An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

Cat Swarm Optimization algorithm for optimal linear phase FIR filter design.

PubMed

Saha, Suman Kumar; Ghoshal, Sakti Prasad; Kar, Rajib; Mandal, Durbadal

2013-11-01

In this paper a new meta-heuristic search method, called Cat Swarm Optimization (CSO) algorithm is applied to determine the best optimal impulse response coefficients of FIR low pass, high pass, band pass and band stop filters, trying to meet the respective ideal frequency response characteristics. CSO is generated by observing the behaviour of cats and composed of two sub-models. In CSO, one can decide how many cats are used in the iteration. Every cat has its' own position composed of M dimensions, velocities for each dimension, a fitness value which represents the accommodation of the cat to the fitness function, and a flag to identify whether the cat is in seeking mode or tracing mode. The final solution would be the best position of one of the cats. CSO keeps the best solution until it reaches the end of the iteration. The results of the proposed CSO based approach have been compared to those of other well-known optimization methods such as Real Coded Genetic Algorithm (RGA), standard Particle Swarm Optimization (PSO) and Differential Evolution (DE). The CSO based results confirm the superiority of the proposed CSO for solving FIR filter design problems. The performances of the CSO based designed FIR filters have proven to be superior as compared to those obtained by RGA, conventional PSO and DE. The simulation results also demonstrate that the CSO is the best optimizer among other relevant techniques, not only in the convergence speed but also in the optimal performances of the designed filters. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal frequency domain textural edge detection filter

NASA Technical Reports Server (NTRS)

Townsend, J. K.; Shanmugan, K. S.; Frost, V. S.

1985-01-01

An optimal frequency domain textural edge detection filter is developed and its performance evaluated. For the given model and filter bandwidth, the filter maximizes the amount of output image energy placed within a specified resolution interval centered on the textural edge. Filter derivation is based on relating textural edge detection to tonal edge detection via the complex low-pass equivalent representation of narrowband bandpass signals and systems. The filter is specified in terms of the prolate spheroidal wave functions translated in frequency. Performance is evaluated using the asymptotic approximation version of the filter. This evaluation demonstrates satisfactory filter performance for ideal and nonideal textures. In addition, the filter can be adjusted to detect textural edges in noisy images at the expense of edge resolution.

GaN nanostructure design for optimal dislocation filtering

NASA Astrophysics Data System (ADS)

Liang, Zhiwen; Colby, Robert; Wildeson, Isaac H.; Ewoldt, David A.; Sands, Timothy D.; Stach, Eric A.; García, R. Edwin

2010-10-01

The effect of image forces in GaN pyramidal nanorod structures is investigated to develop dislocation-free light emitting diodes (LEDs). A model based on the eigenstrain method and nonlocal stress is developed to demonstrate that the pyramidal nanorod efficiently ejects dislocations out of the structure. Two possible regimes of filtering behavior are found: (1) cap-dominated and (2) base-dominated. The cap-dominated regime is shown to be the more effective filtering mechanism. Optimal ranges of fabrication parameters that favor a dislocation-free LED are predicted and corroborated by resorting to available experimental evidence. The filtering probability is summarized as a function of practical processing parameters: the nanorod radius and height. The results suggest an optimal nanorod geometry with a radius of ˜50b (26 nm) and a height of ˜125b (65 nm), in which b is the magnitude of the Burgers vector for the GaN system studied. A filtering probability of greater than 95% is predicted for the optimal geometry.

Optimization of In-Cylinder Pressure Filter for Engine Research

DTIC Science & Technology

2017-06-01

ARL-TR-8034 ● JUN 2017 US Army Research Laboratory Optimization of In-Cylinder Pressure Filter for Engine Research by Kenneth...Laboratory Optimization of In-Cylinder Pressure Filter for Engine Research by Kenneth S Kim, Michael T Szedlmayer, Kurt M Kruger, and Chol-Bum M...

A Low Cost Structurally Optimized Design for Diverse Filter Types

PubMed Central

Kazmi, Majida; Aziz, Arshad; Akhtar, Pervez; Ikram, Nassar

2016-01-01

A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environment. Thus it calls for optimized solutions. Mostly the optimization of these filters are based on exploiting structural properties. A common shortcoming of all previously reported optimized approaches is their restricted applicability only for a specific filter type. These narrow scoped solutions completely disregard the versatility attribute of advanced image processing applications and in turn offset their effectiveness while implementing a complete application. This paper presents an efficient framework which exploits the structural properties of 2D-filters for effectually reducing its computational cost along with an added advantage of versatility for supporting diverse filter types. A composite symmetric filter structure is introduced which exploits the identities of quadrant and circular T-symmetries in two distinct filter regions simultaneously. These T-symmetries effectually reduce the number of filter coefficients and consequently its multipliers count. The proposed framework at the same time empowers this composite filter structure with additional capabilities of realizing all of its Ψ-symmetry based subtypes and also its special asymmetric filters case. The two-fold optimized framework thus reduces filter computational cost up to 75% as compared to the conventional approach as well as its versatility attribute not only supports diverse filter types but also offers further cost reduction via resource sharing for sequential implementation of diversified image

Generalized Optimal-State-Constraint Extended Kalman Filter (OSC-EKF)

DTIC Science & Technology

2017-02-01

ARL-TR-7948• FEB 2017 US Army Research Laboratory GeneralizedOptimal-State-Constraint ExtendedKalman Filter (OSC-EKF) by James M Maley, Kevin...originator. ARL-TR-7948• FEB 2017 US Army Research Laboratory GeneralizedOptimal-State-Constraint ExtendedKalman Filter (OSC-EKF) by James M Maley Weapons and...

Optimal design of active EMC filters

NASA Astrophysics Data System (ADS)

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

2013-07-01

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.

Optimal Filter Estimation for Lucas-Kanade Optical Flow

PubMed Central

Sharmin, Nusrat; Brad, Remus

2012-01-01

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-filtering 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, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filtering approach as a pre-processing step for the Lucas-Kanade pyramidal optical flow algorithm. Based on a study of different types of filtering methods and applied on the Iterative Refined Lucas-Kanade, we have concluded on the best filtering practice. As the Gaussian smoothing filter 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.

On the ``optimal'' spatial distribution and directional anisotropy of the filter-width and grid-resolution in large eddy simulation

NASA Astrophysics Data System (ADS)

Toosi, Siavash; Larsson, Johan

2017-11-01

The accuracy of an LES depends directly on the accuracy of the resolved part of the turbulence. The continuing increase in computational power enables the application of LES to increasingly complex flow problems for which the LES community lacks the experience of knowing what the ``optimal'' or even an ``acceptable'' grid (or equivalently filter-width distribution) is. The goal of this work is to introduce a systematic approach to finding the ``optimal'' grid/filter-width distribution and their ``optimal'' anisotropy. The method is tested first on the turbulent channel flow, mainly to see if it is able to predict the right anisotropy of the filter/grid, and then on the more complicated case of flow over a backward-facing step, to test its ability to predict the right distribution and anisotropy of the filter/grid simultaneously, hence leading to a converged solution. This work has been supported by the Naval Air Warfare Center Aircraft Division at Pax River, MD, under contract N00421132M021. Computing time has been provided by the University of Maryland supercomputing resources (http://hpcc.umd.edu).

Optimal nonlinear filtering using the finite-volume method

NASA Astrophysics Data System (ADS)

Fox, Colin; Morrison, Malcolm E. K.; Norton, Richard A.; Molteno, Timothy C. A.

2018-01-01

Optimal sequential inference, or filtering, for the state of a deterministic dynamical system requires simulation of the Frobenius-Perron operator, that can be formulated as the solution of a continuity equation. For low-dimensional, smooth systems, the finite-volume numerical method provides a solution that conserves probability and gives estimates that converge to the optimal continuous-time values, while a Courant-Friedrichs-Lewy-type condition assures that intermediate discretized solutions remain positive density functions. This method is demonstrated in an example of nonlinear filtering for the state of a simple pendulum, with comparison to results using the unscented Kalman filter, and for a case where rank-deficient observations lead to multimodal probability distributions.

Optimal Recursive Digital Filters for Active Bending Stabilization

NASA Technical Reports Server (NTRS)

Orr, Jeb S.

2013-01-01

In the design of flight control systems for large flexible boosters, it is common practice to utilize active feedback control of the first lateral structural bending mode so as to suppress transients and reduce gust loading. Typically, active stabilization or phase stabilization is achieved by carefully shaping the loop transfer function in the frequency domain via the use of compensating filters combined with the frequency response characteristics of the nozzle/actuator system. In this paper we present a new approach for parameterizing and determining optimal low-order recursive linear digital filters so as to satisfy phase shaping constraints for bending and sloshing dynamics while simultaneously maximizing attenuation in other frequency bands of interest, e.g. near higher frequency parasitic structural modes. By parameterizing the filter directly in the z-plane with certain restrictions, the search space of candidate filter designs that satisfy the constraints is restricted to stable, minimum phase recursive low-pass filters with well-conditioned coefficients. Combined with optimal output feedback blending from multiple rate gyros, the present approach enables rapid and robust parametrization of autopilot bending filters to attain flight control performance objectives. Numerical results are presented that illustrate the application of the present technique to the development of rate gyro filters for an exploration-class multi-engined space launch vehicle.

Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

PubMed

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

2016-08-01

Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

Optimization of adenovirus 40 and 41 recovery from tap water using small disk filters.

PubMed

McMinn, Brian R

2013-11-01

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 filter, but a more cost effective option, the NanoCeram® filter, 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 optimal concentration conditions that are unique for each virus type. This study evaluated the effectiveness of 1MDS and NanoCeram filters in recovering adenovirus (AdV) 40 and 41 from tap water, and optimized 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 filter 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 optimizing secondary elution steps, AdV recovery from tap water could be improved at least two-fold compared to the currently used methodology. Identification of the optimal concentration conditions for human AdV (HAdV) is important for timely and sensitive detection of these viruses from both surface and drinking waters. Published by Elsevier B.V.

Optimized Beam Sculpting with Generalized Fringe-rate Filters

NASA Astrophysics Data System (ADS)

Parsons, Aaron R.; Liu, Adrian; Ali, Zaki S.; Cheng, Carina

2016-03-01

We generalize the technique of fringe-rate filtering, whereby visibilities measured by a radio interferometer are re-weighted according to their temporal variation. As the Earth rotates, radio sources traverse through an interferometer’s fringe pattern at rates that depend on their position on the sky. Capitalizing on this geometric interpretation of fringe rates, we employ time-domain convolution kernels to enact fringe-rate filters that sculpt the effective primary beam of antennas in an interferometer. As we show, beam sculpting through fringe-rate filtering can be used to optimize measurements for a variety of applications, including mapmaking, minimizing polarization leakage, suppressing instrumental systematics, and enhancing the sensitivity of power-spectrum measurements. We show that fringe-rate filtering arises naturally in minimum variance treatments of many of these problems, enabling optimal visibility-based approaches to analyses of interferometric data that avoid systematics potentially introduced by traditional approaches such as imaging. Our techniques have recently been demonstrated in Ali et al., where new upper limits were placed on the 21 {cm} power spectrum from reionization, showcasing the ability of fringe-rate filtering to successfully boost sensitivity and reduce the impact of systematics in deep observations.

A cascaded two-step Kalman filter for estimation of human body segment orientation using MEMS-IMU.

PubMed

Zihajehzadeh, S; Loh, D; Lee, M; Hoskinson, R; Park, E J

2014-01-01

Orientation of human body segments is an important quantity in many biomechanical analyses. To get robust and drift-free 3-D orientation, raw data from miniature body worn MEMS-based inertial measurement units (IMU) should be blended in a Kalman filter. Aiming at less computational cost, this work presents a novel cascaded two-step Kalman filter orientation estimation algorithm. Tilt angles are estimated in the first step of the proposed cascaded Kalman filter. The estimated tilt angles are passed to the second step of the filter for yaw angle calculation. The orientation results are benchmarked against the ones from a highly accurate tactical grade IMU. Experimental results reveal that the proposed algorithm provides robust orientation estimation in both kinematically and magnetically disturbed conditions.

Desensitized Optimal Filtering and Sensor Fusion Toolkit

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.

2015-01-01

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel

Optimal digital filtering for tremor suppression.

PubMed

Gonzalez, J G; Heredia, E A; Rahman, T; Barner, K E; Arce, G R

2000-05-01

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). When human movements are distorted, for instance, by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel tremor filtering framework in which digital equalizers are optimally designed through 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 ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. To address these problems, a new performance indicator in the context of tremor is introduced, and the optimal equalizer according to this new criterion is developed. Ill-conditioning of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with artificially induced vibrations and a subject with Parkinson's disease show significant improvement in performance. Additional results, along with MATLAB source code of the algorithms, and a customizable demo for PC joysticks, are available on the Internet at http:¿tremor-suppression.com.

Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement.

PubMed

Park, Byungwoon; Lim, Cheolsoon; Yun, Youngsun; Kim, Euiho; Kee, Changdon

2017-02-24

The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers.

Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement

PubMed Central

Park, Byungwoon; Lim, Cheolsoon; Yun, Youngsun; Kim, Euiho; Kee, Changdon

2017-01-01

The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers. PMID:28245584

Inverse design of high-Q wave filters in two-dimensional phononic crystals by topology optimization.

PubMed

Dong, Hao-Wen; Wang, Yue-Sheng; Zhang, Chuanzeng

2017-04-01

Topology optimization of a waveguide-cavity structure in phononic crystals for designing narrow band filters under the given operating frequencies is presented in this paper. We show that it is possible to obtain an ultra-high-Q filter by only optimizing the cavity topology without introducing any other coupling medium. The optimized cavity with highly symmetric resonance can be utilized as the multi-channel filter, raising filter and T-splitter. In addition, most optimized high-Q filters have the Fano resonances near the resonant frequencies. Furthermore, our filter optimization based on the waveguide and cavity, and our simple illustration of a computational approach to wave control in phononic crystals can be extended and applied to design other acoustic devices or even opto-mechanical devices. Copyright © 2016 Elsevier B.V. All rights reserved.

Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering.

PubMed

Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V

2015-01-01

Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

Identification of optimal mask size parameter for noise filtering in 99mTc-methylene diphosphonate bone scintigraphy images.

PubMed

Pandey, Anil K; Bisht, Chandan S; Sharma, Param D; ArunRaj, Sreedharan Thankarajan; Taywade, Sameer; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-11-01

Tc-methylene diphosphonate (Tc-MDP) bone scintigraphy images have limited number of counts per pixel. A noise filtering method based on local statistics of the image produces better results than a linear filter. However, the mask size has a significant effect on image quality. In this study, we have identified the optimal mask size that yields a good smooth bone scan image. Forty four bone scan images were processed using mask sizes 3, 5, 7, 9, 11, 13, and 15 pixels. The input and processed images were reviewed in two steps. In the first step, the images were inspected and the mask sizes that produced images with significant loss of clinical details in comparison with the input image were excluded. In the second step, the image quality of the 40 sets of images (each set had input image, and its corresponding three processed images with 3, 5, and 7-pixel masks) was assessed by two nuclear medicine physicians. They selected one good smooth image from each set of images. The image quality was also assessed quantitatively with a line profile. Fisher's exact test was used to find statistically significant differences in image quality processed with 5 and 7-pixel mask at a 5% cut-off. A statistically significant difference was found between the image quality processed with 5 and 7-pixel mask at P=0.00528. The identified optimal mask size to produce a good smooth image was found to be 7 pixels. The best mask size for the John-Sen Lee filter was found to be 7×7 pixels, which yielded Tc-methylene diphosphonate bone scan images with the highest acceptable smoothness.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.

PubMed

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M

2018-04-12

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

PubMed Central

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M.

2018-01-01

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. PMID:29649114

Joint Transmit and Receive Filter Optimization for Sub-Nyquist Delay-Doppler Estimation

NASA Astrophysics Data System (ADS)

Lenz, Andreas; Stein, Manuel S.; Swindlehurst, A. Lee

2018-05-01

In this article, a framework is presented for the joint optimization of the analog transmit and receive filter with respect to a parameter estimation problem. At the receiver, conventional signal processing systems restrict the two-sided bandwidth of the analog pre-filter $B$ to the rate of the analog-to-digital converter $f_s$ to comply with the well-known Nyquist-Shannon sampling theorem. In contrast, here we consider a transceiver that by design violates the common paradigm $B\\leq f_s$. To this end, at the receiver, we allow for a higher pre-filter bandwidth $B>f_s$ and study the achievable parameter estimation accuracy under a fixed sampling rate when the transmit and receive filter are jointly optimized with respect to the Bayesian Cram\\'{e}r-Rao lower bound. For the case of delay-Doppler estimation, we propose to approximate the required Fisher information matrix and solve the transceiver design problem by an alternating optimization algorithm. The presented approach allows us to explore the Pareto-optimal region spanned by transmit and receive filters which are favorable under a weighted mean squared error criterion. We also discuss the computational complexity of the obtained transceiver design by visualizing the resulting ambiguity function. Finally, we verify the performance of the optimized designs by Monte-Carlo simulations of a likelihood-based estimator.

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE PAGES

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

2014-10-23

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

An online replanning method using warm start optimization and aperture morphing for flattening-filter-free beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahunbay, Ergun E., E-mail: eahunbay@mcw.edu; Ates,

Purpose: In a situation where a couch shift for patient positioning is not preferred or prohibited (e.g., MR-linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening-filter-free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here the authors propose a new two-step process to address both the translational effect of FFF beams and the target deformation. Methods: The replanning method consists of an offline and an online step. The offline step is to create a series of preshifted-plans (PSPs) obtained by a so-called “warm start”more » optimization (starting optimization from the original plan, rather than from scratch) at a series of isocenter shifts. The PSPs all have the same number of segments with very similar shapes, since the warm start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by picking the closest PSP or linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated and almost instantaneous (no optimization or dose calculation needed). The previously developed SAM algorithm is then applied for daily deformation. The authors tested the method on sample prostate and pancreas cases. Results: The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. Plan interpolation method is effective in diminishing the unflat beam effect and may allow reducing the required number of PSPs. The whole process takes the same time as the previously reported SAM process (5–10 min). Conclusions: The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation except the delineation of target

Optimizing of a high-order digital filter using PSO algorithm

NASA Astrophysics Data System (ADS)

Xu, Fuchun

2018-04-01

A self-adaptive high-order digital filter, which offers opportunity to simplify the process of tuning parameters and further improve the noise performance, is presented in this paper. The parameters of traditional digital filter are mainly tuned by complex calculation, whereas this paper presents a 5th order digital filter to obtain outstanding performance and the parameters of the proposed filter are optimized by swarm intelligent algorithm. Simulation results with respect to the proposed 5th order digital filter, SNR>122dB and the noise floor under -170dB are obtained in frequency range of [5-150Hz]. In further simulation, the robustness of the proposed 5th order digital is analyzed.

Identifying Optimal Measurement Subspace for the Ensemble Kalman Filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ning; Huang, Zhenyu; Welch, Greg

2012-05-24

To reduce the computational load of the ensemble Kalman filter while maintaining its efficacy, an optimization algorithm based on the generalized eigenvalue decomposition method is proposed for identifying the most informative measurement subspace. When the number of measurements is large, the proposed algorithm can be used to make an effective tradeoff between computational complexity and estimation accuracy. This algorithm also can be extended to other Kalman filters for measurement subspace selection.

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

NASA Astrophysics Data System (ADS)

Li, Minghui; Hayward, Gordon

2017-02-01

The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

Development of adsorptive hybrid filters to enable two-step purification of biologics

PubMed Central

Peck, Michael; Voloshin, Alexei M.; Moreno, Angela M.; Tan, Zhijun; Hester, Jonathan; Borys, Michael C.; Li, Zheng Jian

2017-01-01

ABSTRACT Recent progress in mammalian cell culture process has resulted in significantly increased product titers, but also a substantial increase in process- and product-related impurities. Due to the diverse physicochemical properties of these impurities, there is constant need for new technologies that offer higher productivity and improved economics without sacrificing the process robustness required to meet final drug substance specifications. Here, we examined the use of new synthetic adsorptive hybrid filters (AHF) modified with the high binding capacity of quaternary amine (Emphaze™ AEX) and salt-tolerant biomimetic (Emphaze™ ST-AEX) ligands for clearance of process-related impurities like host cell protein (HCP), residual DNA, and virus. The potential to remove soluble aggregates was also examined. Our aim was to develop a mechanistic understanding of the interactions governing adsorptive removal of impurities during filtration by evaluating the effect of various filter types, feed streams, and process conditions on impurity removal. The ionic capacity of these filters was measured and correlated with their ability to remove impurities for multiple molecules. The ionic capacity of AHF significantly exceeded that of traditional adsorptive depth filters (ADF) by 40% for the Emphaze™ AEX and by 700% for the Emphaze™ ST-AEX, providing substantially higher reduction of soluble anionic impurities, including DNA, HCPs and model virus. Nevertheless, we determined that ADF with filter aid provided additional hydrophobic functionality that resulted in removal of higher molecular weight species than AHF. Implementing AHF demonstrated improved process-related impurity removal and viral clearance after Protein A chromatography and enabled a two-step purification process. The consequences of enhanced process performance are far reaching because it allows the downstream polishing train to be restructured and simplified, and chromatographic purity standards to be

Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering.

