-objective <span class="hlt">optimization</span> problem involving three <span class="hlt">optimization</span> objectives: brake specific fuel consumption (BSFC), exhaust gas emission, and soot. A modified MOPSO is proposed with integration of <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) and a crossover approach. Several benchmark functions are tested, and results reveal that the modified MOPSO is more efficient than the typical MOPSO. Engine control parameter <span class="hlt">optimization</span> with an extended PSO and the modified MOPSO is simulated, respectively. It proved the potential of the modified MOPSO for the engine control parameter <span class="hlt">optimization</span> problem.</p> <div class="credits"> <p class="dwt_author">Wu, Dongmei; Ogawa, Masatoshi; Suzuki, Yasumasa; Ogai, Harutoshi; Kusaka, Jin</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">259</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50551993"> <span id="translatedtitle">Full wave coupled resonator <span class="hlt">filter</span> <span class="hlt">optimization</span> using a multi-port admittance-matrix</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A <span class="hlt">filter</span> <span class="hlt">optimization</span> strategy based on full wave EM simulations is proposed. With the introduction of additional internal ports in the <span class="hlt">filter</span> model, the multi-port admittance-matrix (Y-matrix) is obtained. The main advantage lies in the fact that the <span class="hlt">filter</span>'s basic parameters, as there are the resonant frequency of each resonator, the coupling coefficients and the external Qs are directly accessible</p> <div class="credits"> <p class="dwt_author">S. Otto; A. Lauer; J. Kassner; A. Rennings</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">260</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50671220"> <span id="translatedtitle"><span class="hlt">Optimized</span> design of digital <span class="hlt">filter</span> in Sigma-Delta A\\/D converter</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A multi-stage digital decimator for sigma-delta analog-to-digital converter with an oversampling ratio of 64 is described. To <span class="hlt">optimize</span> the architecture of the digital <span class="hlt">filters</span> and the circuit implementation, multi-rate multi-stage decimation, half-band <span class="hlt">filter</span> and multiplier sharing are used. The <span class="hlt">filter</span> is designed and simulated using SIMULINK and MATLAB while the hardware realization is obtained using FPGA Xilinx technology. A significant</p> <div class="credits"> <p class="dwt_author">Zhao YigianglXingDongyangl; Xing Dongyang; Zhao Hongliang</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_12");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' 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id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_13");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' href="#">4</a> <a onClick='return showDiv("page_5");' href="#">5</a> <a onClick='return showDiv("page_6");' href="#">6</a> <a onClick='return showDiv("page_7");' href="#">7</a> <a onClick='return showDiv("page_8");' href="#">8</a> <a onClick='return showDiv("page_9");' href="#">9</a> <a onClick='return 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">261</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50117051"> <span id="translatedtitle">A neural network model for CAD and <span class="hlt">optimization</span> of microwave <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Improvement of the performance\\/cost ratio for modern microwave <span class="hlt">filters</span> requires manufacturing-oriented design, hence accommodating full-wave tolerance analyses and yield <span class="hlt">optimization</span> which are very computer-insensitive. The use of neural networks for reducing the design effort of microwave <span class="hlt">filters</span>, although still in its infancy, seems to provide a rather promising option. Once properly selected and trained, neural networks can approximate the <span class="hlt">filter</span></p> <div class="credits"> <p class="dwt_author">P. Burrascano; M. Dionigi; C. Fancelli; M. Mongiardo</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">262</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/27090375"> <span id="translatedtitle">Contingency <span class="hlt">Filtering</span> Techniques for Preventive Security-Constrained <span class="hlt">Optimal</span> Power Flow</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper focuses on contingency <span class="hlt">filtering</span> to accelerate the iterative solution of preventive security-constrained <span class="hlt">optimal</span> power flow (PSCOPF) problems. To this end, we propose two novel <span class="hlt">filtering</span> techniques relying on the comparison at an intermediate PSCOPF solution of post-contingency constraint violations among postulated contingencies. We assess these techniques by comparing them with severity index-based <span class="hlt">filtering</span> schemes, on a 60-and a</p> <div class="credits"> <p class="dwt_author">Florin Capitanescu; Mevludin Glavic; Damien Ernst; Louis Wehenkel</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">263</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AdWR...60...47D"> <span id="translatedtitle">Evaluating forecasting performance for data assimilation methods: The ensemble Kalman <span class="hlt">filter</span>, the <span class="hlt">particle</span> <span class="hlt">filter</span>, and the evolutionary-based assimilation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Data assimilation (DA) has facilitated the design and application of hydrological forecasting systems. DA methods such as the ensemble Kalman <span class="hlt">filter</span> (EnKF) and the <span class="hlt">particle</span> <span class="hlt">filter</span> (PF) remain popular in the hydrological literature. But a comparative evaluation of these methods to alternative techniques like the evolutionary based data assimilation (EDA) has not been thoroughly conducted. Evolutionary algorithms have been widely applied in parameter estimation and it appears natural that its application in DA be compared to standard methods, particularly, to evaluate forecasting performance of these methods. This type of evaluation is important for the design of forecasting systems and has implications for real-time forecasting operations.</p> <div class="credits"> <p class="dwt_author">Dumedah, Gift; Coulibaly, Paulin</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">264</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/11723125"> <span id="translatedtitle">Removal of submicron aerosol <span class="hlt">particles</span> and bioaerosols using carbon fiber ionizer assisted fibrous medium <span class="hlt">filter</span> media</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper reports the installation of a carbon fiber ionizer in front of a fibrous medium <span class="hlt">filter</span> to enhance the removal of\\u000a submicron aerosol <span class="hlt">particles</span> and bioaerosols. Test <span class="hlt">particles</span> (KCl) were classified with a size range of 50–600 nm using a differential\\u000a mobility analyzer (DMA). The number concentration of the test <span class="hlt">particles</span> was measured using a condensation <span class="hlt">particle</span> counter\\u000a (CPC).</p> <div class="credits"> <p class="dwt_author">Jae-Hong Park; Ki-Young Yoon; Yang-Seon Kim; Jeong Hoon Byeon; Jungho Hwang</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">265</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13265738"> <span id="translatedtitle">Multi-Objective <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> for robust <span class="hlt">optimization</span> and its hybridization with gradient search</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper proposes an algorithm using multi-objective <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (MOPSO) for finding robust solutions against small perturbations of design variables. If an <span class="hlt">optimal</span> solution is sensitive to small perturbations of variables, it may be inappropriate or risky for practical use. Robust <span class="hlt">optimization</span> finds solutions which are moderately good in terms of <span class="hlt">optimality</span> and also good in terms of robustness</p> <div class="credits"> <p class="dwt_author">Satoshi Ono; Shigeru Nakayama</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">266</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/doepatents/details.jsp?query_id=0&page=0&ostiID=913143"> <span id="translatedtitle">Method for <span class="hlt">optimizing</span> output in ultrashort-pulse multipass laser amplifiers with selective use of a spectral <span class="hlt">filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/doepatents">DOEpatents</a></p> <p class="result-summary">A method for <span class="hlt">optimizing</span> multipass laser amplifier output utilizes a spectral <span class="hlt">filter</span> in early passes but not in later passes. The pulses shift position slightly for each pass through the amplifier, and the <span class="hlt">filter</span> is placed such that early passes intersect the <span class="hlt">filter</span> while later passes bypass it. The <span class="hlt">filter</span> position may be adjust offline in order to adjust the number of passes in each category. The <span class="hlt">filter</span> may be <span class="hlt">optimized</span> for use in a cryogenic amplifier.</p> <div class="credits"> <p class="dwt_author">Backus, Sterling J. (Erie, CO); Kapteyn, Henry C. (Boulder, CO)</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-07-10</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">267</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1522529"> <span id="translatedtitle">Structured design of a 288-tap FIR <span class="hlt">filter</span> by <span class="hlt">optimized</span> partial product tree compression</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A compact 10-b, 288-tap finite impulse response (FIR) <span class="hlt">filter</span> is designed by adopting structured architecture that employs an <span class="hlt">optimized</span> partial product tree compression method. The new scheme is based on the addition of equally weighted partial products resulted from 288 multiplications of the <span class="hlt">filter</span> coefficients and the inputs. The 288 multiplication and 287 addition operations are decomposed to add 1440</p> <div class="credits"> <p class="dwt_author">Jun Rim Choi; Lak Hyun Jang; Seong Wook Jung; Jin Ho Choi</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">268</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50042911"> <span id="translatedtitle">Structured design of a 288-tap FIR <span class="hlt">filter</span> by <span class="hlt">optimized</span> partial product tree compression</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A compact 10-bit, 288-tap FIR <span class="hlt">filter</span> is designed by adopting structured architecture which employs <span class="hlt">optimized</span> partial product tree compression method. The new architecture is based on the addition of equally weighted partial products which result from 288 multiplications of the <span class="hlt">filter</span> coefficients and the inputs. The 288 multiplication and 287 addition operations are decomposed to add 1440 partial products to</p> <div class="credits"> <p class="dwt_author">Jun Rim Choi; Seong Wook Jeong; Lak Hyun Jang; Jin Ho Choi</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">269</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4290575"> <span id="translatedtitle">A Diversity Controlled Genetic Algorithm for <span class="hlt">Optimization</span> of FRM Digital <span class="hlt">Filters</span> over DBNS Multiplier Coefficient Space</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a novel diversity controlled (DC) genetic algorithm (GA) for the <span class="hlt">optimization</span> of frequency-response masking (FRM) FIR digital <span class="hlt">filters</span> over the double base number system (DBNS) multiplier coefficient space. The use of DBNS multiplier coefficients reduces the complexity and power consumption in the hardware implementation of the resulting FRM FIR digital <span class="hlt">filters</span>. A direct application of GAs to</p> <div class="credits"> <p class="dwt_author">Sai Mohan Kilambi; Behrouz Nowrouzian</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">270</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50812086"> <span id="translatedtitle"><span class="hlt">Optimization</span> of FIR <span class="hlt">filters</span> in subexpression space with constrained adder depth</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A popular technique in the design of multiplierless FIR <span class="hlt">filters</span> explores the common subexpression sharing when the <span class="hlt">filter</span> coefficients are <span class="hlt">optimized</span>. In these techniques, the coefficient multiplier are realized as a multiplier block (MB) with shared shifters and adders. Many researches showed that the power consumption of a MB is often not simply proportional to the number of adders but</p> <div class="credits"> <p class="dwt_author">Ya Jun Yu; Yong Ching Lim</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">271</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1420578"> <span id="translatedtitle">Speed estimation of an induction motor drive using an <span class="hlt">optimized</span> extended Kalman <span class="hlt">filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a novel method to achieve good performance of an extended Kalman <span class="hlt">filter</span> (EKF) for speed estimation of an induction motor drive. A real-coded genetic algorithm (GA) is used to <span class="hlt">optimize</span> the noise covariance and weight matrices of the EKF, thereby ensuring <span class="hlt">filter</span> stability and accuracy in speed estimation. Simulation studies on a constant V\\/Hz controller and a</p> <div class="credits"> <p class="dwt_author">K. L. Shi; T. F. Chan; Y. K. Wong; S. L. Ho</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">272</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/391698"> <span id="translatedtitle">Designing <span class="hlt">optimal</span> spatial <span class="hlt">filters</span> for single-trial EEG classification in a movement task</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We devise spatial <span class="hlt">filters</span> for multi-channel EEG that lead to signals which discriminate <span class="hlt">optimally</span> between two conditions. We demonstrate the effectiveness of this method by classifying single-trial EEGs, recorded during preparation for movements of left or right index finger or right foot. Best classification rates for 3 subjects were 94%, 90% and 84%, respectively. The <span class="hlt">filters</span> are estimated from a</p> <div class="credits"> <p class="dwt_author">Johannes Müller-gerking; Gert Pfurtscheller; Henrik Flyvbjerg</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">273</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ijcas.org/admin/paper/files/IJCAS_v6_n3_pp.378-385.pdf"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">Filtering</span> for Linear Discrete-Time Systems with Single Delayed Measurement</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper aims to present a polynomial approach to the steady-state <span class="hlt">optimal</span> <span class="hlt">filtering</span> for delayed systems. The design of the steady-state <span class="hlt">filter</span> involves solving one polynomial equation and one spectral factorization. The key problem in this paper is the derivation of spectral factorization for systems with delayed measurement, which is more difficult than the standard systems without delays. To get</p> <div class="credits"> <p class="dwt_author">Hong-Guo Zhao; Huan-Shui Zhang; Cheng-Hui Zhang; Xin-Min Song</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">274</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4775710"> <span id="translatedtitle"><span class="hlt">Optimal</span> and self-tuning weighted measurement fusion Wiener <span class="hlt">filter</span> for the multisensor multichannel ARMA signals</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">For the multisensor multichannel autoregressive moving average (ARMA) signals with white measurement noises, using the modern time series analysis method, based on the ARMA innovation models, white noise estimators, and measurement predictors, an <span class="hlt">optimal</span> weighted measurement fusion Wiener <span class="hlt">filter</span> is presented by the weighted least squares (WLS) method. It can handle the fused <span class="hlt">filtering</span>, smoothing and prediction problems in a</p> <div class="credits"> <p class="dwt_author">Xiao-jun Sun; Zi-li Deng</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">275</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51150265"> <span id="translatedtitle"><span class="hlt">Optimization</span> of wide-bandpass <span class="hlt">filter</span> within the Terahertz frequency regime</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Passband <span class="hlt">filters</span> in the THz frequency range devices are one the most useful application of metamaterials to cover the so called THz gap. A design procedure to obtain THz <span class="hlt">filters</span> with a broad transmission bandwidth is proposed. We apply the powerful and versatile Periodic Method of Moment (PMM) to evaluate the response of the metamaterial. The design is <span class="hlt">optimized</span> by</p> <div class="credits"> <p class="dwt_author">S. Genovesi; T.-J. Yen; A. Monorchio; E. Prati; Y.-J. Chiang; F. Costa</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">276</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50146680"> <span id="translatedtitle"><span class="hlt">Optimal</span> design of real and complex minimum phase digital FIR <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present a generalized <span class="hlt">optimal</span> minimum phase digital FIR <span class="hlt">filter</span> design algorithm that supports (1) arbitrary magnitude response specifications, (2) high coefficient accuracy, and (3) real and complex <span class="hlt">filters</span>. The algorithm uses the discrete Hilbert transform relationship between the magnitude spectrum of a causal real sequence and its minimum phase delay phase spectrum given by Cizek (1970). We extend the</p> <div class="credits"> <p class="dwt_author">N. Damera-Venkata; Brian L. Evans</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">277</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22319301"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filters</span> with multiple packet losses and its application in wireless sensor networks.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This paper is concerned with the <span class="hlt">filtering</span> problem for both discrete-time stochastic linear (DTSL) systems and discrete-time stochastic nonlinear (DTSN) systems. In DTSL systems, an linear <span class="hlt">optimal</span> <span class="hlt">filter</span> with multiple packet losses is designed based on the orthogonal principle analysis approach over unreliable wireless sensor networks (WSNs), and the experience result verifies feasibility and effectiveness of the proposed linear <span class="hlt">filter</span>; in DTSN systems, an extended minimum variance <span class="hlt">filter</span> with multiple packet losses is derived, and the <span class="hlt">filter</span> is extended to the nonlinear case by the first order Taylor series approximation, which is successfully applied to unreliable WSNs. An application example is given and the corresponding simulation results show that, compared with extended Kalman <span class="hlt">filter</span> (EKF), the proposed extended minimum variance <span class="hlt">filter</span> is feasible and effective in WSNs. PMID:22319301</p> <div class="credits"> <p class="dwt_author">Liu, Yonggui; Xu, Bugong; Feng, Linfang; Li, Shanbin</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-04-06</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">278</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AtmEn..77..385C"> <span id="translatedtitle">Use of Nuclepore <span class="hlt">filters</span> for ambient and workplace nanoparticle exposure assessment—Spherical <span class="hlt">particles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Nuclepore <span class="hlt">filter</span> collection with subsequent electron microscopy analysis for nanoparticles was carried out to examine the feasibility of the method to assess the nanoparticle exposure. The number distribution of nanoparticles collected on the <span class="hlt">filter</span> surface was counted visually and converted to the distribution in the air using existing filtration models for Nuclepore <span class="hlt">filters</span>. To search for a proper model, this paper studied the overall penetrations of three different nanoparticles (PSL, Ag and NaCl), covering a wide range of <span class="hlt">particle</span> sizes (20–800 nm) and densities (1.05–10.5 g cm?3), through Nuclepore <span class="hlt">filters</span> with two different pore diameters (1 and 3 ?m) and different face velocities (2–15 cm s?1). The data were compared with existing <span class="hlt">particle</span> deposition models and modified models proposed by this study, which delivered different results because of different deposition processes considered. It was found that a parameter associated with flow condition and <span class="hlt">filter</span> geometry (density of fluid medium, <span class="hlt">particle</span> density, filtration face velocity, <span class="hlt">filter</span> porosity and pore diameter) should be taken into account to verify the applicability of the models. The data of the overall penetration were in very good agreement with the properly applied models. A good agreement of <span class="hlt">filter</span> surface collection between the validated model and the SEM analysis was obtained, indicating a correct nanoparticle number distribution in the air can be converted from the Nuclepore <span class="hlt">filter</span> surface collection and this method can be applied for nanoparticle exposure assessment.</p> <div class="credits"> <p class="dwt_author">Chen, Sheng-Chieh; Wang, Jing; Fissan, Heinz; Pui, David Y. H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">279</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/6241348"> <span id="translatedtitle"><span class="hlt">Particle</span> size for greatest penetration of HEPA <span class="hlt">filters</span> - and their true efficiency</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The <span class="hlt">particle</span> size that most greatly penetrates a <span class="hlt">filter</span> is a function of <span class="hlt">filter</span> media construction, aerosol density, and air velocity. In this paper the published results of several experiments are compared with a modern filtration theory that predicts single-fiber efficiency and the <span class="hlt">particle</span> size of maximum penetration. For high-efficiency particulate air (HEPA) <span class="hlt">filters</span> used under design conditions this size is calculated to be 0.21 ..mu..m diam. This is in good agreement with the experimental data. The penetration at 0.21 ..mu..m is calculated to be seven times greater than at the 0.3 ..mu..m used for testing HEPA <span class="hlt">filters</span>. Several mechanisms by which <span class="hlt">filters</span> may have a lower efficiency in use than when tested are discussed.</p> <div class="credits"> <p class="dwt_author">da Roza, R.A.</p> <p class="dwt_publisher"></p> <p class="publishDate">1982-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">280</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2000SPIE.4115..302S"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filter</span> in the frequency-time mixed domain to extract moving object</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">There are same occasions to extract the moving object from image sequence in the region of remote sensing, robot vision and so on. The process needs to have high accurate extraction and simpler realization. In this paper, we propose the design method of the <span class="hlt">optimal</span> <span class="hlt">filter</span> in the frequency-time mixed domain. Frequency selective <span class="hlt">filter</span> to dynamic images usually are designed in 3-D frequency domain. But, design method of the <span class="hlt">filter</span> is difficult because of its high parameter degree. By the use of frequency-time mixed domain(MixeD) which constitutes of 2-D frequency domain and 1-D time domain, design of <span class="hlt">filters</span> becomes easier. But usually the desired and noise frequency component of image tend to concentrate near the origin in the frequency domain. Therefore, conventional frequency selective <span class="hlt">filters</span> are difficult to distinguish these. We propose the <span class="hlt">optimal</span> <span class="hlt">filter</span> in the MixeD in the sense of least mean square error. First of all, we apply 2-D spatial Fourier to dynamic images, and at each point in 2-D frequency domain, designed FIR <span class="hlt">filtering</span> is applied to 1-D time signal. In designing the <span class="hlt">optimal</span> <span class="hlt">filter</span>, we use the following information to decide the characteristics of the <span class="hlt">optimal</span> <span class="hlt">filter</span>. (1) The number of finite frames of input images. (2) The velocity vector of the signal desired. (3) The power spectrum of the noise signal. Signals constructed by these information are applied for the evaluation function and it decides <span class="hlt">filter</span> coefficients. After <span class="hlt">filtering</span>, 2-D inverse Fourier transform is applied to obtain the extracted image.</p> <div class="credits"> <p class="dwt_author">Shinmura, Hideyuki; Hiraoka, Kazuhiro; Hamada, Nozomu</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-12-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_13");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> 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showDiv("page_16");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">281</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23037408"> <span id="translatedtitle"><span class="hlt">Optimal</span> tracking of a Brownian <span class="hlt">particle</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Optical tracking of a fluorescent <span class="hlt">particle</span> in solution faces fundamental constraints due to Brownian motion, diffraction, and photon shot noise. Background photons and imperfect tracking apparatus further degrade tracking precision. Here we use a model of <span class="hlt">particle</span> motion to combine information from multiple time-points to improve the localization precision. We derive successive approximations that enable real-time <span class="hlt">particle</span> tracking with well controlled tradeoffs between precision and computational cost. We present the theory in the context of feedback electrokinetic trapping, though the results apply to optical tracking of any <span class="hlt">particle</span> subject to diffusion and drift. We use numerical simulations and experimental data to validate the algorithms' performance. PMID:23037408</p> <div class="credits"> <p class="dwt_author">Fields, Alexander P; Cohen, Adam E</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-09-24</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">282</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/23191543"> <span id="translatedtitle">Modeling the effect of <span class="hlt">particle</span> size and charge on the structure of the <span class="hlt">filter</span> cake in ultrafiltration</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A force balance model was developed to predict the effects of <span class="hlt">particle</span> size, <span class="hlt">particle</span> size distribution and surface potential on the structure of the <span class="hlt">filter</span> cake. The model predicts that a stable <span class="hlt">filter</span> cake is formed at low surface potentials and that the <span class="hlt">filter</span> cake becomes unstable when the surface potential is larger than 30mV. The model predicts a minimum</p> <div class="credits"> <p class="dwt_author">L. Fred Fu; Brian A. Dempsey</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">283</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1451862"> <span id="translatedtitle"><span class="hlt">Optimal</span> mismatched <span class="hlt">filter</span> design for radar ranging, detection, and resolution</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In a multiple-target environment a radar signal processor often uses weighting <span class="hlt">filters</span> that are not matched to the transmitted waveform. In this paper the mean-square range-estimation error, the detection Signal-to-noise ratio (SNR), and the effects of sidelobes are expressed in terms of the impulse response of an arbitrary mismatched <span class="hlt">filter</span>. It is desired to find that impulse response that results</p> <div class="credits"> <p class="dwt_author">ROBERT J. McAULAY; J. Johnson</p> <p class="dwt_publisher"></p> <p class="publishDate">1971-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">284</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/19842323"> <span id="translatedtitle">Effect of open channel <span class="hlt">filter</span> on <span class="hlt">particle</span> emissions of modern diesel engine.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary"><span class="hlt">Particle</span> emissions of modern diesel engines are of a particular interest because of their negative health effects. The special interest is in nanosized solid <span class="hlt">particles</span>. The effect of an open channel <span class="hlt">filter</span> on <span class="hlt">particle</span> emissions of a modern heavy-duty diesel engine (MAN D2066 LF31, model year 2006) was studied. Here, the authors show that the open channel <span class="hlt">filter</span> made from metal screen efficiently reduced the number of the smallest <span class="hlt">particles</span> and, notably, the number and mass concentration of soot <span class="hlt">particles</span>. The <span class="hlt">filter</span> used in this study reached 78% <span class="hlt">particle</span> mass reduction over the European Steady Cycle. Considering the size-segregated number concentration reduction, the collection efficiency was over 95% for <span class="hlt">particles</span> smaller than 10 nm. The diffusion is the dominant collection mechanism in small <span class="hlt">particle</span> sizes, thus the collection efficiency decreased as <span class="hlt">particle</span> size increased, attaining 50% at 100 nm. The overall <span class="hlt">particle</span> number reduction was 66-99%, and for accumulation-mode <span class="hlt">particles</span> the number concentration reduction was 62-69%, both depending on the engine load. PMID:19842323</p> <div class="credits"> <p class="dwt_author">Heikkilä, Juha; Rönkkö, Topi; Lähde, Tero; Lemmetty, Mikko; Arffman, Anssi; Virtanen, Annele; Keskinen, Jorma; Pirjola, Liisa; Rothe, Dieter</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">285</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3478865"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">Filter</span> Estimation for Lucas-Kanade Optical Flow</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-<span class="hlt">filtering</span> step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, <span class="hlt">filtering</span> is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image <span class="hlt">filtering</span> approach as a pre-processing step for the Lucas-Kanade pyramidal optical flow algorithm. Based on a study of different types of <span class="hlt">filtering</span> methods and applied on the Iterative Refined Lucas-Kanade, we have concluded on the best <span class="hlt">filtering</span> practice. As the Gaussian smoothing <span class="hlt">filter</span> was selected, an empirical approach for the Gaussian variance estimation was introduced. Tested on the Middlebury image sequences, a correlation between the image intensity value and the standard deviation value of the Gaussian function was established. Finally, we have found that our selection method offers a better performance for the Lucas-Kanade optical flow algorithm.</p> <div class="credits"> <p class="dwt_author">Sharmin, Nusrat; Brad, Remus</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">286</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1994SPIE.2308..963W"> <span id="translatedtitle">Design of gain-<span class="hlt">optimized</span> perfect reconstruction regular lattice <span class="hlt">filter</span> banks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper considers perfect reconstruction lattice <span class="hlt">filter</span> banks. When <span class="hlt">optimizing</span> for coding gain the purpose is to find a simple perfect reconstruction structure with few multiplication and reasonable gain. We present such a system which also possesses a certain regularity when expanding from N to 2N channels. Results including both obtained gain and the number of <span class="hlt">filter</span> multiplications and <span class="hlt">filter</span> magnitude responses are presented. The results show that the system gives strange <span class="hlt">filter</span> responses, but good coding gain considering the number of multiplications.</p> <div class="credits"> <p class="dwt_author">Waldemar, Patrick; Ramstad, Tor A.</p> <p class="dwt_publisher"></p> <p class="publishDate">1994-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">287</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=30455"> <span id="translatedtitle">AIR <span class="hlt">FILTER</span> <span class="hlt">PARTICLE</span>-SIZE EFFICIENCY TESTING FOR DIAMETERS GREATER THAN 1UM</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">The paper discusses tests of air <span class="hlt">filter</span> <span class="hlt">particle</span>-size efficiency for diameters greater than 1 micrometer. valuation of air cleaner efficiencies in this size range can be quite demanding, depending on the required accuracy. uch <span class="hlt">particles</span> have sufficient mass to require considerati...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">288</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/2391172"> <span id="translatedtitle">[<span class="hlt">Particle</span> load in intensive therapy. Possible solutions using a multi-lumen catheter and Intrapur <span class="hlt">filter</span>].</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Patients at intensive care units need very many drugs applicated via a central venous katheter. <span class="hlt">Particles</span> caused by incompatibility reactions or coming from disposible materials possibly can provoke severe complications such as embolism, anaphylactoid reactions or ARDS. The combined use of multilumen katheters and Intrapur <span class="hlt">filters</span> brings a significant reduction of these <span class="hlt">particles</span>, as shown by an infusion regime. PMID:2391172</p> <div class="credits"> <p class="dwt_author">Schröder, F</p> <p class="dwt_publisher"></p> <p class="publishDate">1990-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">289</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1682069"> <span id="translatedtitle">Visual tracking and recognition using appearance-adaptive models in <span class="hlt">particle</span> <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose an approach that incorporates appearance-based models in a <span class="hlt">particle</span> <span class="hlt">filter</span> to real- ize robust visual tracking and recognition algorithms. In conventional tracking algorithms, the appearance model is either fixed or rapidly changing, and the motion model is simply a ran- dom walk with fixed noise variance. Also, the number of <span class="hlt">particles</span> is typically fixed. All these factors make</p> <div class="credits"> <p class="dwt_author">Shaohua Kevin Zhou; Rama Chellappa; Baback Moghaddam</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">290</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23757586"> <span id="translatedtitle">Distributed <span class="hlt">Optimal</span> Consensus <span class="hlt">Filter</span> for Target Tracking in Heterogeneous Sensor Networks.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This paper is concerned with the problem of <span class="hlt">filter</span> design for target tracking over sensor networks. Different from most existing works on sensor networks, we consider the heterogeneous sensor networks with two types of sensors different on processing abilities (denoted as type-I and type-II sensors, respectively). However, questions of how to deal with the heterogeneity of sensors and how to design a <span class="hlt">filter</span> for target tracking over such kind of networks remain largely unexplored. We propose in this paper a novel distributed consensus <span class="hlt">filter</span> to solve the target tracking problem. Two criteria, namely, unbiasedness and <span class="hlt">optimality</span>, are imposed for the <span class="hlt">filter</span> design. The so-called sequential design scheme is then presented to tackle the heterogeneity of sensors. The minimum principle of Pontryagin is adopted for type-I sensors to <span class="hlt">optimize</span> the estimation errors. As for type-II sensors, the Lagrange multiplier method coupled with the generalized inverse of matrices is then used for <span class="hlt">filter</span> <span class="hlt">optimization</span>. Furthermore, it is proven that convergence property is guaranteed for the proposed consensus <span class="hlt">filter</span> in the presence of process and measurement noise. Simulation results have validated the performance of the proposed <span class="hlt">filter</span>. It is also demonstrated that the heterogeneous sensor networks with the proposed <span class="hlt">filter</span> outperform the homogenous counterparts in light of reduction in the network cost, with slight degradation of estimation performance. PMID:23757586</p> <div class="credits"> <p class="dwt_author">Zhu, Shanying; Chen, Cailian; Li, Wenshuang; Yang, Bo; Guan, Xinping</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-20</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">291</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.navlab.net/Publications/Terrain_Aided_Underwater_Navigation_Using_Point_Mass_And_Particle_Filters.pdf"> <span id="translatedtitle">Terrain Aided Underwater Navigation Using Point Mass and <span class="hlt">Particle</span> <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper focuses on obtaining submerged position fixes for underwater vehicles from comparing bathymetric mea- surements with a bathymetric map. Our algorithms are tested on real data, collected by a HUGIN AUV equipped with a multibeam echo sounder (MBE). Due to our strongly non-linear and non-Gaussian problem, local linearization methods such as the extended Kalman <span class="hlt">filter</span> (EKF), has proven unsuitable</p> <div class="credits"> <p class="dwt_author">Kjetil Bergh; Oddvar Hallingstad</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">292</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013PASP..125..838P"> <span id="translatedtitle">An Efficient and <span class="hlt">Optimal</span> <span class="hlt">Filter</span> for Identifying Point Sources in Millimeter/Submillimeter Wavelength Sky Maps</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A new technique for reliably identifying point sources in millimeter/submillimeter wavelength maps is presented. This method accounts for the frequency dependence of noise in the Fourier domain as well as nonuniformities in the coverage of a field. This <span class="hlt">optimal</span> <span class="hlt">filter</span> is an improvement over commonly-used matched <span class="hlt">filters</span> that ignore coverage gradients. Treating noise variations in the Fourier domain as well as map space is traditionally viewed as a computationally intensive problem. We show that the penalty incurred in terms of computing time is quite small due to casting many of the calculations in terms of FFTs and exploiting the absence of sharp features in the noise spectra of observations. Practical aspects of implementing the <span class="hlt">optimal</span> <span class="hlt">filter</span> are presented in the context of data from the AzTEC bolometer camera. The advantages of using the new <span class="hlt">filter</span> over the standard matched <span class="hlt">filter</span> are also addressed in terms of a typical AzTEC map.</p> <div class="credits"> <p class="dwt_author">Perera, T. A.; Wilson, G. W.; Scott, K. S.; Austermann, J. E.; Schaar, J. R.; Mancera, A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">293</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1992agcp.agar.....A"> <span id="translatedtitle">Multivariable frequency response methods for <span class="hlt">optimal</span> Kalman-Bucy <span class="hlt">filters</span> with applications to radar tracking systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The problem of multi-output, infinite-time, linear time-invariant <span class="hlt">optimal</span> Kalman-Bucy <span class="hlt">filter</span> both in continuous and discrete-time cases in frequency domain is addressed. A simple new algorithm is given for the analytical solution to the steady-state gain of the optimum <span class="hlt">filter</span> based on a transfer function approach. The algorithm is based on spectral factorization of observed spectral density matrix of the <span class="hlt">filter</span> which generates directly the return-difference matrix of the <span class="hlt">optimal</span> <span class="hlt">filter</span>. The method is more direct than by algebraic Riccati equation solution and can easily be implemented on digital computer. The design procedure is illustrated by examples and closed-form solution of ECV and ECA radar tracking <span class="hlt">filters</span> are considered as an application of the method.</p> <div class="credits"> <p class="dwt_author">Arcasoy, C. C.</p> <p class="dwt_publisher"></p> <p class="publishDate">1992-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">294</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007IJIMW..28..627B"> <span id="translatedtitle">Mode Converter Synthesis by the <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) is an effective, simple and promising method intended for the fast search in multi-dimensional space [Kennedy and Eberhart, "<span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span>", Proc. of the 1995 IEEE International Conference on Neural Networks, 1995]. Besides special testing problems a number of engineering tasks of electrodynamics were solved by the PSO successfully [Robinson and Rahmat-Samii, "<span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> in Electromagnetics", IEEE Trans. Antennas Propag., 2004; Jin and Rahmat-Samii, "Parallel <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> and Finite-Difference Time-Domain (PSO/FDTD) Algorithm for Multband and Wide-Band Patch Antenna Designs", IEEE Trans. Antennas Propag., 2005]. On the other hand, the scattering matrix technique is a fast and accurate method of mode converter analysis. We illustrate PSO by a number of converter designs developed for high-power microwaves control: a matching horn for output maser section, a corrugated converter of linear-polarized hybrid modes, a TE01 mitre bend.</p> <div class="credits"> <p class="dwt_author">Bogdashov, Alexandr A.; Rodin, Yury V.</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">295</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/610743"> <span id="translatedtitle"><span class="hlt">Optimized</span> <span class="hlt">filtering</span> of regional and teleseismic seismograms: results of maximizing SNR measurements from the wavelet transform and <span class="hlt">filter</span> banks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Development of a worldwide network to monitor seismic activity requires deployment of seismic sensors in areas which have not been well studied or may have from available recordings. Development and testing of detection and discrimination algorithms requires a robust representative set of calibrated seismic events for a given region. Utilizing events with poor signal-to-noise (SNR) can add significant numbers to usable data sets, but these events must first be adequately <span class="hlt">filtered</span>. Source and path effects can make this a difficult task as <span class="hlt">filtering</span> demands are highly varied as a function of distance, event magnitude, bearing, depth etc. For a given region, conventional methods of <span class="hlt">filter</span> selection can be quite subjective and may require intensive analysis of many events. In addition, <span class="hlt">filter</span> parameters are often overly generalized or contain complicated switching. We have developed a method to provide an <span class="hlt">optimized</span> <span class="hlt">filter</span> for any regional or teleseismically recorded event. Recorded seismic signals contain arrival energy which is localized in frequency and time. Localized temporal signals whose frequency content is different from the frequency content of the pre-arrival record are identified using rms power measurements. The method is based on the decomposition of a time series into a set of time series signals or scales. Each scale represents a time-frequency band with a constant Q. SNR is calculated for a pre-event noise window and for a window estimated to contain the arrival. Scales with high SNR are used to indicate the band pass limits for the <span class="hlt">optimized</span> <span class="hlt">filter</span>.The results offer a significant improvement in SNR particularly for low SNR events. Our method provides a straightforward, <span class="hlt">optimized</span> <span class="hlt">filter</span> which can be immediately applied to unknown regions as knowledge of the geophysical characteristics is not required. The <span class="hlt">filtered</span> signals can be used to map the seismic frequency response of a region and may provide improvements in travel-time picking, bearing estimation regional characterization, and event detection. Results are shown for a set of low SNR events as well as 92 regional and teleseismic events in the Middle East.</p> <div class="credits"> <p class="dwt_author">Leach, R.R.; Schultz, C.; Dowla, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-07-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">296</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/24094750"> <span id="translatedtitle"><span class="hlt">Optimized</span> superficially porous <span class="hlt">particles</span> for protein separations.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Continuing interest in larger therapeutic molecules by pharmaceutical and biotech companies provides the need for improved tools for examining these molecules both during the discovery phase and later during quality control. To meet this need, larger pore superficially porous <span class="hlt">particles</span> with appropriate surface properties (Fused-Core(®) <span class="hlt">particles</span>) have been developed with a pore size of 400?, allowing large molecules (<500kDa) unrestricted access to the bonded phase. In addition, a <span class="hlt">particle</span> size (3.4?m) is employed that allows high-efficiency, low-pressure separations suitable for potentially pressure-sensitive proteins. A study of the shell thickness of the new fused-core <span class="hlt">particles</span> suggests a compromise between a short diffusion path and high efficiency versus adequate retention and mass load tolerance. In addition, superior performance for the reversed-phase separation of proteins requires that specific design properties for the bonded-phase should be incorporated. As a result, columns of the new <span class="hlt">particles</span> with unique bonded phases show excellent stability and high compatibility with mass spectrometry-suitable mobile phases. This report includes fast separations of intact protein mixtures, as well as examples of very high-resolution separations of larger monoclonal antibody materials and associated variants. Investigations of protein recovery, sample loading and dynamic range for analysis are shown. The advantages of these new 400? fused-core <span class="hlt">particles</span>, specifically designed for protein analysis, over traditional <span class="hlt">particles</span> for protein separations are demonstrated. PMID:24094750</p> <div class="credits"> <p class="dwt_author">Schuster, Stephanie A; Wagner, Brian M; Boyes, Barry E; Kirkland, Joseph J</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-19</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">297</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4722816"> <span id="translatedtitle">A novel technique for the design and DCGA <span class="hlt">optimization</span> of bilinear-LDI lattice-based digital IF <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Intermediate frequency (IF) <span class="hlt">filters</span> find diverse practical applications in modern communication systems. This paper presents a novel technique for the design and <span class="hlt">optimization</span> of digital IF <span class="hlt">filters</span>. This technique consists of two separate stages. In the first stage, the bilinear-LDI lattice digital <span class="hlt">filter</span> realization approach is exploited and applied to the design of an infinite- precision digital IF <span class="hlt">filter</span> responsible</p> <div class="credits"> <p class="dwt_author">Yifan Wu; Behrouz Nowrouzian</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">298</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50556810"> <span id="translatedtitle"><span class="hlt">Optimized</span> Resonant Control for Shunt Active Power <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents an <span class="hlt">optimization</span> technique of the resonant controller based on the minimization of an objective function through the Nelder-Mead method. This function allows to evaluate the behavior of the system in steady state and transient conditions. The <span class="hlt">optimized</span> controller has been compared with the Naslin polynomial based one. The results show that by means of the <span class="hlt">optimization</span> technique</p> <div class="credits"> <p class="dwt_author">Antonio Dell'Aquila; Maria Marinelli; Vito Giuseppe Monopoli; Agostino Lecci</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">299</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=115033"> <span id="translatedtitle">NASAL <span class="hlt">FILTERING</span> OF FINE <span class="hlt">PARTICLES</span> IN CHILDREN VS. ADULTS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">Nasal efficiency for removing fine <span class="hlt">particles</span> 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 <span class="hlt">particles</span> (1 and 2um MMAD)...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">300</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009ApPhL..95z1101Y"> <span id="translatedtitle">Design of one-dimensional optical pulse-shaping <span class="hlt">filters</span> by time-domain topology <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Time-domain topology <span class="hlt">optimization</span> is used here to design optical pulse-shaping <span class="hlt">filters</span> in Si/SiO2 thin-film systems. A novel envelope objective function as well as explicit penalization are used to adapt the <span class="hlt">optimization</span> method to this unique class of design problems.</p> <div class="credits"> <p class="dwt_author">Yang, Lirong; Lavrinenko, Andrei V.; Hvam, Jřrn M.; Sigmund, Ole</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_14");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" 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showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_17");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">301</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1640542"> <span id="translatedtitle">GSVD-based <span class="hlt">optimal</span> <span class="hlt">filtering</span> for single and multimicrophone speech enhancement</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A generalized singular value decomposition (GSVD) based algorithm is proposed for enhancing multimicrophone speech signals degraded by additive colored noise. This GSVD-based multimicrophone algorithm can be considered to be an extension of the single-microphone signal subspace algorithms for enhancing noisy speech signals and amounts to a specific <span class="hlt">optimal</span> <span class="hlt">filtering</span> problem when the desired response signal cannot be observed. The <span class="hlt">optimal</span></p> <div class="credits"> <p class="dwt_author">Simon Doclo; Marc Moonen</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">302</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/b2j627hp01643823.pdf"> <span id="translatedtitle">Research on Constrained Layout <span class="hlt">Optimization</span> Problem Using Multi-adaptive Strategies <span class="hlt">Particle</span> Swarm <span class="hlt">Optimizer</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a The complex layout <span class="hlt">optimization</span> problems with behavioral constraints belong to NP-hard problem in math. Due to its complexity,\\u000a the general <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm converges slowly and easily to local optima. Taking the layout problem of\\u000a satellite cabins as background, a novel adaptive <span class="hlt">particle</span> swarm <span class="hlt">optimizer</span> based on multi-modified strategies is proposed in\\u000a the paper, which can not only escape</p> <div class="credits"> <p class="dwt_author">Kaiyou Lei</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">303</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/26105610"> <span id="translatedtitle">A <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> approach to <span class="hlt">optimize</span> component placement in printed circuit board assembly</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) approach has been successfully applied in continuous problems in practice. However,\\u000a its application on the combinatorial search space is relatively new. The component assignment\\/sequencing problem in printed\\u000a circuit board (PCB) has been verified as NP-hard (non-deterministic polynomial time). This paper presents an adaptive <span class="hlt">particle</span>\\u000a swarm <span class="hlt">optimization</span> (APSO) approach to <span class="hlt">optimize</span> the sequence of component placements</p> <div class="credits"> <p class="dwt_author">Yee-Ming Chen; Chun-Ta Lin</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">304</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/19209704"> <span id="translatedtitle">Parameter estimation of in silico biological pathways with <span class="hlt">particle</span> <span class="hlt">filtering</span> towards a petascale computing.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The aim of this paper is to demonstrate the potential power of large-scale <span class="hlt">particle</span> <span class="hlt">filtering</span> for the parameter estimations of in silico biological pathways where time course measurements of biochemical reactions are observable. The method of <span class="hlt">particle</span> <span class="hlt">filtering</span> has been a popular technique in the field of statistical science, which approximates posterior distributions of model parameters of dynamic system by using sequentially-generated Monte Carlo samples. In order to apply the <span class="hlt">particle</span> <span class="hlt">filtering</span> to system identifications of biological pathways, it is often needed to explore the posterior distributions which are defined over an exceedingly high-dimensional parameter space. It is then essential to use a fairly large amount of Monte Carlo samples to obtain an approximation with a high-degree of accuracy. In this paper, we address some implementation issues on large-scale <span class="hlt">particle</span> <span class="hlt">filtering</span>, and then, indicate the importance of large-scale computing for parameter learning of in silico biological pathways. We have tested the ability of the <span class="hlt">particle</span> <span class="hlt">filtering</span> with 10(8) Monte Carlo samples on the transcription circuit of circadian clock that contains 45 unknown kinetic parameters. The proposed approach could reveal clearly the shape of the posterior distributions over the 45 dimensional parameter space. PMID:19209704</p> <div class="credits"> <p class="dwt_author">Nakamura, Kazuyuki; Yoshida, Ryo; Nagasaki, Masao; Miyano, Satoru; Higuchi, Tomoyuki</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">305</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012ChPhB..21f8901B"> <span id="translatedtitle">A genetic resampling <span class="hlt">particle</span> <span class="hlt">filter</span> for freeway traffic-state estimation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">On-line estimation of the state of traffic based on data sampled by electronic detectors is important for intelligent traffic management and control. Because a nonlinear feature exists in the traffic state, and because <span class="hlt">particle</span> <span class="hlt">filters</span> have good characteristics when it comes to solving the nonlinear problem, a genetic resampling <span class="hlt">particle</span> <span class="hlt">filter</span> is proposed to estimate the state of freeway traffic. In this paper, a freeway section of the northern third ring road in the city of Beijing in China is considered as the experimental object. By analysing the traffic-state characteristics of the freeway, the traffic is modeled based on the second-order validated macroscopic traffic flow model. In order to solve the <span class="hlt">particle</span> degeneration issue in the performance of the <span class="hlt">particle</span> <span class="hlt">filter</span>, a genetic mechanism is introduced into the resampling process. The realization of a genetic <span class="hlt">particle</span> <span class="hlt">filter</span> for freeway traffic-state estimation is discussed in detail, and the <span class="hlt">filter</span> estimation performance is validated and evaluated by the achieved experimental data.</p> <div class="credits"> <p class="dwt_author">Bi, Jun; Guan, Wei; Qi, Long-Tao</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">306</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/24154721"> <span id="translatedtitle"><span class="hlt">Optimal</span> control of <span class="hlt">particle</span> separation in inertial microfluidics.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Recently, inertial mircofluidics has emerged as a promising tool to manipulate complex liquids with possible biomedical applications, for example, to <span class="hlt">particle</span> separation. Indeed, in experiments different <span class="hlt">particle</span> types were separated based on their sizes (A.J. Mach, D. Di Carlo, Biotechnol. Bioeng. 107, 302 (2010)). In this article we use a theoretical study to demonstrate how concepts from <span class="hlt">optimal</span> control theory help to design <span class="hlt">optimized</span> profiles of control forces that allow to steer <span class="hlt">particles</span> to almost any position at the outlet of a microfluidic channel. We also show that one specific control force profile is sufficient to guide two types of <span class="hlt">particles</span> to different locations at the channel outlet, where they can be separated from each other. The <span class="hlt">particles</span> just differ by their size which determines the strength of the inertial lift forces they experience. Our approach greatly enhances the efficiency of <span class="hlt">particle</span> separation in the inertial regime. PMID:24154721</p> <div class="credits"> <p class="dwt_author">Prohm, Christopher; Tröltzsch, Fredi; Stark, Holger</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-25</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">307</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50974766"> <span id="translatedtitle">A Binary <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Based on Proportion Probability</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> (PSO), as a novel computational intelligence technique, has succeeded in many continuous problems. But in discrete or binary version there are still some difficulties. In this paper a novel binary PSO is proposed. This algorithm proposes a new definition for the position vector of binary PSO. The probability of a certain <span class="hlt">particle</span> element assuming a value of</p> <div class="credits"> <p class="dwt_author">Enxiu Chen; Zhenliang Pan; Yi Sun; Xiyu Liu</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">308</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50570728"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Based Capacitor Placement on Radial Distribution Systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a novel approach that determines the <span class="hlt">optimal</span> location and size of capacitors on radial distribution systems to improve voltage profile and reduce the active power loss. Capacitor placement & sizing are done by loss sensitivity factors and <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> respectively. The concept of loss sensitivity factors and can be considered as the new contribution in the</p> <div class="credits"> <p class="dwt_author">K. Prakash; M. Sydulu</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">309</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50359578"> <span id="translatedtitle"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> for base station placement in mobile communication</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The tremendous growth in the demand for mobile services results in an explosion in base station (BS) density and network complexity, making the conventional manual planning processes highly inefficient. In this paper, we give some novel adaptation to the recent bio-inspired <span class="hlt">optimization</span> approach, <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO), to form a suitable algorithm for the base station placement problem. Considering the</p> <div class="credits"> <p class="dwt_author">Zhang Yangyang; Ji Chunlin; Yuan Ping; Li Manlin; Wang Chaojin; Wang Guangxing</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">310</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=DE20131038489"> <span id="translatedtitle">Simple Distributed <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> for Dynamic and Noisy Environments.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">In this paper, we present a Simple Distributed <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (SDPSO) algorithm that can be used to track the <span class="hlt">optimal</span> solution in a dynamic and noisy environment. The classic PSO algorithm lacks the ability to track changing optimum in a dyna...</p> <div class="credits"> <p class="dwt_author">J. St. Charles T. E. Potok X. Cui</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">311</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50752313"> <span id="translatedtitle">A wireless sensor network coverage <span class="hlt">optimization</span> algorithm based on <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> and Voronoi diagram</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The coverage problem is a crucial issue in wireless sensor networks (WSN), where a high coverage rate ensures a high quality of service of the WSN. This paper proposes a new algorithm to <span class="hlt">optimize</span> sensor coverage using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) and Voronoi diagram. PSO is used to find the <span class="hlt">optimal</span> deployment of the sensors that gives the best coverage</p> <div class="credits"> <p class="dwt_author">N. A. B. A. Aziz; A. W. Mohemmed; M. Y. Alias</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">312</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.tut.fi/~bogdand/Recent_work/iir_eus.pdf"> <span id="translatedtitle">ON CONVEX STABILITY DOMAIN AND <span class="hlt">OPTIMIZATION</span> OF IIR <span class="hlt">FILTERS</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We discuss descriptions of convex domains containing Schur polynomials, built around a given Schur polynomial. We show that the domain described by a positive realness constraint always contains the domain characterized by Rouche's theorem. We also show how to handle computa- tionally the positive realness condition, using semidefinite programming, in the context of designing stable IIR <span class="hlt">filters</span>. Two recent methods</p> <div class="credits"> <p class="dwt_author">Bogdan Dumitrescu</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">313</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1646919"> <span id="translatedtitle">On-road vehicle detection using evolutionary Gabor <span class="hlt">filter</span> <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Past work on vehicle detection has emphasized the issues of feature extraction and classification, however, less attention has been given on the critical issue of feature selection. The focus of this paper is on improving the performance of on-road vehicle detection by employing a set of Gabor <span class="hlt">filters</span> that have been specifically customized for the problem of vehicle detection. The</p> <div class="credits"> <p class="dwt_author">Zehang Sun; George Bebis; Ronald Miller</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">314</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3482905"> <span id="translatedtitle"><span class="hlt">Optimally</span> designed narrowband guided-mode resonance reflectance <span class="hlt">filters</span> for mid-infrared spectroscopy</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">An alternative to the well-established Fourier transform infrared (FT-IR) spectrometry, termed discrete frequency infrared (DFIR) spectrometry, has recently been proposed. This approach uses narrowband mid-infrared reflectance <span class="hlt">filters</span> based on guided-mode resonance (GMR) in waveguide gratings, but <span class="hlt">filters</span> designed and fabricated have not attained the spectral selectivity (? 32 cm?1) commonly employed for measurements of condensed matter using FT-IR spectroscopy. With the incorporation of dispersion and optical absorption of materials, we present here <span class="hlt">optimal</span> design of double-layer surface-relief silicon nitride-based GMR <span class="hlt">filters</span> in the mid-IR for various narrow bandwidths below 32 cm?1. Both shift of the <span class="hlt">filter</span> resonance wavelengths arising from the dispersion effect and reduction of peak reflection efficiency and electric field enhancement due to the absorption effect show that the optical characteristics of materials must be taken into consideration rigorously for accurate design of narrowband GMR <span class="hlt">filters</span>. By incorporating considerations for background reflections, the <span class="hlt">optimally</span> designed GMR <span class="hlt">filters</span> can have bandwidth narrower than the designed <span class="hlt">filter</span> by the antireflection equivalence method based on the same index modulation magnitude, without sacrificing low sideband reflections near resonance. The reported work will enable use of GMR <span class="hlt">filters</span>-based instrumentation for common measurements of condensed matter, including tissues and polymer samples.</p> <div class="credits"> <p class="dwt_author">Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">315</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13320226"> <span id="translatedtitle">A Study on Smoothing for <span class="hlt">Particle-Filtered</span> 3D Human Body Tracking</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Stochastic models have become the dominant means of approaching the problem of articulated 3D human body tracking, where approximate\\u000a inference is employed to tractably estimate the high-dimensional (?30D) posture space. Of these approximate inference techniques,\\u000a <span class="hlt">particle</span> <span class="hlt">filtering</span> is the most commonly used approach. However <span class="hlt">filtering</span> only takes into account past observations—almost\\u000a no body tracking research employs smoothing to improve the</p> <div class="credits"> <p class="dwt_author">Patrick Peursum; Svetha Venkatesh; Geoff West</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">316</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009istm.book..100I"> <span id="translatedtitle">A Novel <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Approach for Grid Job Scheduling</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper represents a <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) algorithm, for grid job scheduling. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. <span class="hlt">Particles</span> fly in problem search space to find <span class="hlt">optimal</span> or near-<span class="hlt">optimal</span> solutions. In this paper we used a PSO approach for grid job scheduling. The scheduler aims at minimizing makespan and flowtime simultaneously. Experimental studies show that the proposed novel approach is more efficient than the PSO approach reported in the literature.</p> <div class="credits"> <p class="dwt_author">Izakian, Hesam; Tork Ladani, Behrouz; Zamanifar, Kamran; Abraham, Ajith</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">317</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012JQSRT.113..607P"> <span id="translatedtitle">Absorption coefficient measurements of <span class="hlt">particle</span>-laden <span class="hlt">filters</span> using laser heating: Validation with nigrosin</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A laser-heating technique, referred as the laser-driven thermal reactor, was used in conjunction with laser transmissivity measurements to determine the absorption coefficient of <span class="hlt">particle</span>-laden substrates (e.g., quartz-fiber <span class="hlt">filters</span>). The novelty of this approach is that it analyzes a wide variety of specific samples (not just <span class="hlt">filtered</span> samples) and overcomes measurement issues (e.g., absorption enhancement) associated with other <span class="hlt">filter</span>-based <span class="hlt">particle</span> absorption techniques. The absorption coefficient was determined for nigrosin-laden, quartz-fiber <span class="hlt">filters</span> and the effect of the <span class="hlt">filter</span> on the absorption measurements was estimated when compared to the isolated nigrosin results. The isolated nigrosin absorption coefficient compared favorably with Lorenz-Mie calculations for an idealized polydispersion of spherical <span class="hlt">particles</span> (based on a measured nigronsin/de-ionized water suspension size distribution) dispersed throughout a volume equivalent to that of the nigrosin-laden <span class="hlt">filter</span>. To validate the approach, the absorption coefficient of a nigrosin/de-ionized water suspension was in good agreement with results obtained from an ultraviolet/visible spectrometer. In addition, the estimated imaginary part of the refractive index from the Lorenz-Mie calculations compared well with literature values and was used to estimate the absorption coefficient of optically opaque packed nigrosin.</p> <div class="credits"> <p class="dwt_author">Presser, Cary</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">318</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009EGUGA..1110010V"> <span id="translatedtitle">A DiffeRential Evolution Adaptive Metropolis (DREAM) <span class="hlt">Particle</span> <span class="hlt">Filter</span> for Environmental Model Diagnostics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Sequential Monte Carlo (SMC) approaches are increasingly being used in watershed hydrology to approximate the evolving posterior distribution of model parameters and states when new streamflow or other data are becoming available. The typical implementation of SMC requires the use of a set of <span class="hlt">particles</span> to represent the posterior probability density function (pdf) of model parameters and states. These <span class="hlt">particles</span> are propagated forward in time and/or space using the (nonlinear) model operator and updated when new observational data become available. Main difficulty in applying <span class="hlt">particle</span> <span class="hlt">filters</span> in practice is problems with ensemble degeneracy, in which an increasing number of <span class="hlt">particles</span> is exploring unproductive parts of the posterior pdf and assigned a negligible weight. To ensure sufficient <span class="hlt">particle</span> diversity at every stage during the simulation, I will present an efficient SMC scheme that combines <span class="hlt">particle</span> <span class="hlt">filtering</span> with importance resampling and DiffeRential Evolution Adaptive Metropolis (DREAM) sampling. Our method is based on the DREAM adaptive MCMC scheme presented in Vrugt et al. (2009), but implemented sequentially to facilitate posterior tracking of model parameters and states. Initial results using the Sacramento Soil Moisture Accounting (SAC-SMA) model have shown that our DREAM <span class="hlt">particle</span> <span class="hlt">filter</span> has the advantage of requiring far fewer <span class="hlt">particles</span> than conventional SMC approaches. This significantly speeds up convergence to the evolving limiting distribution, and allows parameter and state inference in spatially distributed hydrologic models.</p> <div class="credits"> <p class="dwt_author">Vrugt, J. A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">319</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/22843008"> <span id="translatedtitle">Nonlinear parameter estimation through <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Parameter estimation procedures are very important in the chemical engineering field for development of mathematical models, since design, <span class="hlt">optimization</span> and advanced control of chemical processes depend on model parameter values obtained from experimental data. Model nonlinearity makes the estimation of parameter and the statistical analysis of parameter estimates more difficult and more challenging. In this work, it is shown that</p> <div class="credits"> <p class="dwt_author">Marcio Schwaab; José Luiz Monteiro; José Carlos Pinto</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">320</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/5640339"> <span id="translatedtitle">Terrain Aided Underwater Navigation Using Point Mass and <span class="hlt">Particle</span> <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Abstract—This paper focuses on obtaining submerged,position fixes for underwater,vehicles from,comparing,bathymetric,mea- surements,with a bathymetric,map. Our algorithms,are tested on real data, collected by a HUGIN AUV equipped with a multibeam,echo sounder,(MBE). Due to our strongly non-linear and non-Gaussian problem, local linearization methods such as the extended Kalman <span class="hlt">filter</span> (EKF), has proven unsuitable in many,terrain types. We therefore focus on two different recursive</p> <div class="credits"> <p class="dwt_author">Kjetil Bergh Anonsen; Oddvar Hallingstad</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_15");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return 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title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">321</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/837305"> <span id="translatedtitle">Removal of <span class="hlt">Particles</span> and Acid Gases (SO2 or HCl) with a Ceramic <span class="hlt">Filter</span> by Addition of Dry Sorbents</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The present investigation intends to add to the fundamental process design know-how for dry flue gas cleaning, especially with respect to process flexibility, in cases where variations in the type of fuel and thus in concentration of contaminants in the flue gas require <span class="hlt">optimization</span> of operating conditions. In particular, temperature effects of the physical and chemical processes occurring simultaneously in the gas-<span class="hlt">particle</span> dispersion and in the <span class="hlt">filter</span> cake/<span class="hlt">filter</span> medium are investigated in order to improve the predictive capabilities for identifying optimum operating conditions. Sodium bicarbonate (NaHCO{sub 3}) and calcium hydroxide (Ca(OH){sub 2}) are known as efficient sorbents for neutralizing acid flue gas components such as HCl, HF, and SO{sub 2}. According to their physical properties (e.g. porosity, pore size) and chemical behavior (e.g. thermal decomposition, reactivity for gas-solid reactions), optimum conditions for their application vary widely. The results presented concentrate on the development of quantitative data for filtration stability and overall removal efficiency as affected by operating temperature. Experiments were performed in a small pilot unit with a ceramic <span class="hlt">filter</span> disk of the type Dia-Schumalith 10-20 (Fig. 1, described in more detail in Hemmer 2002 and Hemmer et al. 1999), using model flue gases containing SO{sub 2} and HCl, flyash from wood bark combustion, and NaHCO{sub 3} as well as Ca(OH){sub 2} as sorbent material (<span class="hlt">particle</span> size d{sub 50}/d{sub 84} : 35/192 {micro}m, and 3.5/16, respectively). The pilot unit consists of an entrained flow reactor (gas duct) representing the raw gas volume of a <span class="hlt">filter</span> house and the <span class="hlt">filter</span> disk with a <span class="hlt">filter</span> cake, operating continuously, simulating <span class="hlt">filter</span> cake build-up and cleaning of the <span class="hlt">filter</span> medium by jet pulse. Temperatures varied from 200 to 600 C, sorbent stoichiometric ratios from zero to 2, inlet concentrations were on the order of 500 to 700 mg/m{sup 3}, water vapor contents ranged from zero to 20 vol%. The experimental program with NaHCO{sub 3} is listed in Table 1. In addition, model calculations were carried out based on own and published experimental results that estimate residence time and temperature effects on removal efficiencies.</p> <div class="credits"> <p class="dwt_author">Hemmer, G.; Kasper, G.; Wang, J.; Schaub, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-09-20</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">322</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009IJTFM.129..681T"> <span id="translatedtitle">Multi-Resonator Generation by Genetic <span class="hlt">Optimization</span> for Application to Planar-Circuit Bandpass <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper proposes a design method of arbitrarily-shaped bandpass <span class="hlt">filters</span> with multiple resonators in the limited space. Although the proposed method is based on the genetic-algorithm (GA) <span class="hlt">optimization</span>, we newly introduce the fitness function which estimates not only the magnitude of S-parameters but also the phase characteristics in a passband. Conventional GAs without phase evaluation are difficult to design a <span class="hlt">filter</span> having the specified number of resonators efficiently, whereas the present method can easily construct such a <span class="hlt">filter</span>. As an example, arbitrarily-shaped planar-circuit <span class="hlt">filters</span> with 3 and 4 resonators are <span class="hlt">optimized</span> in the limited space and fabricated. The effectiveness of the present technique is verified by comparison of frequency responses between the calculated and the measured results.</p> <div class="credits"> <p class="dwt_author">Tsuji, Mikio; Deguchi, Hiroyuki; Kido, Akinori; Ohira, Masataka</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">323</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/19529515"> <span id="translatedtitle">Design of multichannel DWDM fiber Bragg grating <span class="hlt">filters</span> by Lagrange multiplier constrained <span class="hlt">optimization</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We present the synthesis of multi-channel fiber Bragg grating (MCFBG) <span class="hlt">filters</span> for dense wavelength-division-multiplexing (DWDM) application by using a simple <span class="hlt">optimization</span> approach based on a Lagrange multiplier <span class="hlt">optimization</span> (LMO) method. We demonstrate for the first time that the LMO method can be used to constrain various parameters of the designed MCFBG <span class="hlt">filters</span> for practical application demands and fabrication requirements. The designed <span class="hlt">filters</span> have a number of merits, i.e., flat-top and low dispersion spectral response as well as single stage. Above all, the maximum amplitude of the index modulation profiles of the designed MCFBGs can be substantially reduced under the applied constrained condition. The simulation results demonstrate that the LMO algorithm can provide a potential alternative for complex fiber grating <span class="hlt">filter</span> design problems. PMID:19529515</p> <div class="credits"> <p class="dwt_author">Lee, Cheng-Ling; Lee, Ray-Kuang; Kao, Yee-Mou</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-11-13</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">324</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007SPIE.6732E..24S"> <span id="translatedtitle"><span class="hlt">Optimization</span> of the fine structure and flow behavior of anisotropic porous <span class="hlt">filters</span>, synthesized by SLS method</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The main goal of the work was <span class="hlt">optimization</span> of the phase and porous fine structures of <span class="hlt">filter</span> elements and subsequent laser synthesis by the method layer-by-layer Selective Laser Sintering (SLS) of functional devices, exploration of their properties and requirements of synthesis. Common methodical approaches are developed by the searching <span class="hlt">optimal</span> requirements of layer-by-layer synthesis usable to different powder compositions and concrete guidelines (conditions of sintering, powder composition, etc.) for SLS of <span class="hlt">filter</span> elements (including anisotropic) from metal-polymer powder mixture - brass + polycarbonate{PC} = 6:1. As a result of numerical simulations it designed an original graph - numerical procedure and represented a computer program for definition of flow <span class="hlt">filter</span> performances, as homogeneous (isotropic) as heterogeneous (anisotropic), having the cylindrical shape. Calculation of flow behavior for anisotropic <span class="hlt">filter</span> elements allows predicting their future applications and managing its.</p> <div class="credits"> <p class="dwt_author">Shishkovsky, I.; Sherbakov, V.; Pitrov, A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">325</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012OptEn..51d7203L"> <span id="translatedtitle">Feature-driven motion model-based <span class="hlt">particle-filter</span> tracking method with abrupt motion handling</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The potential for the research of object tracking in computer vision has been well established, but previous object-tracking methods, which consider only continuous and smooth motion, are limited in handling abrupt motions. We introduce an efficient algorithm to tackle this limitation. A feature-driven (FD) motion model-based features from accelerated segment test (FAST) feature matching is proposed in the <span class="hlt">particle-filtering</span> framework. Various evaluations have demonstrated that this motion model can improve existing methods' performances to handle abrupt motion significantly. The proposed model can be applied to most existing <span class="hlt">particle-filter</span> tracking methods.</p> <div class="credits"> <p class="dwt_author">Liu, Yu; Lai, Shiming; Wang, Bin; Zhang, Maojun; Wang, Wei</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">326</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.3008P"> <span id="translatedtitle">Joint global <span class="hlt">optimization</span> of tomographic data based on <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> and decision theory</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search <span class="hlt">optimization</span> methods used to find an <span class="hlt">optimal</span> model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global <span class="hlt">optimization</span> (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the <span class="hlt">optimal</span> model independently from the starting model. Additionally, they can be used to find sets of <span class="hlt">optimal</span> models allowing a further analysis of model parameter uncertainties. Here we employ <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) to realize the global <span class="hlt">optimization</span> of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards <span class="hlt">optimal</span> solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of <span class="hlt">particles</span> cruise a multi-dimensional solution space striving to find <span class="hlt">optimal</span> model solutions explaining the acquired data. The <span class="hlt">particles</span> communicate their positions and success and direct their movement according to the position of the currently most successful <span class="hlt">particle</span> of the swarm. The success of a <span class="hlt">particle</span>, i.e. the quality of the currently found model by a <span class="hlt">particle</span>, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the <span class="hlt">optimization</span> solution has to satisfy multiple <span class="hlt">optimization</span> objectives, at least one for each data set. Unique determination of the most successful <span class="hlt">particle</span> currently leading the swarm is not possible. Instead, only statements about the Pareto <span class="hlt">optimality</span> of the found solutions can be made. Identification of the leading <span class="hlt">particle</span> traditionally requires a costly combination of ranking and niching techniques. In our approach, we use a decision rule under uncertainty to identify the currently leading <span class="hlt">particle</span> of the swarm. In doing so, we consider the different objectives of our <span class="hlt">optimization</span> problem as competing agents with partially conflicting interests. Analysis of the maximin fitness function allows for robust and cheap identification of the currently leading <span class="hlt">particle</span>. The final <span class="hlt">optimization</span> result comprises a set of possible models spread along the Pareto front. For convex Pareto fronts, solution density is expected to be maximal in the region ideally compromising all objectives, i.e. the region of highest curvature.</p> <div class="credits"> <p class="dwt_author">Paasche, H.; Tronicke, J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">327</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/39928549"> <span id="translatedtitle">On <span class="hlt">optimal</span> <span class="hlt">filtering</span> of GPS dual frequency observations without using orbit information</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The concept of <span class="hlt">optimal</span> <span class="hlt">filtering</span> of observations collected with a dual frequency GPS P-code receiver is investigated in comparison\\u000a to an approach for C\\/A-code units. The <span class="hlt">filter</span> presented here uses only data gathered between one receiver and one satellite.\\u000a The estimated state vector consists of a one-way pseudorange, ionospheric influence, and ambiguity biases. Neither orbit information\\u000a nor station information is</p> <div class="credits"> <p class="dwt_author">Hans-Juergen Eueler; Clyde C. Goad</p> <p class="dwt_publisher"></p> <p class="publishDate">1991-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">328</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23961391"> <span id="translatedtitle">Gravity inversion of a fault by <span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> (PSO).</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> is a heuristic global <span class="hlt">optimization</span> method and also an <span class="hlt">optimization</span> algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. In this paper we introduce and use this method in gravity inverse problem. We discuss the solution for the inverse problem of determining the shape of a fault whose gravity anomaly is known. Application of the proposed algorithm to this problem has proven its capability to deal with difficult <span class="hlt">optimization</span> problems. The technique proved to work efficiently when tested to a number of models. PMID:23961391</p> <div class="credits"> <p class="dwt_author">Toushmalani, Reza</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-07-15</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">329</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=DE82702124"> <span id="translatedtitle">Retention of Airborne <span class="hlt">Particles</span> in Granular Bed <span class="hlt">Filters</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">A literature survey was made on theoretical models for the prediction of <span class="hlt">particle</span> retention in sand beds. Also data on observed retention was collected from the literature. Based on this information, a semi-empirical model was compiled. Comparison of the ...</p> <div class="credits"> <p class="dwt_author">L. Stroem</p> <p class="dwt_publisher"></p> <p class="publishDate">1981-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">330</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=DE84701882"> <span id="translatedtitle">Time Resolution of Liquid Argon Detectors. Part 1. <span class="hlt">Optimal</span> <span class="hlt">Filter</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">A study was made on the dependence of time resolution of liquid argon ionization chamber on electronic circuit parameters, energy losses in chamber gap, detector capacity and Ar purity. The technique for evaluating <span class="hlt">optimal</span> filtration of signals is present...</p> <div class="credits"> <p class="dwt_author">R. N. Krasnokutskij N. N. Fedyakin R. S. Shuvalov</p> <p class="dwt_publisher"></p> <p class="publishDate">1983-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">331</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22345542"> <span id="translatedtitle">Design of almost symmetric orthogonal wavelet <span class="hlt">filter</span> bank via direct <span class="hlt">optimization</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">It is a well-known fact that (compact-support) dyadic wavelets [based on the two channel <span class="hlt">filter</span> banks (FBs)] cannot be simultaneously orthogonal and symmetric. Although orthogonal wavelets have the energy preservation property, biorthogonal wavelets are preferred in image processing applications because of their symmetric property. In this paper, a novel method is presented for the design of almost symmetric orthogonal wavelet FB. Orthogonality is structurally imposed by using the unnormalized lattice structure, and this leads to an objective function, which is relatively simple to <span class="hlt">optimize</span>. The designed <span class="hlt">filters</span> have good frequency response, flat group delay, almost symmetric <span class="hlt">filter</span> coefficients, and symmetric wavelet function. PMID:22345542</p> <div class="credits"> <p class="dwt_author">Murugesan, Selvaraaju; Tay, David B H</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-02-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">332</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/15603077"> <span id="translatedtitle">Two-stage hybrid <span class="hlt">optimization</span> of fiber Bragg gratings for design of linear phase <span class="hlt">filters</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We present a new hybrid <span class="hlt">optimization</span> method for the synthesis of fiber Bragg gratings (FBGs) with complex characteristics. The hybrid <span class="hlt">optimization</span> method is a two-tier search that employs a global <span class="hlt">optimization</span> algorithm [i.e., the tabu search (TS) algorithm] and a local <span class="hlt">optimization</span> method (i.e., the quasi-Netwon method). First the TS global <span class="hlt">optimization</span> algorithm is used to find a "promising" FBG structure that has a spectral response as close as possible to the targeted spectral response. Then the quasi-Newton local <span class="hlt">optimization</span> method is applied to further <span class="hlt">optimize</span> the FBG structure obtained from the TS algorithm to arrive at a targeted spectral response. A dynamic mechanism for weighting of different requirements of the spectral response is employed to enhance the <span class="hlt">optimization</span> efficiency. To demonstrate the effectiveness of the method, the synthesis of three linear-phase optical <span class="hlt">filters</span> based on FBGs with different grating lengths is described. PMID:15603077</p> <div class="credits"> <p class="dwt_author">Zheng, Rui Tao; Ngo, Nam Quoc; Le Binh, Nguyen; Tjin, Swee Chuan</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">333</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004JOSAA..21.2399Z"> <span id="translatedtitle">Two-stage hybrid <span class="hlt">optimization</span> of fiber Bragg gratings for design of linear phase <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present a new hybrid <span class="hlt">optimization</span> method for the synthesis of fiber Bragg gratings (FBGs) with complex characteristics. The hybrid <span class="hlt">optimization</span> method is a two-tier search that employs a global <span class="hlt">optimization</span> algorithm [i.e., the tabu search (TS) algorithm] and a local <span class="hlt">optimization</span> method (i.e., the quasi-Netwon method). First the TS global <span class="hlt">optimization</span> algorithm is used to find a ``promising'' FBG structure that has a spectral response as close as possible to the targeted spectral response. Then the quasi-Newton local <span class="hlt">optimization</span> method is applied to further <span class="hlt">optimize</span> the FBG structure obtained from the TS algorithm to arrive at a targeted spectral response. A dynamic mechanism for weighting of different requirements of the spectral response is employed to enhance the <span class="hlt">optimization</span> efficiency. To demonstrate the effectiveness of the method, the synthesis of three linear-phase optical <span class="hlt">filters</span> based on FBGs with different grating lengths is described.</p> <div class="credits"> <p class="dwt_author">Zheng, Rui Tao; Ngo, Nam Quoc; Binh, Le Nguyen; Tjin, Swee Chuan</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">334</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://randomsets.ee.unimelb.edu.au/docs/AES2final.pdf"> <span id="translatedtitle"><span class="hlt">Particle</span> PHD <span class="hlt">Filter</span> Multiple Target Tracking in Sonar Images</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">ó Two contrasting approaches for tracking multiple targets in multi-beam forward-looking sonar images are consid- ered. The rst approach is based on assigning a Kalman lter to each target and managing the measurements with gating and a measurement-to-track data association technique. The second approach uses the recently developed <span class="hlt">particle</span> implementation of the multiple-target Probability Hypothesis Density (PHD) lter and a</p> <div class="credits"> <p class="dwt_author">Daniel Clark; Ioseba Tena Ruiz; Yvan Petillot; Judith Bell</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">335</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013PhRvA..88c5601J"> <span id="translatedtitle"><span class="hlt">Optimal</span> quantum control of Bose-Einstein condensates in magnetic microtraps: Consideration of <span class="hlt">filter</span> effects</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We theoretically investigate protocols based on <span class="hlt">optimal</span> control theory (OCT) for manipulating Bose-Einstein condensates in magnetic microtraps, using the framework of the Gross-Pitaevskii equation. In our approach we explicitly account for <span class="hlt">filter</span> functions that distort the computed <span class="hlt">optimal</span> control, a situation inherent to many experimental OCT implementations. We apply our scheme to the shakeup process of a condensate from the ground to the first excited state, following a recent experimental and theoretical study, and demonstrate that the fidelity of OCT protocols is not significantly deteriorated by typical <span class="hlt">filters</span>.</p> <div class="credits"> <p class="dwt_author">Jäger, Georg; Hohenester, Ulrich</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">336</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2266978"> <span id="translatedtitle">Classifying EEG for Brain-Computer Interface: Learning <span class="hlt">Optimal</span> <span class="hlt">Filters</span> for Dynamical System Features</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning <span class="hlt">optimal</span> <span class="hlt">filters</span> automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal <span class="hlt">filters</span> <span class="hlt">optimized</span> using the proposed learning approach.</p> <div class="credits"> <p class="dwt_author">Song, Le; Epps, Julien</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">337</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/5435007"> <span id="translatedtitle">Comparison of Interior Point <span class="hlt">Filter</span> Line Search Strategies for Constrained <span class="hlt">Optimization</span> by Performance Profiles</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Abstract—This paper,presents,a performance,evaluation,of three sets of modifications,that can,be incorporated,into the primal-dual interior point <span class="hlt">filter</span> line search method,for nonlinear programming herein illustrated. In this framework, each entry in the <span class="hlt">filter</span> relies on three components, the feasibility, the centrality and the <span class="hlt">optimality</span>, that are present in the first-order <span class="hlt">optimality</span> conditions. The modifications,are concerned,with an acceptance condition, a barrier parameter update formula and</p> <div class="credits"> <p class="dwt_author">M. Fernanda P. Costa; Edite M. G. P. Fernandes</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">338</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18364986"> <span id="translatedtitle">Classifying EEG for brain-computer interface: learning <span class="hlt">optimal</span> <span class="hlt">filters</span> for dynamical system features.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning <span class="hlt">optimal</span> <span class="hlt">filters</span> automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal <span class="hlt">filters</span> <span class="hlt">optimized</span> using the proposed learning approach. PMID:18364986</p> <div class="credits"> <p class="dwt_author">Song, Le; Epps, Julien</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">339</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cffs.uky.edu/environment/pubs/jmicroscopy%20v217n3p225y2005.pdf"> <span id="translatedtitle">Characterization of ultrafine coal fly ash <span class="hlt">particles</span> by energy-<span class="hlt">filtered</span> TEM</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Summary In this study, energy-<span class="hlt">filtered</span> transmission electron microscopy is demonstrated to be a valuable tool for characterizing ultrafine coal fly ash <span class="hlt">particles</span>, especially those <span class="hlt">particles</span> encapsulated in or associated with carbon. By examining a series of elemental maps (K-edge maps of C and O, and L-edge maps of Si, Al, Ti and Fe) recorded using the three-window method, consider- able</p> <div class="credits"> <p class="dwt_author">Y. CHEN; N. SHAH; F. E. HUGGINS; G. P. HUFFMAN; A. DOZIER</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">340</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/21096346"> <span id="translatedtitle"><span class="hlt">Optimization</span> of MFCC parameters using <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> for diagnosis of infant hypothyroidism using Multi- Layer Perceptron.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This paper presents a new application of the <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) algorithm to <span class="hlt">optimize</span> Mel Frequency Cepstrum Coefficients (MFCC) parameters, in order to extract an <span class="hlt">optimal</span> feature set for diagnosis of hypothyroidism in infants using Multi-Layer Perceptrons (MLP) neural network. MFCC features is influenced by the number of <span class="hlt">filter</span> banks (f(b)) and the number of coefficients (n(c)) used. These parameters are critical in representation of the features as they affect the resolution and dimensionality of the features. In this paper, the PSO algorithm was used to <span class="hlt">optimize</span> the values of f(b) and n(c). The MFCC features based on the PSO <span class="hlt">optimization</span> were extracted from healthy and unhealthy infant cry signals and used to train MLP in the classification of hypothyroid infant cries. The results indicate that the PSO algorithm could determine the optimum combination of f(b) and n(c) that produce the best classification accuracy of the MLP. PMID:21096346</p> <div class="credits"> <p class="dwt_author">Zabidi, A; Lee, Yoot Khuan; Mansor, W; Yassin, I M; Sahak, R</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_16");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">341</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48501212"> <span id="translatedtitle"><span class="hlt">Optimization</span> of vertical well placement by using a hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Locating wells is an important step in oil exploitation. This paper proposes a novel approach, which first combines <span class="hlt">particle</span>\\u000a swarm <span class="hlt">optimization</span>, genetic algorithm, and a reservoir simulation evaluation tool to <span class="hlt">optimize</span> the locations of vertical wells.