PubMed

Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N

2017-10-17

The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

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 filter 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 filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter 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 optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Improvement of the fringe analysis algorithm for wavelength scanning interferometry based on filter parameter optimization.

PubMed

Zhang, Tao; Gao, Feng; Muhamedsalih, Hussam; Lou, Shan; Martin, Haydn; Jiang, Xiangqian

2018-03-20

The phase slope method which estimates height through fringe pattern frequency and the algorithm which estimates height through the fringe phase are the fringe analysis algorithms widely used in interferometry. Generally they both extract the phase information by filtering the signal in frequency domain after Fourier transform. Among the numerous papers in the literature about these algorithms, it is found that the design of the filter, which plays an important role, has never been discussed in detail. This paper focuses on the filter design in these algorithms for wavelength scanning interferometry (WSI), trying to optimize the parameters to acquire the optimal results. The spectral characteristics of the interference signal are analyzed first. The effective signal is found to be narrow-band (near single frequency), and the central frequency is calculated theoretically. Therefore, the position of the filter pass-band is determined. The width of the filter window is optimized with the simulation to balance the elimination of the noise and the ringing of the filter. Experimental validation of the approach is provided, and the results agree very well with the simulation. The experiment shows that accuracy can be improved by optimizing the filter design, especially when the signal quality, i.e., the signal noise ratio (SNR), is low. The proposed method also shows the potential of improving the immunity to the environmental noise by adapting the signal to acquire the optimal results through designing an adaptive filter once the signal SNR can be estimated accurately.

Optimal Sharpening of Compensated Comb Decimation Filters: Analysis and Design

PubMed Central

Troncoso Romero, David Ernesto

2014-01-01

Comb filters are a class of low-complexity filters especially useful for multistage decimation processes. However, the magnitude response of comb filters presents a droop in the passband region and low stopband attenuation, which is undesirable in many applications. In this work, it is shown that, for stringent magnitude specifications, sharpening compensated comb filters requires a lower-degree sharpening polynomial compared to sharpening comb filters without compensation, resulting in a solution with lower computational complexity. Using a simple three-addition compensator and an optimization-based derivation of sharpening polynomials, we introduce an effective low-complexity filtering scheme. Design examples are presented in order to show the performance improvement in terms of passband distortion and selectivity compared to other methods based on the traditional Kaiser-Hamming sharpening and the Chebyshev sharpening techniques recently introduced in the literature. PMID:24578674

Optimal sharpening of compensated comb decimation filters: analysis and design.

PubMed

Troncoso Romero, David Ernesto; Laddomada, Massimiliano; Jovanovic Dolecek, Gordana

2014-01-01

Comb filters are a class of low-complexity filters especially useful for multistage decimation processes. However, the magnitude response of comb filters presents a droop in the passband region and low stopband attenuation, which is undesirable in many applications. In this work, it is shown that, for stringent magnitude specifications, sharpening compensated comb filters requires a lower-degree sharpening polynomial compared to sharpening comb filters without compensation, resulting in a solution with lower computational complexity. Using a simple three-addition compensator and an optimization-based derivation of sharpening polynomials, we introduce an effective low-complexity filtering scheme. Design examples are presented in order to show the performance improvement in terms of passband distortion and selectivity compared to other methods based on the traditional Kaiser-Hamming sharpening and the Chebyshev sharpening techniques recently introduced in the literature.

Optimally designed narrowband guided-mode resonance reflectance filters for mid-infrared spectroscopy

PubMed Central

Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.

2011-01-01

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 filters based on guided-mode resonance (GMR) in waveguide gratings, but filters 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 optimal design of double-layer surface-relief silicon nitride-based GMR filters in the mid-IR for various narrow bandwidths below 32 cm−1. Both shift of the filter 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 filters. By incorporating considerations for background reflections, the optimally designed GMR filters can have bandwidth narrower than the designed filter 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 filters-based instrumentation for common measurements of condensed matter, including tissues and polymer samples. PMID:22109445

Comparison of older adults' steps per day using NL-1000 pedometer and two GT3X+ accelerometer filters.

PubMed

Barreira, Tiago V; Brouillette, Robert M; Foil, Heather C; Keller, Jeffrey N; Tudor-Locke, Catrine

2013-10-01

The purpose of this study was to compare the steps/d derived from the ActiGraph GT3X+ using the manufacturer's default filter (DF) and low-frequency-extension filter (LFX) with those from the NL-1000 pedometer in an older adult sample. Fifteen older adults (61-82 yr) wore a GT3X+ (24 hr/day) and an NL-1000 (waking hours) for 7 d. Day was the unit of analysis (n = 86 valid days) comparing (a) GT3X+ DF and NL-1000 steps/d and (b) GT3X+ LFX and NL-1000 steps/d. DF was highly correlated with NL-1000 (r = .80), but there was a significant mean difference (-769 steps/d). LFX and NL-1000 were highly correlated (r = .90), but there also was a significant mean difference (8,140 steps/d). Percent difference and absolute percent difference between DF and NL-1000 were -7.4% and 16.0%, respectively, and for LFX and NL-1000 both were 121.9%. Regardless of filter used, GT3X+ did not provide comparable pedometer estimates of steps/d in this older adult sample.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

PubMed

Jia, Jie; Barnard, Kenneth J; Hirakawa, Keigo

2016-04-01

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.

Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space.

PubMed

Huang, Jianyong; Qin, Lei; Peng, Xiaoling; Zhu, Tao; Xiong, Chunyang; Zhang, Youyi; Fang, Jing

2009-08-21

Quantitative estimation of cellular traction has significant physiological and clinical implications. As an inverse problem, traction force recovery is essentially susceptible to noise in the measured displacement data. For traditional procedure of Fourier transform traction cytometry (FTTC), noise amplification is accompanied in the force reconstruction and small tractions cannot be recovered from the displacement field with low signal-noise ratio (SNR). To improve the FTTC process, we develop an optimal filtering scheme to suppress the noise in the force reconstruction procedure. In the framework of the Wiener filtering theory, four filtering parameters are introduced in two-dimensional Fourier space and their analytical expressions are derived in terms of the minimum-mean-squared-error (MMSE) optimization criterion. The optimal filtering approach is validated with simulations and experimental data associated with the adhesion of single cardiac myocyte to elastic substrate. The results indicate that the proposed method can highly enhance SNR of the recovered forces to reveal tiny tractions in cell-substrate interaction.

An exact algorithm for optimal MAE stack filter design.

PubMed

Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior

2007-02-01

We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.

Design Optimization of Vena Cava Filters: An application to dual filtration devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singer, M A; Wang, S L; Diachin, D P

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 filter 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 optimization to determine the configuration of trapped thrombi that minimizes the hemodynamic disruption. The resulting configuration has implications for constructing an optimally designed vena cava filter. Computational fluid dynamics is coupled with a nonlinear optimization algorithm to determine the optimal configuration of trapped modelmore » 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 optimization framework that is broadly applicable. Changes to thrombus location and shape alter the velocity contours and wall shear stress profiles significantly. For vena cava filters 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 optimization is a useful tool for developing vena cava filters. 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.« less

On salesmen and tourists: Two-step optimization in deterministic foragers

NASA Astrophysics Data System (ADS)

Maya, Miguel; Miramontes, Octavio; Boyer, Denis

2017-02-01

We explore a two-step optimization problem in random environments, the so-called restaurant-coffee shop problem, where a walker aims at visiting the nearest and better restaurant in an area and then move to the nearest and better coffee-shop. This is an extension of the Tourist Problem, a one-step optimization dynamics that can be viewed as a deterministic walk in a random medium. A certain amount of heterogeneity in the values of the resources to be visited causes the emergence of power-laws distributions for the steps performed by the walker, similarly to a Lévy flight. The fluctuations of the step lengths tend to decrease as a consequence of multiple-step planning, thus reducing the foraging uncertainty. We find that the first and second steps of each planned movement play very different roles in heterogeneous environments. The two-step process improves only slightly the foraging efficiency compared to the one-step optimization, at a much higher computational cost. We discuss the implications of these findings for animal and human mobility, in particular in relation to the computational effort that informed agents should deploy to solve search problems.

A Kalman filter for a two-dimensional shallow-water model

NASA Technical Reports Server (NTRS)

Parrish, D. F.; Cohn, S. E.

1985-01-01

A two-dimensional Kalman filter is described for data assimilation for making weather forecasts. The filter is regarded as superior to the optimal interpolation method because the filter determines the forecast error covariance matrix exactly instead of using an approximation. A generalized time step is defined which includes expressions for one time step of the forecast model, the error covariance matrix, the gain matrix, and the evolution of the covariance matrix. Subsequent time steps are achieved by quantifying the forecast variables or employing a linear extrapolation from a current variable set, assuming the forecast dynamics are linear. Calculations for the evolution of the error covariance matrix are banded, i.e., are performed only with the elements significantly different from zero. Experimental results are provided from an application of the filter to a shallow-water simulation covering a 6000 x 6000 km grid.

Optimizing the number of steps in learning tasks for complex skills.

PubMed

Nadolski, Rob J; Kirschner, Paul A; van Merriënboer, Jeroen J G

2005-06-01

Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimized for efficient and effective learning. The aim of the study is to investigate the relation between the number of steps provided to learners and the quality of their learning of complex skills. It is hypothesized that students receiving an optimized number of steps will learn better than those receiving either the whole task in only one step or those receiving a large number of steps. Participants were 35 sophomore law students studying at Dutch universities, mean age=22.8 years (SD=3.5), 63% were female. Participants were randomly assigned to 1 of 3 computer-delivered versions of a multimedia programme on how to prepare and carry out a law plea. The versions differed only in the number of learning steps provided. Videotaped plea-performance results were determined, various related learning measures were acquired and all computer actions were logged and analyzed. Participants exposed to an intermediate (i.e. optimized) number of steps outperformed all others on the compulsory learning task. No differences in performance on a transfer task were found. A high number of steps proved to be less efficient for carrying out the learning task. An intermediate number of steps is the most effective, proving that the number of steps can be optimized for improving learning.

Real-time localization of mobile device by filtering method for sensor fusion

NASA Astrophysics Data System (ADS)

Fuse, Takashi; Nagara, Keita

2017-06-01

Most of the applications with mobile devices require self-localization of the devices. GPS cannot be used in indoor environment, the positions of mobile devices are estimated autonomously by using IMU. Since the self-localization is based on IMU of low accuracy, and then the self-localization in indoor environment is still challenging. The selflocalization method using images have been developed, and the accuracy of the method is increasing. This paper develops the self-localization method without GPS in indoor environment by integrating sensors, such as IMU and cameras, on mobile devices simultaneously. The proposed method consists of observations, forecasting and filtering. The position and velocity of the mobile device are defined as a state vector. In the self-localization, observations correspond to observation data from IMU and camera (observation vector), forecasting to mobile device moving model (system model) and filtering to tracking method by inertial surveying and coplanarity condition and inverse depth model (observation model). Positions of a mobile device being tracked are estimated by system model (forecasting step), which are assumed as linearly moving model. Then estimated positions are optimized referring to the new observation data based on likelihood (filtering step). The optimization at filtering step corresponds to estimation of the maximum a posterior probability. Particle filter are utilized for the calculation through forecasting and filtering steps. The proposed method is applied to data acquired by mobile devices in indoor environment. Through the experiments, the high performance of the method is confirmed.

Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network

NASA Astrophysics Data System (ADS)

He, Fei; Han, Ye; Wang, Han; Ji, Jinchao; Liu, Yuanning; Ma, Zhiqiang

2017-03-01

Gabor filters are widely utilized to detect iris texture information in several state-of-the-art iris recognition systems. However, the proper Gabor kernels and the generative pattern of iris Gabor features need to be predetermined in application. The traditional empirical Gabor filters and shallow iris encoding ways are incapable of dealing with such complex variations in iris imaging including illumination, aging, deformation, and device variations. Thereby, an adaptive Gabor filter selection strategy and deep learning architecture are presented. We first employ particle swarm optimization approach and its binary version to define a set of data-driven Gabor kernels for fitting the most informative filtering bands, and then capture complex pattern from the optimal Gabor filtered coefficients by a trained deep belief network. A succession of comparative experiments validate that our optimal Gabor filters may produce more distinctive Gabor coefficients and our iris deep representations be more robust and stable than traditional iris Gabor codes. Furthermore, the depth and scales of the deep learning architecture are also discussed.

Method for optimizing output in ultrashort-pulse multipass laser amplifiers with selective use of a spectral filter

DOEpatents

Backus, Sterling J [Erie, CO; Kapteyn, Henry C [Boulder, CO

2007-07-10

A method for optimizing multipass laser amplifier output utilizes a spectral filter in early passes but not in later passes. The pulses shift position slightly for each pass through the amplifier, and the filter is placed such that early passes intersect the filter while later passes bypass it. The filter position may be adjust offline in order to adjust the number of passes in each category. The filter may be optimized for use in a cryogenic amplifier.

Direct aperture optimization: a turnkey solution for step-and-shoot IMRT.

PubMed

Shepard, D M; Earl, M A; Li, X A; Naqvi, S; Yu, C

2002-06-01

IMRT treatment plans for step-and-shoot delivery have traditionally been produced through the optimization of intensity distributions (or maps) for each beam angle. The optimization step is followed by the application of a leaf-sequencing algorithm that translates each intensity map into a set of deliverable aperture shapes. In this article, we introduce an automated planning system in which we bypass the traditional intensity optimization, and instead directly optimize the shapes and the weights of the apertures. We call this approach "direct aperture optimization." This technique allows the user to specify the maximum number of apertures per beam direction, and hence provides significant control over the complexity of the treatment delivery. This is possible because the machine dependent delivery constraints imposed by the MLC are enforced within the aperture optimization algorithm rather than in a separate leaf-sequencing step. The leaf settings and the aperture intensities are optimized simultaneously using a simulated annealing algorithm. We have tested direct aperture optimization on a variety of patient cases using the EGS4/BEAM Monte Carlo package for our dose calculation engine. The results demonstrate that direct aperture optimization can produce highly conformal step-and-shoot treatment plans using only three to five apertures per beam direction. As compared with traditional optimization strategies, our studies demonstrate that direct aperture optimization can result in a significant reduction in both the number of beam segments and the number of monitor units. Direct aperture optimization therefore produces highly efficient treatment deliveries that maintain the full dosimetric benefits of IMRT.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Achieving a Successful Scale-Down Model and Optimized Economics through Parvovirus Filter Validation using Purified TrueSpikeTM Viruses.

PubMed

De Vilmorin, Philippe; Slocum, Ashley; Jaber, Tareq; Schaefer, Oliver; Ruppach, Horst; Genest, Paul

2015-01-01

This article describes a four virus panel validation of EMD Millipore's (Bedford, MA) small virus-retentive filter, Viresolve® Pro, using TrueSpike(TM) viruses for a Biogen Idec process intermediate. The study was performed at Charles River Labs in King of Prussia, PA. Greater than 900 L/m(2) filter throughput was achieved with the approximately 8 g/L monoclonal antibody feed. No viruses were detected in any filtrate samples. All virus log reduction values were between ≥3.66 and ≥5.60. The use of TrueSpike(TM) at Charles River Labs allowed Biogen Idec to achieve a more representative scaled-down model and potentially reduce the cost of its virus filtration step and the overall cost of goods. The body of data presented here is an example of the benefits of following the guidance from the PDA Technical Report 47, The Preparation of Virus Spikes Used for Viral Clearance Studies. The safety of biopharmaceuticals is assured through the use of multiple steps in the purification process that are capable of virus clearance, including filtration with virus-retentive filters. The amount of virus present at the downstream stages in the process is expected to be and is typically low. The viral clearance capability of the filtration step is assessed in a validation study. The study utilizes a small version of the larger manufacturing size filter, and a large, known amount of virus is added to the feed prior to filtration. Viral assay before and after filtration allows the virus log reduction value to be quantified. The representativeness of the small-scale model is supported by comparing large-scale filter performance to small-scale filter performance. The large-scale and small-scale filtration runs are performed using the same operating conditions. If the filter performance at both scales is comparable, it supports the applicability of the virus log reduction value obtained with the small-scale filter to the large-scale manufacturing process. However, the virus

A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm.

PubMed

Feng, Kaiqiang; Li, Jie; Zhang, Xiaoming; Shen, Chong; Bi, Yu; Zheng, Tao; Liu, Jun

2017-09-19

In order to reduce the computational complexity, and improve the pitch/roll estimation accuracy of the low-cost attitude heading reference system (AHRS) under conditions of magnetic-distortion, a novel linear Kalman filter, suitable for nonlinear attitude estimation, is proposed in this paper. The new algorithm is the combination of two-step geometrically-intuitive correction (TGIC) and the Kalman filter. In the proposed algorithm, the sequential two-step geometrically-intuitive correction scheme is used to make the current estimation of pitch/roll immune to magnetic distortion. Meanwhile, the TGIC produces a computed quaternion input for the Kalman filter, which avoids the linearization error of measurement equations and reduces the computational complexity. Several experiments have been carried out to validate the performance of the filter design. The results demonstrate that the mean time consumption and the root mean square error (RMSE) of pitch/roll estimation under magnetic disturbances are reduced by 45.9% and 33.8%, respectively, when compared with a standard filter. In addition, the proposed filter is applicable for attitude estimation under various dynamic conditions.

A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm

PubMed Central

Feng, Kaiqiang; Li, Jie; Zhang, Xiaoming; Shen, Chong; Bi, Yu; Zheng, Tao; Liu, Jun

2017-01-01

In order to reduce the computational complexity, and improve the pitch/roll estimation accuracy of the low-cost attitude heading reference system (AHRS) under conditions of magnetic-distortion, a novel linear Kalman filter, suitable for nonlinear attitude estimation, is proposed in this paper. The new algorithm is the combination of two-step geometrically-intuitive correction (TGIC) and the Kalman filter. In the proposed algorithm, the sequential two-step geometrically-intuitive correction scheme is used to make the current estimation of pitch/roll immune to magnetic distortion. Meanwhile, the TGIC produces a computed quaternion input for the Kalman filter, which avoids the linearization error of measurement equations and reduces the computational complexity. Several experiments have been carried out to validate the performance of the filter design. The results demonstrate that the mean time consumption and the root mean square error (RMSE) of pitch/roll estimation under magnetic disturbances are reduced by 45.9% and 33.8%, respectively, when compared with a standard filter. In addition, the proposed filter is applicable for attitude estimation under various dynamic conditions. PMID:28925979

Optimal interpolation and the Kalman filter. [for analysis of numerical weather predictions

NASA Technical Reports Server (NTRS)

Cohn, S.; Isaacson, E.; Ghil, M.

1981-01-01

The estimation theory of stochastic-dynamic systems is described and used in a numerical study of optimal interpolation. The general form of data assimilation methods is reviewed. The Kalman-Bucy, KB filter, and optimal interpolation (OI) filters are examined for effectiveness in performance as gain matrices using a one-dimensional form of the shallow-water equations. Control runs in the numerical analyses were performed for a ten-day forecast in concert with the OI method. The effects of optimality, initialization, and assimilation were studied. It was found that correct initialization is necessary in order to localize errors, especially near boundary points. Also, the use of small forecast error growth rates over data-sparse areas was determined to offset inaccurate modeling of correlation functions near boundaries.