\\u000a Simulation results show that the convergence efficiency of our approach outperforms traditional genetic algorithm and overcomes\\u000a the disadvantage of <span class="hlt">particle</span> swarm algorithm that would</p> <div class="credits"> <p class="dwt_author">Xiaojian Dong; Zhijian Wu; Chao Dong; Zhangxin Chen; Hui Wang</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">342</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2881565"> <span id="translatedtitle">An <span class="hlt">optimized</span> blockwise nonlocal means denoising <span class="hlt">filter</span> for 3-D magnetic resonance images</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. Denoising is a crucial step to increase image quality and to improve the performance of all the tasks needed for quantitative imaging analysis. The method proposed in this paper is based on a 3D <span class="hlt">optimized</span> blockwise version of the Non Local (NL) means <span class="hlt">filter</span> [1]. The NL-means <span class="hlt">filter</span> uses the redundancy of information in the image under study to remove the noise. The performance of the NL-means <span class="hlt">filter</span> has been already demonstrated for 2D images, but reducing the computational burden is a critical aspect to extend the method to 3D images. To overcome this problem, we propose improvements to reduce the computational complexity. These different improvements allow to drastically divide the computational time while preserving the performances of the NL-means <span class="hlt">filter</span>. A fully-automated and <span class="hlt">optimized</span> version of the NL-means <span class="hlt">filter</span> is then presented. Our contributions to the NL-means <span class="hlt">filter</span> are: (a) an automatic tuning of the smoothing parameter, (b) a selection of the most relevant voxels, (c) a blockwise implementation and (d) a parallelized computation. Quantitative validation was carried out on synthetic datasets generated with BrainWeb [2]. The results show that our <span class="hlt">optimized</span> NL-means <span class="hlt">filter</span> outperforms the classical implementation of the NL-means <span class="hlt">filter</span>, as well as two other classical denoising methods (Anisotropic Diffusion [3] and Total Variation minimization process [4]) in terms of accuracy (measured by the Peak Signal to Noise Ratio) with low computation time. Finally, qualitative results on real data are presented.</p> <div class="credits"> <p class="dwt_author">Coupe, Pierrick; Yger, Pierre; Prima, Sylvain; Hellier, Pierre; Kervrann, Charles; Barillot, Christian</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">343</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007RScI...78h5105A"> <span id="translatedtitle">High-efficiency particulate air <span class="hlt">filter</span> test stand and aerosol generator for <span class="hlt">particle</span> loading studies</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This manuscript describes the design, characterization, and operational range of a test stand and high-output aerosol generator developed to evaluate the performance of 30×30×29 cm3 nuclear grade high-efficiency particulate air (HEPA) <span class="hlt">filters</span> under variable, highly controlled conditions. The test stand system is operable at volumetric flow rates ranging from 1.5 to 12 standard m3/min. Relative humidity levels are controllable from 5%-90% and the temperature of the aerosol stream is variable from ambient to 150 °C. Test aerosols are produced through spray drying source material solutions that are introduced into a heated stainless steel evaporation chamber through an air-atomizing nozzle. Regulation of the <span class="hlt">particle</span> size distribution of the aerosol challenge is achieved by varying source solution concentrations and through the use of a postgeneration cyclone. The aerosol generation system is unique in that it facilitates the testing of standard HEPA <span class="hlt">filters</span> at and beyond rated media velocities by consistently providing, into a nominal flow of 7 standard m3/min, high mass concentrations (~25 mg/m3) of dry aerosol streams having count mean diameters centered near the most penetrating <span class="hlt">particle</span> size for HEPA <span class="hlt">filters</span> (120-160 nm). Aerosol streams that have been generated and characterized include those derived from various concentrations of KCl, NaCl, and sucrose solutions. Additionally, a water insoluble aerosol stream in which the solid component is predominantly iron (III) has been produced. Multiple ports are available on the test stand for making simultaneous aerosol measurements upstream and downstream of the test <span class="hlt">filter</span>. Types of <span class="hlt">filter</span> performance related studies that can be performed using this test stand system include <span class="hlt">filter</span> lifetime studies, <span class="hlt">filtering</span> efficiency testing, media velocity testing, evaluations under high mass loading and high humidity conditions, and determination of the downstream <span class="hlt">particle</span> size distributions.</p> <div class="credits"> <p class="dwt_author">Arunkumar, R.; Hogancamp, Kristina U.; Parsons, Michael S.; Rogers, Donna M.; Norton, Olin P.; Nagel, Brian A.; Alderman, Steven L.; Waggoner, Charles A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">344</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50409179"> <span id="translatedtitle">Design and synchronization of Gaussian <span class="hlt">particle</span> <span class="hlt">filter</span> using distributed controller scheme</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents design and synchronization method for Gaussian <span class="hlt">particle</span> <span class="hlt">filter</span> (GPF) using distributed controller scheme. The GPF has many processing blocks where each processing block computes very complex arithmetic operations. Data dependency among processing blocks in the GPF creates an opportunity for efficient distributed controller, which guarantees correct operation. We verify its correctness using Verilog and SystemC. Each processing</p> <div class="credits"> <p class="dwt_author">Sangjiii Hong; Xiaoyao Liang; Miodrag Bolic; P. M. Djuric</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">345</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://cmsv043.rrzn.uni-hannover.de/fileadmin/WPNC06/Proceedings/32_A_new_Particle_Filter_for_Localization_of_a_Mobile_Base_Station_Based_on.pdf"> <span id="translatedtitle">A new <span class="hlt">Particle</span> <span class="hlt">Filter</span> for Localization of a Mobile Base Station Based on Microwave Backscatter</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This work presents an improved <span class="hlt">particle</span> <span class="hlt">filter</span> algorithm for a precise measurement of the local position of a mobile target. The presented measurement system consists of a mobile radar base station to be tracked and several active transponders located at predefined points of the working area. The system measures the range between the transponders and the base station like Frequency</p> <div class="credits"> <p class="dwt_author">Haytham Qasem; Christoph Ament; Leonhard Reindl</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">346</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57790923"> <span id="translatedtitle"><span class="hlt">Filter</span>-Feeding Behavior and <span class="hlt">Particle</span> Retention Efficiency of Sacramento Blackfish</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We analyzed the feeding behavior and <span class="hlt">particle</span> retention efficiency of pump <span class="hlt">filter</span>-feeding Sacramento blackfish Orthodon microlepidotus presented with plastic microspheres and zooplankton. The rate of water processing by Sacramento blackfish was the product of buccal volume and pumping rate. Buccal volume increased exponentially with fish size whereas pumping rate decreased with fish size. Pumping rate, determined from slow-motion videotape playback,</p> <div class="credits"> <p class="dwt_author">Philip C. Johnson; Gary L. Vinyard</p> <p class="dwt_publisher"></p> <p class="publishDate">1987-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">347</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50658547"> <span id="translatedtitle">Interacting multiple <span class="hlt">particle</span> <span class="hlt">filters</span> for fault diagnosis of non-linear stochastic systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, an approach to fault diagnosis in a nonlinear stochastic dynamic system is proposed using the interacting multiple <span class="hlt">particle</span> <span class="hlt">filtering</span> (IMPF) algorithm. The fault diagnostic approach is formulated as a hybrid multiple- model estimation scheme. The proposed diagnostic approach provides an integrated framework to estimate the system's current operational or faulty mode, as well as the unmeasured state</p> <div class="credits"> <p class="dwt_author">Xudong Wang; Vassilis L. Syrmos</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">348</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1615911"> <span id="translatedtitle"><span class="hlt">Optimizing</span> <span class="hlt">particle</span> collection for enhanced surface-based biosensors</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this article, electrode structures that combine dielectrophoretic effects with electrohydrodynamic fluid flow to concentrate <span class="hlt">particles</span> on active sensor surfaces were presented. To <span class="hlt">optimize</span> the collection effect on a surface, a novel electrode configuration called zipper electrodes has been developed. The local enrichment effect of these electrodes is such that <span class="hlt">particles</span> at local concentration of 5×103 spores\\/mL can be collected</p> <div class="credits"> <p class="dwt_author">KAI F. HOETTGES; MICHAEL P. HUGHES; ANDREW COTTON; N. A. E. Hopkins; M. B. McDonnell</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">349</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AIPC.1558..578B"> <span id="translatedtitle">Genetic algorithm and <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> combined with Powell method</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In recent years, the population algorithms are becoming increasingly robust and easy to use, based on Darwin's Theory of Evolution, perform a search for the best solution around a population that will progress according to several generations. This paper present variants of hybrid genetic algorithm - Genetic Algorithm and a bio-inspired hybrid algorithm - <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span>, both combined with the local method - Powell Method. The developed methods were tested with twelve test functions from unconstrained <span class="hlt">optimization</span> context.</p> <div class="credits"> <p class="dwt_author">Bento, David; Pinho, Diana; Pereira, Ana I.; Lima, Rui</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">350</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1464136"> <span id="translatedtitle"><span class="hlt">Optimized</span> <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (OPSO) and its application to artificial neural network training</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Background <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) is an established method for parameter <span class="hlt">optimization</span>. It represents a population-based adaptive <span class="hlt">optimization</span> technique that is influenced by several "strategy parameters". Choosing reasonable parameter values for the PSO is crucial for its convergence behavior, and depends on the <span class="hlt">optimization</span> task. We present a method for parameter meta-<span class="hlt">optimization</span> based on PSO and its application to neural network training. The concept of the <span class="hlt">Optimized</span> <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (OPSO) is to <span class="hlt">optimize</span> the free parameters of the PSO by having swarms within a swarm. We assessed the performance of the OPSO method on a set of five artificial fitness functions and compared it to the performance of two popular PSO implementations. Results Our results indicate that PSO performance can be improved if meta-<span class="hlt">optimized</span> parameter sets are applied. In addition, we could improve <span class="hlt">optimization</span> speed and quality on the other PSO methods in the majority of our experiments. We applied the OPSO method to neural network training with the aim to build a quantitative model for predicting blood-brain barrier permeation of small organic molecules. On average, training time decreased by a factor of four and two in comparison to the other PSO methods, respectively. By applying the OPSO method, a prediction model showing good correlation with training-, test- and validation data was obtained. Conclusion <span class="hlt">Optimizing</span> the free parameters of the PSO method can result in performance gain. The OPSO approach yields parameter combinations improving overall <span class="hlt">optimization</span> performance. Its conceptual simplicity makes implementing the method a straightforward task.</p> <div class="credits"> <p class="dwt_author">Meissner, Michael; Schmuker, Michael; Schneider, Gisbert</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">351</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1495975"> <span id="translatedtitle">A <span class="hlt">particle</span> swarm <span class="hlt">optimization</span>-based method for multiobjective design <span class="hlt">optimizations</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) based algorithm for finding the Pareto solutions of multiobjective design problems is proposed. To enhance the global searching ability of the available PSOs, a novel formula for updating the <span class="hlt">particles</span>' velocity and position, as well as the introduction of craziness, are reported. To handle a multiobjective design problem using the improved PSO, a new fitness</p> <div class="credits"> <p class="dwt_author">S. L. Ho; Shiyou Yang; Guangzheng Ni; Edward W. C. Lo; H. C. Wong</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">352</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50612452"> <span id="translatedtitle"><span class="hlt">Optimal</span> scheduling of generator maintenance using modified discrete <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a modified discrete <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) based technique for generating <span class="hlt">optimal</span> preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. While GA and other analytical methods might suffer from premature convergence and the curse of dimensionality, heuristics based swarm intelligence can be</p> <div class="credits"> <p class="dwt_author">Yusuf Yare; Ganesh K. Venayagamoorthy</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">353</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20388988"> <span id="translatedtitle">Recycling of spent <span class="hlt">filter</span> backwash water using coagulation-assisted membrane filtration: effects of submicrometre <span class="hlt">particles</span> on membrane flux.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Membrane separation technology has been widely used for recycling of spent <span class="hlt">filter</span> backwash water (SFBW) in water treatment plant. Membrane filtration performance is subject to characteristics of the <span class="hlt">particles</span> in the SFBW. A bench-scale microfiltration (MF) coupled with pre-coagulation was set up to evaluate the recovery efficiency of SFBW. Effect of <span class="hlt">particle</span> size distribution and zeta potential of the coagulated SFBW on the membrane filtration as well as the coagulation strategies were investigated. Pore clogging was more severe on the membrane with 1.0 mum pore size than on the membrane with 0.5 mum pore size due to the fact that submicrometre <span class="hlt">particles</span> are dominant and their diameters are exactly closed to the pore size of the MF membrane. Pre-settling induced more severe irreversible fouling because only the submicrometre <span class="hlt">particles</span> in the water become predominant after settling, resulting in the occurrence of more acute pore blocking of membrane. By contrast, pre-coagulation mitigates membrane fouling and improves membrane flux via enlarging <span class="hlt">particle</span> size on membrane surface. The variations of zeta potential in response to coagulant dosing as well as fractal dimension were also compared with the performance of the subsequent filtration. The result showed that pre-coagulation induced by charge neutralization at the optimum dosage where the zeta potential is around zero leads to the <span class="hlt">optimal</span> performance of the subsequent membrane filtration for SFBW recycling. At such condition, the fractal dimension of coagulated flocs reached minimum. PMID:20388988</p> <div class="credits"> <p class="dwt_author">Huang, Chihpin; Lin, Jr-Lin; Wu, C L; Chu, C P</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">354</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JCoPh.237..320B"> <span id="translatedtitle"><span class="hlt">Optimal</span> <span class="hlt">filtering</span> of complex turbulent systems with memory depth through consistency constraints</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this article, we develop a linear theory for <span class="hlt">optimal</span> <span class="hlt">filtering</span> of complex turbulent signals with model errors through linear autoregressive models. We will show that when the autoregressive model parameters are chosen such that they satisfy absolute stability and consistency conditions of at least order-2 of the classical multistep method for solving initial value problems, the <span class="hlt">filtered</span> solutions with autoregressive models of order p?2 are <span class="hlt">optimal</span> in the sense that they are comparable to the estimates obtained from the true <span class="hlt">filter</span> with perfect model. This result is reminiscent of the Lax-equivalence fundamental theorem in the analysis of finite difference discretization scheme for the numerical solutions of partial differential equations. We will apply this linear theory to <span class="hlt">filter</span> two nonlinear problems, the slowest mode of the truncated Burgers-Hopf and the Lorenz-96 model. On these nonlinear problems, we will show that whenever these linear conditions are satisfied, the <span class="hlt">filtered</span> solutions accuracy is significantly improved. Finally, we will also apply the recently developed offline test criteria to understand the robustness of the multistep <span class="hlt">filter</span> on various turbulent nature, including the stochastically forced linear advection-diffusion equation and a toy model for barotropic turbulent Rossby waves.</p> <div class="credits"> <p class="dwt_author">Bakunova, Eugenia S.; Harlim, John</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">355</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23523646"> <span id="translatedtitle"><span class="hlt">Optimizing</span> the bandpass <span class="hlt">filter</span> for acoustic stimuli in recording ocular vestibular-evoked myogenic potentials.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This study aimed to determine the <span class="hlt">optimal</span> bandpass <span class="hlt">filter</span> (BPF) setting for acoustic stimuli in recording the ocular vestibular-evoked myogenic potential (oVEMP). Twelve healthy volunteers underwent oVEMP tests using acoustic stimuli with various high-pass <span class="hlt">filters</span> (1, 10 and 100Hz) and low-pass <span class="hlt">filters</span> (500, 1000 and 2000Hz). Initially, various effects of high-pass <span class="hlt">filter</span> on the oVEMPs were examined under Conditions A (BPF of 1-1000Hz), B (BPF of 10-1000Hz) and C (BPF of 100-1000Hz). Of these conditions, Condition A showed 100% response rate and had larger nI-pI amplitude than Conditions B and C. Thus, Condition A was selected for subsequent analysis of the various effects of low-pass <span class="hlt">filter</span> on the oVEMPs. However, Condition A (BPF of 1-1000Hz) did not significantly differ from Conditions D (BPF of 1-500Hz) and E (BPF of 1-2000Hz) in terms of the latencies and amplitudes of oVEMPs. Condition A thus is supposed to be the <span class="hlt">optimal</span> recording condition for oVEMPs. In conclusion, the <span class="hlt">optimal</span> BPF setting for acoustic stimuli in recording oVEMPs is suggested to be between 1 and 1000Hz. PMID:23523646</p> <div class="credits"> <p class="dwt_author">Wang, Shou-Jen; Jaw, Fu-Shan; Young, Yi-Ho</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-21</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">356</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/14458056"> <span id="translatedtitle"><span class="hlt">Optimal</span> and self-tuning white noise estimators with applications to deconvolution and <span class="hlt">filtering</span> problems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Using the innovation analysis method in the time domain, based on the autoregressive moving average (ARMA) innovation model, this paper presents a unified white noise estimation theory that includes both input and measurement white noise estimators, and presents a new steady-state <span class="hlt">optimal</span> state estimation theory. Non-recursive <span class="hlt">optimal</span> state estimators are given, whose recursive version gives a steady-state Kalman <span class="hlt">filter</span>, where</p> <div class="credits"> <p class="dwt_author">Zi-Li Deng; Huan-Shui Zhang; Shu-Jun Liu; Lu Zhou</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">357</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/12693038"> <span id="translatedtitle">Weinberg angle, current coupling constant, and mass of <span class="hlt">particles</span> as properties of culminating-point <span class="hlt">filters</span> - consequences for <span class="hlt">particle</span> astrophysics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Culminating-point <span class="hlt">filter</span> construction for <span class="hlt">particle</span> points is distinguished from torus construction for wave functions in the tangent objects of their neighborhoods. Both constructions are not united by a general manifold diffeomorphism, but are united by a map of a hidden conformal $S^{1}\\\\times S^{3}$ charge with harmonic (Maxwell) potentials into a physical space formed by culminating points, tangent objects, and Feynman</p> <div class="credits"> <p class="dwt_author">E. Donth</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">358</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22393815"> <span id="translatedtitle">Ultrafine <span class="hlt">particle</span> emission from incinerators: the role of the fabric <span class="hlt">filter</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Incinerators are claimed to be responsible of <span class="hlt">particle</span> and gaseous emissions: to this purpose Best Available Techniques (BAT) are used in the flue-gas treatment sections leading to pollutant emission lower than established threshold limit values. As regard <span class="hlt">particle</span> emission, only a mass-based threshold limit is required by the regulatory authorities. However; in the last years the attention of medical experts moved from coarse and fine <span class="hlt">particles</span> towards ultrafine <span class="hlt">particles</span> (UFPs; diameter less than 0.1 microm), mainly emitted by combustion processes. According to toxicological and epidemiological studies, ultrafine <span class="hlt">particles</span> could represent a risk for health and environment. Therefore, it is necessary to quantify <span class="hlt">particle</span> emissions from incinerators also to perform an exposure assessment for the human populations living in their surrounding areas. A further topic to be stressed in the UFP emission from incinerators is the <span class="hlt">particle</span> filtration efficiency as function of different flue-gas treatment sections. In fact, it could be somehow important to know which <span class="hlt">particle</span> filtration method is able to assure high abatement efficiency also in terms of UFPs. To this purpose, in the present work experimental results in terms of ultrafine <span class="hlt">particle</span> emissions from several incineration plants are reported. Experimental campaigns were carried out in the period 2007-2010 by measuring UFP number distributions and total concentrations at the stack of five plants through condensation <span class="hlt">particle</span> counters and mobility <span class="hlt">particle</span> sizer spectrometers. Average total <span class="hlt">particle</span> number concentrations ranging from 0.4 x 10(3) to 6.0 x 10(3) <span class="hlt">particles</span> cm(-3) were measured at the stack of the analyzed plants. Further experimental campaigns were performed to characterize <span class="hlt">particle</span> levels before the fabric <span class="hlt">filters</span> in two of the analyzed plants in order to deepen their <span class="hlt">particle</span> reduction effect; <span class="hlt">particle</span> concentrations higher than 1 x 10(7) <span class="hlt">particles</span> cm(-3) were measured, leading to filtration efficiency greater than 99.99%. PMID:22393815</p> <div class="credits"> <p class="dwt_author">Buonanno, G; Scungio, M; Stabile, L; Tirler, W</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">359</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011SMaS...20g5021L"> <span id="translatedtitle">A regularized auxiliary <span class="hlt">particle</span> <span class="hlt">filtering</span> approach for system state estimation and battery life prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">System current state estimation (or condition monitoring) and future state prediction (or failure prognostics) constitute the core elements of condition-based maintenance programs. For complex systems whose internal state variables are either inaccessible to sensors or hard to measure under normal operational conditions, inference has to be made from indirect measurements using approaches such as Bayesian learning. In recent years, the auxiliary <span class="hlt">particle</span> <span class="hlt">filter</span> (APF) has gained popularity in Bayesian state estimation; the APF technique, however, has some potential limitations in real-world applications. For example, the diversity of the <span class="hlt">particles</span> may deteriorate when the process noise is small, and the variance of the importance weights could become extremely large when the likelihood varies dramatically over the prior. To tackle these problems, a regularized auxiliary <span class="hlt">particle</span> <span class="hlt">filter</span> (RAPF) is developed in this paper for system state estimation and forecasting. This RAPF aims to improve the performance of the APF through two innovative steps: (1) regularize the approximating empirical density and redraw samples from a continuous distribution so as to diversify the <span class="hlt">particles</span>; and (2) smooth out the rather diffused proposals by a rejection/resampling approach so as to improve the robustness of <span class="hlt">particle</span> <span class="hlt">filtering</span>. The effectiveness of the proposed RAPF technique is evaluated through simulations of a nonlinear/non-Gaussian benchmark model for state estimation. It is also implemented for a real application in the remaining useful life (RUL) prediction of lithium-ion batteries.</p> <div class="credits"> <p class="dwt_author">Liu, Jie; Wang, Wilson; Ma, Fai</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">360</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/17610985"> <span id="translatedtitle">Genetic algorithm matched <span class="hlt">filter</span> <span class="hlt">optimization</span> for automated detection of blood vessels from digital retinal images.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Due to the importance of the matched <span class="hlt">filter</span> in the automated detection of blood vessels in digital retinal images, improving its response is highly desirable. This <span class="hlt">filter</span> may vary in many ways depending on the parameters that govern its response. In this paper, new parameters to <span class="hlt">optimize</span> the sensitivity of the matched <span class="hlt">filter</span> are found using genetic algorithms on the test set of the DRIVE databases. The area under the receiver operating curve (ROC) is used as a fitness function for the genetic algorithm. To evaluate the improved matched <span class="hlt">filter</span>, the maximum average accuracy (MAA) is calculated to be 0.9422 and the average area under ROC is 0.9582. PMID:17610985</p> <div class="credits"> <p class="dwt_author">Al-Rawi, Mohammed; Karajeh, Huda</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-07-03</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_17");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">361</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012SPIE.8401E..20M"> <span id="translatedtitle"><span class="hlt">Optimization</span> of high speed pipelining in FPGA-based FIR <span class="hlt">filter</span> design using genetic algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper compares FPGA-based full pipelined multiplierless FIR <span class="hlt">filter</span> design options. Comparison of Distributed Arithmetic (DA), Common Sub-Expression (CSE) sharing and n-dimensional Reduced Adder Graph (RAG-n) multiplierless <span class="hlt">filter</span> design methods in term of size, speed, and A*T product are provided. Since DA designs are table-based and CSE/RAG-n designs are adder-based, FPGA synthesis design data are used for a realistic comparison. Superior results of a genetic algorithm based <span class="hlt">optimization</span> of pipeline registers and non-output fundamental coefficients are shown. FIR <span class="hlt">filters</span> (posted as open source by Kastner et al.) for <span class="hlt">filters</span> in the length from 6 to 151 coefficients are used.</p> <div class="credits"> <p class="dwt_author">Meyer-Baese, Uwe; Botella, Guillermo; Romero, David E. T.; Kumm, Martin</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">362</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20643606"> <span id="translatedtitle"><span class="hlt">Optimal</span> design of FIR triplet halfband <span class="hlt">filter</span> bank and application in image coding.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This correspondence proposes an efficient semidefinite programming (SDP) method for the design of a class of linear phase finite impulse response triplet halfband <span class="hlt">filter</span> banks whose <span class="hlt">filters</span> have <span class="hlt">optimal</span> frequency selectivity for a prescribed regularity order. The design problem is formulated as the minimization of the least square error subject to peak error constraints and regularity constraints. By using the linear matrix inequality characterization of the trigonometric semi-infinite constraints, it can then be exactly cast as a SDP problem with a small number of variables and, hence, can be solved efficiently. Several design examples of the triplet halfband <span class="hlt">filter</span> bank are provided for illustration and comparison with previous works. Finally, the image coding performance of the <span class="hlt">filter</span> bank is presented. PMID:20643606</p> <div class="credits"> <p class="dwt_author">Kha, H H; Tuan, H D; Nguyen, T Q</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-07-19</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">363</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007SPIE.6569E...5Y"> <span id="translatedtitle">Collaborative multimodel Rao-Blackwellised <span class="hlt">particle</span> <span class="hlt">filter</span> for target tracking in acoustic sensor networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">An energy-aware, collaborative target tracking algorithm is proposed for ad-hoc wireless sensor networks. At every time step, current measurements from four sensors are chosen for target motion estimation and prediction. The algorithm is implemented distributively by passing sensing and computation operations from a subset of sensors to another. A robust multimodel Rao-Blackwellised <span class="hlt">particle</span> <span class="hlt">filter</span> algorithm is presented for tracking high maneuvering ground target in the sensor field. Not only is the proposed algorithm more computation efficient than generic <span class="hlt">particle</span> <span class="hlt">filter</span> for high dimension nonlinear and non-Gaussian estimation problems, but also it can tackle the target's maneuver perfectly by stratified <span class="hlt">particles</span> sampling from a set of system models. In the simulation comparison, a high maneuvering target moves through an acoustic sensor network field. The target is tracked by both generic PF and the multimodel RBPF algorithms. The results show that our approach has great performance improvements, especially when the target is making maneuver.