The optimal digital filters of sine and cosine transforms for geophysical transient electromagnetic method

NASA Astrophysics Data System (ADS)

Zhao, Yun-wei; Zhu, Zi-qiang; Lu, Guang-yin; Han, Bo

2018-03-01

The sine and cosine transforms implemented with digital filters have been used in the Transient electromagnetic methods for a few decades. Kong (2007) proposed a method of obtaining filter coefficients, which are computed in the sample domain by Hankel transform pair. However, the curve shape of Hankel transform pair changes with a parameter, which usually is set to be 1 or 3 in the process of obtaining the digital filter coefficients of sine and cosine transforms. First, this study investigates the influence of the parameter on the digital filter algorithm of sine and cosine transforms based on the digital filter algorithm of Hankel transform and the relationship between the sine, cosine function and the ±1/2 order Bessel function of the first kind. The results show that the selection of the parameter highly influences the precision of digital filter algorithm. Second, upon the optimal selection of the parameter, it is found that an optimal sampling interval s also exists to achieve the best precision of digital filter algorithm. Finally, this study proposes four groups of sine and cosine transform digital filter coefficients with different length, which may help to develop the digital filter algorithm of sine and cosine transforms, and promote its application.

Combined adaptive multiple subtraction based on optimized event tracing and extended wiener filtering

NASA Astrophysics Data System (ADS)

Tan, Jun; Song, Peng; Li, Jinshan; Wang, Lei; Zhong, Mengxuan; Zhang, Xiaobo

2017-06-01

The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

Optimal-adaptive filters for modelling spectral shape, site amplification, and source scaling

USGS Publications Warehouse

Safak, Erdal

1989-01-01

This paper introduces some applications of optimal filtering techniques to earthquake engineering by using the so-called ARMAX models. Three applications are presented: (a) spectral modelling of ground accelerations, (b) site amplification (i.e., the relationship between two records obtained at different sites during an earthquake), and (c) source scaling (i.e., the relationship between two records obtained at a site during two different earthquakes). A numerical example for each application is presented by using recorded ground motions. The results show that the optimal filtering techniques provide elegant solutions to above problems, and can be a useful tool in earthquake engineering.

Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises

PubMed Central

Grama, Ion; Liu, Quansheng

2017-01-01

In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise. PMID:28692667

Optimal Weights Mixed Filter for removing mixture of Gaussian and impulse noises.

PubMed

Jin, Qiyu; Grama, Ion; Liu, Quansheng

2017-01-01

In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a new algorithm called Optimal Weights Mixed Filter (OWMF) to deal with the mixed noise. Our simulation results show that the proposed filter is effective for mixed noises, as well as for single impulse noise and for single Gaussian noise.

STUDY ON A STEP-ADVANCED FILTER MONITOR FOR CONTINUOUS RADON PROGENY MEASUREMENT.

PubMed

Zhang, Lei; Yang, Jinmin; Guo, Qiuju

2017-04-01

Traditional fixed-filter radon progeny monitors are usually clogged with the loading of dust and cannot be used for radon progeny continuous measurement for long period. To solve this problem, a step-advanced filter (SAF) monitor for radon progeny measurement was developed. This monitor automatically roll and stop the filter at each interview. Radon progeny is collected on a 'fresh' filter at a flowrate of 3 L/min. At the same time, alpha and beta particles emitted from filter are recorded by a PIPS detector. A newly developed alpha-beta spectrum method was used for radon progeny concentration calculation. The 218Po, 214Pb and 214Bi concentrations as well as equilibrium equivalent concentration (EEC) could be worked out at the same time. The lower level limit detection of this monitor is 0.48 Bq m-3 (EEC) for 1h interval. Comparison experiments were carried out in the radon chamber at the National Institute of Metrology of China. The measurement results of this SAF monitor are consistent with EQF3220 (SARAD GmbH, Germany), and the uncertainty is smaller. Due to its high sensitivity, the periodical variation of radon progeny concentration can be easily observed by this monitor. The SAF moniter is suitable for continuous measurement in both indoor and outdoor environments. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Quantum-behaved particle swarm optimization for the synthesis of fibre Bragg gratings filter

NASA Astrophysics Data System (ADS)

Yu, Xuelian; Sun, Yunxu; Yao, Yong; Tian, Jiajun; Cong, Shan

2011-12-01

A method based on the quantum-behaved particle swarm optimization algorithm is presented to design a bandpass filter of the fibre Bragg gratings. In contrast to the other optimization algorithms such as the genetic algorithm and particle swarm optimization algorithm, this method is simpler and easier to implement. To demonstrate the effectiveness of the QPSO algorithm, we consider a bandpass filter. With the parameters the half the bandwidth of the filter 0.05 nm, the Bragg wavelength 1550 nm, the grating length with 2cm is divided into 40 uniform sections and its index modulation is what should be optimized and whole feasible solution space is searched for the index modulation. After the index modulation profile is known for all the sections, the transfer matrix method is used to verify the final optimal index modulation by calculating the refection spectrum. The results show the group delay is less than 12ps in band and the calculated dispersion is relatively flat inside the passband. It is further found that the reflective spectrum has sidelobes around -30dB and the worst in-band dispersion value is less than 200ps/nm . In addition, for this design, it takes approximately several minutes to find the acceptable index modulation values with a notebook computer.

Optimization of internet content filtering-Combined with KNN and OCAT algorithms

NASA Astrophysics Data System (ADS)

Guo, Tianze; Wu, Lingjing; Liu, Jiaming

2018-04-01

The face of the status quo that rampant illegal content in the Internet, the result of traditional way to filter information, keyword recognition and manual screening, is getting worse. Based on this, this paper uses OCAT algorithm nested by KNN classification algorithm to construct a corpus training library that can dynamically learn and update, which can be improved on the filter corpus for constantly updated illegal content of the network, including text and pictures, and thus can better filter and investigate illegal content and its source. After that, the research direction will focus on the simplified updating of recognition and comparison algorithms and the optimization of the corpus learning ability in order to improve the efficiency of filtering, save time and resources.

Metrics for comparing plasma mass filters

NASA Astrophysics Data System (ADS)

Fetterman, Abraham J.; Fisch, Nathaniel J.

2011-10-01

High-throughput mass separation of nuclear waste may be useful for optimal storage, disposal, or environmental remediation. The most dangerous part of nuclear waste is the fission product, which produces most of the heat and medium-term radiation. Plasmas are well-suited to separating nuclear waste because they can separate many different species in a single step. A number of plasma devices have been designed for such mass separation, but there has been no standardized comparison between these devices. We define a standard metric, the separative power per unit volume, and derive it for three different plasma mass filters: the plasma centrifuge, Ohkawa filter, and the magnetic centrifugal mass filter.

Single step optimization of manipulator maneuvers with variable structure control

NASA Technical Reports Server (NTRS)

Chen, N.; Dwyer, T. A. W., III

1987-01-01

One step ahead optimization has been recently proposed for spacecraft attitude maneuvers as well as for robot manipulator maneuvers. Such a technique yields a discrete time control algorithm implementable as a sequence of state-dependent, quadratic programming problems for acceleration optimization. Its sensitivity to model accuracy, for the required inversion of the system dynamics, is shown in this paper to be alleviated by a fast variable structure control correction, acting between the sampling intervals of the slow one step ahead discrete time acceleration command generation algorithm. The slow and fast looping concept chosen follows that recently proposed for optimal aiming strategies with variable structure control. Accelerations required by the VSC correction are reserved during the slow one step ahead command generation so that the ability to overshoot the sliding surface is guaranteed.

Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

NASA Astrophysics Data System (ADS)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.

Comparison of Kalman filter and optimal smoother estimates of spacecraft attitude

NASA Technical Reports Server (NTRS)

Sedlak, J.

1994-01-01

Given a valid system model and adequate observability, a Kalman filter will converge toward the true system state with error statistics given by the estimated error covariance matrix. The errors generally do not continue to decrease. Rather, a balance is reached between the gain of information from new measurements and the loss of information during propagation. The errors can be further reduced, however, by a second pass through the data with an optimal smoother. This algorithm obtains the optimally weighted average of forward and backward propagating Kalman filters. It roughly halves the error covariance by including future as well as past measurements in each estimate. This paper investigates whether such benefits actually accrue in the application of an optimal smoother to spacecraft attitude determination. Tests are performed both with actual spacecraft data from the Extreme Ultraviolet Explorer (EUVE) and with simulated data for which the true state vector and noise statistics are exactly known.

Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

PubMed

Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

2016-12-01

Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

Design of almost symmetric orthogonal wavelet filter bank via direct optimization.

PubMed

Murugesan, Selvaraaju; Tay, David B H

2012-05-01

It is a well-known fact that (compact-support) dyadic wavelets [based on the two channel filter 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 optimize. The designed filters have good frequency response, flat group delay, almost symmetric filter coefficients, and symmetric wavelet function.

Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

PubMed Central

Saha, S. K.; Dutta, R.; Choudhury, R.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. 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 filter 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 filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems. PMID:23844390

Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm.

PubMed

Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. 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 filter 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 filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

Optimizing binary phase and amplitude filters for PCE, SNR, and discrimination

NASA Technical Reports Server (NTRS)

Downie, John D.

1992-01-01

Binary phase-only filters (BPOFs) have generated much study because of their implementation on currently available spatial light modulator devices. On polarization-rotating devices such as the magneto-optic spatial light modulator (SLM), it is also possible to encode binary amplitude information into two SLM transmission states, in addition to the binary phase information. This is done by varying the rotation angle of the polarization analyzer following the SLM in the optical train. Through this parameter, a continuum of filters may be designed that span the space of binary phase and amplitude filters (BPAFs) between BPOFs and binary amplitude filters. In this study, we investigate the design of optimal BPAFs for the key correlation characteristics of peak sharpness (through the peak-to-correlation energy (PCE) metric), signal-to-noise ratio (SNR), and discrimination between in-class and out-of-class images. We present simulation results illustrating improvements obtained over conventional BPOFs, and trade-offs between the different performance criteria in terms of the filter design parameter.

A Peptide Filtering Relation Quantifies MHC Class I Peptide Optimization

PubMed Central

Goldstein, Leonard D.; Howarth, Mark; Cardelli, Luca; Emmott, Stephen; Elliott, Tim; Werner, Joern M.

2011-01-01

Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human

Quantum demolition filtering and optimal control of unstable systems.

PubMed

Belavkin, V P

2012-11-28

A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.

Optimization Algorithm for Kalman Filter Exploiting the Numerical Characteristics of SINS/GPS Integrated Navigation Systems.

PubMed

Hu, Shaoxing; Xu, Shike; Wang, Duhu; Zhang, Aiwu

2015-11-11

Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the sparseness and/or symmetry of matrices to simplify the computational procedure. Thus plenty of invalid operations can be avoided by offline derivation using a block matrix technique. For enhanced efficiency, a new parallel computational mechanism is established by subdividing and restructuring calculation processes after analyzing the extracted "useful" data. As a result, the algorithm saves about 90% of the CPU processing time and 66% of the memory usage needed in a classical Kalman filter. Meanwhile, the method as a numerical approach needs no precise-loss transformation/approximation of system modules and the accuracy suffers little in comparison with the filter before computational optimization. Furthermore, since no complicated matrix theories are needed, the algorithm can be easily transplanted into other modified filters as a secondary optimization method to achieve further efficiency.

Texas two-step: a framework for optimal multi-input single-output deconvolution.

PubMed

Neelamani, Ramesh; Deffenbaugh, Max; Baraniuk, Richard G

2007-11-01

Multi-input single-output deconvolution (MISO-D) aims to extract a deblurred estimate of a target signal from several blurred and noisy observations. This paper develops a new two step framework--Texas Two-Step--to solve MISO-D problems with known blurs. Texas Two-Step first reduces the MISO-D problem to a related single-input single-output deconvolution (SISO-D) problem by invoking the concept of sufficient statistics (SSs) and then solves the simpler SISO-D problem using an appropriate technique. The two-step framework enables new MISO-D techniques (both optimal and suboptimal) based on the rich suite of existing SISO-D techniques. In fact, the properties of SSs imply that a MISO-D algorithm is mean-squared-error optimal if and only if it can be rearranged to conform to the Texas Two-Step framework. Using this insight, we construct new wavelet- and curvelet-based MISO-D algorithms with asymptotically optimal performance. Simulated and real data experiments verify that the framework is indeed effective.

Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features

PubMed Central

Song, Le; Epps, Julien

2007-01-01

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 optimal filters 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 filters optimized using the proposed learning approach. PMID:18364986

Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation

PubMed Central

Budde, Matthew D.; Skinner, Nathan P.; Muftuler, L. Tugan; Schmit, Brian D.; Kurpad, Shekar N.

2017-01-01

Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the

Optimal filter parameters for low SNR seismograms as a function of station and event location

NASA Astrophysics Data System (ADS)

Leach, Richard R.; Dowla, Farid U.; Schultz, Craig A.

1999-06-01

Global seismic monitoring requires deployment of seismic sensors worldwide, in many areas that have not been studied or have few useable recordings. Using events with lower signal-to-noise ratios (SNR) would increase the amount of data from these regions. Lower SNR events can add significant numbers to data sets, but recordings of these events must be carefully filtered. For a given region, conventional methods of filter selection can be quite subjective and may require intensive analysis of many events. To reduce this laborious process, we have developed an automated method to provide optimal filters for low SNR regional or teleseismic events. As seismic signals are often localized in frequency and time with distinct time-frequency characteristics, our method is based on the decomposition of a time series into a set of subsignals, each representing a band with f/Δ f constant (constant Q). The SNR is calculated on the pre-event noise and signal window. The band pass signals with high SNR are used to indicate the cutoff filter limits for the optimized filter. Results indicate a significant improvement in SNR, particularly for low SNR events. The method provides an optimum filter which can be immediately applied to unknown regions. The filtered signals are used to map the seismic frequency response of a region and may provide improvements in travel-time picking, azimuth estimation, regional characterization, and event detection. For example, when an event is detected and a preliminary location is determined, the computer could automatically select optimal filter bands for data from non-reporting stations. Results are shown for a set of low SNR events as well as 379 regional and teleseismic events recorded at stations ABKT, KIV, and ANTO in the Middle East.

A chaos wolf optimization algorithm with self-adaptive variable step-size

NASA Astrophysics Data System (ADS)

Zhu, Yong; Jiang, Wanlu; Kong, Xiangdong; Quan, Lingxiao; Zhang, Yongshun

2017-10-01

To explore the problem of parameter optimization for complex nonlinear function, a chaos wolf optimization algorithm (CWOA) with self-adaptive variable step-size was proposed. The algorithm was based on the swarm intelligence of wolf pack, which fully simulated the predation behavior and prey distribution way of wolves. It possessed three intelligent behaviors such as migration, summons and siege. And the competition rule as "winner-take-all" and the update mechanism as "survival of the fittest" were also the characteristics of the algorithm. Moreover, it combined the strategies of self-adaptive variable step-size search and chaos optimization. The CWOA was utilized in parameter optimization of twelve typical and complex nonlinear functions. And the obtained results were compared with many existing algorithms, including the classical genetic algorithm, the particle swarm optimization algorithm and the leader wolf pack search algorithm. The investigation results indicate that CWOA possess preferable optimization ability. There are advantages in optimization accuracy and convergence rate. Furthermore, it demonstrates high robustness and global searching ability.

Optimization of an enhanced ceramic micro-filter for concentrating E.coli in water

NASA Astrophysics Data System (ADS)

Zhang, Yushan; Guo, Tianyi; Xu, Changqing; Hong, Lingcheng

2017-02-01

Recently lower limit of detection (LOD) is necessary for rapid bacteria detection and analysis applications in clinical practices and daily life. A critical pre-conditioning step for these applications is bacterial concentration, especially for low level of pathogens. Sample volume can be largely reduced with an efficient pre-concentration process. Some approaches such as hollow-fiber ultra-filtration and electrokinetic technique have been applied to bacterial concentration. Since none of these methods can provide a concentrating method with a stable recovery efficiency, bacterial concentration still remains challenging Ceramic micro- filter can be used to concentrate the bacteria but the cross flow system keeps the bacteria in suspension. Similar harvesting bacteria using ultra-filtration showed an average recovery efficiency of 43% [1] and other studies achieved recovery rates greater than 50% [2]. In this study, an enhanced ceramic micro-filter with 0.14 μm pore size was proposed and demonstrated to optimize the concentration of E.coli. A high recovery rate (mean value >90%) and a high volumetric concentration ratio (>100) were achieved. Known quantities (104 to 106 CFU/ml) of E.coli cells were spiked to different amounts of phosphate buffered saline (0.1 to 1 L), and then concentrated to a final retentate of 5 ml to 10 ml. An average recovery efficiency of 95.3% with a standard deviation of 5.6% was achieved when the volumetric con- centration ratio was 10. No significant recovery rate loss was indicated when the volumetric concentration ratio reached up to 100. The effects of multiple parameters on E.coli recovery rate were also studied. The obtained results indicated that the optimized ceramic micro- filtration system can successfully concentrate E.coli cells in water with an average recovery rate of 90.8%.

[Numerical simulation and operation optimization of biological filter].

PubMed

Zou, Zong-Sen; Shi, Han-Chang; Chen, Xiang-Qiang; Xie, Xiao-Qing

2014-12-01

BioWin software and two sensitivity analysis methods were used to simulate the Denitrification Biological Filter (DNBF) + Biological Aerated Filter (BAF) process in Yuandang Wastewater Treatment Plant. Based on the BioWin model of DNBF + BAF process, the operation data of September 2013 were used for sensitivity analysis and model calibration, and the operation data of October 2013 were used for model validation. The results indicated that the calibrated model could accurately simulate practical DNBF + BAF processes, and the most sensitive parameters were the parameters related to biofilm, OHOs and aeration. After the validation and calibration of model, it was used for process optimization with simulating operation results under different conditions. The results showed that, the best operation condition for discharge standard B was: reflux ratio = 50%, ceasing methanol addition, influent C/N = 4.43; while the best operation condition for discharge standard A was: reflux ratio = 50%, influent COD = 155 mg x L(-1) after methanol addition, influent C/N = 5.10.

Internal Structure and Morphology Profile in Optimizing Filter Membrane Performance

NASA Astrophysics Data System (ADS)

Sanaei, Pejman; Cummings, Linda J.

Membrane filters are in widespread use, and manufacturers have considerable interest in improving their performance, in terms of particle retention properties, and total throughput over the filter lifetime. A good question to ask is therefore: what is the optimal configuration of filter membranes, in terms of internal morphology (pore size and shape), to achieve the most efficient filtration? To answer this question, we must first propose a robust measure of filtration performance. As filtration occurs the membrane becomes blocked, or fouled, by the impurities in the feed solution, and any performance measure must take account of this. For example, one performance measure might be the total throughput (the volume of filtered feed solution) at the end of the filtration process, when the membrane is so badly blocked that it is deemed no longer functional. Here we present a simplified mathematical model, which (i) characterizes membrane internal pore structure via pore or permeability profiles in the depth of the membrane; (ii) accounts for various membrane fouling mechanisms (adsorption, blocking and cake formation); and (iv) predicts the optimum pore profile for our chosen performance measure. NSF DMS-1261596 and NSF DMS-1615719.

Bioaerosol DNA Extraction Technique from Air Filters Collected from Marine and Freshwater Locations

NASA Astrophysics Data System (ADS)

Beckwith, M.; Crandall, S. G.; Barnes, A.; Paytan, A.

2015-12-01

Bioaerosols are composed of microorganisms suspended in air. Among these organisms include bacteria, fungi, virus, and protists. Microbes introduced into the atmosphere can drift, primarily by wind, into natural environments different from their point of origin. Although bioaerosols can impact atmospheric dynamics as well as the ecology and biogeochemistry of terrestrial systems, very little is known about the composition of bioaerosols collected from marine and freshwater environments. The first step to determine composition of airborne microbes is to successfully extract environmental DNA from air filters. We asked 1) can DNA be extracted from quartz (SiO2) air filters? and 2) how can we optimize the DNA yield for downstream metagenomic sequencing? Aerosol filters were collected and archived on a weekly basis from aquatic sites (USA, Bermuda, Israel) over the course of 10 years. We successfully extracted DNA from a subsample of ~ 20 filters. We modified a DNA extraction protocol (Qiagen) by adding a beadbeating step to mechanically shear cell walls in order to optimize our DNA product. We quantified our DNA yield using a spectrophotometer (Nanodrop 1000). Results indicate that DNA can indeed be extracted from quartz filters. The additional beadbeating step helped increase our yield - up to twice as much DNA product was obtained compared to when this step was omitted. Moreover, bioaerosol DNA content does vary across time. For instance, the DNA extracted from filters from Lake Tahoe, USA collected near the end of June decreased from 9.9 ng/μL in 2007 to 3.8 ng/μL in 2008. Further next-generation sequencing analysis of our extracted DNA will be performed to determine the composition of these microbes. We will also model the meteorological and chemical factors that are good predictors for microbial composition for our samples over time and space.

SU-F-J-66: Anatomy Deformation Based Comparison Between One-Step and Two-Step Optimization for Online ART

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Z; Yu, G; Qin, S

Purpose: This study investigated that how the quality of adapted plan was affected by inter-fractional anatomy deformation by using one-step and two-step optimization for on line adaptive radiotherapy (ART) procedure. Methods: 10 lung carcinoma patients were chosen randomly to produce IMRT plan by one-step and two-step algorithms respectively, and the prescribed dose was set as 60 Gy on the planning target volume (PTV) for all patients. To simulate inter-fractional target deformation, four specific cases were created by systematic anatomy variation; including target superior shift 0.5 cm, 0.3cm contraction, 0.3 cm expansion and 45-degree rotation. Based on these four anatomy deformation,more » adapted plan, regenerated plan and non-adapted plan were created to evaluate quality of adaptation. Adapted plans were generated automatically by using one-step and two-step algorithms respectively to optimize original plans, and regenerated plans were manually created by experience physicists. Non-adapted plans were produced by recalculating the dose distribution based on corresponding original plans. The deviations among these three plans were statistically analyzed by paired T-test. Results: In PTV superior shift case, adapted plans had significantly better PTV coverage by using two-step algorithm compared with one-step one, and meanwhile there was a significant difference of V95 by comparison with adapted and non-adapted plans (p=0.0025). In target contraction deformation, with almost same PTV coverage, the total lung received lower dose using one-step algorithm than two-step algorithm (p=0.0143,0.0126 for V20, Dmean respectively). In other two deformation cases, there were no significant differences observed by both two optimized algorithms. Conclusion: In geometry deformation such as target contraction, with comparable PTV coverage, one-step algorithm gave better OAR sparing than two-step algorithm. Reversely, the adaptation by using two-step algorithm had higher

Optimal design of FIR triplet halfband filter bank and application in image coding.

PubMed

Kha, H H; Tuan, H D; Nguyen, T Q

2011-02-01

This correspondence proposes an efficient semidefinite programming (SDP) method for the design of a class of linear phase finite impulse response triplet halfband filter banks whose filters have optimal 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 filter bank are provided for illustration and comparison with previous works. Finally, the image coding performance of the filter bank is presented.

Systematic Biological Filter Design with a Desired I/O Filtering Response Based on Promoter-RBS Libraries.

PubMed

Hsu, Chih-Yuan; Pan, Zhen-Ming; Hu, Rei-Hsing; Chang, Chih-Chun; Cheng, Hsiao-Chun; Lin, Che; Chen, Bor-Sen

2015-01-01

In this study, robust biological filters with an external control to match a desired input/output (I/O) filtering response are engineered based on the well-characterized promoter-RBS libraries and a cascade gene circuit topology. In the field of synthetic biology, the biological filter system serves as a powerful detector or sensor to sense different molecular signals and produces a specific output response only if the concentration of the input molecular signal is higher or lower than a specified threshold. The proposed systematic design method of robust biological filters is summarized into three steps. Firstly, several well-characterized promoter-RBS libraries are established for biological filter design by identifying and collecting the quantitative and qualitative characteristics of their promoter-RBS components via nonlinear parameter estimation method. Then, the topology of synthetic biological filter is decomposed into three cascade gene regulatory modules, and an appropriate promoter-RBS library is selected for each module to achieve the desired I/O specification of a biological filter. Finally, based on the proposed systematic method, a robust externally tunable biological filter is engineered by searching the promoter-RBS component libraries and a control inducer concentration library to achieve the optimal reference match for the specified I/O filtering response.

Approximation of optimal filter for Ornstein-Uhlenbeck process with quantised discrete-time observation

NASA Astrophysics Data System (ADS)

Bania, Piotr; Baranowski, Jerzy

2018-02-01

Quantisation of signals is a ubiquitous property of digital processing. In many cases, it introduces significant difficulties in state estimation and in consequence control. Popular approaches either do not address properly the problem of system disturbances or lead to biased estimates. Our intention was to find a method for state estimation for stochastic systems with quantised and discrete observation, that is free of the mentioned drawbacks. We have formulated a general form of the optimal filter derived by a solution of Fokker-Planck equation. We then propose the approximation method based on Galerkin projections. We illustrate the approach for the Ornstein-Uhlenbeck process, and derive analytic formulae for the approximated optimal filter, also extending the results for the variant with control. Operation is illustrated with numerical experiments and compared with classical discrete-continuous Kalman filter. Results of comparison are substantially in favour of our approach, with over 20 times lower mean squared error. The proposed filter is especially effective for signal amplitudes comparable to the quantisation thresholds. Additionally, it was observed that for high order of approximation, state estimate is very close to the true process value. The results open the possibilities of further analysis, especially for more complex processes.

Blurred image restoration using knife-edge function and optimal window Wiener filtering.

PubMed

Wang, Min; Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects.

Blurred image restoration using knife-edge function and optimal window Wiener filtering

PubMed Central

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

Exploring an optimal wavelet-based filter for cryo-ET imaging.

PubMed

Huang, Xinrui; Li, Sha; Gao, Song

2018-02-07

Cryo-electron tomography (cryo-ET) is one of the most advanced technologies for the in situ visualization of molecular machines by producing three-dimensional (3D) biological structures. However, cryo-ET imaging has two serious disadvantages-low dose and low image contrast-which result in high-resolution information being obscured by noise and image quality being degraded, and this causes errors in biological interpretation. The purpose of this research is to explore an optimal wavelet denoising technique to reduce noise in cryo-ET images. We perform tests using simulation data and design a filter using the optimum selected wavelet parameters (three-level decomposition, level-1 zeroed out, subband-dependent threshold, a soft-thresholding and spline-based discrete dyadic wavelet transform (DDWT)), which we call a modified wavelet shrinkage filter; this filter is suitable for noisy cryo-ET data. When testing using real cryo-ET experiment data, higher quality images and more accurate measures of a biological structure can be obtained with the modified wavelet shrinkage filter processing compared with conventional processing. Because the proposed method provides an inherent advantage when dealing with cryo-ET images, it can therefore extend the current state-of-the-art technology in assisting all aspects of cryo-ET studies: visualization, reconstruction, structural analysis, and interpretation.

Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-11-30

Common spatial pattern (CSP) has been most popularly applied to motor-imagery (MI) feature extraction for classification in brain-computer interface (BCI) application. Successful application of CSP depends on the filter band selection to a large degree. However, the most proper band is typically subject-specific and can hardly be determined manually. This study proposes a sparse filter band common spatial pattern (SFBCSP) for optimizing the spatial patterns. SFBCSP estimates CSP features on multiple signals that are filtered from raw EEG data at a set of overlapping bands. The filter bands that result in significant CSP features are then selected in a supervised way by exploiting sparse regression. A support vector machine (SVM) is implemented on the selected features for MI classification. Two public EEG datasets (BCI Competition III dataset IVa and BCI Competition IV IIb) are used to validate the proposed SFBCSP method. Experimental results demonstrate that SFBCSP help improve the classification performance of MI. The optimized spatial patterns by SFBCSP give overall better MI classification accuracy in comparison with several competing methods. The proposed SFBCSP is a potential method for improving the performance of MI-based BCI. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimized FPGA Implementation of Multi-Rate FIR Filters Through Thread Decomposition

NASA Technical Reports Server (NTRS)

Zheng, Jason Xin; Nguyen, Kayla; He, Yutao

2010-01-01

Multirate (decimation/interpolation) filters are among the essential signal processing components in spaceborne instruments where Finite Impulse Response (FIR) filters are often used to minimize nonlinear group delay and finite-precision effects. Cascaded (multi-stage) designs of Multi-Rate FIR (MRFIR) filters are further used for large rate change ratio, in order to lower the required throughput while simultaneously achieving comparable or better performance than single-stage designs. Traditional representation and implementation of MRFIR employ polyphase decomposition of the original filter structure, whose main purpose is to compute only the needed output at the lowest possible sampling rate. In this paper, an alternative representation and implementation technique, called TD-MRFIR (Thread Decomposition MRFIR), is presented. The basic idea is to decompose MRFIR into output computational threads, in contrast to a structural decomposition of the original filter as done in the polyphase decomposition. Each thread represents an instance of the finite convolution required to produce a single output of the MRFIR. The filter is thus viewed as a finite collection of concurrent threads. The technical details of TD-MRFIR will be explained, first showing its applicability to the implementation of downsampling, upsampling, and resampling FIR filters, and then describing a general strategy to optimally allocate the number of filter taps. A particular FPGA design of multi-stage TD-MRFIR for the L-band radar of NASA's SMAP (Soil Moisture Active Passive) instrument is demonstrated; and its implementation results in several targeted FPGA devices are summarized in terms of the functional (bit width, fixed-point error) and performance (time closure, resource usage, and power estimation) parameters.

Stochastic simulation and robust design optimization of integrated photonic filters

NASA Astrophysics Data System (ADS)

Weng, Tsui-Wei; Melati, Daniele; Melloni, Andrea; Daniel, Luca

2017-01-01

Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic coupled ring resonator filters are considered as an example of significant interest. The sparsity structure in photonic circuits is exploited to construct a sparse combined generalized polynomial chaos model, which is then used to analyze related statistics and perform robust design optimization. Simulation results show that the optimized circuits are more robust to fabrication process variations and achieve a reduction of 11%-35% in the mean square errors of the 3 dB bandwidth compared to unoptimized nominal designs.

DC-pass filter design with notch filters superposition for CPW rectenna at low power level

NASA Astrophysics Data System (ADS)

Rivière, J.; Douyère, A.; Alicalapa, F.; Luk, J.-D. Lan Sun

2016-03-01

In this paper the challenging coplanar waveguide direct current (DC) pass filter is designed, analysed, fabricated and measured. As the ground plane and the conductive line are etched on the same plane, this technology allows the connection of series and shunt elements to the active devices without via holes through the substrate. Indeed, this study presents the first step in the optimization of a complete rectenna in coplanar waveguide (CPW) technology: key element of a radio frequency (RF) energy harvesting system. The measurement of the proposed filter shows good performance in the rejection of F0=2.45 GHz and F1=4.9 GHz. Additionally, a harmonic balance (HB) simulation of the complete rectenna is performed and shows a maximum RF-to-DC conversion efficiency of 37% with the studied DC-pass filter for an input power of 10 µW at 2.45 GHz.

GPU Accelerated Vector Median Filter

NASA Technical Reports Server (NTRS)

Aras, Rifat; Shen, Yuzhong

2011-01-01

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

Creation of an iOS and Android Mobile Application for Inferior Vena Cava (IVC) Filters: A Powerful Tool to Optimize Care of Patients with IVC Filters

PubMed Central

Deso, Steven E.; Idakoji, Ibrahim A.; Muelly, Michael C.; Kuo, William T.

2016-01-01

Owing to a myriad of inferior vena cava (IVC) filter types and their potential complications, rapid and correct identification may be challenging when encountered on routine imaging. The authors aimed to develop an interactive mobile application that allows recognition of all IVC filters and related complications, to optimize the care of patients with indwelling IVC filters. The FDA Premarket Notification Database was queried from 1980 to 2014 to identify all IVC filter types in the United States. An electronic search was then performed on MEDLINE and the FDA MAUDE database to identify all reported complications associated with each device. High-resolution photos were taken of each filter type and corresponding computed tomographic and fluoroscopic images were obtained from an institutional review board–approved IVC filter registry. A wireframe and storyboard were created, and software was developed using HTML5/CSS compliant code. The software was deployed using PhoneGap (Adobe, San Jose, CA), and the prototype was tested and refined. Twenty-three IVC filter types were identified for inclusion. Safety data from FDA MAUDE and 72 relevant peer-reviewed studies were acquired, and complication rates for each filter type were highlighted in the application. Digital photos, fluoroscopic images, and CT DICOM files were seamlessly incorporated. All data were succinctly organized electronically, and the software was successfully deployed into Android (Google, Mountain View, CA) and iOS (Apple, Cupertino, CA) platforms. A powerful electronic mobile application was successfully created to allow rapid identification of all IVC filter types and related complications. This application may be used to optimize the care of patients with IVC filters. PMID:27247483

Creation of an iOS and Android Mobile Application for Inferior Vena Cava (IVC) Filters: A Powerful Tool to Optimize Care of Patients with IVC Filters.

PubMed

Deso, Steven E; Idakoji, Ibrahim A; Muelly, Michael C; Kuo, William T

2016-06-01

Owing to a myriad of inferior vena cava (IVC) filter types and their potential complications, rapid and correct identification may be challenging when encountered on routine imaging. The authors aimed to develop an interactive mobile application that allows recognition of all IVC filters and related complications, to optimize the care of patients with indwelling IVC filters. The FDA Premarket Notification Database was queried from 1980 to 2014 to identify all IVC filter types in the United States. An electronic search was then performed on MEDLINE and the FDA MAUDE database to identify all reported complications associated with each device. High-resolution photos were taken of each filter type and corresponding computed tomographic and fluoroscopic images were obtained from an institutional review board-approved IVC filter registry. A wireframe and storyboard were created, and software was developed using HTML5/CSS compliant code. The software was deployed using PhoneGap (Adobe, San Jose, CA), and the prototype was tested and refined. Twenty-three IVC filter types were identified for inclusion. Safety data from FDA MAUDE and 72 relevant peer-reviewed studies were acquired, and complication rates for each filter type were highlighted in the application. Digital photos, fluoroscopic images, and CT DICOM files were seamlessly incorporated. All data were succinctly organized electronically, and the software was successfully deployed into Android (Google, Mountain View, CA) and iOS (Apple, Cupertino, CA) platforms. A powerful electronic mobile application was successfully created to allow rapid identification of all IVC filter types and related complications. This application may be used to optimize the care of patients with IVC filters.

Optimal filter bandwidth for pulse oximetry

NASA Astrophysics Data System (ADS)

Stuban, Norbert; Niwayama, Masatsugu

2012-10-01

Pulse oximeters contain one or more signal filtering stages between the photodiode and microcontroller. These filters are responsible for removing the noise while retaining the useful frequency components of the signal, thus improving the signal-to-noise ratio. The corner frequencies of these filters affect not only the noise level, but also the shape of the pulse signal. Narrow filter bandwidth effectively suppresses the noise; however, at the same time, it distorts the useful signal components by decreasing the harmonic content. In this paper, we investigated the influence of the filter bandwidth on the accuracy of pulse oximeters. We used a pulse oximeter tester device to produce stable, repetitive pulse waves with digitally adjustable R ratio and heart rate. We built a pulse oximeter and attached it to the tester device. The pulse oximeter digitized the current of its photodiode directly, without any analog signal conditioning. We varied the corner frequency of the low-pass filter in the pulse oximeter in the range of 0.66-15 Hz by software. For the tester device, the R ratio was set to R = 1.00, and the R ratio deviation measured by the pulse oximeter was monitored as a function of the corner frequency of the low-pass filter. The results revealed that lowering the corner frequency of the low-pass filter did not decrease the accuracy of the oxygen level measurements. The lowest possible value of the corner frequency of the low-pass filter is the fundamental frequency of the pulse signal. We concluded that the harmonics of the pulse signal do not contribute to the accuracy of pulse oximetry. The results achieved by the pulse oximeter tester were verified by human experiments, performed on five healthy subjects. The results of the human measurements confirmed that filtering out the harmonics of the pulse signal does not degrade the accuracy of pulse oximetry.

Optimal filter bandwidth for pulse oximetry.

PubMed

Stuban, Norbert; Niwayama, Masatsugu

2012-10-01

Pulse oximeters contain one or more signal filtering stages between the photodiode and microcontroller. These filters are responsible for removing the noise while retaining the useful frequency components of the signal, thus improving the signal-to-noise ratio. The corner frequencies of these filters affect not only the noise level, but also the shape of the pulse signal. Narrow filter bandwidth effectively suppresses the noise; however, at the same time, it distorts the useful signal components by decreasing the harmonic content. In this paper, we investigated the influence of the filter bandwidth on the accuracy of pulse oximeters. We used a pulse oximeter tester device to produce stable, repetitive pulse waves with digitally adjustable R ratio and heart rate. We built a pulse oximeter and attached it to the tester device. The pulse oximeter digitized the current of its photodiode directly, without any analog signal conditioning. We varied the corner frequency of the low-pass filter in the pulse oximeter in the range of 0.66-15 Hz by software. For the tester device, the R ratio was set to R = 1.00, and the R ratio deviation measured by the pulse oximeter was monitored as a function of the corner frequency of the low-pass filter. The results revealed that lowering the corner frequency of the low-pass filter did not decrease the accuracy of the oxygen level measurements. The lowest possible value of the corner frequency of the low-pass filter is the fundamental frequency of the pulse signal. We concluded that the harmonics of the pulse signal do not contribute to the accuracy of pulse oximetry. The results achieved by the pulse oximeter tester were verified by human experiments, performed on five healthy subjects. The results of the human measurements confirmed that filtering out the harmonics of the pulse signal does not degrade the accuracy of pulse oximetry.

Nonlinear Attitude Filtering Methods

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Crassidis, John L.; Cheng, Yang

2005-01-01

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

Nonlinear Motion Cueing Algorithm: Filtering at Pilot Station and Development of the Nonlinear Optimal Filters for Pitch and Roll

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Telban and Cardullo have developed and successfully implemented the non-linear optimal motion cueing algorithm at the Visual Motion Simulator (VMS) at the NASA Langley Research Center in 2005. The latest version of the non-linear algorithm performed filtering of motion cues in all degrees-of-freedom except for pitch and roll. This manuscript describes the development and implementation of the non-linear optimal motion cueing algorithm for the pitch and roll degrees of freedom. Presented results indicate improved cues in the specified channels as compared to the original design. To further advance motion cueing in general, this manuscript describes modifications to the existing algorithm, which allow for filtering at the location of the pilot's head as opposed to the centroid of the motion platform. The rational for such modification to the cueing algorithms is that the location of the pilot's vestibular system must be taken into account as opposed to the off-set of the centroid of the cockpit relative to the center of rotation alone. Results provided in this report suggest improved performance of the motion cueing algorithm.

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

Optimizing The Number Of Steps In Learning Tasks For Complex Skills

ERIC Educational Resources Information Center

Nadolski, Rob J.; Kirschner, Paul A.; van Merrienboer, Jeroen J.G.

2005-01-01

Background: Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimized for efficient and effective learning. Aim: The aim of the study is to investigate the relation between the number of…

Multidisciplinary Analysis and Optimization Generation 1 and Next Steps

NASA Technical Reports Server (NTRS)

Naiman, Cynthia Gutierrez

2008-01-01

The Multidisciplinary Analysis & Optimization Working Group (MDAO WG) of the Systems Analysis Design & Optimization (SAD&O) discipline in the Fundamental Aeronautics Program s Subsonic Fixed Wing (SFW) project completed three major milestones during Fiscal Year (FY)08: "Requirements Definition" Milestone (1/31/08); "GEN 1 Integrated Multi-disciplinary Toolset" (Annual Performance Goal) (6/30/08); and "Define Architecture & Interfaces for Next Generation Open Source MDAO Framework" Milestone (9/30/08). Details of all three milestones are explained including documentation available, potential partner collaborations, and next steps in FY09.

Optimization of ecosystem model parameters with different temporal variabilities using tower flux data and an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

He, L.; Chen, J. M.; Liu, J.; Mo, G.; Zhen, T.; Chen, B.; Wang, R.; Arain, M.