</p> <div class="credits"> <p class="dwt_author">Yu, Zhi-jun; Wei, Jian-ming; Zhao, Jun-yu; Liu, Hai-tao</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">364</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18726819"> <span id="translatedtitle">Evaluation of the effect of media velocity on <span class="hlt">filter</span> efficiency and most penetrating <span class="hlt">particle</span> size of nuclear grade high-efficiency particulate air <span class="hlt">filters</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">High-efficiency particulate air (HEPA) <span class="hlt">filters</span> are widely used to control particulate matter emissions from processes that involve management or treatment of radioactive materials. Section FC of the American Society of Mechanical Engineers AG-1 Code on Nuclear Air and Gas Treatment currently restricts media velocity to a maximum of 2.5 cm/sec in any application where this standard is invoked. There is some desire to eliminate or increase this media velocity limit. A concern is that increasing media velocity will result in higher emissions of ultrafine <span class="hlt">particles</span>; thus, it is unlikely that higher media velocities will be allowed without data to demonstrate the effect of media velocity on removal of ultrafine <span class="hlt">particles</span>. In this study, the performance of nuclear grade HEPA <span class="hlt">filters</span>, with respect to <span class="hlt">filter</span> efficiency and most penetrating <span class="hlt">particle</span> size, was evaluated as a function of media velocity. Deep-pleat nuclear grade HEPA <span class="hlt">filters</span> (31 cm x 31 cm x 29 cm) were evaluated at media velocities ranging from 2.0 to 4.5 cm/sec using a potassium chloride aerosol challenge having a <span class="hlt">particle</span> size distribution centered near the HEPA <span class="hlt">filter</span> most penetrating <span class="hlt">particle</span> size. <span class="hlt">Filters</span> were challenged under two distinct mass loading rate regimes through the use of or exclusion of a 3 microm aerodynamic diameter cut point cyclone. <span class="hlt">Filter</span> efficiency and most penetrating <span class="hlt">particle</span> size measurements were made throughout the duration of <span class="hlt">filter</span> testing. <span class="hlt">Filter</span> efficiency measured at the onset of aerosol challenge was noted to decrease with increasing media velocity, with values ranging from 99.999 to 99.977%. The <span class="hlt">filter</span> most penetrating <span class="hlt">particle</span> size recorded at the onset of testing was noted to decrease slightly as media velocity was increased and was typically in the range of 110-130 nm. Although additional testing is needed, these findings indicate that <span class="hlt">filters</span> operating at media velocities up to 4.5 cm/sec will meet or exceed current <span class="hlt">filter</span> efficiency requirements. Additionally, increased emission of ultrafine <span class="hlt">particles</span> is seemingly negligible. PMID:18726819</p> <div class="credits"> <p class="dwt_author">Alderman, Steven L; Parsons, Michael S; Hogancamp, Kristina U; Waggoner, Charles A</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">365</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/27073205"> <span id="translatedtitle"><span class="hlt">Optimal</span> H2 <span class="hlt">Filtering</span> in Networked Control Systems With Multiple Packet Dropout</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This note studies the problem of <span class="hlt">optimal</span> H2 <span class="hlt">filtering</span> in networked control systems (NCSs) with multiple packet dropout. A new formulation is employed to model the multiple packet dropout case, where the random dropout rate is transformed into a stochastic parameter in the system's representation. By generalization of the H2-norm definition, new relations for the stochastic -norm of a linear</p> <div class="credits"> <p class="dwt_author">Mehrdad Sahebsara; Tongwen Chen; Sirish L. Shah</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">366</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4783786"> <span id="translatedtitle">Synthesis and <span class="hlt">Optimization</span> of 2D <span class="hlt">Filter</span> Designs for Heterogeneous FPGAs</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Many image processing applications require fast convolution of an image with one or more 2D <span class="hlt">filters</span>. Field-Programmable Gate Arrays (FPGAs) are often used to achieve this goal due to their fine grain parallelism and reconfigurability. However, the heterogeneous nature of modern reconfigurable devices is not usually considered during design <span class="hlt">optimization</span>. This article proposes an algorithm that explores the space of</p> <div class="credits"> <p class="dwt_author">Christos-savvas Bouganis; Sung-boem Park; George A. Constantinides; Peter Y. K. Cheung</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">367</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/262384"> <span id="translatedtitle">An effective coded excitation scheme based on a predistorted FM signal and an <span class="hlt">optimized</span> digital <span class="hlt">filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Presents a coded excitation imaging system based on a predistorted FM excitation and a digital compression <span class="hlt">filter</span> designed for medical ultrasonic applications, in order to preserve both axial resolution and contrast. In radars, <span class="hlt">optimal</span> Chebyshev windows efficiently weight a nearly rectangular spectrum. For the small time-bandwidth (TB) products available in ultrasound, the rectangular spectrum approximation is not valid, which reduces</p> <div class="credits"> <p class="dwt_author">Thanassis X. Misaridis; J. A. Jensen</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">368</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2051656"> <span id="translatedtitle">Performance evaluation of subband coding and <span class="hlt">optimization</span> of its <span class="hlt">filter</span> coefficients</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, two analytical methods to evaluate coding performance of subband coding are proposed, and <span class="hlt">optimization</span> of its <span class="hlt">filter</span> coefficients from the viewpoint of energy compaction property is considered. The first method is based on matrix representation of subband coding in time domain, where the coding gain given by Jayant and Noll is introduced as a performance measure for</p> <div class="credits"> <p class="dwt_author">Jiro Katto; Yasuhiko Yasuda</p> <p class="dwt_publisher"></p> <p class="publishDate">1991-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">369</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=N9322024"> <span id="translatedtitle">Multivariable Frequency Response Methods for <span class="hlt">Optimal</span> Kalman-Bucy <span class="hlt">Filters</span> with Applications to Radar Tracking Systems.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The problem of multi-output, infinite-time, linear time-invariant <span class="hlt">optimal</span> Kalman-Bucy <span class="hlt">filter</span> both in continuous and discrete-time cases in frequency domain is addressed. A simple new algorithm is given for the analytical solution to the steady-state gain ...</p> <div class="credits"> <p class="dwt_author">C. C. Arcasoy</p> <p class="dwt_publisher"></p> <p class="publishDate">1992-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">370</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23844390"> <span id="translatedtitle">Efficient and accurate <span class="hlt">optimal</span> linear phase FIR <span class="hlt">filter</span> design using opposition-based harmony search algorithm.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">In this paper, opposition-based harmony search has been applied for the <span class="hlt">optimal</span> design of linear phase FIR <span class="hlt">filters</span>. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR <span class="hlt">filter</span> design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR <span class="hlt">filters</span> are designed with the proposed OHS and other aforementioned algorithms individually for comparative <span class="hlt">optimization</span> performance. A comparison of simulation results reveals the <span class="hlt">optimization</span> efficacy of the OHS over the other <span class="hlt">optimization</span> techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR <span class="hlt">filter</span> design problems. PMID:23844390</p> <div class="credits"> <p class="dwt_author">Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-10</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">371</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1502341"> <span id="translatedtitle">Efficient electromagnetic <span class="hlt">optimization</span> of microwave <span class="hlt">filters</span> and multiplexers using rational models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A method is presented for the efficient <span class="hlt">optimization</span> of microwave <span class="hlt">filters</span> and multiplexers designed from an ideal prototype. The method is based on the estimation of a rational function adjusted to a reduced number of samples of the microwave device response obtained either through electromagnetic analysis or measurements. From this rational function, a circuital network having the previously known topology</p> <div class="credits"> <p class="dwt_author">Alejandro García-Lampérez; Sergio Llorente-Romano; Magdalena Salazar-Palma; Tapan K. Sarkar</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">372</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50323162"> <span id="translatedtitle"><span class="hlt">Optimal</span> online parameter estimation for a class of infinite dimensional systems using Kalman <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We consider the problem of online parameter estimation for a class of structurally perturbed infinite dimensional systems. By viewing the system as an augmented system with the unknown constant parameters being the additional states, a time varying infinite dimensional system results whose evolution operator depends on the available output signal. An <span class="hlt">optimal</span> <span class="hlt">filter</span> for the resulting time varying system is</p> <div class="credits"> <p class="dwt_author">Michael A. Demetriou; Kazufumi Ito</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">373</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/49245977"> <span id="translatedtitle">Wind energy assessment incorporating <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> method</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, wind energy in Taiwan is assessed according to Weibull function. The heuristic searching technique, <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO), is applied originally to find the Weibull parameters. Wind data used is measured by three wind turbines located at different climate regions, i.e. Dayuan, Hengchun and Penghu. The results show that the PSO is powerful in searching parameters. Three</p> <div class="credits"> <p class="dwt_author">Tian Pau Chang</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">374</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/26647060"> <span id="translatedtitle">Chaotic <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> based robust load flow</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A reliable load flow algorithm based on chaotic <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (CPSO) technique has been developed. To obtain optimum solution efficiently and accurately, an innovative formula for adaptive inertia weight factor (AIWF) has been introduced. Novel formulae for constriction factors have been designed for the load flow problems which are also adaptive. In addition to that, chaotic local search (CLS)</p> <div class="credits"> <p class="dwt_author">P. Acharjee; S. K. Goswami</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">375</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4709912"> <span id="translatedtitle"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> algorithm for emergency resource allocation on expressway</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In order to allocate traffic emergency rescue resources on expressway, considering rescue time and resources costs as the objective, stochastic variables are introduced into constraints and a corresponding stochastic programming model is established, due to the stochastic resource requirements of accidents. Because of large numbers of rescue depots and black-spots, a stochastic simulation of <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm is</p> <div class="credits"> <p class="dwt_author">Chai Gan; Sun Ying-ying; Zhu Cang-hui</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">376</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51077215"> <span id="translatedtitle"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> and evolutionary methods for plasmonic biomedical applications</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper the Evolutionary Method (EM) and the <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO), which are based on competitiveness and collaborative algorithms respectively, are investigated for plasmonic design. Actually, plasmonics repre- sents a rapidly expanding interdisciplinary field with numerous devices for physical, biological and medicine applications. In this study, four EM and PSO algorithms are tested in two different plasmonic applications:</p> <div class="credits"> <p class="dwt_author">Sameh Kessentini; Dominique Barchiesi; Thomas Grosges; Marc Lamy de la Chapelle</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">377</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1717974"> <span id="translatedtitle">Fuzzy Cognitive Maps Learning Using <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper introduces a new learning algorithm for Fuzzy Cognitive Maps, which is based on the application of a swarm intelligence algorithm, namely <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span>. The proposed approach is applied to detect weight matrices that lead the Fuzzy Cognitive Map to desired steady states, thereby refining the initial weight approximation provided by the experts. This is performed through the</p> <div class="credits"> <p class="dwt_author">Elpiniki I. Papageorgiou; Konstantinos E. Parsopoulos; Chrysostomos D. Stylios; Petros P. Groumpos; Michael N. Vrahatis</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">378</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4773474"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> for Sorted Adapted Gaussian Mixture Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Recently, we introduced the sorted Gaussian mixture models (SGMMs) algorithm providing the means to tradeoff performance for operational speed and thus permitting the speed-up of GMM-based classification schemes. The performance of the SGMM algorithm depends on the proper choice of the sorting function, and the proper adjustment of its parameters. In the present work, we employ <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO)</p> <div class="credits"> <p class="dwt_author">Rahim Saeidi; H. R. S. Mohammadi; T. Ganchev; R. D. Rodman</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">379</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2203887"> <span id="translatedtitle">Modeling Transcriptional Regulation in Chondrogenesis Using <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Chondrogenesis is a complex developmental process involving many transcription factors. Using mRNA expression data and regulatory DNA sequences, we formulated a quantitative model to predict a set of transcription-factor binding motifs (TFBMs) as a combinatorial problem. To solve such a problem, an efficient computational algorithm should be employed. In the current study, <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> was applied. Swarm intelligence is</p> <div class="credits"> <p class="dwt_author">Yunlong Liu; Hiroki Yokota</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">380</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50865689"> <span id="translatedtitle">Application of Adaptive <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> in Portfolio Selection</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, we present an asset allocation model and typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. Another, we use Conditional Value-at-Risk(CVaR) to control the corresponding risk. Also, We use Adaptive <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (APSO) to solve the given model and numerical results show the suitability and promise of our methodology.</p> <div class="credits"> <p class="dwt_author">Xinli Zhang; Kecun Zhang</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_18");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" 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showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_21");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">381</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/6512083"> <span id="translatedtitle">Blind Image Deconvolution via <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> with Entropy Evaluation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This study addresses a blind image deconvolution which uses only blurred image and tiny point spread function (PSF) information to restore the original image. In order to mitigate the problem trapping into a local solution in conventional algorithms, the evolutionary learning is reasonably to apply to this task. In this paper, <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) is therefore utilized to seek</p> <div class="credits"> <p class="dwt_author">Tsung-ying Sun; Chan-cheng Liu; Yu-peng Jheng; Jyun-hong Jheng; Shang-jeng Tsai; Sheng-ta Hsieh</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">382</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/742067"> <span id="translatedtitle">The <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm: convergence analysis and parameter selection</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm is analyzed using standard results from the dynamic system theory. Graphical parameter selection guidelines are derived. The exploration–exploitation tradeoff is discussed and illustrated. Examples of performance on benchmark functions superior to previously published results are given.</p> <div class="credits"> <p class="dwt_author">Ioan Cristian Trelea</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">383</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51136799"> <span id="translatedtitle">Chord recognition using neural networks based on <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A sequence of musical chords can facilitate musicians in music arrangement and accompaniment. To implement an intelligent system for chord recognition, in this paper we propose a novel approach using Artificial Neural Networks (ANN) trained by the <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) technique and Backpropagation (BP) learning algorithm. All the training and testing data are generated from Musical Instrument Digital Interface</p> <div class="credits"> <p class="dwt_author">Cheng-Jian Lin; Chin-Ling Lee; Chun-Cheng Peng</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">384</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50878981"> <span id="translatedtitle">Coverage in wireless sensor networks based on individual <span class="hlt">particle</span> <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Effective sensor coverage is one of the key topics addressed in wireless sensor networks (WSNs) study, which refers to the deployment and detection probability of WSNs. This paper proposes a novel deployment algorithm for mobile sensor networks, based on individual <span class="hlt">particle</span> <span class="hlt">optimization</span> (IPO). The algorithm is designed for real-time online deployment for the purpose of maximum coverage in the environment.</p> <div class="credits"> <p class="dwt_author">S. M. A Salehizadeh; A. Dirafzoon; M. B. Menhaj; A. Afshar</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">385</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13985271"> <span id="translatedtitle">Frankenstein's PSO: A Composite <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">During the last decade, many variants of the original <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm have been proposed. In many cases, the difference between two variants can be seen as an algorithmic component being present in one variant but not in the other. In the first part of the paper, we present the results and insights obtained from a detailed empirical</p> <div class="credits"> <p class="dwt_author">Marco Antonio Montes de Oca; Thomas Stützle; Mauro Birattari; Marco Dorigo</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">386</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1650158"> <span id="translatedtitle">A hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> for distribution state estimation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper proposes a hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (HPSO) for a practical distribution state estimation. The proposed method considers nonlinear characteristics of the practical equipment and actual limited measurements in distribution systems. The method can estimate load and distributed generation output values at each node by minimizing the difference between measured and calculated voltages and currents. The feasibility of the</p> <div class="credits"> <p class="dwt_author">Shigenori Naka; T. Genji; T. Yura; Y. Fukuyama</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">387</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50222857"> <span id="translatedtitle">Practical distribution state estimation using hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper proposes a practical distribution system state estimation method using a hybrid <span class="hlt">particle</span> swarm <span class="hlt">optimization</span>. The proposed method considers nonlinear characteristics of the practical equipment and actual measurements in distribution systems. The method can estimate load and distributed generation output values at each node by minimizing the difference between measured and calculated state variables. The feasibility of the proposed</p> <div class="credits"> <p class="dwt_author">Shigenori Naka; Takamu Genji; Toshiki Yura; Y. Fukuyama</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">388</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009SPIE.7182E..34Z"> <span id="translatedtitle">Microscopy with spatial <span class="hlt">filtering</span> for sorting <span class="hlt">particles</span> and monitoring subcellular morphology</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Optical scatter imaging (OSI) was developed to non-invasively track real-time changes in <span class="hlt">particle</span> morphology with submicron sensitivity in situ without exogenous labeling, cell fixing, or organelle isolation. For spherical <span class="hlt">particles</span>, the intensity ratio of wide-to-narrow angle scatter (OSIR, Optical Scatter Image Ratio) was shown to decrease monotonically with diameter and agree with Mie theory. In living cells, we recently reported this technique is able to detect mitochondrial morphological alterations, which were mediated by the Bcl-xL transmembrane domain, and could not be observed by fluorescence or differential interference contrast images. Here we further extend the ability of morphology assessment by adopting a digital micromirror device (DMD) for Fourier <span class="hlt">filtering</span>. When placed in the Fourier plane the DMD can be used to select scattering intensities at desired combination of scattering angles. We designed an optical <span class="hlt">filter</span> bank consisting of Gabor-like <span class="hlt">filters</span> with various scales and rotations based on Gabor <span class="hlt">filters</span>, which have been widely used for localization of spatial and frequency information in digital images and texture analysis. Using a model system consisting of mixtures of polystyrene spheres and bacteria, we show how this system can be used to sort <span class="hlt">particles</span> on a microscopic slide based on their size, orientation and aspect ratio. We are currently applying this technique to characterize the morphology of subcellular organelles to help understand fundamental biological processes.</p> <div class="credits"> <p class="dwt_author">Zheng, Jing-Yi; Qian, Zhen; Pasternack, Robert M.; Boustany, Nada N.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">389</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23818832"> <span id="translatedtitle"><span class="hlt">Optimal</span> control for a parallel hybrid hydraulic excavator using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary"><span class="hlt">Optimal</span> control using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) is put forward in a parallel hybrid hydraulic excavator (PHHE). A power-train mathematical model of PHHE is illustrated along with the analysis of components' parameters. Then, the <span class="hlt">optimal</span> control problem is addressed, and PSO algorithm is introduced to deal with this nonlinear <span class="hlt">optimal</span> problem which contains lots of inequality/equality constraints. Then, the comparisons between the <span class="hlt">optimal</span> control and rule-based one are made, and the results show that hybrids with the <span class="hlt">optimal</span> control would increase fuel economy. Although PSO algorithm is off-line <span class="hlt">optimization</span>, still it would bring performance benchmark for PHHE and also help have a deep insight into hybrid excavators. PMID:23818832</p> <div class="credits"> <p class="dwt_author">Wang, Dong-yun; Guan, Chen</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-02</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">390</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51157655"> <span id="translatedtitle">A Framework for 3D Model-Based Visual Tracking Using a GPU-Accelerated <span class="hlt">Particle</span> <span class="hlt">Filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A novel framework for acceleration of <span class="hlt">particle</span> <span class="hlt">filtering</span> approaches to 3D model-based, markerless visual tracking in monocular video is described. Specifically, we present a methodology for partitioning and mapping the computationally expensive weight-update stage of a <span class="hlt">particle</span> <span class="hlt">filter</span> to a graphics processing unit (GPU) to achieve <span class="hlt">particle</span>- and pixel-level parallelism. Nvidia CUDA and Direct3D are employed to harness the massively</p> <div class="credits"> <p class="dwt_author">James Anthony Brown; David W. Capson</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">391</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1993gnc..conf.1740A"> <span id="translatedtitle">Development of an <span class="hlt">optimized</span> LEB <span class="hlt">filter</span> and its application to INS/GPS test data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">An <span class="hlt">optimized</span> linear-ellipsoidal-bounded (LEB) <span class="hlt">filter</span> has been developed and applied to data obtained from a ground test using a combined INS/GPS configuration. In this cascaded configuration, the <span class="hlt">filter</span> receives eight outputs from the INS (accelerations, velocity, angles, altitude) and six outputs from the GPS (velocities and positions). The GPS measurements have included the effect of SA of varying or unknown spectrum which, although likely to be estimated and compensated with some modelling techniques at the expense of including extra state variables, could also be dealt with the approach indicated in this article at much less effort. An <span class="hlt">optimized</span> formulation for the LEB <span class="hlt">filter</span> is presented in which the volume of the ellipsoid containing the estimation errors is minimized at every step or at selected intervals. The SA effect is modelled as an unknown-but-bounded (UBB) noise process. Comparisons with an Extended Kalman <span class="hlt">filter</span> (KF) show that KF innovations are not white and the LEB <span class="hlt">filter</span> estimates are one order of magnitude smaller that those produced by the KF.</p> <div class="credits"> <p class="dwt_author">Antonini, Claudio D.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">392</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013IJEEP..14..477B"> <span id="translatedtitle">Decoupled Control Strategy of Grid Interactive Inverter System with <span class="hlt">Optimal</span> LCL <span class="hlt">Filter</span> Design</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This article presents a control strategy for a three-phase grid interactive voltage source inverter that links a renewable energy source to the utility grid through a LCL-type <span class="hlt">filter</span>. An <span class="hlt">optimized</span> LCL-type <span class="hlt">filter</span> has been designed and modeled so as to reduce the current harmonics in the grid, considering the conduction and switching losses at constant modulation index (Ma). The control strategy adopted here decouples the active and reactive power loops, thus achieving desirable performance with independent control of active and reactive power injected into the grid. The startup transients can also be controlled by the implementation of this proposed control strategy: in addition to this, <span class="hlt">optimal</span> LCL <span class="hlt">filter</span> with lesser conduction and switching copper losses as well as core losses. A trade-off has been made between the total losses in the LCL <span class="hlt">filter</span> and the Total Harmonic Distortion (THD%) of the grid current, and the <span class="hlt">filter</span> inductor has been designed accordingly. In order to study the dynamic performance of the system and to confirm the analytical results, the models are simulated in the MATLAB/Simulink environment, and the results are analyzed.</p> <div class="credits"> <p class="dwt_author">Babu, B. Chitti; Anurag, Anup; Sowmya, Tontepu; Marandi, Debati; Bal, Satarupa</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">393</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AIPC.1185..306C"> <span id="translatedtitle">A Wavelet-based <span class="hlt">Optimal</span> <span class="hlt">Filtering</span> Method for Adaptive Detection: Application to Metallic Magnetic Calorimeters</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Optimal</span> <span class="hlt">filtering</span> allows the maximization of signal-over-noise ratio for the improvement of both energy threshold and resolution. Nevertheless, its effective efficiency depends on the estimation of signal and noise spectra. In practice, these are often estimated by averaging over a set of carefully chosen data. In case of time-varying noise, adaptive non-linear algorithms can be used if the shape of the signal is known. However, their convergence is not guaranteed, especially with 1/f-type noise. In this paper, a new method is presented for adaptive noise whitening and template signal estimation. First, the noise is continuously characterized in the wavelet domain, where the signal is decomposed over a set of scales, corresponding to band-pass <span class="hlt">filters</span>. Both time resolution and decorrelation properties of the wavelet transform allow an accurate and robust estimation of the noise structure, even if pulses or correlated noise are present. The whitening step then amounts to a normalization of each scale by the estimated noise variance. A matched <span class="hlt">filter</span> is then applied on the whitened signal. The required signal template is constructed from a single event, denoised by a <span class="hlt">filtering</span> technique called wavelet thresholding. As an example, application to metallic magnetic calorimeter data is presented. The method reaches the precision of conventional <span class="hlt">optimal</span> <span class="hlt">filtering</span>, further allowing noise monitoring, adaptive threshold and improving the energy resolution of up to 8% in some cases.</p> <div class="credits"> <p class="dwt_author">Censier, B.; Rodrigues, M.; Loidl, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">394</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20887016"> <span id="translatedtitle">Design <span class="hlt">optimization</span> of vena cava <span class="hlt">filters</span>: an application to dual filtration devices.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Pulmonary embolism (PE) is a significant medical problem that results in over 300,000 fatalities per year. A common preventative treatment for PE is the insertion of a metallic <span class="hlt">filter</span> into the inferior vena cava that traps thrombi before they reach the lungs. The goal of this work is to use methods of mathematical modeling and design <span class="hlt">optimization</span> to determine the configuration of trapped thrombi that minimizes the hemodynamic disruption. The resulting configuration has implications for constructing an <span class="hlt">optimally</span> designed vena cava <span class="hlt">filter</span>. Computational fluid dynamics is coupled with a nonlinear <span class="hlt">optimization</span> algorithm to determine the <span class="hlt">optimal</span> configuration of a trapped model thrombus in the inferior vena cava. The location and shape of the thrombus are parametrized, and an objective function, based on wall shear stresses, determines the worthiness of a given configuration. The methods are fully automated and demonstrate the capabilities of a design <span class="hlt">optimization</span> framework that is broadly applicable. Changes to thrombus location and shape alter the velocity contours and wall shear stress profiles significantly. For vena cava <span class="hlt">filters</span> that trap two thrombi simultaneously, the undesirable flow dynamics past one thrombus can be mitigated by leveraging the flow past the other thrombus. Streamlining the shape of the thrombus trapped along the cava wall reduces the disruption to the flow but increases the area exposed to low wall shear stress. Computer-based design <span class="hlt">optimization</span> is a useful tool for developing vena cava <span class="hlt">filters</span>. Characterizing and parametrizing the design requirements and constraints is essential for constructing devices that address clinical complications. In addition, formulating a well-defined objective function that quantifies clinical risks and benefits is needed for designing devices that are clinically viable. PMID:20887016</p> <div class="credits"> <p class="dwt_author">Singer, Michael A; Wang, Stephen L; Diachin, Darin P</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">395</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/1010409"> <span id="translatedtitle">Design <span class="hlt">Optimization</span> of Vena Cava <span class="hlt">Filters</span>: An application to dual filtration devices</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Pulmonary embolism (PE) is a significant medical problem that results in over 300,000 fatalities per year. A common preventative treatment for PE is the insertion of a metallic <span class="hlt">filter</span> into the inferior vena cava that traps thrombi before they reach the lungs. The goal of this work is to use methods of mathematical modeling and design <span class="hlt">optimization</span> to determine the configuration of trapped thrombi that minimizes the hemodynamic disruption. The resulting configuration has implications for constructing an <span class="hlt">optimally</span> designed vena cava <span class="hlt">filter</span>. Computational fluid dynamics is coupled with a nonlinear <span class="hlt">optimization</span> algorithm to determine the <span class="hlt">optimal</span> configuration of trapped model thrombus in the inferior vena cava. The location and shape of the thrombus are parameterized, and an objective function, based on wall shear stresses, determines the worthiness of a given configuration. The methods are fully automated and demonstrate the capabilities of a design <span class="hlt">optimization</span> framework that is broadly applicable. Changes to thrombus location and shape alter the velocity contours and wall shear stress profiles significantly. For vena cava <span class="hlt">filters</span> that trap two thrombi simultaneously, the undesirable flow dynamics past one thrombus can be mitigated by leveraging the flow past the other thrombus. Streamlining the shape of thrombus trapped along the cava wall reduces the disruption to the flow, but increases the area exposed to abnormal wall shear stress. Computer-based design <span class="hlt">optimization</span> is a useful tool for developing vena cava <span class="hlt">filters</span>. Characterizing and parameterizing the design requirements and constraints is essential for constructing devices that address clinical complications. In addition, formulating a well-defined objective function that quantifies clinical risks and benefits is needed for designing devices that are clinically viable.</p> <div class="credits"> <p class="dwt_author">Singer, M A; Wang, S L; Diachin, D P</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-03</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">396</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007ITEIS.127..787M"> <span id="translatedtitle">Proposal of <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Methods with Nonlinear Dissipative Term</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Optimization</span> methods based on meta-heuristics are proposed as a class of global <span class="hlt">optimization</span> methods, by which the global minimum can be obtained without trapping in local minima. <span class="hlt">Particle</span> swarm <span class="hlt">optimization</span>(PSO), which is one of those methods, is known for its high search ability and easy implement. However, it might be difficult to find the global optimum for <span class="hlt">optimization</span> problems which have a lot of decision variables and local optima. In this paper, we propose three types of new PSO to clear the weak point. One is a model with the nonlinear dissipative term intoroduced by Fujita, Yasuda and Yokoyama(4) to prohibit the search point's velocity being zero. The others are models with the nonlinear dissipative term with the pbest or the gbest information to disturb the search around them.</p> <div class="credits"> <p class="dwt_author">Murata, Hideki; Yasuda, Keiichiro; Aiyoshi, Eitaro</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">397</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007NIMPA.579..695K"> <span id="translatedtitle"><span class="hlt">Optimization</span> of monolithic charged-<span class="hlt">particle</span> sensor arrays</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Direct-detection CMOS image sensors <span class="hlt">optimized</span> for charged-<span class="hlt">particle</span> imaging applications, such as electron microscopy and <span class="hlt">particle</span> physics, have been designed, fabricated and characterized. These devices directly image charged <span class="hlt">particles</span> without reliance on image-degrading hybrid technologies such as the use of scintillating materials. Based on standard CMOS Active Pixel Sensor (APS) technology, the sensor arrays use an 8 20 ?m thick epitaxial layer that acts as a sensitive region for the generation and collection of ionization electrons resulting from impinging high-energy <span class="hlt">particles</span>. A range of <span class="hlt">optimizations</span> to this technology have been developed via simulation and experimental device design. These include the simulation and measurement of charge-collection efficiency vs. recombination, effect of diode area and stray capacitance vs. signal gain and noise, and the effect of different epitaxial silicon depths. Several experimental devices and full-scale prototypes are presented, including two prototypes that systematically and independently vary pixel pitch and diode area, and a complete high-resolution camera for electron microscopy <span class="hlt">optimized</span> through experiment and simulation. The electron microscope camera has 1×1 k2 pixels with a 5 ?m pixel pitch and an 8 ?m epitaxial silicon thickness.</p> <div class="credits"> <p class="dwt_author">Kleinfelder, Stuart; Li, Shengdong; Chen, Yandong</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">398</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009pcms.confE..89B"> <span id="translatedtitle">Sub-<span class="hlt">Optimal</span> Ensemble <span class="hlt">Filters</span> and distributed hydrologic modeling: a new challenge in flood forecasting</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Data assimilation techniques based on Ensemble <span class="hlt">Filtering</span> are widely regarded as the best approach in solving forecast and calibration problems in geophysics models. Often the implementation of statistical <span class="hlt">optimal</span> techniques, like the Ensemble Kalman <span class="hlt">Filter</span>, is unfeasible because of the large amount of replicas used in each time step of the model for updating the error covariance matrix. Therefore the sub <span class="hlt">optimal</span> approach seems to be a more suitable choice. Various sub-<span class="hlt">optimal</span> techniques were tested in atmospheric and oceanographic models, some of them are based on the detection of a "null space". Distributed Hydrologic Models differ from the other geo-fluid-dynamics models in some fundamental aspects that make complex to understanding the relative efficiency of the different suboptimal techniques. Those aspects include threshold processes , preferential trajectories for convection and diffusion, low observability of the main state variables and high parametric uncertainty. This research study is focused on such topics and explore them through some numerical experiments on an continuous hydrologic model, MOBIDIC. This model include both water mass balance and surface energy balance, so it's able to assimilate a wide variety of datasets like traditional hydrometric "on ground" measurements or land surface temperature retrieval from satellite. The experiments that we present concern to a basin of 700 kmq in center Italy, with hourly dataset on a 8 months period that includes both drought and flood events, in this first set of experiment we worked on a low spatial resolution version of the hydrologic model (3.2 km). A new Kalman <span class="hlt">Filter</span> based algorithm is presented : this <span class="hlt">filter</span> try to address the main challenges of hydrological modeling uncertainty. The proposed <span class="hlt">filter</span> use in Forecast step a COFFEE (Complementary Orthogonal <span class="hlt">Filter</span> For Efficient Ensembles) approach with a propagation of both deterministic and stochastic ensembles to improve robustness and convergence proprieties. After, through a P.O.D. Reduction from control theory, we compute a Reduced Order Forecast Covariance matrix . In analysis step the <span class="hlt">filter</span> uses a LE (Local Ensemble) Kalman <span class="hlt">Filter</span> approach. We modify the LE Kalman <span class="hlt">Filter</span> assimilation scheme and we adapt its formulation to the P.O.D. Reduced sub-space propagated in forecast step. Through this, assimilation of observations is made only in the maximum covariance directions of the model error. Then the efficiency of this technique is weighed in term of hydrometric forecast accuracy in a preliminary convergence test of a synthetic rainfall event toward a real rain fall event.</p> <div class="credits"> <p class="dwt_author">Baroncini, F.; Castelli, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">399</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008AGUFM.H31A0824K"> <span id="translatedtitle">Real-Time Flood Forecasting System Using Channel Flow Routing Model with Updating by <span class="hlt">Particle</span> <span class="hlt">Filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">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 <span class="hlt">Particle</span> <span class="hlt">filtering</span> of the downstream part model as well as by the extended Kalman <span class="hlt">filtering</span> of the upstream part model and the tributary part models. The <span class="hlt">Particle</span> <span class="hlt">filtering</span> 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 <span class="hlt">Particle</span> <span class="hlt">filtering</span> and extended Kalman <span class="hlt">filtering</span> and that of the system with only extended Kalman <span class="hlt">filtering</span> 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 <span class="hlt">Particle</span> <span class="hlt">filtering</span> of the downstream part model improves forecasting accuracy of runoff at verification stations as well as at reference stations, although observed data at verification stations were not used for updating of the model.</p> <div class="credits"> <p class="dwt_author">Kudo, R.; Chikamori, H.; Nagai, A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">400</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JSemi..34b5011H"> <span id="translatedtitle">Discrete ternary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> for area <span class="hlt">optimization</span> of MPRM circuits</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Having the advantage of simplicity, robustness and low computational costs, the <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm is a powerful evolutionary computation tool for synthesis and <span class="hlt">optimization</span> of Reed-Muller logic based circuits. Exploring discrete PSO and probabilistic transition rules, the discrete ternary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (DTPSO) is proposed for mixed polarity Reed-Muller (MPRM) circuits. According to the characteristics of mixed polarity OR/XNOR expression, a tabular technique is improved, and it is applied in the polarity conversion of MPRM functions. DTPSO is introduced to search the best polarity for an area of MPRM circuits by building parameter mapping relationships between <span class="hlt">particles</span> and polarities. The computational results show that the proposed DTPSO outperforms the reported method using maxterm conversion starting from POS Boolean functions. The average saving in the number of terms is about 11.5%; the algorithm is quite efficient in terms of CPU time and achieves 12.2% improvement on average.</p> <div class="credits"> <p class="dwt_author">Haizhen, Yu; Pengjun, Wang; Disheng, Wang; Huihong, Zhang</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-02-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_19");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> 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</span> </span> <a id="NextPageLink" onclick='return showDiv("page_22");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">401</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009MeScT..20e5203A"> <span id="translatedtitle">Hybrid extended <span class="hlt">particle</span> <span class="hlt">filter</span> (HEPF) for integrated inertial navigation and global positioning systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Navigation includes the integration of methodologies and systems for estimating time-varying position, velocity and attitude of moving objects. Navigation incorporating the integrated inertial navigation system (INS) and global positioning system (GPS) generally requires extensive evaluations of nonlinear equations involving double integration. Currently, integrated navigation systems are commonly implemented using the extended Kalman <span class="hlt">filter</span> (EKF). The EKF assumes a linearized process, measurement models and Gaussian noise distributions. These assumptions are unrealistic for highly nonlinear systems like land vehicle navigation and may cause <span class="hlt">filter</span> divergence. A <span class="hlt">particle</span> <span class="hlt">filter</span> (PF) is developed to enhance integrated INS/GPS system performance as it can easily deal with nonlinearity and non-Gaussian noises. In this paper, a hybrid extended <span class="hlt">particle</span> <span class="hlt">filter</span> (HEPF) is developed as an alternative to the well-known EKF to achieve better navigation data accuracy for low-cost microelectromechanical system sensors. The results show that the HEPF performs better than the EKF during GPS outages, especially when simulated outages are located in periods with high vehicle dynamics.</p> <div class="credits"> <p class="dwt_author">Aggarwal, Priyanka; Syed, Zainab; El-Sheimy, Naser</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">402</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/900219"> <span id="translatedtitle">A MECHANISTIC MODEL FOR <span class="hlt">PARTICLE</span> DEPOSITION IN DIESEL PARTICLUATE <span class="hlt">FILTERS</span> USING THE LATTICE-BOLTZMANN TECHNIQUE</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Cordierite diesel particulate <span class="hlt">filters</span> (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 <span class="hlt">filter</span> 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 <span class="hlt">filter</span> 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 <span class="hlt">particles</span> are introduced and tracked as they move through the flow field and are deposited on the <span class="hlt">filter</span> substrate or previously deposited <span class="hlt">particles</span>. 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.</p> <div class="credits"> <p class="dwt_author">Stewart, Mark L.; Rector, David R.; Muntean, George G.; Maupin, Gary D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">403</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005SPIE.6041..560S"> <span id="translatedtitle">Highest probability data association and <span class="hlt">particle</span> <span class="hlt">filtering</span> for target tracking in clutter</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">There proposed a new method of data association called highest probability data association (HPDA) combined with <span class="hlt">particle</span> <span class="hlt">filtering</span> and applied to passive sonar tracking in clutter. The HPDA method evaluated the probabilities of one-to-one assignments of measurement-to-track. All of the bearing measurements at the present sampling instance were lined up in the order of signal strength. The measurement with the highest probability was selected to be target-originated and the measurement was used for probabilistic weight update of <span class="hlt">particle</span> <span class="hlt">filtering</span>. The proposed HPDA algorithm can be easily extended to multi-target tracking problems. It can be used to avoid track coalescence phenomenon that prevails when several tracks move very close together.</p> <div class="credits"> <p class="dwt_author">Song, Taek L.; Kim, Da S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">404</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3324861"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">Filtering</span> with Region-based Matching for Tracking of Partially Occluded and Scaled Targets*</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Visual tracking of arbitrary targets in clutter is important for a wide range of military and civilian applications. We propose a general framework for the tracking of scaled and partially occluded targets, which do not necessarily have prominent features. The algorithm proposed in the present paper utilizes a modified normalized cross-correlation as the likelihood for a <span class="hlt">particle</span> <span class="hlt">filter</span>. The algorithm divides the template, selected by the user in the first video frame, into numerous patches. The matching process of these patches by <span class="hlt">particle</span> <span class="hlt">filtering</span> allows one to handle the target’s occlusions and scaling. Experimental results with fixed rectangular templates show that the method is reliable for videos with nonstationary, noisy, and cluttered background, and provides accurate trajectories in cases of target translation, scaling, and occlusion.</p> <div class="credits"> <p class="dwt_author">Nakhmani, Arie; Tannenbaum, Allen</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">405</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20081945"> <span id="translatedtitle"><span class="hlt">Particle</span>-swarm <span class="hlt">optimization</span> of broadband nanoplasmonic arrays.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We used the <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm, an evolutionary computational technique, to design metal nanoparticle arrays that produce broadband plasmonic field enhancement over the entire visible spectral range. The resulting structures turn out to be aperiodic and feature dense Fourier spectra with many closely packed <span class="hlt">particle</span> clusters. We conclude that broadband field-enhancement effects in nanoplasmonics can be achieved by engineering aperiodic arrays with a large number of spatial frequencies that provide the necessary interplay between long-range diffractive interactions at multiple length scales and near-field quasi-static coupling within small nanoparticle clusters. PMID:20081945</p> <div class="credits"> <p class="dwt_author">Forestiere, Carlo; Donelli, Massimo; Walsh, Gary F; Zeni, Edoardo; Miano, Giovanni; Dal Negro, Luca</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">406</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/r47755547435q067.pdf"> <span id="translatedtitle">Determination of transuranic and thorium isotopes in ocean water: In solution and in <span class="hlt">filterable</span> <span class="hlt">particles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A sensitive technique for the measurement of dissolved and particulate actinide concentrations and water column distributions is described. Pu, Am, and Th isotopes are collected using large-volume, wire-mounted electrical pumping systems. <span class="hlt">Particles</span> were removed by filtration, and actinides by absorption on MnO2-coated <span class="hlt">filters</span>. The very large volumes processed (up to 4000 liters) result in very sensitive and precise concentration measurements</p> <div class="credits"> <p class="dwt_author">H. D. Livingston; J. K. Cochran</p> <p class="dwt_publisher"></p> <p class="publishDate">1987-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">407</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51031424"> <span id="translatedtitle"><span class="hlt">Particle</span> <span class="hlt">Filtered</span> Modified Compressive Sensing (PaFiMoCS) for tracking signal sequences</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, we propose a novel algorithm for recursive reconstruction of a time sequence of sparse signals from highly under-sampled random linear measurements. In our method, the idea of recently proposed regularized modified compressive sensing (reg-mod-CS) is merged with sequential Monte Carlo techniques like <span class="hlt">particle</span> <span class="hlt">filtering</span>. Reg-mod-CS facilitates sequential reconstruction by utilizing a partial knowledge of the support and</p> <div class="credits"> <p class="dwt_author">Samarjit Das; Namrata Vaswani</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">408</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/05hfm3u65a2c8um9.pdf"> <span id="translatedtitle">Stereovision-Based Head Tracking Using Color and Ellipse Fitting in a <span class="hlt">Particle</span> <span class="hlt">Filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a This paper proposes the use of a <span class="hlt">particle</span> <span class="hlt">filter</span> combined with color, depth information, gradient and shape features as an\\u000a efficient and effective way of dealing with tracking of a head on the basis of image stream coming from a mobile stereovision\\u000a camera. The head is modeled in the 2D image domain by an ellipse. A weighting function is used</p> <div class="credits"> <p class="dwt_author">Bogdan Kwolek; W. Pola</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">409</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.eecs.berkeley.edu/Programs/ugrad/superb/papers2006/Ortiz.pdf"> <span id="translatedtitle">Sensitivity Analysis for Intruder Tracking Using <span class="hlt">Particle</span> <span class="hlt">Filtering</span> and a Network of Binary Sensors</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Our lab has designed a security system to automatically track and capture photos of an intruder using a high-resolution robotic pan-tilt-zoom camera using a wireless network of inexpensive binary sensors. The sensors suffer from a refractory period during which they may be unresponsive. An estimation method based on <span class="hlt">Particle</span> <span class="hlt">Filtering</span>, a numerical sequential Monte Carlo technique, takes the data from</p> <div class="credits"> <p class="dwt_author">Enrique G. Ortiz; Jeremy Schiff; Ken Goldberg</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">410</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/47769103"> <span id="translatedtitle">Multitarget bearings-only tracking using fuzzy clustering technique and Gaussian <span class="hlt">particle</span> <span class="hlt">filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, a novel multitarget bearings-only tracking algorithm that combines the fuzzy clustering data association technique\\u000a together with a Gaussian <span class="hlt">particle</span> <span class="hlt">filter</span> (GPF) is presented. Firstly, to deal with the data association problem that arises\\u000a due to the uncertainty of the measurements, the fuzzy clustering method with the maximum entropy principle is utilized, which\\u000a eliminates those invalid measurements. Secondly,</p> <div class="credits"> <p class="dwt_author">Jungen Zhang; Hongbing Ji; Cheng Ouyang</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">411</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50627972"> <span id="translatedtitle">New Constriction <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> for Security-Constrained <span class="hlt">Optimal</span> Power Flow Solution</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a new version of constriction <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (NCPSO) with mutation mechanism for solving the security-constrained <span class="hlt">optimal</span> power flow (OPF) with both the steady-state security constraints and the transient stability constraints. The objective of SCOPF in considering the valve-point loading effect of the unit and the operating limits of FACTS devices is defined not only to minimize</p> <div class="credits"> <p class="dwt_author">Zwe-Lee Gaing; Xun-Han Liu</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">412</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50881304"> <span id="translatedtitle"><span class="hlt">Optimal</span> Reactive Power Dispatch by <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> with Cauchy and Adaptive Mutations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) with cauchy mutation (PSO-CM) and adaptive mutation (PSO-AM) approaches are used to solve <span class="hlt">optimal</span> reactive power dispatch (ORPD) problem. The different mutations are integrated with the classical PSO to overcome its drawbacks. The performance of the proposed approach is demonstrated with the IEEE 14 bus and IEEE 30-bus and also the performance of</p> <div class="credits"> <p class="dwt_author">P. Subbaraj; P. N. Rajnarayanan</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">413</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50475703"> <span id="translatedtitle">Constrained <span class="hlt">optimal</span> power flow by mixed-integer <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents an efficient mixed-integer <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (MIPSO) for solving the constrained <span class="hlt">optimal</span> power flow (OPF) with a mixture of continuous and discrete control variables and discontinuous fuel cost functions. In the MIPSO-based method, the individual that contains the real-value mixture of continuous and discrete control variables is defined, two mutation schemes are proposed to deal with the</p> <div class="credits"> <p class="dwt_author">Zwe-lee Gaing</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">414</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22624307"> <span id="translatedtitle">Fitting complex population models by combining <span class="hlt">particle</span> <span class="hlt">filters</span> with Markov chain Monte Carlo.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We show how a recent framework combining Markov chain Monte Carlo (MCMC) with <span class="hlt">particle</span> <span class="hlt">filters</span> (PFMCMC) may be used to estimate population state-space models. With the purpose of utilizing the strengths of each method, PFMCMC explores hidden states by <span class="hlt">particle</span> <span class="hlt">filters</span>, while process and observation parameters are estimated using an MCMC algorithm. PFMCMC is exemplified by analyzing time series data on a red kangaroo (Macropus rufus) population in New South Wales, Australia, using MCMC over model parameters based on an adaptive Metropolis-Hastings algorithm. We fit three population models to these data; a density-dependent logistic diffusion model with environmental variance, an unregulated stochastic exponential growth model, and a random-walk model. Bayes factors and posterior model probabilities show that there is little support for density dependence and that the random-walk model is the most parsimonious model. The <span class="hlt">particle</span> <span class="hlt">filter</span> Metropolis-Hastings algorithm is a brute-force method that may be used to fit a range of complex population models. Implementation is straightforward and less involved than standard MCMC for many models, and marginal densities for model selection can be obtained with little additional effort. The cost is mainly computational, resulting in long running times that may be improved by parallelizing the algorithm. PMID:22624307</p> <div class="credits"> <p class="dwt_author">Knape, Jonas; de Valpine, Perry</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">415</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21413209"> <span id="translatedtitle"><span class="hlt">Optimal</span> configurations of <span class="hlt">filter</span> cavity in future gravitational-wave detectors</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Sensitivity of future laser interferometric gravitational wave detectors can be improved using squeezed light with frequency-dependent squeeze angle and/or amplitude, which can be created using additional so-called <span class="hlt">filter</span> cavities. Here we compare performances of several variants of this scheme, proposed during the last few years, assuming the case of a single relatively short (tens of meters) <span class="hlt">filter</span> cavity suitable for implementation already during the life cycle of the second-generation detectors, like Advanced LIGO. Using numerical <span class="hlt">optimization</span>, we show that the phase <span class="hlt">filtering</span> scheme proposed by Kimble et al [H. J. Kimble, Yu. Levin, A. B. Matsko, K. S. Thorne, and S. P. Vyatchanin, Phys. Rev. D 65, 022002 (2001).] looks like the best candidate for this scenario.</p> <div class="credits"> <p class="dwt_author">Khalili, F. Ya. [Physics Faculty, Moscow State University, Moscow 119992 (Russian Federation)</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-06-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">416</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/19516623"> <span id="translatedtitle">Design <span class="hlt">optimization</span> of integrated BiDi triplexer optical <span class="hlt">filter</span> based on planar lightwave circuit.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Design <span class="hlt">optimization</span> of a novel integrated bi-directional (BiDi) triplexer <span class="hlt">filter</span> based on planar lightwave circuit (PLC) for fiber-to-the premise (FTTP) applications is described. A multi-mode interference (MMI) device is used to <span class="hlt">filter</span> the up-stream 1310nm signal from the down-stream 1490nm and 1555nm signals. An array waveguide grating (AWG) device performs the dense WDM function by further separating the two down-stream signals. The MMI and AWG are built on the same substrate with monolithic integration. The design is validated by simulation, which shows excellent performance in terms of <span class="hlt">filter</span> spectral characteristics (e.g., bandwidth, cross-talk, etc.) as well as insertion loss. PMID:19516623</p> <div class="credits"> <p class="dwt_author">Xu, Chenglin; Hong, Xiaobin; Huang, Wei-Ping</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-05-29</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">417</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009ITEIS.129...59O"> <span id="translatedtitle"><span class="hlt">Optimal</span> Design of CSD Coefficient FIR <span class="hlt">Filters</span> Subject to Number of Nonzero Digits</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In a hardware implementation of FIR(Finite Impulse Response) digital <span class="hlt">filters</span>, it is desired to reduce a total number of nonzero digits used for a representation of <span class="hlt">filter</span> coefficients. In general, a design problem of FIR <span class="hlt">filters</span> with CSD(Canonic Signed Digit) representation, which is efficient one for the reduction of numbers of multiplier units, is often considered as one of the 0-1 combinational problems. In such the problem, some difficult constraints make us prevent to linearize the problem. Although many kinds of heuristic approaches have been applied to solve the problem, the solution obtained by such a manner could not guarantee its <span class="hlt">optimality</span>. In this paper, we attempt to formulate the design problem as the 0-1 mixed integer linear programming problem and solve it by using the branch and bound technique, which is a powerful method for solving integer programming problem. Several design examples are shown to present an efficient performance of the proposed method.</p> <div class="credits"> <p class="dwt_author">Ozaki, Yuichi; Suyama, Kenji</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">418</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48540556"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> for Markerless Full Body Motion Capture</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a The estimation of full body pose is a very difficult problem in Computer Vision. Due to high dimensionality of the pose space,\\u000a it is challenging to search the true body configurations for any search strategy. In this chapter, we apply the stochastic\\u000a <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) algorithm to full body pose estimation problem. Our method fits an articulated body model</p> <div class="credits"> <p class="dwt_author">Zheng Zhang; Hock Soon Seah; Chee Kwang Quah</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">419</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13274393"> <span id="translatedtitle">Face Detection Using <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> and Support Vector Machines</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a In this paper, a face detection algorithm that uses <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO) for searching the image is proposed.\\u000a The algorithm uses a linear Support Vector Machine (SVM) as a fast and accurate classifier in order to search for a face in\\u000a the two-dimension solution space. Using PSO, the exhaustive search in all possible combinations of the 2D coordinates can</p> <div class="credits"> <p class="dwt_author">Ermioni Marami; Anastasios Tefas</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">420</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/17891226"> <span id="translatedtitle">Parallel global <span class="hlt">optimization</span> with the <span class="hlt">particle</span> swarm algorithm.