2013-12-01

Terrestrial ecosystem models have been widely used to simulate carbon, water and energy fluxes and climate-ecosystem interactions. In these models, some vegetation and soil parameters are determined based on limited studies from literatures without consideration of their seasonal variations. Data assimilation (DA) provides an effective way to optimize these parameters at different time scales . In this study, an ensemble Kalman filter (EnKF) is developed and applied to optimize two key parameters of an ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS): (1) the maximum photosynthetic carboxylation rate (Vcmax) at 25 °C, and (2) the soil water stress factor (fw) for stomatal conductance formulation. These parameters are optimized through assimilating observations of gross primary productivity (GPP) and latent heat (LE) fluxes measured in a 74 year-old pine forest, which is part of the Turkey Point Flux Station's age-sequence sites. Vcmax is related to leaf nitrogen concentration and varies slowly over the season and from year to year. In contrast, fw varies rapidly in response to soil moisture dynamics in the root-zone. Earlier studies suggested that DA of vegetation parameters at daily time steps leads to Vcmax values that are unrealistic. To overcome the problem, we developed a three-step scheme to optimize Vcmax and fw. First, the EnKF is applied daily to obtain precursor estimates of Vcmax and fw. Then Vcmax is optimized at different time scales assuming fw is unchanged from first step. The best temporal period or window size is then determined by analyzing the magnitude of the minimized cost-function, and the coefficient of determination (R2) and Root-mean-square deviation (RMSE) of GPP and LE between simulation and observation. Finally, the daily fw value is optimized for rain free days corresponding to the Vcmax curve from the best window size. The optimized fw is then used to model its relationship with soil moisture. We found that

Design optimization of integrated BiDi triplexer optical filter based on planar lightwave circuit.

PubMed

Xu, Chenglin; Hong, Xiaobin; Huang, Wei-Ping

2006-05-29

Design optimization of a novel integrated bi-directional (BiDi) triplexer filter based on planar lightwave circuit (PLC) for fiber-to-the premise (FTTP) applications is described. A multi-mode interference (MMI) device is used to filter 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 filter spectral characteristics (e.g., bandwidth, cross-talk, etc.) as well as insertion loss.

Design optimization of integrated BiDi triplexer optical filter based on planar lightwave circuit

NASA Astrophysics Data System (ADS)

Xu, Chenglin; Hong, Xiaobin; Huang, Wei-Ping

2006-05-01

Design optimization of a novel integrated bi-directional (BiDi) triplexer filter based on planar lightwave circuit (PLC) for fiber-to-the premise (FTTP) applications is described. A multi-mode interference (MMI) device is used to filter 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 filter spectral characteristics (e.g., bandwidth, cross-talk, etc.) as well as insertion loss.

Signal-to-noise enhancement techniques for quantum cascade absorption spectrometers employing optimal filtering and other approaches

NASA Astrophysics Data System (ADS)

Disselkamp, R. S.; Kelly, J. F.; Sams, R. L.; Anderson, G. A.

Optical feedback to the laser source in tunable diode laser spectroscopy (TDLS) is known to create intensity modulation noise due to elatoning and optical feedback (i.e. multiplicative technical noise) that usually limits spectral signal-to-noise (S/N). The large technical noise often limits absorption spectroscopy to noise floors 100-fold greater than the Poisson shot noise limit due to fluctuations in the laser intensity. The high output powers generated from quantum cascade (QC) lasers, along with their high gain, makes these injection laser systems especially susceptible to technical noise. In this article we discuss a method of using optimal filtering to reduce technical noise. We have observed S/N enhancements ranging from 20% to a factor of 50. The degree to which optimal filtering enhances S/N depends on the similarity between the Fourier components of the technical noise and those of the signal, with lower S/N enhancements observed for more similar Fourier decompositions of the signal and technical noise. We also examine the linearity of optimal filtered spectra in both time and intensity. This was accomplished by creating a synthetic spectrum for the species being studied (CH4, N2O, CO2 and H2O in ambient air) utilizing line positions and linewidths with an assumed Voigt profile from a commercial database (HITRAN). Agreement better than 0.036% in wavenumber and 1.64% in intensity (up to a 260-fold intensity ratio employed) was observed. Our results suggest that rapid ex post facto digital optimal filtering can be used to enhance S/N for routine trace gas detection.

Optimization of self-acting step thrust bearings for load capacity and stiffness.

NASA Technical Reports Server (NTRS)

Hamrock, B. J.

1972-01-01

Linearized analysis of a finite-width rectangular step thrust bearing. Dimensionless load capacity and stiffness are expressed in terms of a Fourier cosine series. The dimensionless load capacity and stiffness were found to be a function of the dimensionless bearing number, the pad length-to-width ratio, the film thickness ratio, the step location parameter, and the feed groove parameter. The equations obtained in the analysis were verified. The assumptions imposed were substantiated by comparing the results with an existing exact solution for the infinite width bearing. A digital computer program was developed which determines optimal bearing configuration for maximum load capacity or stiffness. Simple design curves are presented. Results are shown for both compressible and incompressible lubrication. Through a parameter transformation the results are directly usable in designing optimal step sector thrust bearings.

Comparison of filtering methods for extracellular gastric slow wave recordings.

PubMed

Paskaranandavadivel, Niranchan; O'Grady, Gregory; Du, Peng; Cheng, Leo K

2013-01-01

Extracellular recordings are used to define gastric slow wave propagation. Signal filtering is a key step in the analysis and interpretation of extracellular slow wave data; however, there is controversy and uncertainty regarding the appropriate filtering settings. This study investigated the effect of various standard filters on the morphology and measurement of extracellular gastric slow waves. Experimental extracellular gastric slow waves were recorded from the serosal surface of the stomach from pigs and humans. Four digital filters: finite impulse response filter (0.05-1 Hz); Savitzky-Golay filter (0-1.98 Hz); Bessel filter (2-100 Hz); and Butterworth filter (5-100 Hz); were applied on extracellular gastric slow wave signals to compare the changes temporally (morphology of the signal) and spectrally (signals in the frequency domain). The extracellular slow wave activity is represented in the frequency domain by a dominant frequency and its associated harmonics in diminishing power. Optimal filters apply cutoff frequencies consistent with the dominant slow wave frequency (3-5 cpm) and main harmonics (up to ≈ 2 Hz). Applying filters with cutoff frequencies above or below the dominant and harmonic frequencies was found to distort or eliminate slow wave signal content. Investigators must be cognizant of these optimal filtering practices when detecting, analyzing, and interpreting extracellular slow wave recordings. The use of frequency domain analysis is important for identifying the dominant and harmonics of the signal of interest. Capturing the dominant frequency and major harmonics of slow wave is crucial for accurate representation of slow wave activity in the time domain. Standardized filter settings should be determined. © 2012 Blackwell Publishing Ltd.

Optimization of a matched-filter receiver for frequency hopping code acquisition in jamming

NASA Astrophysics Data System (ADS)

Pawlowski, P. R.; Polydoros, A.

A matched-filter receiver for frequency hopping (FH) code acquisition is optimized when either partial-band tone jamming or partial-band Gaussian noise jamming is present. The receiver is matched to a segment of the FH code sequence, sums hard per-channel decisions to form a test, and uses multiple tests to verify acquisition. The length of the matched filter and the number of verification tests are fixed. Optimization is then choosing thresholds to maximize performance based upon the receiver's degree of knowledge about the jammer ('side-information'). Four levels of side-information are considered, ranging from none to complete. The latter level results in a constant-false-alarm-rate (CFAR) design. At each level, performance sensitivity to threshold choice is analyzed. Robust thresholds are chosen to maximize performance as the jammer varies its power distribution, resulting in simple design rules which aid threshold selection. Performance results, which show that optimum distributions for the jammer power over the total FH bandwidth exist, are presented.

An optimized Kalman filter for the estimate of trunk orientation from inertial sensors data during treadmill walking.

PubMed

Mazzà, Claudia; Donati, Marco; McCamley, John; Picerno, Pietro; Cappozzo, Aurelio

2012-01-01

The aim of this study was the fine tuning of a Kalman filter with the intent to provide optimal estimates of lower trunk orientation in the frontal and sagittal planes during treadmill walking at different speeds using measured linear acceleration and angular velocity components represented in a local system of reference. Data were simultaneously collected using both an inertial measurement unit (IMU) and a stereophotogrammetric system from three healthy subjects walking on a treadmill at natural, slow and fast speeds. These data were used to estimate the parameters of the Kalman filter that minimized the difference between the trunk orientations provided by the filter and those obtained through stereophotogrammetry. The optimized parameters were then used to process the data collected from a further 15 healthy subjects of both genders and different anthropometry performing the same walking tasks with the aim of determining the robustness of the filter set up. The filter proved to be very robust. The root mean square values of the differences between the angles estimated through the IMU and through stereophotogrammetry were lower than 1.0° and the correlation coefficients between the corresponding curves were greater than 0.91. The proposed filter design can be used to reliably estimate trunk lateral and frontal bending during walking from inertial sensor data. Further studies are needed to determine the filter parameters that are most suitable for other motor tasks. Copyright © 2011. Published by Elsevier B.V.

SU-E-I-57: Evaluation and Optimization of Effective-Dose Using Different Beam-Hardening Filters in Clinical Pediatric Shunt CT Protocol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gill, K; Aldoohan, S; Collier, J

Purpose: Study image optimization and radiation dose reduction in pediatric shunt CT scanning protocol through the use of different beam-hardening filters Methods: A 64-slice CT scanner at OU Childrens Hospital has been used to evaluate CT image contrast-to-noise ratio (CNR) and measure effective-doses based on the concept of CT dose index (CTDIvol) using the pediatric head shunt scanning protocol. The routine axial pediatric head shunt scanning protocol that has been optimized for the intrinsic x-ray tube filter has been used to evaluate CNR by acquiring images using the ACR approved CT-phantom and radiation dose CTphantom, which was used to measuremore » CTDIvol. These results were set as reference points to study and evaluate the effects of adding different filtering materials (i.e. Tungsten, Tantalum, Titanium, Nickel and Copper filters) to the existing filter on image quality and radiation dose. To ensure optimal image quality, the scanner routine air calibration was run for each added filter. The image CNR was evaluated for different kVps and wide range of mAs values using above mentioned beam-hardening filters. These scanning protocols were run under axial as well as under helical techniques. The CTDIvol and the effective-dose were measured and calculated for all scanning protocols and added filtration, including the intrinsic x-ray tube filter. Results: Beam-hardening filter shapes energy spectrum, which reduces the dose by 27%. No noticeable changes in image low contrast detectability Conclusion: Effective-dose is very much dependent on the CTDIVol, which is further very much dependent on beam-hardening filters. Substantial reduction in effective-dose is realized using beam-hardening filters as compare to the intrinsic filter. This phantom study showed that significant radiation dose reduction could be achieved in CT pediatric shunt scanning protocols without compromising in diagnostic value of image quality.« less

A Machine-Learning and Filtering Based Data Assimilation Framework for Geologic Carbon Sequestration Monitoring Optimization

NASA Astrophysics Data System (ADS)

Chen, B.; Harp, D. R.; Lin, Y.; Keating, E. H.; Pawar, R.

2017-12-01

Monitoring is a crucial aspect of geologic carbon sequestration (GCS) risk management. It has gained importance as a means to ensure CO2 is safely and permanently stored underground throughout the lifecycle of a GCS project. Three issues are often involved in a monitoring project: (i) where is the optimal location to place the monitoring well(s), (ii) what type of data (pressure, rate and/or CO2 concentration) should be measured, and (iii) What is the optimal frequency to collect the data. In order to address these important issues, a filtering-based data assimilation procedure is developed to perform the monitoring optimization. The optimal monitoring strategy is selected based on the uncertainty reduction of the objective of interest (e.g., cumulative CO2 leak) for all potential monitoring strategies. To reduce the computational cost of the filtering-based data assimilation process, two machine-learning algorithms: Support Vector Regression (SVR) and Multivariate Adaptive Regression Splines (MARS) are used to develop the computationally efficient reduced-order-models (ROMs) from full numerical simulations of CO2 and brine flow. The proposed framework for GCS monitoring optimization is demonstrated with two examples: a simple 3D synthetic case and a real field case named Rock Spring Uplift carbon storage site in Southwestern Wyoming.

Nonlinear optimal filter technique for analyzing energy depositions in TES sensors driven into saturation

DOE PAGES

Shank, B.; Yen, J. J.; Cabrera, B.; ...

2014-11-04

We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs) connected to quasiparticle (qp) traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search) Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.

Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

2014-12-01

Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

Sub-wavelength efficient polarization filter (SWEP filter)

DOEpatents

Simpson, Marcus L.; Simpson, John T.

2003-12-09

A polarization sensitive filter includes a first sub-wavelength resonant grating structure (SWS) for receiving incident light, and a second SWS. The SWS are disposed relative to one another such that incident light which is transmitted by the first SWS passes through the second SWS. The filter has a polarization sensitive resonance, the polarization sensitive resonance substantially reflecting a first polarization component of incident light while substantially transmitting a second polarization component of the incident light, the polarization components being orthogonal to one another. A method for forming polarization filters includes the steps of forming first and second SWS, the first and second SWS disposed relative to one another such that a portion of incident light applied to the first SWS passes through the second SWS. A method for separating polarizations of light, includes the steps of providing a filter formed from a first and second SWS, shining incident light having orthogonal polarization components on the first SWS, and substantially reflecting one of the orthogonal polarization components while substantially transmitting the other orthogonal polarization component. A high Q narrowband filter includes a first and second SWS, the first and second SWS are spaced apart a distance being at least one half an optical wavelength.

Fishing for drifts: detecting buoyancy changes of a top marine predator using a step-wise filtering method

PubMed Central

Gordine, Samantha Alex; Fedak, Michael; Boehme, Lars

2015-01-01

ABSTRACT In southern elephant seals (Mirounga leonina), fasting- and foraging-related fluctuations in body composition are reflected by buoyancy changes. Such buoyancy changes can be monitored by measuring changes in the rate at which a seal drifts passively through the water column, i.e. when all active swimming motion ceases. Here, we present an improved knowledge-based method for detecting buoyancy changes from compressed and abstracted dive profiles received through telemetry. By step-wise filtering of the dive data, the developed algorithm identifies fragments of dives that correspond to times when animals drift. In the dive records of 11 southern elephant seals from South Georgia, this filtering method identified 0.8–2.2% of all dives as drift dives, indicating large individual variation in drift diving behaviour. The obtained drift rate time series exhibit that, at the beginning of each migration, all individuals were strongly negatively buoyant. Over the following 75–150 days, the buoyancy of all individuals peaked close to or at neutral buoyancy, indicative of a seal's foraging success. Independent verification with visually inspected detailed high-resolution dive data confirmed that this method is capable of reliably detecting buoyancy changes in the dive records of drift diving species using abstracted data. This also affirms that abstracted dive profiles convey the geometric shape of drift dives in sufficient detail for them to be identified. Further, it suggests that, using this step-wise filtering method, buoyancy changes could be detected even in old datasets with compressed dive information, for which conventional drift dive classification previously failed. PMID:26486362

Compressive spectral testbed imaging system based on thin-film color-patterned filter arrays.

PubMed

Rueda, Hoover; Arguello, Henry; Arce, Gonzalo R

2016-11-20

Compressive spectral imaging systems can reliably capture multispectral data using far fewer measurements than traditional scanning techniques. In this paper, a thin-film patterned filter array-based compressive spectral imager is demonstrated, including its optical design and implementation. The use of a patterned filter array entails a single-step three-dimensional spatial-spectral coding on the input data cube, which provides higher flexibility on the selection of voxels being multiplexed on the sensor. The patterned filter array is designed and fabricated with micrometer pitch size thin films, referred to as pixelated filters, with three different wavelengths. The performance of the system is evaluated in terms of references measured by a commercially available spectrometer and the visual quality of the reconstructed images. Different distributions of the pixelated filters, including random and optimized structures, are explored.

Technology optimization techniques for multicomponent optical band-pass filter manufacturing

NASA Astrophysics Data System (ADS)

Baranov, Yuri P.; Gryaznov, Georgiy M.; Rodionov, Andrey Y.; Obrezkov, Andrey V.; Medvedev, Roman V.; Chivanov, Alexey N.

2016-04-01

Narrowband optical devices (like IR-sensing devices, celestial navigation systems, solar-blind UV-systems and many others) are one of the most fast-growing areas in optical manufacturing. However, signal strength in this type of applications is quite low and performance of devices depends on attenuation level of wavelengths out of operating range. Modern detectors (photodiodes, matrix detectors, photomultiplier tubes and others) usually do not have required selectivity or have higher sensitivity to background spectrum at worst. Manufacturing of a single component band-pass filter with high attenuation level of wavelength is resource-intensive task. Sometimes it's not possible to find solution for this problem using existing technologies. Different types of filters have technology variations of transmittance profile shape due to various production factors. At the same time there are multiple tasks with strict requirements for background spectrum attenuation in narrowband optical devices. For example, in solar-blind UV-system wavelengths above 290-300 nm must be attenuated by 180dB. In this paper techniques of multi-component optical band-pass filters assembly from multiple single elements with technology variations of transmittance profile shape for optimal signal-tonoise ratio (SNR) were proposed. Relationships between signal-to-noise ratio and different characteristics of transmittance profile shape were shown. Obtained practical results were in rather good agreement with our calculations.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, Jan P.; Ochoa, Ellen; Sweeney, Donald W.

1990-01-01

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.

Optimal filter design with progressive genetic algorithm for local damage detection in rolling bearings

NASA Astrophysics Data System (ADS)

Wodecki, Jacek; Michalak, Anna; Zimroz, Radoslaw

2018-03-01

Harsh industrial conditions present in underground mining cause a lot of difficulties for local damage detection in heavy-duty machinery. For vibration signals one of the most intuitive approaches of obtaining signal with expected properties, such as clearly visible informative features, is prefiltration with appropriately prepared filter. Design of such filter is very broad field of research on its own. In this paper authors propose a novel approach to dedicated optimal filter design using progressive genetic algorithm. Presented method is fully data-driven and requires no prior knowledge of the signal. It has been tested against a set of real and simulated data. Effectiveness of operation has been proven for both healthy and damaged case. Termination criterion for evolution process was developed, and diagnostic decision making feature has been proposed for final result determinance.

Pixelated filters for spatial imaging

NASA Astrophysics Data System (ADS)

Mathieu, Karine; Lequime, Michel; Lumeau, Julien; Abel-Tiberini, Laetitia; Savin De Larclause, Isabelle; Berthon, Jacques

2015-10-01

Small satellites are often used by spatial agencies to meet scientific spatial mission requirements. Their payloads are composed of various instruments collecting an increasing amount of data, as well as respecting the growing constraints relative to volume and mass; So small-sized integrated camera have taken a favored place among these instruments. To ensure scene specific color information sensing, pixelated filters seem to be more attractive than filter wheels. The work presented here, in collaboration with Institut Fresnel, deals with the manufacturing of this kind of component, based on thin film technologies and photolithography processes. CCD detectors with a pixel pitch about 30 μm were considered. In the configuration where the matrix filters are positioned the closest to the detector, the matrix filters are composed of 2x2 macro pixels (e.g. 4 filters). These 4 filters have a bandwidth about 40 nm and are respectively centered at 550, 700, 770 and 840 nm with a specific rejection rate defined on the visible spectral range [500 - 900 nm]. After an intense design step, 4 thin-film structures have been elaborated with a maximum thickness of 5 μm. A run of tests has allowed us to choose the optimal micro-structuration parameters. The 100x100 matrix filters prototypes have been successfully manufactured with lift-off and ion assisted deposition processes. High spatial and spectral characterization, with a dedicated metrology bench, showed that initial specifications and simulations were globally met. These excellent performances knock down the technological barriers for high-end integrated specific multi spectral imaging.

Designing manufacturable filters for a 16-band plenoptic camera using differential evolution

NASA Astrophysics Data System (ADS)

Doster, Timothy; Olson, Colin C.; Fleet, Erin; Yetzbacher, Michael; Kanaev, Andrey; Lebow, Paul; Leathers, Robert

2017-05-01

A 16-band plenoptic camera allows for the rapid exchange of filter sets via a 4x4 filter array on the lens's front aperture. This ability to change out filters allows for an operator to quickly adapt to different locales or threat intelligence. Typically, such a system incorporates a default set of 16 equally spaced at-topped filters. Knowing the operating theater or the likely targets of interest it becomes advantageous to tune the filters. We propose using a modified beta distribution to parameterize the different possible filters and differential evolution (DE) to search over the space of possible filter designs. The modified beta distribution allows us to jointly optimize the width, taper and wavelength center of each single- or multi-pass filter in the set over a number of evolutionary steps. Further, by constraining the function parameters we can develop solutions which are not just theoretical but manufacturable. We examine two independent tasks: general spectral sensing and target detection. In the general spectral sensing task we utilize the theory of compressive sensing (CS) and find filters that generate codings which minimize the CS reconstruction error based on a fixed spectral dictionary of endmembers. For the target detection task and a set of known targets, we train the filters to optimize the separation of the background and target signature. We compare our results to the default 16 at-topped non-overlapping filter set which comes with the plenoptic camera and full hyperspectral resolution data which was previously acquired.