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Present day engineering <span class="hlt">optimization</span> problems often impose large computational demands, resulting in long solution times even on a modern high-end processor. To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm. Parallel PSO performance was evaluated using two categories of <span class="hlt">optimization</span> problems possessing multiple local minima-large-scale analytical test problems with computationally cheap function evaluations and medium-scale biomechanical system identification problems with computationally expensive function evaluations. For load-balanced analytical test problems formulated using 128 design variables, speedup was close to ideal and parallel efficiency above 95% for up to 32 nodes on a Beowulf cluster. In contrast, for load-imbalanced biomechanical system identification problems with 12 design variables, speedup plateaued and parallel efficiency decreased almost linearly with increasing number of nodes. The primary factor affecting parallel performance was the synchronization requirement of the parallel algorithm, which dictated that each iteration must wait for completion of the slowest fitness evaluation. When the analytical problems were solved using a fixed number of swarm iterations, a single population of 128 <span class="hlt">particles</span> produced a better convergence rate than did multiple independent runs performed using sub-populations (8 runs with 16 <span class="hlt">particles</span>, 4 runs with 32 <span class="hlt">particles</span>, or 2 runs with 64 <span class="hlt">particles</span>). These results suggest that (1) parallel PSO exhibits excellent parallel performance under load-balanced conditions, (2) an asynchronous implementation would be valuable for real-life problems subject to load imbalance, and (3) larger population sizes should be considered when multiple processors are available. PMID:17891226</p> <div class="credits"> <p class="dwt_author">Schutte, J F; Reinbolt, J A; Fregly, B J; Haftka, R T; George, A D</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-12-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_20");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return 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title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">421</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005SPIE.5852..352J"> <span id="translatedtitle"><span class="hlt">Optimized</span> SU-8 UV-lithographical process for a Ka-band <span class="hlt">filter</span> fabrication</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Rapidly expanding of millimeter wave communication has made Ka-band <span class="hlt">filter</span> fabrication to gain more and more attention from the researcher. Described in this paper is a high quality UV-lithographic process for making high aspect ratio parts of a coaxial Ka band dual mode <span class="hlt">filter</span> using an ultra-thick SU-8 photoresist layer, which has a potential application in LMDS systems. Due to the strict requirements on the perpendicular geometry of the <span class="hlt">filter</span> parts, the microfabrication research work has been concentrated on modifying the SU-8 UV-lithographical process to improve the vertical angle of sidewalls and high aspect ratio. Based on the study of the photoactive property of ultra-thick SU-8 layers, an <span class="hlt">optimized</span> prebake time has been found for obtaining the minimum UV absorption by SU-8. The <span class="hlt">optimization</span> principle has been tested using a series of experiments of UV-lithography on different prebake times, and proved effective. An <span class="hlt">optimized</span> SU-8 UV-lithographical process has been developed for the fabrication of thick layer <span class="hlt">filter</span> structures. During the test fabrication, microstructures with aspect ratio as high as 40 have been produced in 1000 mm ultra-thick SU-8 layers using the standard UV-lithography equipment. The sidewall angles are controlled between 85~90 degrees. The high quality SU-8 structures will then be used as positive moulds for producing copper structures using electroforming process. The microfabication process presented in this paper suits the proposed <span class="hlt">filter</span> well. It also reveals a good potential for volume production of high quality RF devices.</p> <div class="credits"> <p class="dwt_author">Jin, Peng; Jiang, Kyle; Tan, Jiubin; Lancaster, M. J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">422</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/1009716"> <span id="translatedtitle"><span class="hlt">Optimizing</span> Magnetite Nanoparticles for Mass Sensitivity in Magnetic <span class="hlt">Particle</span> Imaging</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Purpose: Magnetic <span class="hlt">particle</span> imaging (MPI), using magnetite nanoparticles (MNPs) as tracer material, shows great promise as a platform for fast tomographic imaging. To date, the magnetic properties of MNPs used in imaging have not been <span class="hlt">optimized</span>. As nanoparticle magnetism shows strong size dependence, we explore how varying MNP size impacts imaging performance in order to determine <span class="hlt">optimal</span> MNP characteristics for MPI at any driving field frequency, ?. Methods: Monodisperse MNPs of varying size were synthesized and their magnetic properties characterized. Their MPI response was measured experimentally, at an arbitrarily chosen ? = 250 kHz, using a custom-built MPI transceiver designed to detect the third harmonic of MNP magnetization. Results were interpreted using a model of dynamic MNP magnetization that is based on the Langevin theory of superparamagnetism and accounts for sample size distribution, and size-dependent magnetic relaxation. Results: Our experimental results show clear variation in the MPI signal intensity as a function of MNP size that is in good agreement with modeled results. A maxima in the plot of MPI signal vs. MNP size indicates there is a particular size that is <span class="hlt">optimal</span> for the chosen frequency of 250 kHz. Conclusions: For MPI at any chosen frequency, there will exist a characteristic <span class="hlt">particle</span> size that generates maximum signal amplitude. We illustrate this at 250 kHz with <span class="hlt">particles</span> of 15 nm core diameter.</p> <div class="credits"> <p class="dwt_author">Ferguson, R. Matthew; Minard, Kevin R.; Khandhar, Amit P.; Krishnan, Kannan M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">423</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhFl...24h3302S"> <span id="translatedtitle">Inertial <span class="hlt">particle</span> acceleration statistics in turbulence: Effects of <span class="hlt">filtering</span>, biased sampling, and flow topology</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this study, we investigate the effect of ``biased sampling,'' i.e., the clustering of inertial <span class="hlt">particles</span> in regions of the flow with low vorticity, and ``<span class="hlt">filtering</span>,'' i.e., the tendency of inertial <span class="hlt">particles</span> to attenuate the fluid velocity fluctuations, on the probability density function of inertial <span class="hlt">particle</span> accelerations. In particular, we find that the concept of ``biased <span class="hlt">filtering</span>'' introduced by Ayyalasomayajula et al. [``Modeling inertial <span class="hlt">particle</span> acceleration statistics in isotropic turbulence,'' Phys. Fluids 20, 0945104 (2008)], in which <span class="hlt">particles</span> <span class="hlt">filter</span> stronger acceleration events more than weaker ones, is relevant to the higher order moments of acceleration. Flow topology and its connection to acceleration is explored through invariants of the velocity-gradient, strain-rate, and rotation-rate tensors. A semi-quantitative analysis is performed where we assess the contribution of specific flow topologies to acceleration moments. Our findings show that the contributions of regions of high vorticity and low strain decrease significantly with Stokes number, a non-dimensional measure of <span class="hlt">particle</span> inertia. The contribution from regions of low vorticity and high strain exhibits a peak at a Stokes number of approximately 0.2. Following the methodology of Ooi et al. [``A study of the evolution and characteristics of the invariants of the velocity-gradient tensor in isotropic turbulence,'' J. Fluid Mech. 381, 141 (1999)], we compute mean conditional trajectories in planes formed by pairs of tensor invariants in time. Among the interesting findings is the existence of a stable focus in the plane formed by the second invariants of the strain-rate and rotation-rate tensors. Contradicting the results of Ooi et al., we find a stable focus in the plane formed by the second and third invariants of the strain-rate tensor for fluid tracers. We confirm, at an even higher Reynolds number, the conjecture of Collins and Keswani [``Reynolds number scaling of <span class="hlt">particle</span> clustering in turbulent aerosols,'' New J. Phys. 6, 119 (2004)] that inertial <span class="hlt">particle</span> clustering saturates at large Reynolds numbers. The result is supported by the theory presented in Chun et al. [``Clustering of aerosol <span class="hlt">particles</span> in isotropic turbulence,'' J. Fluid Mech. 536, 219 (2005)].</p> <div class="credits"> <p class="dwt_author">Salazar, Juan P. L. C.; Collins, Lance R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">424</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50633090"> <span id="translatedtitle">Bit-Level <span class="hlt">Optimization</span> of Shift-and-Add Based FIR <span class="hlt">Filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Implementation of FIR <span class="hlt">filters</span> using shift-and-add multipliers has been an active research area for the last decade. However, almost all algorithms so far has been focused on reducing the number of adders and subtractors, while little effort was put on the bit-level implementation. In this work we propose a method to <span class="hlt">optimize</span> the number of full adders and half adders</p> <div class="credits"> <p class="dwt_author">Kenny Johansson; Oscar Gustafsson; Lars Wanhammar</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">425</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23796954"> <span id="translatedtitle"><span class="hlt">Optimization</span> of adenovirus 40 and 41 recovery from tap water using small disk <span class="hlt">filters</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Currently, the U.S. Environmental Protection Agency's Information Collection Rule (ICR) for the primary concentration of viruses from drinking and surface waters uses the 1MDS <span class="hlt">filter</span>, but a more cost effective option, the NanoCeram(®) <span class="hlt">filter</span>, has been shown to recover comparable levels of enterovirus and norovirus from both matrices. In order to achieve the highest viral recoveries, filtration methods require the identification of <span class="hlt">optimal</span> concentration conditions that are unique for each virus type. This study evaluated the effectiveness of 1MDS and NanoCeram <span class="hlt">filters</span> in recovering adenovirus (AdV) 40 and 41 from tap water, and <span class="hlt">optimized</span> two secondary concentration procedures the celite and organic flocculation method. Adjustments in pH were made to both virus elution solutions and sample matrices to determine which resulted in higher virus recovery. Samples were analyzed by quantitative PCR (qPCR) and Most Probable Number (MPN) techniques and AdV recoveries were determined by comparing levels of virus in sample concentrates to that in the initial input. The recovery of adenovirus was highest for samples in unconditioned tap water (pH 8) using the 1MDS <span class="hlt">filter</span> and celite for secondary concentration. Elution buffer containing 0.1% sodium polyphosphate at pH 10.0 was determined to be most effective overall for both AdV types. Under these conditions, the average recovery for AdV40 and 41 was 49% and 60%, respectively. By <span class="hlt">optimizing</span> secondary elution steps, AdV recovery from tap water could be improved at least two-fold compared to the currently used methodology. Identification of the <span class="hlt">optimal</span> concentration conditions for human AdV (HAdV) is important for timely and sensitive detection of these viruses from both surface and drinking waters. PMID:23796954</p> <div class="credits"> <p class="dwt_author">McMinn, Brian R</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-21</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">426</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18583726"> <span id="translatedtitle">Adaptive wavelet EMG compression based on local <span class="hlt">optimization</span> of <span class="hlt">filter</span> banks.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This paper presents an adaptive wavelet technique for compression of surface electromyographic signals. The technique employs an <span class="hlt">optimization</span> algorithm to adjust the wavelet <span class="hlt">filter</span> bank in order to minimize the distortion of the compressed signal. Orthogonality of the transform is ensured by using a restriction-free parametrization described elsewhere. A case study involving real-life isotonic and isometric electromyographic signals is presented for illustration. The results show that the proposed approach outperforms the standard non-<span class="hlt">optimized</span> wavelet technique in terms of the percent residual difference for a given compression factor. PMID:18583726</p> <div class="credits"> <p class="dwt_author">Paiva, Juliana Pereira Lisboa M; Kelencz, Carlos Alberto; Paiva, Henrique Mohallem; Galvăo, Roberto Kawakami H; Magini, Marcio</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-06-26</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">427</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/20856467"> <span id="translatedtitle"><span class="hlt">Optimization</span> of interference <span class="hlt">filters</span> with genetic algorithms applied to silver-based heat mirrors.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">In the <span class="hlt">optimization</span> of multilayer stacks for various optical <span class="hlt">filtering</span> purposes not only the thicknesses of the thin films are to be <span class="hlt">optimized</span>, but also the sequence of materials. Materials with very different optical properties, such as metals and dielectrics, may be combined. A genetic algorithm is introduced to search for the <span class="hlt">optimal</span> sequence of materials along with their optical thicknesses. This procedure is applied to a heat mirror in combination with a blackbody absorber for thermal solar energy applications at elevated temperatures (250 °C). The heat mirror is based on silver films with antireflective dielectric layers. Seven dielectrics have been considered. For a five-layer stack the sequence (TiO(2)/Ag/TiO(2)/Ag/Y(2)O(3)) is found to be <span class="hlt">optimal</span>. PMID:20856467</p> <div class="credits"> <p class="dwt_author">Eisenhammer, T; Lazarov, M; Leutbecher, M; Schöffel, U; Sizmann, R</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">428</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011OptFT..17..291H"> <span id="translatedtitle">Simple index modulation profile with fast-converging design <span class="hlt">optimization</span> for multichannel fiber Bragg grating <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this paper, a novel hybrid algorithm featuring a simple index modulation profile with fast-converging <span class="hlt">optimization</span> is proposed towards the design of dense wavelength-division-multiplexing systems (DWDM) multichannel fiber Bragg grating (FBG) <span class="hlt">filters</span>. The approach is based on utilizing one of other FBG design approaches that may suffer from spectral distortion as the first step, then performing Lagrange multiplier <span class="hlt">optimization</span> (LMO) for <span class="hlt">optimized</span> correction of the spectral distortion. In our design examples, the superposition method is employed as the first design step for its merits of easy fabrication, and the discrete layer-peeling (DLP) algorithm is used to rapidly obtain the initial index modulation profiles for the superposition method. On account of the initially near-optimum index modulation profiles from the first step, the LMO <span class="hlt">optimization</span> algorithm shows fast convergence to the target reflection spectra in the second step and the design outcome still retains the advantage of easy fabrication.</p> <div class="credits"> <p class="dwt_author">Hsin, Chen-Wei</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">429</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51091370"> <span id="translatedtitle">Polymer properties on-line estimation for gas-phase polyethylene based on <span class="hlt">particle</span> <span class="hlt">filtering</span> joint estimation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Due to the lack of suitable on-line polymer property measurements, the control of multi-grade product quality in industrial polymerization reactors is difficult. In this article, a predictive model of polymer properties is deduced for industrial polyethylene process by combining the first principle model and the feature modeling scheme. Combining the extended Kalman <span class="hlt">filtering</span>, a method of design the <span class="hlt">particle</span> <span class="hlt">filtering</span></p> <div class="credits"> <p class="dwt_author">Zhong Zhao; Min Cui</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">430</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.obs-vlfr.fr/~claustre/fichiers%20PDF/Tassan_et%20al_JPR_00.pdf"> <span id="translatedtitle">Variability of the amplification factor of light absorption by <span class="hlt">filter</span>-retained aquatic <span class="hlt">particles</span> in the coastal environment</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The amplification of light absorption by aquatic <span class="hlt">particles</span> retained on glass-fiber <span class="hlt">filters</span>, the so-called b factor, has been measured for 29 stations located in the varying coastal environment of the northern basin of the Adriatic Sea. The spectral values of the optical density of <span class="hlt">particles</span> have been determined on glass-fiber <span class="hlt">filters</span> by the standard transmittance (T) method as well as</p> <div class="credits"> <p class="dwt_author">Stelvio Tassan; Giovanni Massimo Ferrari; Annick Bricaud; Marcel Babin</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">431</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/24336611"> <span id="translatedtitle">Prediction of Dimensionless Cutsize for Size?Fractionated Measurements of <span class="hlt">Particles</span> that Impact on a Sintered Stainless?Steel <span class="hlt">Filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This investigation experimentally studied the penetration curve of <span class="hlt">particles</span> that impact on a sintered stainless?steel <span class="hlt">filter</span> with various pore sizes, sampling flow rates and jet diameters. The penetration curves were compared to those with an aluminum foil substrate. Test data reveal that when the sintered stainless?steel <span class="hlt">filter</span> has larger pore sizes (100 µm or 40 µm), the <span class="hlt">particle</span> penetration, P(%), is lower</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">432</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/22824765"> <span id="translatedtitle">Catalytic activation of ceramic <span class="hlt">filter</span> elements for combined <span class="hlt">particle</span> separation, NO x removal and VOC total oxidation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The development of a catalytically active <span class="hlt">filter</span> element for combined <span class="hlt">particle</span> separation and NOx removal or VOC total oxidation, respectively, is presented. For NOx removal by selective catalytic reduction (SCR) a catalytic coating based on a TiO2–V2O5–WO3 catalyst system was developed on a ceramic <span class="hlt">filter</span> element. Different TiO2 sols of tailor-made mean <span class="hlt">particle</span> size between 40 and 190nm were prepared</p> <div class="credits"> <p class="dwt_author">Manfred Nacken; Steffen Heidenreich; Marius Hackel; Georg Schaub</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">433</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AIPC.1298....7R"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm and Ant Colony Approaches in Multiobjective <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The social behavior of groups of birds, ants, insects and fish has been used to develop evolutionary algorithms known as swarm intelligence techniques for solving <span class="hlt">optimization</span> problems. This work presents the development of strategies for the application of two of the popular swarm intelligence techniques, namely the <span class="hlt">particle</span> swarm and ant colony methods, for the solution of multiobjective <span class="hlt">optimization</span> problems. In a multiobjective <span class="hlt">optimization</span> problem, the objectives exhibit a conflicting nature and hence no design vector can minimize all the objectives simultaneously. The concept of Pareto-<span class="hlt">optimal</span> solution is used in finding a compromise solution. A modified cooperative game theory approach, in which each objective is associated with a different player, is used in this work. The applicability and computational efficiencies of the proposed techniques are demonstrated through several illustrative examples involving unconstrained and constrained problems with single and multiple objectives and continuous and mixed design variables. The present methodologies are expected to be useful for the solution of a variety of practical continuous and mixed <span class="hlt">optimization</span> problems involving single or multiple objectives with or without constraints.</p> <div class="credits"> <p class="dwt_author">Rao, S. S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">434</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=48142"> <span id="translatedtitle">USE OF AN INERT RADIOACTIVE <span class="hlt">PARTICLE</span> FOR MEASURING <span class="hlt">PARTICLE</span> ACCUMULATION BY <span class="hlt">FILTER</span>-FEEDING BIVALVE MOLLUSCS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">The use of an inert, radioactively labeled microsphere as a measure of <span class="hlt">particle</span> accumulation (filtration activity) by Mulinia lateralis (Say) and Mytilus edulis L. was evaluated. Bottom sediment plus temperature and salinity of the water were varied to induce changes in filtratio...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">435</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3773454"> <span id="translatedtitle">Discrete <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> with Scout <span class="hlt">Particles</span> for Library Materials Acquisition</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Materials acquisition is one of the critical challenges faced by academic libraries. This paper presents an integer programming model of the studied problem by considering how to select materials in order to maximize the average preference and the budget execution rate under some practical restrictions including departmental budget, limitation of the number of materials in each category and each language. To tackle the constrained problem, we propose a discrete <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (DPSO) with scout <span class="hlt">particles</span>, where each <span class="hlt">particle</span>, represented as a binary matrix, corresponds to a candidate solution to the problem. An initialization algorithm and a penalty function are designed to cope with the constraints, and the scout <span class="hlt">particles</span> are employed to enhance the exploration within the solution space. To demonstrate the effectiveness and efficiency of the proposed DPSO, a series of computational experiments are designed and conducted. The results are statistically analyzed, and it is evinced that the proposed DPSO is an effective approach for the studied problem.</p> <div class="credits"> <p class="dwt_author">Lin, Bertrand M. T.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">436</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/24072983"> <span id="translatedtitle">Discrete <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> with scout <span class="hlt">particles</span> for library materials acquisition.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Materials acquisition is one of the critical challenges faced by academic libraries. This paper presents an integer programming model of the studied problem by considering how to select materials in order to maximize the average preference and the budget execution rate under some practical restrictions including departmental budget, limitation of the number of materials in each category and each language. To tackle the constrained problem, we propose a discrete <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (DPSO) with scout <span class="hlt">particles</span>, where each <span class="hlt">particle</span>, represented as a binary matrix, corresponds to a candidate solution to the problem. An initialization algorithm and a penalty function are designed to cope with the constraints, and the scout <span class="hlt">particles</span> are employed to enhance the exploration within the solution space. To demonstrate the effectiveness and efficiency of the proposed DPSO, a series of computational experiments are designed and conducted. The results are statistically analyzed, and it is evinced that the proposed DPSO is an effective approach for the studied problem. PMID:24072983</p> <div class="credits"> <p class="dwt_author">Wu, Yi-Ling; Ho, Tsu-Feng; Shyu, Shyong Jian; Lin, Bertrand M T</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">437</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50192300"> <span id="translatedtitle">Computer diagnosis and tuning of microwave <span class="hlt">filters</span> using model-based parameter estimation and multi-level <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper describes an approach for the computer diagnosis and tuning of microwave <span class="hlt">filters</span> relying upon model-based parameter estimation and multi-level <span class="hlt">optimization</span>. This approach uses the reduced-order system and the effect of measurement noise is also considered. This approach can be applied to many classes of the <span class="hlt">filters</span>. Examples are presented to demonstrate its feasibility</p> <div class="credits"> <p class="dwt_author">Masoud Kahrizi; Safieddin Safavi-Naeini; Sujeet K. Chaudhuri</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">438</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFMGC51A0928O"> <span id="translatedtitle">Efficient Bayesian updating with PCE-based <span class="hlt">particle</span> <span class="hlt">filters</span> based on polynomial chaos expansion and CO2 storage</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Underground flow systems, such as oil or gas reservoirs and CO2 storage sites, are an important and challenging class of complex dynamic systems. Lacking information about distributed systems properties (such as porosity, permeability,...) leads to model uncertainties up to a level where quantification of uncertainties may become the dominant question in application tasks. History matching to past production data becomes an extremely important issue in order to improve the confidence of prediction. The accuracy of history matching depends on the quality of the established physical model (including, e.g. seismic, geological and hydrodynamic characteristics, fluid properties etc). The history matching procedure itself is very time consuming from the computational point of view. Even one single forward deterministic simulation may require parallel high-performance computing. This fact makes a brute-force non-linear <span class="hlt">optimization</span> approach not feasible, especially for large-scale simulations. We present a novel framework for history matching which takes into consideration the nonlinearity of the model and of inversion, and provides a cheap but highly accurate tool for reducing prediction uncertainty. We propose an advanced framework for history matching based on the polynomial chaos expansion (PCE). Our framework reduces complex reservoir models and consists of two main steps. In step one, the original model is projected onto a so-called integrative response surface via very recent PCE technique. This projection is totally non-intrusive (following a probabilistic collocation method) and <span class="hlt">optimally</span> constructed for available reservoir data at the prior stage of Bayesian updating. The integrative response surface keeps the nonlinearity of the initial model at high order and incorporates all suitable parameters, such as uncertain parameters (porosity, permeability etc.) and design or control variables (injection rate, depth etc.). Technically, the computational costs for 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 <span class="hlt">particle</span> <span class="hlt">filtering</span> on the integrative response surface constructed at step one. <span class="hlt">Particle</span> <span class="hlt">filtering</span> is a strong technique for Bayesian updating which takes into consideration the nonlinearity of inverse problem in history matching more accurately than Ensemble Kalman <span class="hlt">filter</span> 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.</p> <div class="credits"> <p class="dwt_author">Oladyshkin, S.; Class, H.; Helmig, R.; Nowak, W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">439</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23679548"> <span id="translatedtitle"><span class="hlt">Optimal</span> interpolation schemes for <span class="hlt">particle</span> tracking in turbulence.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">An important aspect in numerical simulations of <span class="hlt">particle</span>-laden turbulent flows is the interpolation of the flow field needed for the computation of the Lagrangian trajectories. The accuracy of the interpolation method has direct consequences for the acceleration spectrum of the fluid <span class="hlt">particles</span> and is therefore also important for the correct evaluation of the hydrodynamic forces for almost neutrally buoyant <span class="hlt">particles</span>, common in many environmental applications. In order to systematically choose the <span class="hlt">optimal</span> tradeoff between interpolation accuracy and computational cost we focus on comparing errors: the interpolation error is compared with the discretization error of the flow field. In this way one can prevent unnecessary computations and still retain the accuracy of the turbulent flow simulation. From the analysis a practical method is proposed that enables direct estimation of the interpolation and discretization error from the energy spectrum. The theory is validated by means of direct numerical simulations (DNS) of homogeneous, isotropic turbulence using a spectral code, where the trajectories of fluid tracers are computed using several interpolation methods. We show that B-spline interpolation has the best accuracy given the computational cost. Finally, the <span class="hlt">optimal</span> interpolation order for the different methods is shown as a function of the resolution of the DNS simulation. PMID:23679548</p> <div class="credits"> <p class="dwt_author">van Hinsberg, M A T; Boonkkamp, J H M ten Thije; Toschi, F; Clercx, H J H</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">440</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013PhRvE..87d3307V"> <span id="translatedtitle"><span class="hlt">Optimal</span> interpolation schemes for <span class="hlt">particle</span> tracking in turbulence</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">An important aspect in numerical simulations of <span class="hlt">particle</span>-laden turbulent flows is the interpolation of the flow field needed for the computation of the Lagrangian trajectories. The accuracy of the interpolation method has direct consequences for the acceleration spectrum of the fluid <span class="hlt">particles</span> and is therefore also important for the correct evaluation of the hydrodynamic forces for almost neutrally buoyant <span class="hlt">particles</span>, common in many environmental applications. In order to systematically choose the <span class="hlt">optimal</span> tradeoff between interpolation accuracy and computational cost we focus on comparing errors: the interpolation error is compared with the discretization error of the flow field. In this way one can prevent unnecessary computations and still retain the accuracy of the turbulent flow simulation. From the analysis a practical method is proposed that enables direct estimation of the interpolation and discretization error from the energy spectrum. The theory is validated by means of direct numerical simulations (DNS) of homogeneous, isotropic turbulence using a spectral code, where the trajectories of fluid tracers are computed using several interpolation methods. We show that B-spline interpolation has the best accuracy given the computational cost. Finally, the <span class="hlt">optimal</span> interpolation order for the different methods is shown as a function of the resolution of the DNS simulation.</p> <div class="credits"> <p class="dwt_author">van Hinsberg, M. A. T.; Boonkkamp, J. H. M. ten Thije; Toschi, F.; Clercx, H. J. H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_21");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_22");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' href="#">4</a> <a onClick='return showDiv("page_5");' href="#">5</a> <a onClick='return showDiv("page_6");' href="#">6</a> <a onClick='return showDiv("page_7");' href="#">7</a> <a onClick='return showDiv("page_8");' href="#">8</a> <a onClick='return showDiv("page_9");' href="#">9</a> <a onClick='return showDiv("page_10");' href="#">10</a> <a onClick='return showDiv("page_11");' href="#">11</a> <a onClick='return showDiv("page_12");' href="#">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a onClick='return showDiv("page_16");' href="#">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a style="font-weight: bold;">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_24");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">441</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22240558"> <span id="translatedtitle"><span class="hlt">Optimization</span> of a <span class="hlt">filter</span>-lysis protocol to purify rat testicular homogenates for automated spermatid counting.