Initial steps of inactivation at the K+ channel selectivity filter

PubMed Central

Thomson, Andrew S.; Heer, Florian T.; Smith, Frank J.; Hendron, Eunan; Bernèche, Simon; Rothberg, Brad S.

2014-01-01

K+ efflux through K+ channels can be controlled by C-type inactivation, which is thought to arise from a conformational change near the channel’s selectivity filter. Inactivation is modulated by ion binding near the selectivity filter; however, the molecular forces that initiate inactivation remain unclear. We probe these driving forces by electrophysiology and molecular simulation of MthK, a prototypical K+ channel. Either Mg2+ or Ca2+ can reduce K+ efflux through MthK channels. However, Ca2+, but not Mg2+, can enhance entry to the inactivated state. Molecular simulations illustrate that, in the MthK pore, Ca2+ ions can partially dehydrate, enabling selective accessibility of Ca2+ to a site at the entry to the selectivity filter. Ca2+ binding at the site interacts with K+ ions in the selectivity filter, facilitating a conformational change within the filter and subsequent inactivation. These results support an ionic mechanism that precedes changes in channel conformation to initiate inactivation. PMID:24733889

Technical note: optimization for improved tube-loading efficiency in the dual-energy computed tomography coupled with balanced filter method.

PubMed

Saito, Masatoshi

2010-08-01

This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.

A two-step crushed lava rock filter unit for grey water treatment at household level in an urban slum.

PubMed

Katukiza, A Y; Ronteltap, M; Niwagaba, C B; Kansiime, F; Lens, P N L

2014-01-15

Decentralised grey water treatment in urban slums using low-cost and robust technologies offers opportunities to minimise public health risks and to reduce environmental pollution caused by the highly polluted grey water i.e. with a COD and N concentration of 3000-6000 mg L(-1) and 30-40 mg L(-1), respectively. However, there has been very limited action research to reduce the pollution load from uncontrolled grey water discharge by households in urban slums. This study was therefore carried out to investigate the potential of a two-step filtration process to reduce the grey water pollution load in an urban slum using a crushed lava rock filter, to determine the main filter design and operation parameters and the effect of intermittent flow on the grey water effluent quality. A two-step crushed lava rock filter unit was designed and implemented for use by a household in the Bwaise III slum in Kampala city (Uganda). It was monitored at a varying hydraulic loading rate (HLR) of 0.5-1.1 m d(-1) as well as at a constant HLR of 0.39 m d(-1). The removal efficiencies of COD, TP and TKN were, respectively, 85.9%, 58% and 65.5% under a varying HLR and 90.5%, 59.5% and 69%, when operating at a constant HLR regime. In addition, the log removal of Escherichia coli, Salmonella spp. and total coliforms was, respectively, 3.8, 3.2 and 3.9 under the varying HLR and 3.9, 3.5 and 3.9 at a constant HLR. The results show that the use of a two-step filtration process as well as a lower constant HLR increased the pollutant removal efficiencies. Further research is needed to investigate the feasibility of adding a tertiary treatment step to increase the nutrients and microorganisms removal from grey water. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optical ranked-order filtering using threshold decomposition

DOEpatents

Allebach, J.P.; Ochoa, E.; Sweeney, D.W.

1987-10-09

A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.

Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method.

PubMed

Saito, Masatoshi

2009-08-01

Dual-energy computed tomography (DECT) has the potential for measuring electron density distribution in a human body to predict the range of particle beams for treatment planning in proton or heavy-ion radiotherapy. However, thus far, a practical dual-energy method that can be used to precisely determine electron density for treatment planning in particle radiotherapy has not been developed. In this article, another DECT technique involving a balanced filter method using a conventional x-ray tube is described. For the spectral optimization of DECT using balanced filters, the author calculates beam-hardening error and air kerma required to achieve a desired noise level in electron density and effective atomic number images of a cylindrical water phantom with 50 cm diameter. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimized parameters were applied to cases with different phantom diameters ranging from 5 to 50 cm for the calculations. The author predicts that the optimal combination of tube voltages would be 80 and 140 kV with Tb/Hf and Bi/Mo filter pairs for the 50-cm-diameter water phantom. When a single phantom calibration at a diameter of 25 cm was employed to cover all phantom sizes, maximum absolute beam-hardening errors were 0.3% and 0.03% for electron density and effective atomic number, respectively, over a range of diameters of the water phantom. The beam-hardening errors were 1/10 or less as compared to those obtained by conventional DECT, although the dose was twice that of the conventional DECT case. From the viewpoint of beam hardening and the tube-loading efficiency, the present DECT using balanced filters would be significantly more effective in measuring the electron density than the conventional DECT. Nevertheless, further developments of low-exposure imaging technology should be necessary as well as x-ray tubes with higher outputs to apply DECT coupled with the

Optimal Matched Filter in the Low-number Count Poisson Noise Regime and Implications for X-Ray Source Detection

NASA Astrophysics Data System (ADS)

Ofek, Eran O.; Zackay, Barak

2018-04-01

Detection of templates (e.g., sources) embedded in low-number count Poisson noise is a common problem in astrophysics. Examples include source detection in X-ray images, γ-rays, UV, neutrinos, and search for clusters of galaxies and stellar streams. However, the solutions in the X-ray-related literature are sub-optimal in some cases by considerable factors. Using the lemma of Neyman–Pearson, we derive the optimal statistics for template detection in the presence of Poisson noise. We demonstrate that, for known template shape (e.g., point sources), this method provides higher completeness, for a fixed false-alarm probability value, compared with filtering the image with the point-spread function (PSF). In turn, we find that filtering by the PSF is better than filtering the image using the Mexican-hat wavelet (used by wavdetect). For some background levels, our method improves the sensitivity of source detection by more than a factor of two over the popular Mexican-hat wavelet filtering. This filtering technique can also be used for fast PSF photometry and flare detection; it is efficient and straightforward to implement. We provide an implementation in MATLAB. The development of a complete code that works on real data, including the complexities of background subtraction and PSF variations, is deferred for future publication.

Optimization of flow cytometric detection and cell sorting of transgenic Plasmodium parasites using interchangeable optical filters

PubMed Central

2012-01-01

Background Malaria remains a major cause of morbidity and mortality worldwide. Flow cytometry-based assays that take advantage of fluorescent protein (FP)-expressing malaria parasites have proven to be valuable tools for quantification and sorting of specific subpopulations of parasite-infected red blood cells. However, identification of rare subpopulations of parasites using green fluorescent protein (GFP) labelling is complicated by autofluorescence (AF) of red blood cells and low signal from transgenic parasites. It has been suggested that cell sorting yield could be improved by using filters that precisely match the emission spectrum of GFP. Methods Detection of transgenic Plasmodium falciparum parasites expressing either tdTomato or GFP was performed using a flow cytometer with interchangeable optical filters. Parasitaemia was evaluated using different optical filters and, after optimization of optics, the GFP-expressing parasites were sorted and analysed by microscopy after cytospin preparation and by imaging cytometry. Results A new approach to evaluate filter performance in flow cytometry using two-dimensional dot blot was developed. By selecting optical filters with narrow bandpass (BP) and maximum position of filter emission close to GFP maximum emission in the FL1 channel (510/20, 512/20 and 517/20; dichroics 502LP and 466LP), AF was markedly decreased and signal-background improve dramatically. Sorting of GFP-expressing parasite populations in infected red blood cells at 90 or 95% purity with these filters resulted in 50-150% increased yield when compared to the standard filter set-up. The purity of the sorted population was confirmed using imaging cytometry and microscopy of cytospin preparations of sorted red blood cells infected with transgenic malaria parasites. Discussion Filter optimization is particularly important for applications where the FP signal and percentage of positive events are relatively low, such as analysis of parasite

A step-by-step guide to systematically identify all relevant animal studies.

PubMed

Leenaars, Marlies; Hooijmans, Carlijn R; van Veggel, Nieky; ter Riet, Gerben; Leeflang, Mariska; Hooft, Lotty; van der Wilt, Gert Jan; Tillema, Alice; Ritskes-Hoitinga, Merel

2012-01-01

Before starting a new animal experiment, thorough analysis of previously performed experiments is essential from a scientific as well as from an ethical point of view. The method that is most suitable to carry out such a thorough analysis of the literature is a systematic review (SR). An essential first step in an SR is to search and find all potentially relevant studies. It is important to include all available evidence in an SR to minimize bias and reduce hampered interpretation of experimental outcomes. Despite the recent development of search filters to find animal studies in PubMed and EMBASE, searching for all available animal studies remains a challenge. Available guidelines from the clinical field cannot be copied directly to the situation within animal research, and although there are plenty of books and courses on searching the literature, there is no compact guide available to search and find relevant animal studies. Therefore, in order to facilitate a structured, thorough and transparent search for animal studies (in both preclinical and fundamental science), an easy-to-use, step-by-step guide was prepared and optimized using feedback from scientists in the field of animal experimentation. The step-by-step guide will assist scientists in performing a comprehensive literature search and, consequently, improve the scientific quality of the resulting review and prevent unnecessary animal use in the future.

A step-by-step guide to systematically identify all relevant animal studies

PubMed Central

Leenaars, Marlies; Hooijmans, Carlijn R; van Veggel, Nieky; ter Riet, Gerben; Leeflang, Mariska; Hooft, Lotty; van der Wilt, Gert Jan; Tillema, Alice; Ritskes-Hoitinga, Merel

2012-01-01

Before starting a new animal experiment, thorough analysis of previously performed experiments is essential from a scientific as well as from an ethical point of view. The method that is most suitable to carry out such a thorough analysis of the literature is a systematic review (SR). An essential first step in an SR is to search and find all potentially relevant studies. It is important to include all available evidence in an SR to minimize bias and reduce hampered interpretation of experimental outcomes. Despite the recent development of search filters to find animal studies in PubMed and EMBASE, searching for all available animal studies remains a challenge. Available guidelines from the clinical field cannot be copied directly to the situation within animal research, and although there are plenty of books and courses on searching the literature, there is no compact guide available to search and find relevant animal studies. Therefore, in order to facilitate a structured, thorough and transparent search for animal studies (in both preclinical and fundamental science), an easy-to-use, step-by-step guide was prepared and optimized using feedback from scientists in the field of animal experimentation. The step-by-step guide will assist scientists in performing a comprehensive literature search and, consequently, improve the scientific quality of the resulting review and prevent unnecessary animal use in the future. PMID:22037056

Application of a territorial-based filtering algorithm in turbomachinery blade design optimization

NASA Astrophysics Data System (ADS)

Bahrami, Salman; Khelghatibana, Maryam; Tribes, Christophe; Yi Lo, Suk; von Fellenberg, Sven; Trépanier, Jean-Yves; Guibault, François

2017-02-01

A territorial-based filtering algorithm (TBFA) is proposed as an integration tool in a multi-level design optimization methodology. The design evaluation burden is split between low- and high-cost levels in order to properly balance the cost and required accuracy in different design stages, based on the characteristics and requirements of the case at hand. TBFA is in charge of connecting those levels by selecting a given number of geometrically different promising solutions from the low-cost level to be evaluated in the high-cost level. Two test case studies, a Francis runner and a transonic fan rotor, have demonstrated the robustness and functionality of TBFA in real industrial optimization problems.

Multi-Bandwidth Frequency Selective Surfaces for Near Infrared Filtering: Design and Optimization

NASA Technical Reports Server (NTRS)

Cwik, Tom; Fernandez, Salvador; Ksendzov, A.; LaBaw, Clayton C.; Maker, Paul D.; Muller, Richard E.

1999-01-01

Frequency selective surfaces are widely used in the microwave and millimeter wave regions of the spectrum for filtering signals. They are used in telecommunication systems for multi-frequency operation or in instrument detectors for spectroscopy. The frequency selective surface operation depends on a periodic array of elements resonating at prescribed wavelengths producing a filter response. The size of the elements is on the order of half the electrical wavelength, and the array period is typically less than a wavelength for efficient operation. When operating in the optical region, diffraction gratings are used for filtering. In this regime the period of the grating may be several wavelengths producing multiple orders of light in reflection or transmission. In regions between these bands (specifically in the infrared band) frequency selective filters consisting of patterned metal layers fabricated using electron beam lithography are beginning to be developed. The operation is completely analogous to surfaces made in the microwave and millimeter wave region except for the choice of materials used and the fabrication process. In addition, the lithography process allows an arbitrary distribution of patterns corresponding to resonances at various wavelengths to be produced. The design of sub-millimeter filters follows the design methods used in the microwave region. Exacting modal matching, integral equation or finite element methods can be used for design. A major difference though is the introduction of material parameters and thicknesses tha_ may not be important in longer wavelength designs. This paper describes the design of multi-bandwidth filters operating in the I-5 micrometer wavelength range. This work follows on previous design [1,2]. In this paper extensions based on further optimization and an examination of the specific shape of the element in the periodic cell will be reported. Results from the design, manufacture and test of linear wedge filters built

Multi-Bandwidth Frequency Selective Surfaces for Near Infrared Filtering: Design and Optimization

NASA Technical Reports Server (NTRS)

Cwik, Tom; Fernandez, Salvador; Ksendzov, A.; LaBaw, Clayton C.; Maker, Paul D.; Muller, Richard E.

1998-01-01

Frequency selective surfaces are widely used in the microwave and millimeter wave regions of the spectrum for filtering signals. They are used in telecommunication systems for multi-frequency operation or in instrument detectors for spectroscopy. The frequency selective surface operation depends on a periodic array of elements resonating at prescribed wavelengths producing a filter response. The size of the elements is on the order of half the electrical wavelength, and the array period is typically less than a wavelength for efficient operation. When operating in the optical region, diffraction gratings are used for filtering. In this regime the period of the grating may be several wavelengths producing multiple orders of light in reflection or transmission. In regions between these bands (specifically in the infrared band) frequency selective filters consisting of patterned metal layers fabricated using electron beam lithography are beginning to be developed. The operation is completely analogous to surfaces made in the microwave and millimeter wave region except for the choice of materials used and the fabrication process. In addition, the lithography process allows an arbitrary distribution of patterns corresponding to resonances at various wavelengths to be produced. The design of sub-millimeter filters follows the design methods used in the microwave region. Exacting modal matching, integral equation or finite element methods can be used for design. A major difference though is the introduction of material parameters and thicknesses that may not be important in longer wavelength designs. This paper describes the design of multi- bandwidth filters operating in the 1-5 micrometer wavelength range. This work follows on a previous design. In this paper extensions based on further optimization and an examination of the specific shape of the element in the periodic cell will be reported. Results from the design, manufacture and test of linear wedge filters built

Filter and method of fabricating

DOEpatents

Janney, Mark A.

2006-02-14

A method of making a filter includes the steps of: providing a substrate having a porous surface; applying to the porous surface a coating of dry powder comprising particles to form a filter preform; and heating the filter preform to bind the substrate and the particles together to form a filter.

Optimization of nonlinear, non-Gaussian Bayesian filtering for diagnosis and prognosis of monotonic degradation processes

NASA Astrophysics Data System (ADS)

Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.

2018-05-01

The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.

Collaborative emitter tracking using Rao-Blackwellized random exchange diffusion particle filtering

NASA Astrophysics Data System (ADS)

Bruno, Marcelo G. S.; Dias, Stiven S.

2014-12-01

We introduce in this paper the fully distributed, random exchange diffusion particle filter (ReDif-PF) to track a moving emitter using multiple received signal strength (RSS) sensors. We consider scenarios with both known and unknown sensor model parameters. In the unknown parameter case, a Rao-Blackwellized (RB) version of the random exchange diffusion particle filter, referred to as the RB ReDif-PF, is introduced. In a simulated scenario with a partially connected network, the proposed ReDif-PF outperformed a PF tracker that assimilates local neighboring measurements only and also outperformed a linearized random exchange distributed extended Kalman filter (ReDif-EKF). Furthermore, the novel ReDif-PF matched the tracking error performance of alternative suboptimal distributed PFs based respectively on iterative Markov chain move steps and selective average gossiping with an inter-node communication cost that is roughly two orders of magnitude lower than the corresponding cost for the Markov chain and selective gossip filters. Compared to a broadcast-based filter which exactly mimics the optimal centralized tracker or its equivalent (exact) consensus-based implementations, ReDif-PF showed a degradation in steady-state error performance. However, compared to the optimal consensus-based trackers, ReDif-PF is better suited for real-time applications since it does not require iterative inter-node communication between measurement arrivals.

Geomagnetic modeling by optimal recursive filtering

NASA Technical Reports Server (NTRS)

Gibbs, B. P.; Estes, R. H.

1981-01-01

The results of a preliminary study to determine the feasibility of using Kalman filter techniques for geomagnetic field modeling are given. Specifically, five separate field models were computed using observatory annual means, satellite, survey and airborne data for the years 1950 to 1976. Each of the individual field models used approximately five years of data. These five models were combined using a recursive information filter (a Kalman filter written in terms of information matrices rather than covariance matrices.) The resulting estimate of the geomagnetic field and its secular variation was propogated four years past the data to the time of the MAGSAT data. The accuracy with which this field model matched the MAGSAT data was evaluated by comparisons with predictions from other pre-MAGSAT field models. The field estimate obtained by recursive estimation was found to be superior to all other models.

Ridge filter design and optimization for the broad-beam three-dimensional irradiation system for heavy-ion radiotherapy.

PubMed

Schaffner, B; Kanai, T; Futami, Y; Shimbo, M; Urakabe, E

2000-04-01

The broad-beam three-dimensional irradiation system under development at National Institute of Radiological Sciences (NIRS) requires a small ridge filter to spread the initially monoenergetic heavy-ion beam to a small spread-out Bragg peak (SOBP). A large SOBP covering the target volume is then achieved by a superposition of differently weighted and displaced small SOBPs. Two approaches were studied for the definition of a suitable ridge filter and experimental verifications were performed. Both approaches show a good agreement between the calculated and measured dose and lead to a good homogeneity of the biological dose in the target. However, the ridge filter design that produces a Gaussian-shaped spectrum of the particle ranges was found to be more robust to small errors and uncertainties in the beam application. Furthermore, an optimization procedure for two fields was applied to compensate for the missing dose from the fragmentation tail for the case of a simple-geometry target. The optimized biological dose distributions show that a very good homogeneity is achievable in the target.

Bilateral step length estimation using a single inertial measurement unit attached to the pelvis

PubMed Central

2012-01-01

Background The estimation of the spatio-temporal gait parameters is of primary importance in both physical activity monitoring and clinical contexts. A method for estimating step length bilaterally, during level walking, using a single inertial measurement unit (IMU) attached to the pelvis is proposed. In contrast to previous studies, based either on a simplified representation of the human gait mechanics or on a general linear regressive model, the proposed method estimates the step length directly from the integration of the acceleration along the direction of progression. Methods The IMU was placed at pelvis level fixed to the subject's belt on the right side. The method was validated using measurements from a stereo-photogrammetric system as a gold standard on nine subjects walking ten laps along a closed loop track of about 25 m, varying their speed. For each loop, only the IMU data recorded in a 4 m long portion of the track included in the calibrated volume of the SP system, were used for the analysis. The method takes advantage of the cyclic nature of gait and it requires an accurate determination of the foot contact instances. A combination of a Kalman filter and of an optimally filtered direct and reverse integration applied to the IMU signals formed a single novel method (Kalman and Optimally filtered Step length Estimation - KOSE method). A correction of the IMU displacement due to the pelvic rotation occurring in gait was implemented to estimate the step length and the traversed distance. Results The step length was estimated for all subjects with less than 3% error. Traversed distance was assessed with less than 2% error. Conclusions The proposed method provided estimates of step length and traversed distance more accurate than any other method applied to measurements obtained from a single IMU that can be found in the literature. In healthy subjects, it is reasonable to expect that, errors in traversed distance estimation during daily monitoring

Dual-energy approach to contrast-enhanced mammography using the balanced filter method: spectral optimization and preliminary phantom measurement.

PubMed

Saito, Masatoshi

2007-11-01

Dual-energy contrast agent-enhanced mammography is a technique of demonstrating breast cancers obscured by a cluttered background resulting from the contrast between soft tissues in the breast. The technique has usually been implemented by exploiting two exposures to different x-ray tube voltages. In this article, another dual-energy approach using the balanced filter method without switching the tube voltages is described. For the spectral optimization of dual-energy mammography using the balanced filters, we applied a theoretical framework reported by Lemacks et al. [Med. Phys. 29, 1739-1751 (2002)] to calculate the signal-to-noise ratio (SNR) in an iodinated contrast agent subtraction image. This permits the selection of beam parameters such as tube voltage and balanced filter material, and the optimization of the latter's thickness with respect to some critical quantity-in this case, mean glandular dose. For an imaging system with a 0.1 mm thick CsI:T1 scintillator, we predict that the optimal tube voltage would be 45 kVp for a tungsten anode using zirconium, iodine, and neodymium balanced filters. A mean glandular dose of 1.0 mGy is required to obtain an SNR of 5 in order to detect 1.0 mg/cm2 iodine in the resulting clutter-free image of a 5 cm thick breast composed of 50% adipose and 50% glandular tissue. In addition to spectral optimization, we carried out phantom measurements to demonstrate the present dual-energy approach for obtaining a clutter-free image, which preferentially shows iodine, of a breast phantom comprising three major components-acrylic spheres, olive oil, and an iodinated contrast agent. The detection of iodine details on the cluttered background originating from the contrast between acrylic spheres and olive oil is analogous to the task of distinguishing contrast agents in a mixture of glandular and adipose tissues.

Teaching learning based optimization-functional link artificial neural network filter for mixed noise reduction from magnetic resonance image.

PubMed

Kumar, M; Mishra, S K

2017-01-01

The clinical magnetic resonance imaging (MRI) images may get corrupted due to the presence of the mixture of different types of noises such as Rician, Gaussian, impulse, etc. Most of the available filtering algorithms are noise specific, linear, and non-adaptive. There is a need to develop a nonlinear adaptive filter that adapts itself according to the requirement and effectively applied for suppression of mixed noise from different MRI images. In view of this, a novel nonlinear neural network based adaptive filter i.e. functional link artificial neural network (FLANN) whose weights are trained by a recently developed derivative free meta-heuristic technique i.e. teaching learning based optimization (TLBO) is proposed and implemented. The performance of the proposed filter is compared with five other adaptive filters and analyzed by considering quantitative metrics and evaluating the nonparametric statistical test. The convergence curve and computational time are also included for investigating the efficiency of the proposed as well as competitive filters. The simulation outcomes of proposed filter outperform the other adaptive filters. The proposed filter can be hybridized with other evolutionary technique and utilized for removing different noise and artifacts from others medical images more competently.

Initial Ares I Bending Filter Design

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Bedrossian, Nazareth; Hall, Robert; Norris, H. Lee; Hall, Charles; Jackson, Mark

2007-01-01

The Ares-I launch vehicle represents a challenging flex-body structural environment for control system design. Software filtering of the inertial sensor output will be required to ensure control system stability and adequate performance. This paper presents a design methodology employing numerical optimization to develop the Ares-I bending filters. The filter design methodology was based on a numerical constrained optimization approach to maximize stability margins while meeting performance requirements. The resulting bending filter designs achieved stability by adding lag to the first structural frequency and hence phase stabilizing the first Ares-I flex mode. To minimize rigid body performance impacts, a priority was placed via constraints in the optimization algorithm to minimize bandwidth decrease with the addition of the bending filters. The bending filters provided here have been demonstrated to provide a stable first stage control system in both the frequency domain and the MSFC MAVERIC time domain simulation.

Optimal design of monitoring networks for multiple groundwater quality parameters using a Kalman filter: application to the Irapuato-Valle aquifer.

PubMed

Júnez-Ferreira, H E; Herrera, G S; González-Hita, L; Cardona, A; Mora-Rodríguez, J

2016-01-01

A new method for the optimal design of groundwater quality monitoring networks is introduced in this paper. Various indicator parameters were considered simultaneously and tested for the Irapuato-Valle aquifer in Mexico. The steps followed in the design were (1) establishment of the monitoring network objectives, (2) definition of a groundwater quality conceptual model for the study area, (3) selection of the parameters to be sampled, and (4) selection of a monitoring network by choosing the well positions that minimize the estimate error variance of the selected indicator parameters. Equal weight for each parameter was given to most of the aquifer positions and a higher weight to priority zones. The objective for the monitoring network in the specific application was to obtain a general reconnaissance of the water quality, including water types, water origin, and first indications of contamination. Water quality indicator parameters were chosen in accordance with this objective, and for the selection of the optimal monitoring sites, it was sought to obtain a low-uncertainty estimate of these parameters for the entire aquifer and with more certainty in priority zones. The optimal monitoring network was selected using a combination of geostatistical methods, a Kalman filter and a heuristic optimization method. Results show that when monitoring the 69 locations with higher priority order (the optimal monitoring network), the joint average standard error in the study area for all the groundwater quality parameters was approximately 90 % of the obtained with the 140 available sampling locations (the set of pilot wells). This demonstrates that an optimal design can help to reduce monitoring costs, by avoiding redundancy in data acquisition.

Strengthening the revenue cycle: a 4-step method for optimizing payment.

PubMed

Clark, Jonathan J

2008-10-01

Four steps for enhancing the revenue cycle to ensure optimal payment are: *Establish key performance indicator dashboards in each department that compare current with targeted performance; *Create proper organizational structures for each department; *Ensure that high-performing leaders are hired in all management and supervisory positions; *Implement efficient processes in underperforming operations.

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring

NASA Astrophysics Data System (ADS)

Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.

2017-08-01

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

Spatio-spectral color filter array design for optimal image recovery.

PubMed

Hirakawa, Keigo; Wolfe, Patrick J

2008-10-01

In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array-a physical construction whereby only a single color value is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the implications of such arrays for subsequent digital processing, including in particular the canonical demosaicking task of reconstructing a full color image from spatially subsampled and incomplete color data acquired under a particular choice of array pattern. In contrast to the majority of the demosaicking literature, we consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and-after proving sub-optimality of a wide class of existing array patterns-provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

Mini-batch optimized full waveform inversion with geological constrained gradient filtering

NASA Astrophysics Data System (ADS)

Yang, Hui; Jia, Junxiong; Wu, Bangyu; Gao, Jinghuai

2018-05-01

High computation cost and generating solutions without geological sense have hindered the wide application of Full Waveform Inversion (FWI). Source encoding technique is a way to dramatically reduce the cost of FWI but subject to fix-spread acquisition setup requirement and slow convergence for the suppression of cross-talk. Traditionally, gradient regularization or preconditioning is applied to mitigate the ill-posedness. An isotropic smoothing filter applied on gradients generally gives non-geological inversion results, and could also introduce artifacts. In this work, we propose to address both the efficiency and ill-posedness of FWI by a geological constrained mini-batch gradient optimization method. The mini-batch gradient descent optimization is adopted to reduce the computation time by choosing a subset of entire shots for each iteration. By jointly applying the structure-oriented smoothing to the mini-batch gradient, the inversion converges faster and gives results with more geological meaning. Stylized Marmousi model is used to show the performance of the proposed method on realistic synthetic model.

Impact of atmospheric correction and image filtering on hyperspectral classification of tree species using support vector machine

NASA Astrophysics Data System (ADS)

Shahriari Nia, Morteza; Wang, Daisy Zhe; Bohlman, Stephanie Ann; Gader, Paul; Graves, Sarah J.; Petrovic, Milenko

2015-01-01

Hyperspectral images can be used to identify savannah tree species at the landscape scale, which is a key step in measuring biomass and carbon, and tracking changes in species distributions, including invasive species, in these ecosystems. Before automated species mapping can be performed, image processing and atmospheric correction is often performed, which can potentially affect the performance of classification algorithms. We determine how three processing and correction techniques (atmospheric correction, Gaussian filters, and shade/green vegetation filters) affect the prediction accuracy of classification of tree species at pixel level from airborne visible/infrared imaging spectrometer imagery of longleaf pine savanna in Central Florida, United States. Species classification using fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) atmospheric correction outperformed ATCOR in the majority of cases. Green vegetation (normalized difference vegetation index) and shade (near-infrared) filters did not increase classification accuracy when applied to large and continuous patches of specific species. Finally, applying a Gaussian filter reduces interband noise and increases species classification accuracy. Using the optimal preprocessing steps, our classification accuracy of six species classes is about 75%.

Role of step size and max dwell time in anatomy based inverse optimization for prostate implants

PubMed Central

Manikandan, Arjunan; Sarkar, Biplab; Rajendran, Vivek Thirupathur; King, Paul R.; Sresty, N.V. Madhusudhana; Holla, Ragavendra; Kotur, Sachin; Nadendla, Sujatha

2013-01-01

In high dose rate (HDR) brachytherapy, the source dwell times and dwell positions are vital parameters in achieving a desirable implant dose distribution. Inverse treatment planning requires an optimal choice of these parameters to achieve the desired target coverage with the lowest achievable dose to the organs at risk (OAR). This study was designed to evaluate the optimum source step size and maximum source dwell time for prostate brachytherapy implants using an Ir-192 source. In total, one hundred inverse treatment plans were generated for the four patients included in this study. Twenty-five treatment plans were created for each patient by varying the step size and maximum source dwell time during anatomy-based, inverse-planned optimization. Other relevant treatment planning parameters were kept constant, including the dose constraints and source dwell positions. Each plan was evaluated for target coverage, urethral and rectal dose sparing, treatment time, relative target dose homogeneity, and nonuniformity ratio. The plans with 0.5 cm step size were seen to have clinically acceptable tumor coverage, minimal normal structure doses, and minimum treatment time as compared with the other step sizes. The target coverage for this step size is 87% of the prescription dose, while the urethral and maximum rectal doses were 107.3 and 68.7%, respectively. No appreciable difference in plan quality was observed with variation in maximum source dwell time. The step size plays a significant role in plan optimization for prostate implants. Our study supports use of a 0.5 cm step size for prostate implants. PMID:24049323

Automatic selection of optimal Savitzky-Golay filter parameters for Coronary Wave Intensity Analysis.

PubMed

Rivolo, Simone; Nagel, Eike; Smith, Nicolas P; Lee, Jack

2014-01-01

Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. The cWIA ability to establish a mechanistic link between coronary haemodynamics measurements and the underlying pathophysiology has been widely demonstrated. Moreover, the prognostic value of a cWIA-derived metric has been recently proved. However, the clinical application of cWIA has been hindered due to the strong dependence on the practitioners, mainly ascribable to the cWIA-derived indices sensitivity to the pre-processing parameters. Specifically, as recently demonstrated, the cWIA-derived metrics are strongly sensitive to the Savitzky-Golay (S-G) filter, typically used to smooth the acquired traces. This is mainly due to the inability of the S-G filter to deal with the different timescale features present in the measured waveforms. Therefore, we propose to apply an adaptive S-G algorithm that automatically selects pointwise the optimal filter parameters. The newly proposed algorithm accuracy is assessed against a cWIA gold standard, provided by a newly developed in-silico cWIA modelling framework, when physiological noise is added to the simulated traces. The adaptive S-G algorithm, when used to automatically select the polynomial degree of the S-G filter, provides satisfactory results with ≤ 10% error for all the metrics through all the levels of noise tested. Therefore, the newly proposed method makes cWIA fully automatic and independent from the practitioners, opening the possibility to multi-centre trials.

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

NASA Technical Reports Server (NTRS)

Rabinowitz, Matthew (Inventor)

2002-01-01

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

The effect of spectral filters on visual search in stroke patients.

PubMed

Beasley, Ian G; Davies, Leon N

2013-01-01

Visual search impairment can occur following stroke. The utility of optimal spectral filters on visual search in stroke patients has not been considered to date. The present study measured the effect of optimal spectral filters on visual search response time and accuracy, using a task requiring serial processing. A stroke and control cohort undertook the task three times: (i) using an optimally selected spectral filter; (ii) the subjects were randomly assigned to two groups with group 1 using an optimal filter for two weeks, whereas group 2 used a grey filter for two weeks; (iii) the groups were crossed over with group 1 using a grey filter for a further two weeks and group 2 given an optimal filter, before undertaking the task for the final time. Initial use of an optimal spectral filter improved visual search response time but not error scores in the stroke cohort. Prolonged use of neither an optimal nor a grey filter improved response time or reduced error scores. In fact, response times increased with the filter, regardless of its type, for stroke and control subjects; this outcome may be due to contrast reduction or a reflection of task design, given that significant practice effects were noted.

Sparse gammatone signal model optimized for English speech does not match the human auditory filters.

PubMed

Strahl, Stefan; Mertins, Alfred

2008-07-18

Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.

Filtering for networked control systems with single/multiple measurement packets subject to multiple-step measurement delays and multiple packet dropouts

NASA Astrophysics Data System (ADS)

Moayedi, Maryam; Foo, Yung Kuan; Chai Soh, Yeng

2011-03-01

The minimum-variance filtering problem in networked control systems, where both random measurement transmission delays and packet dropouts may occur, is investigated in this article. Instead of following the many existing results that solve the problem by using probabilistic approaches based on the probabilities of the uncertainties occurring between the sensor and the filter, we propose a non-probabilistic approach by time-stamping the measurement packets. Both single-measurement and multiple measurement packets are studied. We also consider the case of burst arrivals, where more than one packet may arrive between the receiver's previous and current sampling times; the scenario where the control input is non-zero and subject to delays and packet dropouts is examined as well. It is shown that, in such a situation, the optimal state estimate would generally be dependent on the possible control input. Simulations are presented to demonstrate the performance of the various proposed filters.

Two-step optimization of pressure and recovery of reverse osmosis desalination process.

PubMed

Liang, Shuang; Liu, Cui; Song, Lianfa

2009-05-01

Driving pressure and recovery are two primary design variables of a reverse osmosis process that largely determine the total cost of seawater and brackish water desalination. A two-step optimization procedure was developed in this paper to determine the values of driving pressure and recovery that minimize the total cost of RO desalination. It was demonstrated that the optimal net driving pressure is solely determined by the electricity price and the membrane price index, which is a lumped parameter to collectively reflect membrane price, resistance, and service time. On the other hand, the optimal recovery is determined by the electricity price, initial osmotic pressure, and costs for pretreatment of raw water and handling of retentate. Concise equations were derived for the optimal net driving pressure and recovery. The dependences of the optimal net driving pressure and recovery on the electricity price, membrane price, and costs for raw water pretreatment and retentate handling were discussed.

An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming

NASA Astrophysics Data System (ADS)

Wang, Liwei; Liu, Xinggao; Zhang, Zeyin

2017-02-01

An efficient primal-dual interior-point algorithm using a new non-monotone line search filter method is presented for nonlinear constrained programming, which is widely applied in engineering optimization. The new non-monotone line search technique is introduced to lead to relaxed step acceptance conditions and improved convergence performance. It can also avoid the choice of the upper bound on the memory, which brings obvious disadvantages to traditional techniques. Under mild assumptions, the global convergence of the new non-monotone line search filter method is analysed, and fast local convergence is ensured by second order corrections. The proposed algorithm is applied to the classical alkylation process optimization problem and the results illustrate its effectiveness. Some comprehensive comparisons to existing methods are also presented.

Stepped Care to Optimize Pain care Effectiveness (SCOPE) trial study design and sample characteristics.

PubMed

Kroenke, Kurt; Krebs, Erin; Wu, Jingwei; Bair, Matthew J; Damush, Teresa; Chumbler, Neale; York, Tish; Weitlauf, Sharon; McCalley, Stephanie; Evans, Erica; Barnd, Jeffrey; Yu, Zhangsheng

2013-03-01

Pain is the most common physical symptom in primary care, accounting for an enormous burden in terms of patient suffering, quality of life, work and social disability, and health care and societal costs. Although collaborative care interventions are well-established for conditions such as depression, fewer systems-based interventions have been tested for chronic pain. This paper describes the study design and baseline characteristics of the enrolled sample for the Stepped Care to Optimize Pain care Effectiveness (SCOPE) study, a randomized clinical effectiveness trial conducted in five primary care clinics. SCOPE has enrolled 250 primary care veterans with persistent (3 months or longer) musculoskeletal pain of moderate severity and randomized them to either the stepped care intervention or usual care control group. Using a telemedicine collaborative care approach, the intervention couples automated symptom monitoring with a telephone-based, nurse care manager/physician pain specialist team to treat pain. The goal is to optimize analgesic management using a stepped care approach to drug selection, symptom monitoring, dose adjustment, and switching or adding medications. All subjects undergo comprehensive outcome assessments at baseline, 1, 3, 6 and 12 months by interviewers blinded to treatment group. The primary outcome is pain severity/disability, and secondary outcomes include pain beliefs and behaviors, psychological functioning, health-related quality of life and treatment satisfaction. Innovations of SCOPE include optimized analgesic management (including a stepped care approach, opioid risk stratification, and criteria-based medication adjustment), automated monitoring, and centralized care management that can cover multiple primary care practices. Published by Elsevier Inc.

Dimension reduction: additional benefit of an optimal filter for independent component analysis to extract event-related potentials.

PubMed

Cong, Fengyu; Leppänen, Paavo H T; Astikainen, Piia; Hämäläinen, Jarmo; Hietanen, Jari K; Ristaniemi, Tapani

2011-09-30

The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the number of sources) simultaneously. We demonstrated these effects using two datasets, one containing visual and the other auditory ERPs. The results showed that the method including OF and ICA extracted much more reliable components than the sole ICA without OF did, and that OF removed some non-targeted sources and made the underdetermined model of EEG recordings approach to the determined one. Thus, we suggest designing an OF based on the properties of an ERP to filter recordings before using ICA decomposition to extract the targeted ERP component. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimization of plasma parameters with magnetic filter field and pressure to maximize H{sup −} ion density in a negative hydrogen ion source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, Won-Hwi; Dang, Jeong-Jeung; Kim, June Young

2016-02-15

Transverse magnetic filter field as well as operating pressure is considered to be an important control knob to enhance negative hydrogen ion production via plasma parameter optimization in volume-produced negative hydrogen ion sources. Stronger filter field to reduce electron temperature sufficiently in the extraction region is favorable, but generally known to be limited by electron density drop near the extraction region. In this study, unexpected electron density increase instead of density drop is observed in front of the extraction region when the applied transverse filter field increases monotonically toward the extraction aperture. Measurements of plasma parameters with a movable Langmuirmore » probe indicate that the increased electron density may be caused by low energy electron accumulation in the filter region decreasing perpendicular diffusion coefficients across the increasing filter field. Negative hydrogen ion populations are estimated from the measured profiles of electron temperatures and densities and confirmed to be consistent with laser photo-detachment measurements of the H{sup −} populations for various filter field strengths and pressures. Enhanced H{sup −} population near the extraction region due to the increased low energy electrons in the filter region may be utilized to increase negative hydrogen beam currents by moving the extraction position accordingly. This new finding can be used to design efficient H{sup −} sources with an optimal filtering system by maximizing high energy electron filtering while keeping low energy electrons available in the extraction region.« less

Drying step optimization to obtain large-size transparent magnesium-aluminate spinel samples

NASA Astrophysics Data System (ADS)

Petit, Johan; Lallemant, Lucile

2017-05-01

In the transparent ceramics processing, the green body elaboration step is probably the most critical one. Among the known techniques, wet shaping processes are particularly interesting because they enable the particles to find an optimum position on their own. Nevertheless, the presence of water molecules leads to drying issues. During the water removal, its concentration gradient induces cracks limiting the sample size: laboratory samples are generally less damaged because of their small size but upscaling the samples for industrial applications lead to an increasing cracking probability. Thanks to the drying step optimization, large size spinel samples were obtained.

Demonstration of differential phase-shift keying demodulation at 10 Gbit/s optimal fiber Bragg grating filters.

PubMed

Gatti, Davide; Galzerano, Gianluca; Laporta, Paolo; Longhi, Stefano; Janner, Davide; Guglierame, Andrea; Belmonte, Michele

2008-07-01

Optimal demodulation of differential phase-shift keying signals at 10 Gbit/s is experimentally demonstrated using a specially designed structured fiber Bragg grating composed by Fabry-Perot coupled cavities. Bit-error-rate measurements show that, as compared with a conventional Gaussian-shaped filter, our demodulator gives approximately 2.8 dB performance improvement.