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Quantifying testicular homogenization-resistant spermatid heads (HRSH) is a powerful indicator of spermatogenesis. These counts have traditionally been performed manually using a hemocytometer, but this method can be time consuming and biased. We aimed to develop a protocol to reduce debris for the application of automated counting, which would allow for efficient and unbiased quantification of rat HRSH. We developed a <span class="hlt">filter</span>-lysis protocol that effectively removes debris from rat testicular homogenates. After <span class="hlt">filtering</span> and lysing the homogenates, we found no statistical differences between manual (classic and <span class="hlt">filter</span>-lysis) and automated (<span class="hlt">filter</span>-lysis) counts using 1-way analysis of variance with Bonferroni's multiple comparison test. In addition, Pearson's correlation coefficients were calculated to compare the counting methods, and there was a strong correlation between the classic manual counts and the <span class="hlt">filter</span>-lysis manual (r = 0.85, P = .002) and the <span class="hlt">filter</span>-lysis automated (r = 0.89, P = .0005) counts. We also tested the utility of the automated method in a low-dose exposure model known to decrease HRSH. Adult Fischer 344 rats exposed to 0.33% 2,5-hexanedione in the drinking water for 12 weeks demonstrated decreased body (P = .02) and testes (P = .002) weights. In addition, there was a significant reduction in the number of HRSH per testis (P = .002) when compared to controls. A filterlysis protocol was <span class="hlt">optimized</span> to purify rat testicular homogenates for automated HRSH counts. Automated counting systems yield unbiased data and can be applied to detect changes in the testis after low-dose toxicant exposure. PMID:22240558</p> <div class="credits"> <p class="dwt_author">Pacheco, Sara E; Anderson, Linnea M; Boekelheide, Kim</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-12</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">442</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/g733t4644n3051m6.pdf"> <span id="translatedtitle">Mixed-State <span class="hlt">Particle</span> <span class="hlt">Filtering</span> for Simultaneous Tracking and Re-identification in Non-overlapping Camera Networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a This article presents a novel approach to person tracking within large-scale indoor environments monitored by non-overlapping\\u000a field-of-view camera networks. We address the image-based tracking problem with distributed <span class="hlt">particle</span> <span class="hlt">filters</span> using a hierarchical\\u000a color model. The novelty of our approach resides in the embedding of an already-seen-people database in the <span class="hlt">particle</span> <span class="hlt">filter</span>\\u000a framework. Doing so, the <span class="hlt">filter</span> performs not only position</p> <div class="credits"> <p class="dwt_author">Boris Meden; Patrick Sayd; Frédéric Lerasle</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">443</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3417150"> <span id="translatedtitle">Alignment of 3-D Optical Coherence Tomography Scans to Correct Eye Movement Using a <span class="hlt">Particle</span> <span class="hlt">Filtering</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Eye movement artifacts occurring during 3-D optical coherence tomography (OCT) scanning is a well-recognized problem that may adversely affect image analysis and interpretation. A <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithm is presented in this paper to correct motion in a 3-D dataset by considering eye movement as a target tracking problem in a dynamic system. The proposed <span class="hlt">particle</span> <span class="hlt">filtering</span> algorithm is an independent 3-D alignment approach, which does not rely on any reference image. 3-D OCT data is considered as a dynamic system, while the location of each A-scan is represented by the state space. A <span class="hlt">particle</span> set is used to approximate the probability density of the state in the dynamic system. The state of the system is updated frame by frame to detect A-scan movement. The proposed method was applied on both simulated data for objective evaluation and experimental data for subjective evaluation. The sensitivity and specificity of the x-movement detection were 98.85% and 99.43%, respectively, in the simulated data. For the experimental data (74 3-D OCT images), all the images were improved after z-alignment, while 81.1% images were improved after x-alignment. The proposed algorithm is an efficient way to align 3-D OCT volume data and correct the eye movement without using references.</p> <div class="credits"> <p class="dwt_author">Xu, Juan; Ishikawa, Hiroshi; Wollstein, Gadi; Kagemann, Larry; Schuman, Joel S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">444</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22255310"> <span id="translatedtitle">Ordering samples along environmental gradients using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Due to the enormity of the solution space for sequential ordering problems, non-exhaustive heuristic techniques have been the focus of many research efforts, particularly in the field of operations research. In this paper, we outline an ecologically motivated problem in which environmental samples have been obtained along a gradient (e.g. pH), with which we desire to recover the sample order. Not only do we model the problem for the benefit of an <span class="hlt">optimization</span> approach, we also incorporate hybrid <span class="hlt">particle</span> swarm techniques to address the problem. The described method is implemented on a real dataset from which 22 biological samples were obtained along a pH gradient. We show that we are able to approach the <span class="hlt">optimal</span> permutation of samples by evaluating only approximately 5000 solutions--infinitesimally smaller than the 22! possible solutions. PMID:22255310</p> <div class="credits"> <p class="dwt_author">Essinger, Steven; Polikar, Robi; Rosen, Gail</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">445</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22254916"> <span id="translatedtitle">Binary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> for feature selection in detection of infants with hypothyroidism.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Hypothyroidism in infants is caused by the insufficient production of hormones by the thyroid gland. Due to stress in the chest cavity as a result of the enlarged liver, their cry signals are unique and can be distinguished from the healthy infant cries. This study investigates the effect of feature selection with Binary <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> on the performance of MultiLayer Perceptron classifier in discriminating between the healthy infants and infants with hypothyroidism from their cry signals. The feature extraction process was performed on the Mel Frequency Cepstral coefficients. Performance of the MLP classifier was examined by varying the number of coefficients. It was found that the BPSO enhances the classification accuracy while reducing the computation load of the MLP classifier. The highest classification accuracy of 99.65% was achieved for the MLP classifier, with 36 <span class="hlt">filter</span> banks, 5 hidden nodes and 11 BPS optimised MFC coefficients. PMID:22254916</p> <div class="credits"> <p class="dwt_author">Zabidi, A; Khuan, L Y; Mansor, W; Yassin, I M; Sahak, R</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">446</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011JPhCS.278a2033C"> <span id="translatedtitle">Photothermal depth profiling for multilayered Structures by <span class="hlt">particle</span> swarm <span class="hlt">optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper presents a method to reconstruct thermal conductivity depth profile of a layered medium using noisy photothermal data. The method tries to obtain an accurate reconstruction of discontinuous profile using <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) algorithm and total variation (TV) regularization. The reconstructions of different thermal conductivity profiles have been tested on simulated photothermal data. The simulation results show that the method can find accurately the locations of discontinuities, and the reconstructed profiles are in agreement with the original ones. Moreover, the results also show the method has good robustness and anti-noise capability.</p> <div class="credits"> <p class="dwt_author">Chen, Z. J.; Fang, J. W.; Zhang, S. Y.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">447</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/956894"> <span id="translatedtitle"><span class="hlt">Optimization</span> of nanoparticle core size for magnetic <span class="hlt">particle</span> imaging</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Magnetic <span class="hlt">Particle</span> Imaging (MPI) is a powerful new diagnostic visualization platform designed for measuring the amount and location of superparamagnetic nanoscale molecular probes (NMPs) in biological tissues. Promising initial results indicate that MPI can be extremely sensitive and fast, with good spatial resolution for imaging human patients or live animals. Here, we present modeling results that show how MPI sensitivity and spatial resolution both depend on NMP-core physical properties, and how MPI performance can be effectively <span class="hlt">optimized</span> through rational core design. Monodisperse magnetite cores are attractive since they are readily produced with a biocompatible coating and controllable size that facilitates quantitative imaging.</p> <div class="credits"> <p class="dwt_author">Ferguson, Matthew R.; Minard, Kevin R.; Krishnan, Kannan M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">448</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010LNCS.6466..506Z"> <span id="translatedtitle"><span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> with Watts-Strogatz Model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span> (PSO) is a popular swarm intelligent methodology by simulating the animal social behaviors. Recent study shows that this type of social behaviors is a complex system, however, for most variants of PSO, all individuals lie in a fixed topology, and conflict this natural phenomenon. Therefore, in this paper, a new variant of PSO combined with Watts-Strogatz small-world topology model, called WSPSO, is proposed. In WSPSO, the topology is changed according to Watts-Strogatz rules within the whole evolutionary process. Simulation results show the proposed algorithm is effective and efficient.</p> <div class="credits"> <p class="dwt_author">Zhu, Zhuanghua</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">449</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010IEITC..91.1636Z"> <span id="translatedtitle">Multiuser Detection for Asynchronous Multicarrier CDMA Using <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Due to the computational complexity of the optimum maximum likelihood detector (OMD) growing exponentially with the number of users, suboptimum techniques have received significant attention. We have proposed the <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) for the multiuser detection (MUD) in asynchronous multicarrier code division multiple access (MC-CDMA) system. The performance of PSO based MUD is near optimum, while its computational complexity is far less than OMD. Performance of PSO-MUD has also been shown to be better than that of genetic algorithm based MUD (GA-MUD) at practical SNR.</p> <div class="credits"> <p class="dwt_author">Zubair, Muhammad; Choudhry, Muhammad A. S.; Naveed, Aqdas; Qureshi, Ijaz Mansoor</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">450</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42329244"> <span id="translatedtitle">“Worst Case” Aerosol Testing Parameters: I. Sodium Chloride and Dioctyl Phthalate Aerosol <span class="hlt">Filter</span> Efficiency as a Function of <span class="hlt">Particle</span> Size and Flow Rate</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The efficiency of <span class="hlt">filter</span> media is dependent on the characteristics of the challenge aerosol and the <span class="hlt">filter</span>'s construction. Challenge aerosol Parameters, Such as <span class="hlt">Particle</span> Size, density, shape, electrical charge, and flow rate, are influential in determining the <span class="hlt">filter</span>'s efficiency. In this regard, a so-called “worst case” set of conditions has been proposed for testing respirator <span class="hlt">filter</span> efficiency in order to</p> <div class="credits"> <p class="dwt_author">GREGORY A. STEVENS; ERNEST S. MOYER</p> <p class="dwt_publisher"></p> <p class="publishDate">1989-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">451</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21032643"> <span id="translatedtitle">State to State and Charged <span class="hlt">Particle</span> Kinetic Modeling of Time <span class="hlt">Filtering</span> and Cs Addition</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We present here an account on the progress of kinetic simulation of non equilibrium plasmas in conditions of interest for negative ion production by using the 1D Bari code for hydrogen plasma simulation. The model includes the state to state kinetics of the vibrational level population of hydrogen molecules, plus a PIC/MCC module for the multispecies dynamics of charged <span class="hlt">particles</span>. In particular we present new results for the modeling of two issues of great interest: the time <span class="hlt">filtering</span> and the Cs addition via surface coverage.</p> <div class="credits"> <p class="dwt_author">Capitelli, M.; Gorse, C.; Longo, S. [Chemistry Department, Bari University, Bari (Italy); IMIP-CNR, Sezione Territoriale di Bari, Bari (Italy); Diomede, P.; Pagano, D. [Chemistry Department, Bari University, Bari (Italy)</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-08-10</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">452</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007AIPC..925...11C"> <span id="translatedtitle">State to State and Charged <span class="hlt">Particle</span> Kinetic Modeling of Time <span class="hlt">Filtering</span> and Cs Addition</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present here an account on the progress of kinetic simulation of non equilibrium plasmas in conditions of interest for negative ion production by using the 1D Bari code for hydrogen plasma simulation. The model includes the state to state kinetics of the vibrational level population of hydrogen molecules, plus a PIC/MCC module for the multispecies dynamics of charged <span class="hlt">particles</span>. In particular we present new results for the modeling of two issues of great interest: the time <span class="hlt">filtering</span> and the Cs addition via surface coverage.</p> <div class="credits"> <p class="dwt_author">Capitelli, M.; Diomede, P.; Gorse, C.; Longo, S.; Pagano, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">453</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2888536"> <span id="translatedtitle">Actin Filament Tracking Based on <span class="hlt">Particle</span> <span class="hlt">Filters</span> and Stretching Open Active Contour Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">We introduce a novel algorithm for actin filament tracking and elongation measurement. <span class="hlt">Particle</span> <span class="hlt">Filters</span> (PF) and Stretching Open Active Contours (SOAC) work cooperatively to simplify the modeling of PF in a one-dimensional state space while naturally integrating filament body constraints to tip estimation. Existing microtubule (MT) tracking methods track either MT tips or entire bodies in high-dimensional state spaces. In contrast, our algorithm reduces the PF state spaces to one-dimensional spaces by tracking filament bodies using SOAC and probabilistically estimating tip locations along the curve length of SOACs. Experimental evaluation on TIRFM image sequences with very low SNRs demonstrates the accuracy and robustness of the proposed approach.</p> <div class="credits"> <p class="dwt_author">Li, Hongsheng; Shen, Tian; Vavylonis, Dimitrios; Huang, Xiaolei</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">454</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009OptEn..48h0501L"> <span id="translatedtitle"><span class="hlt">Optimal</span> design of single resonant and ultrabroadband long-period fiber grating <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We propose a spectral flat-top, single resonant, and ultrabroadband-more than 180 nm in a -20-dB bandwidth-long-period fiber grating (LPG) <span class="hlt">filter</span>. The ultrabroadband LPG is based on a thin cladding layer LPG synthesized by the Lagrange multiplier <span class="hlt">optimization</span> (LMO) algorithm. As the bandwidth and resonant spectra cover a very wide band, both material dispersion and waveguide dispersion were included in the calculations of the LMO method. To the best of our knowledge, the bandwidth of the designed flat-top LPG <span class="hlt">filter</span> in the -20-dB coupling is the broadest currently existing in the literature. Such designed LPG devices can be very useful for a variety of applications in broadband optical communication systems.</p> <div class="credits"> <p class="dwt_author">Lee, Cheng-Ling; Han, Pin</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">455</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010LNCS.6466..639S"> <span id="translatedtitle">Security Constrained <span class="hlt">Optimal</span> Power Flow with FACTS Devices Using Modified <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper presents new computationally efficient improved <span class="hlt">Particle</span> Swarm algorithms for solving Security Constrained <span class="hlt">Optimal</span> Power Flow (SCOPF) in power systems with the inclusion of FACTS devices. The proposed algorithms are developed based on the combined application of Gaussian and Cauchy Probability distribution functions incorporated in <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> (PSO). The power flow algorithm with the presence of Static Var Compensator (SVC) Thyristor Controlled Series Capacitor (TCSC) and Unified Power Flow Controller (UPFC), has been formulated and solved. The proposed algorithms are tested on standard IEEE 30-bus system. The analysis using PSO and modified PSO reveals that the proposed algorithms are relatively simple, efficient, reliable and suitable for real-time applications. And these algorithms can provide accurate solution with fast convergence and have the potential to be applied to other power engineering problems.</p> <div class="credits"> <p class="dwt_author">Somasundaram, P.; Muthuselvan, N. B.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">456</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009SPIE.7495E..39C"> <span id="translatedtitle">Fusion of cues for occlusion handling in tracking with <span class="hlt">particle</span> <span class="hlt">filters</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this paper, a new approach is presented for tracking object accurately and steadily when the target encountering occlusion in video sequences. First, we use Canny algorithm to extract the edges of the object. The edge pixels are classified as foreground/background for each frame using background subtraction. On the next stage, a set of cues including a motion model, an elliptical shape model, a spatial-color mixture of Gaussians appearance model, and an edge orientation histogram model is fused in a principled manner. All these cues could be modeled by a data likelihood function; Then, a <span class="hlt">particle</span> <span class="hlt">filter</span> algorithm is used for tracking and the <span class="hlt">particles</span> are re-sampled based on the fusion of the cues. Result form simulations and experiments with real video sequences show the effectiveness of our approach for tracking people under occlusion conditions.</p> <div class="credits"> <p class="dwt_author">Chen, Xiaobo; Men, Aidong; Pan, Xinting; Yang, Bo; Wang, Wei</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">457</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012JPhCS.385a2012W"> <span id="translatedtitle">GPU-Based Asynchronous Global <span class="hlt">Optimization</span> with <span class="hlt">Particle</span> Swarm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The recent upsurge in research into general-purpose applications for graphics processing units (GPUs) has made low cost high-performance computing increasingly more accessible. Many global <span class="hlt">optimization</span> algorithms that have previously benefited from parallel computation are now poised to take advantage of general-purpose GPU computing as well. In this paper, a global parallel asynchronous <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (PSO) approach is employed to solve three relatively complex, realistic parameter estimation problems in which each processor performs significant computation. Although PSO is readily parallelizable, memory bandwidth limitations with GPUs must be addressed, which is accomplished by minimizing communication among individual population members though asynchronous operations. The effect of asynchronous PSO on robustness and efficiency is assessed as a function of problem and population size. Experiments were performed with different population sizes on NVIDIA GPUs and on single-core CPUs. Results for successful trials exhibit marked speedup increases with the population size, indicating that more <span class="hlt">particles</span> may be used to improve algorithm robustness while maintaining nearly constant time. This work also suggests that asynchronous operations on the GPU may be viable in stochastic population-based algorithms to increase efficiency without sacrificing the quality of the solutions.</p> <div class="credits"> <p class="dwt_author">Wachowiak, M. P.; Lambe Foster, A. E.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">458</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=131206"> <span id="translatedtitle">MODELING REFLECTANCE AND TRANSMITTANCE OF QUARTZ-FIBER <span class="hlt">FILTER</span> SAMPLES CONTAINING ELEMENTAL CARBON <span class="hlt">PARTICLES</span>: IMPLICATIONS FOR THERMAL/OPTICAL ANALYSIS. (R831086)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">A radiative transfer scheme that considers absorption, scattering, and distribution of light-absorbing elemental carbon (EC) <span class="hlt">particles</span> collected on a quartz-fiber <span class="hlt">filter</span> was developed to explain simultaneous <span class="hlt">filter</span> reflectance and transmittance observations prior to and during...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">459</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/6357212"> <span id="translatedtitle">A prior knowledge based <span class="hlt">optimal</span> Wiener <span class="hlt">filtering</span> approach to ultrasonic scattering amplitude estimation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Advances in component life prediction techniques have prompted increased interest in quantitative nondestructive characterization of flaws in engineering materials. Flaw characterization techniques utilize a signature from the flaw. In ultrasonics, the signature is estimated from noise-corrupted experimental measurements of the scattered acoustic wave field resulting from insonification of the flaw. Estimating the flaw's signature involves removing the effects of the measurement system in the presence of noise. In the frequency domain, the flaw's signature is called a scattering amplitude. The purpose of this work is to evaluate an <span class="hlt">optimal</span> Wiener <span class="hlt">filtering</span> approach to scattering amplitude estimation.</p> <div class="credits"> <p class="dwt_author">Neal, S.P.</p> <p class="dwt_publisher"></p> <p class="publishDate">1989-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">460</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/46626895"> <span id="translatedtitle">An <span class="hlt">optimized</span> solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman <span class="hlt">filter</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve <span class="hlt">optimal</span> system performances. This paper explores the use of the Kalman <span class="hlt">filter</span> to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find <span class="hlt">optimal</span> solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in</p> <div class="credits"> <p class="dwt_author">Pece V. Gorsevski; Piotr Jankowski</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_22");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return 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href="#">11</a> <a onClick='return showDiv("page_12");' href="#">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a onClick='return showDiv("page_16");' href="#">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a style="font-weight: bold;">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_25");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">461</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13983477"> <span id="translatedtitle">Designing airfoils using a reference point based evolutionary many-objective <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, we illustrate the use of a reference point based many-objective <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm to <span class="hlt">optimize</span> low-speed airfoil aerodynamic designs. Our framework combines a flexible airfoil parameterization scheme and a computational flow solver in the evaluation of <span class="hlt">particles</span>. Each <span class="hlt">particle</span>, which represents a set of decision variables, is passed through this framework to construct and evaluate the</p> <div class="credits"> <p class="dwt_author">Upali K. Wickramasinghe; Robert Carrese; Xiaodong Li</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">462</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50461323"> <span id="translatedtitle">Fuzzy logic controlled <span class="hlt">particle</span> swarm for reactive power <span class="hlt">optimization</span> considering voltage stability</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents the application of a fuzzy logic controlled <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (FLCPSO) to reactive power and voltage control (Volt\\/VAR control or VVC) considering voltage stability. An improved <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> with three fuzzy controllers based on some heuristics is proposed to adaptively adjust the parameters of PSO, such as the inertia weight and learning factors, during the <span class="hlt">optimization</span></p> <div class="credits"> <p class="dwt_author">W. Zhang; Y. Liu</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">463</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50461830"> <span id="translatedtitle">A Novel Binary <span class="hlt">Particle</span> Swarm <span class="hlt">Optimization</span> Method Using Artificial Immune System</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Particle</span> swarm <span class="hlt">optimization</span>, a nature-inspired evolutionary algorithm, has been successful in solving a wide range of real value <span class="hlt">optimization</span> problems. However, little attempts have been made to extend it to discrete problems. In this paper, a new binary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> method based on the theory of immunity in biology is proposed. In spite of the simplicity of the technique,</p> <div class="credits"> <p class="dwt_author">Farzaneh Afshinmanesh; Alireza Marandi; Ashkan Rahimi-Kian</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">464</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51024274"> <span id="translatedtitle"><span class="hlt">Optimization</span> of space domes using modified binary <span class="hlt">particle</span> swarm method (Modified BPSO)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, the <span class="hlt">optimal</span> sizing design of space domes with discrete variables is studied using modified binary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (Modified BPSO). The objective function considered is the total weight of the structure subjected to material and performance constraints in the form of stress and deflection limits. Binary <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (BPSO) is cooperative, population based, global search, swarm</p> <div class="credits"> <p class="dwt_author">Ghader Bagheri; Asghar Rasouli</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">465</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3773995"> <span id="translatedtitle">Convergence Analysis of <span class="hlt">Particle</span> Swarm <span class="hlt">Optimizer</span> and Its Improved Algorithm Based on Velocity Differential Evolution</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">This paper presents an analysis of the relationship of <span class="hlt">particle</span> velocity and convergence of the <span class="hlt">particle</span> swarm <span class="hlt">optimization</span>. Its premature convergence is due to the decrease of <span class="hlt">particle</span> velocity in search space that leads to a total implosion and ultimately fitness stagnation of the swarm. An improved algorithm which introduces a velocity differential evolution (DE) strategy for the hierarchical <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (H-PSO) is proposed to improve its performance. The DE is employed to regulate the <span class="hlt">particle</span> velocity rather than the traditional <span class="hlt">particle</span> position in case that the <span class="hlt">optimal</span> result has not improved after several iterations. The benchmark functions will be illustrated to demonstrate the effectiveness of the proposed method.</p> <div class="credits"> <p class="dwt_author">Luo, Wenguang; Li, Zhenqiang</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">466</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011JNEng...8b5012S"> <span id="translatedtitle">CSP patches: an ensemble of <span class="hlt">optimized</span> spatial <span class="hlt">filters</span>. An evaluation study</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Laplacian <span class="hlt">filters</span> are widely used in neuroscience. In the context of brain-computer interfacing, they might be preferred to data-driven approaches such as common spatial patterns (CSP) in a variety of scenarios such as, e.g., when no or few user data are available or a calibration session with a multi-channel recording is not possible, which is the case in various applications. In this paper we propose the use of an ensemble of local CSP patches (CSPP) which can be considered as a compromise between Laplacian <span class="hlt">filters</span> and CSP. Our CSPP only needs a very small number of trials to be <span class="hlt">optimized</span> and significantly outperforms Laplacian <span class="hlt">filters</span> in all settings studied. Additionally, CSPP also outperforms multi-channel CSP and a regularized version of CSP even when only very few calibration data are available, acting as a CSP regularizer without the need of additional hyperparameters and at a very low cost: 2-5 min of data recording, i.e. ten times less than CSP.</p> <div class="credits"> <p class="dwt_author">Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">467</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50891088"> <span id="translatedtitle">A novel weight-improved <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> algorithm for <span class="hlt">optimal</span> power flow and economic load dispatch problems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The <span class="hlt">optimization</span> problems of <span class="hlt">optimal</span> power flow (OPF) and the economic load dispatch (ELD) with valve-point effects in power systems are recently solved by some types of artificial intelligent (AI) algorithms. In this paper, based on improving the function of weight parameters, we present a novel weight-improved <span class="hlt">particle</span> swarm <span class="hlt">optimization</span> (WIPSO) method for computing two above problems. To evaluate the</p> <div class="credits"> <p class="dwt_author">PhanTu Vu; DinhLuong Le; NgocDieu Vo; Josef Tlusty</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">468</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/5808584"> <span id="translatedtitle">Temporal and spatial <span class="hlt">filtering</span> remedies for dispersion in electromagnetic <span class="hlt">particle</span> codes</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">There has been considerable interest over the last decade in the physics of intense electromagnetic signals in plasmas -- much of it in the context of laser fusion and pulsar astrophysics. Simulations of these phenomena test the limits of <span class="hlt">particle</span> simulation and in particular the standard leapfrog algorithm for advancing the electromagnetic fields. As shock fronts and sheaths develop within the plasma in response to intense electromagnetic waves, numerical dispersion in trinsic to the leapfrog algorithm can cause unphysical ripples to appear in the field solution which can interact with <span class="hlt">particles</span>. Fourier analysis of the leapfrog scheme in 1D yields the dispersion relation for a Courant number /nu/ /triple bond/ c/Delta/t//Delta/x = 0.5. As we can see, the phase velocity of the modes falls off the light line at high k/Delta/x. Thus modes that are poorly resolved will tend to disperse and trail the main pulse as ripples. There are several approaches to finding a remedy for these ripples. High-order finite difference methods can be considerably less dispersive. Also, improving resolution can move the physics to lower k/Delta/x where the dispersion is less. Often these options are not available, either because of difficulty in implementation or because computer resources are insufficient. This leaves <span class="hlt">filtering</span> as the main option, with two routes to schemes that remove high k/Delta/x modes -- temporal and spatial <span class="hlt">filtering</span>. In this paper we present techniques to remove dispersion from <span class="hlt">particle</span> simulations using both methods. 5 refs., 1 fig.</p> <div class="credits"> <p class="dwt_author">Rambo, P.W.; Ambrosiano, J.; Friedman, A.; Nielsen, D.E. Jr.</p> <p class="dwt_publisher"></p> <p class="publishDate">1989-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">469</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/lin