Application of reversible denoising and lifting steps with step skipping to color space transforms for improved lossless compression

NASA Astrophysics Data System (ADS)

Starosolski, Roman

2016-07-01

Reversible denoising and lifting steps (RDLS) are lifting steps integrated with denoising filters in such a way that, despite the inherently irreversible nature of denoising, they are perfectly reversible. We investigated the application of RDLS to reversible color space transforms: RCT, YCoCg-R, RDgDb, and LDgEb. In order to improve RDLS effects, we propose a heuristic for image-adaptive denoising filter selection, a fast estimator of the compressed image bitrate, and a special filter that may result in skipping of the steps. We analyzed the properties of the presented methods, paying special attention to their usefulness from a practical standpoint. For a diverse image test-set and lossless JPEG-LS, JPEG 2000, and JPEG XR algorithms, RDLS improves the bitrates of all the examined transforms. The most interesting results were obtained for an estimation-based heuristic filter selection out of a set of seven filters; the cost of this variant was similar to or lower than the transform cost, and it improved the average lossless JPEG 2000 bitrates by 2.65% for RDgDb and by over 1% for other transforms; bitrates of certain images were improved to a significantly greater extent.

Optimization of an incubation step to maximize sulforaphane content in pre-processed broccoli.

PubMed

Mahn, Andrea; Pérez, Carmen

2016-11-01

Sulforaphane is a powerful anticancer compound, found naturally in food, which comes from the hydrolysis of glucoraphanin, the main glucosinolate of broccoli. The aim of this work was to maximize sulforaphane content in broccoli by designing an incubation step after subjecting broccoli pieces to an optimized blanching step. Incubation was optimized through a Box-Behnken design using ascorbic acid concentration, incubation temperature and incubation time as factors. The optimal incubation conditions were 38 °C for 3 h and 0.22 mg ascorbic acid per g fresh broccoli. The maximum sulforaphane concentration predicted by the model was 8.0 µmol g -1 , which was confirmed experimentally yielding a value of 8.1 ± 0.3 µmol g -1 . This represents a 585% increase with respect to fresh broccoli and a 119% increase in relation to blanched broccoli, equivalent to a conversion of 94% of glucoraphanin. The process proposed here allows maximizing sulforaphane content, thus avoiding artificial chemical synthesis. The compound could probably be isolated from broccoli, and may find application as nutraceutical or functional ingredient.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

The Influence of Added Mass on Optimal Step Length in Running.

PubMed

Reenalda, Jasper; Maas, Maurice T F; de Koning, Jos J

2016-10-01

To examine the influence of induced changes in the morphology of the leg by adding mass on the optimal step length (OSL) in experienced runners to get more insight into parameters that influence preferred step length (PSL) and OSL. Thirteen experienced male runners (mean age 26.9 ± 6.1 y, height 183.7 ± 7.1 cm, mass 71.8 ± 5.9 kg) ran on a treadmill in 3 different conditions: unloaded (UL), loaded with 2 kg mass at the ankles (MA), and loaded with 2 kg mass at the hips (MH) at 7 different step lengths (SLs). SL deviations were expressed as deviations in relative leg length (%LL) from the individual PSL: 0%LL, ±5%LL, ±10%LL, and ±15%LL. Trials lasted 8 min, and 8 min of rest was given between trials. Oxygen uptake (V̇O 2 ) was expressed as a fraction of V̇O 2 at PSL + 0%LL in the unloaded condition (%V̇O 2 ). The %SL with the lowest value of %V̇O 2 was considered the OSL for this group of participants. OSL at the UL condition was 6% shorter than PSL. The MA condition resulted in a 7%LL larger OSL than at UL and MH (P < .05). The mass distribution of the leg is a determinant of the OSL. As a consequence of the added mass to the ankles, OSL was 7%LL longer. Morphological characteristics of the leg might therefore play an important role in determining the runner's individual optimal SL.

Optimal setups for forced-choice staircases with fixed step sizes.

PubMed

García-Pérez, M A

2000-01-01

Forced-choice staircases with fixed step sizes are used in a variety of formats whose relative merits have never been studied. This paper presents a comparative study aimed at determining their optimal format. Factors included in the study were the up/down rule, the length (number of reversals), and the size of the steps. The study also addressed the issue of whether a protocol involving three staircases running for N reversals each (with a subsequent average of the estimates provided by each individual staircase) has better statistical properties than an alternative protocol involving a single staircase running for 3N reversals. In all cases the size of a step up was different from that of a step down, in the appropriate ratio determined by García-Pérez (Vision Research, 1998, 38, 1861 - 1881). The results of a simulation study indicate that a) there are no conditions in which the 1-down/1-up rule is advisable; b) different combinations of up/down rule and number of reversals appear equivalent in terms of precision and cost: c) using a single long staircase with 3N reversals is more efficient than running three staircases with N reversals each: d) to avoid bias and attain sufficient accuracy, threshold estimates should be based on at least 30 reversals: and e) to avoid excessive cost and imprecision, the size of the step up should be between 2/3 and 3/3 the (known or presumed) spread of the psychometric function. An empirical study with human subjects confirmed the major characteristics revealed by the simulations.

SkyMapper Filter Set: Design and Fabrication of Large-Scale Optical Filters

NASA Astrophysics Data System (ADS)

Bessell, Michael; Bloxham, Gabe; Schmidt, Brian; Keller, Stefan; Tisserand, Patrick; Francis, Paul

2011-07-01

The SkyMapper Southern Sky Survey will be conducted from Siding Spring Observatory with u, v, g, r, i, and z filters that comprise glued glass combination filters with dimensions of 309 × 309 × 15 mm. In this article we discuss the rationale for our bandpasses and physical characteristics of the filter set. The u, v, g, and z filters are entirely glass filters, which provide highly uniform bandpasses across the complete filter aperture. The i filter uses glass with a short-wave pass coating, and the r filter is a complete dielectric filter. We describe the process by which the filters were constructed, including the processes used to obtain uniform dielectric coatings and optimized narrowband antireflection coatings, as well as the technique of gluing the large glass pieces together after coating using UV transparent epoxy cement. The measured passbands, including extinction and CCD QE, are presented.

Sci-Thur AM: YIS – 07: Optimizing dual-energy x-ray parameters using a single filter for both high and low-energy images to enhance soft-tissue imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowman, Wesley; Sattarivand, Mike

Objective: To optimize dual-energy parameters of ExacTrac stereoscopic x-ray imaging system for lung SBRT patients Methods: Simulated spectra and a lung phantom were used to optimize filter material, thickness, kVps, and weighting factors to obtain bone subtracted dual-energy images. Spektr simulations were used to identify material in the atomic number (Z) range [3–83] based on a metric defined to separate spectrums of high and low energies. Both energies used the same filter due to time constraints of image acquisition in lung SBRT imaging. A lung phantom containing bone, soft tissue, and a tumor mimicking material was imaged with filter thicknessesmore » range [0–1] mm and kVp range [60–140]. A cost function based on contrast-to-noise-ratio of bone, soft tissue, and tumor, as well as image noise content, was defined to optimize filter thickness and kVp. Using the optimized parameters, dual-energy images of anthropomorphic Rando phantom were acquired and evaluated for bone subtraction. Imaging dose was measured with dual-energy technique using tin filtering. Results: Tin was the material of choice providing the best energy separation, non-toxicity, and non-reactiveness. The best soft-tissue-only image in the lung phantom was obtained using 0.3 mm tin and [140, 80] kVp pair. Dual-energy images of the Rando phantom had noticeable bone elimination when compared to no filtration. Dose was lower with tin filtering compared to no filtration. Conclusions: Dual-energy soft-tissue imaging is feasible using ExacTrac stereoscopic imaging system utilizing a single tin filter for both high and low energies and optimized acquisition parameters.« less

Performance index: A method for quantitative evaluation of filters used in clinical SPECT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Contino, J.; Touya, J.J.; Corbus, H.F.

1984-01-01

The purpose of this study was to design a method for optimal filter selection during the reconstruction of clinical SPECT images. Hamming, Bartlett, Parzen and Butterworth filters were evaluated at different cutoff frequencies when applied to reconstruction of the Jaszczak phantom and liver SPECTs. The phantom filled with 6 mCi of Tc-99m was imaged following 4 different protocols which varied in matrix sizes (128 x 128 or 64 x 64) and in number of steps (128 or 64). Total imaging time in the 4 protocols was 24 minutes. A total of 160 reconstructions were analyzed. Liver SPECTs from 2 patientsmore » with small metastatic lesions from colon Ca were similarly studied. An ECT Performance Index (ECT PI) was defined as the product of the contrast efficiency function (ECT C) and uniformity (ECT U). ECT C as a function of the radius was measured following Rollo's approach. ECT U was measured as the ratio between min. and max. counts per pixel in a known uniform region. ECT PI was computed on a slice through the void spheres region of the phantom. In liver SPECTs the ECT U was measured over the spleen. The most favorable ECT PI (0.35, radius 7.9 mm) was obtained with images in 128 x 128 matrices, 128 steps, processed with a Butterworth cutoff frequency of 0.19, filter order 4. When images were acquired in 64 x 64 matrices using 64 steps the ECT PI was lower and influenced to a lesser degree by both choice of filter and cutoff frequency. Results in the two liver SPECT examinations were parallel to those found in the phantom studies confirming the clinical usefulness of the ECT PI in the evaluation of filters for reconstruction of SPECT images.« less

Analysis of Time Filters in Multistep Methods

NASA Astrophysics Data System (ADS)

Hurl, Nicholas

Geophysical ow simulations have evolved sophisticated implicit-explicit time stepping methods (based on fast-slow wave splittings) followed by time filters to control any unstable models that result. Time filters are modular and parallel. Their effect on stability of the overall process has been tested in numerous simulations, but never analyzed. Stability is proven herein for the Crank-Nicolson Leapfrog (CNLF) method with the Robert-Asselin (RA) time filter and for the Crank-Nicolson Leapfrog method with the Robert-Asselin-Williams (RAW) time filter for systems by energy methods. We derive an equivalent multistep method for CNLF+RA and CNLF+RAW and stability regions are obtained. The time step restriction for energy stability of CNLF+RA is smaller than CNLF and CNLF+RAW time step restriction is even smaller. Numerical tests find that RA and RAW add numerical dissipation. This thesis also shows that all modes of the Crank-Nicolson Leap Frog (CNLF) method are asymptotically stable under the standard timestep condition.

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2011-01-01

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation

Single-step fabrication of thin-film linear variable bandpass filters based on metal-insulator-metal geometry.

PubMed

Williams, Calum; Rughoobur, Girish; Flewitt, Andrew J; Wilkinson, Timothy D

2016-11-10

A single-step fabrication method is presented for ultra-thin, linearly variable optical bandpass filters (LVBFs) based on a metal-insulator-metal arrangement using modified evaporation deposition techniques. This alternate process methodology offers reduced complexity and cost in comparison to conventional techniques for fabricating LVBFs. We are able to achieve linear variation of insulator thickness across a sample, by adjusting the geometrical parameters of a typical physical vapor deposition process. We demonstrate LVBFs with spectral selectivity from 400 to 850 nm based on Ag (25 nm) and MgF₂ (75-250 nm). Maximum spectral transmittance is measured at ∼70% with a Q-factor of ∼20.

Optimization of semi-continuous anaerobic digestion of sugarcane straw co-digested with filter cake: Effects of macronutrients supplementation on conversion kinetics.

PubMed

Janke, Leandro; Weinrich, Sören; Leite, Athaydes F; Schüch, Andrea; Nikolausz, Marcell; Nelles, Michael; Stinner, Walter

2017-12-01

Anaerobic digestion of sugarcane straw co-digested with sugarcane filter cake was investigated with a special focus on macronutrients supplementation for an optimized conversion process. Experimental data from batch tests and a semi-continuous experiment operated in different supplementation phases were used for modeling the conversion kinetics based on continuous stirred-tank reactors. The semi-continuous experiment showed an overall decrease in the performance along the inoculum washout from the reactors. By supplementing nitrogen alone or in combination to phosphorus and sulfur the specific methane production significantly increased (P<0.05) by 17% and 44%, respectively. Although the two-pool one-step model has fitted well to the batch experimental data (R 2 >0.99), the use of the depicted kinetics did not provide a good estimation for process simulation of the semi-continuous process (in any supplementation phase), possibly due to the different feeding modes and inoculum source, activity and adaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter

PubMed Central

Sindelar, Charles V.; Grigorieff, Nikolaus

2012-01-01

The high noise level found in single-particle electron cryo-microscopy (cryo-EM) image data presents a special challenge for three-dimensional (3D) reconstruction of the imaged molecules. The spectral signal-to-noise ratio (SSNR) and related Fourier shell correlation (FSC) functions are commonly used to assess and mitigate the noise-generated error in the reconstruction. Calculation of the SSNR and FSC usually includes the noise in the solvent region surrounding the particle and therefore does not accurately reflect the signal in the particle density itself. Here we show that the SSNR in a reconstructed 3D particle map is linearly proportional to the fractional volume occupied by the particle. Using this relationship, we devise a novel filter (the “single-particle Wiener filter”) to minimize the error in a reconstructed particle map, if the particle volume is known. Moreover, we show how to approximate this filter even when the volume of the particle is not known, by optimizing the signal within a representative interior region of the particle. We show that the new filter improves on previously proposed error-reduction schemes, including the conventional Wiener filter as well as figure-of-merit weighting, and quantify the relationship between all of these methods by theoretical analysis as well as numeric evaluation of both simulated and experimentally collected data. The single-particle Wiener filter is applicable across a broad range of existing 3D reconstruction techniques, but is particularly well suited to the Fourier inversion method, leading to an efficient and accurate implementation. PMID:22613568

Microfabrication of three-dimensional filters for liposome extrusion

NASA Astrophysics Data System (ADS)

Baldacchini, Tommaso; Nuñez, Vicente; LaFratta, Christopher N.; Grech, Joseph S.; Vullev, Valentine I.; Zadoyan, Ruben

2015-03-01

Liposomes play a relevant role in the biomedical field of drug delivery. The ability of these lipid vesicles to encapsulate and transport a variety of bioactive molecules has fostered their use in several therapeutic applications, from cancer treatments to the administration of drugs with antiviral activities. Size and uniformity are key parameters to take into consideration when preparing liposomes; these factors greatly influence their effectiveness in both in vitro and in vivo experiments. A popular technique employed to achieve the optimal liposome dimension (around 100 nm in diameter) and uniform size distribution is repetitive extrusion through a polycarbonate filter. We investigated two femtosecond laser direct writing techniques for the fabrication of three-dimensional filters within a microfluidics chip for liposomes extrusion. The miniaturization of the extrusion process in a microfluidic system is the first step toward a complete solution for lab-on-a-chip preparation of liposomes from vesicles self-assembly to optical characterization.

Two-Step Optimization for Spatial Accessibility Improvement: A Case Study of Health Care Planning in Rural China

PubMed Central

Luo, Jing; Tian, Lingling; Luo, Lei; Yi, Hong

2017-01-01

A recent advancement in location-allocation modeling formulates a two-step approach to a new problem of minimizing disparity of spatial accessibility. Our field work in a health care planning project in a rural county in China indicated that residents valued distance or travel time from the nearest hospital foremost and then considered quality of care including less waiting time as a secondary desirability. Based on the case study, this paper further clarifies the sequential decision-making approach, termed “two-step optimization for spatial accessibility improvement (2SO4SAI).” The first step is to find the best locations to site new facilities by emphasizing accessibility as proximity to the nearest facilities with several alternative objectives under consideration. The second step adjusts the capacities of facilities for minimal inequality in accessibility, where the measure of accessibility accounts for the match ratio of supply and demand and complex spatial interaction between them. The case study illustrates how the two-step optimization method improves both aspects of spatial accessibility for health care access in rural China. PMID:28484707

Two-Step Optimization for Spatial Accessibility Improvement: A Case Study of Health Care Planning in Rural China.

PubMed

Luo, Jing; Tian, Lingling; Luo, Lei; Yi, Hong; Wang, Fahui

2017-01-01

A recent advancement in location-allocation modeling formulates a two-step approach to a new problem of minimizing disparity of spatial accessibility. Our field work in a health care planning project in a rural county in China indicated that residents valued distance or travel time from the nearest hospital foremost and then considered quality of care including less waiting time as a secondary desirability. Based on the case study, this paper further clarifies the sequential decision-making approach, termed "two-step optimization for spatial accessibility improvement (2SO4SAI)." The first step is to find the best locations to site new facilities by emphasizing accessibility as proximity to the nearest facilities with several alternative objectives under consideration. The second step adjusts the capacities of facilities for minimal inequality in accessibility, where the measure of accessibility accounts for the match ratio of supply and demand and complex spatial interaction between them. The case study illustrates how the two-step optimization method improves both aspects of spatial accessibility for health care access in rural China.

Comparison of cryogenic low-pass filters.

PubMed

Thalmann, M; Pernau, H-F; Strunk, C; Scheer, E; Pietsch, T

2017-11-01

Low-temperature electronic transport measurements with high energy resolution require both effective low-pass filtering of high-frequency input noise and an optimized thermalization of the electronic system of the experiment. In recent years, elaborate filter designs have been developed for cryogenic low-level measurements, driven by the growing interest in fundamental quantum-physical phenomena at energy scales corresponding to temperatures in the few millikelvin regime. However, a single filter concept is often insufficient to thermalize the electronic system to the cryogenic bath and eliminate spurious high frequency noise. Moreover, the available concepts often provide inadequate filtering to operate at temperatures below 10 mK, which are routinely available now in dilution cryogenic systems. Herein we provide a comprehensive analysis of commonly used filter types, introduce a novel compact filter type based on ferrite compounds optimized for the frequency range above 20 GHz, and develop an improved filtering scheme providing adaptable broad-band low-pass characteristic for cryogenic low-level and quantum measurement applications at temperatures down to few millikelvin.

Comparison of cryogenic low-pass filters

NASA Astrophysics Data System (ADS)

Thalmann, M.; Pernau, H.-F.; Strunk, C.; Scheer, E.; Pietsch, T.

2017-11-01

Low-temperature electronic transport measurements with high energy resolution require both effective low-pass filtering of high-frequency input noise and an optimized thermalization of the electronic system of the experiment. In recent years, elaborate filter designs have been developed for cryogenic low-level measurements, driven by the growing interest in fundamental quantum-physical phenomena at energy scales corresponding to temperatures in the few millikelvin regime. However, a single filter concept is often insufficient to thermalize the electronic system to the cryogenic bath and eliminate spurious high frequency noise. Moreover, the available concepts often provide inadequate filtering to operate at temperatures below 10 mK, which are routinely available now in dilution cryogenic systems. Herein we provide a comprehensive analysis of commonly used filter types, introduce a novel compact filter type based on ferrite compounds optimized for the frequency range above 20 GHz, and develop an improved filtering scheme providing adaptable broad-band low-pass characteristic for cryogenic low-level and quantum measurement applications at temperatures down to few millikelvin.

Change Detection via Selective Guided Contrasting Filters

NASA Astrophysics Data System (ADS)

Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.

2017-05-01

Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample) as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map) could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO) is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC). The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC), mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All implemented

3D early embryogenesis image filtering by nonlinear partial differential equations.

PubMed

Krivá, Z; Mikula, K; Peyriéras, N; Rizzi, B; Sarti, A; Stasová, O

2010-08-01

We present nonlinear diffusion equations, numerical schemes to solve them and their application for filtering 3D images obtained from laser scanning microscopy (LSM) of living zebrafish embryos, with a goal to identify the optimal filtering method and its parameters. In the large scale applications dealing with analysis of 3D+time embryogenesis images, an important objective is a correct detection of the number and position of cell nuclei yielding the spatio-temporal cell lineage tree of embryogenesis. The filtering is the first and necessary step of the image analysis chain and must lead to correct results, removing the noise, sharpening the nuclei edges and correcting the acquisition errors related to spuriously connected subregions. In this paper we study such properties for the regularized Perona-Malik model and for the generalized mean curvature flow equations in the level-set formulation. A comparison with other nonlinear diffusion filters, like tensor anisotropic diffusion and Beltrami flow, is also included. All numerical schemes are based on the same discretization principles, i.e. finite volume method in space and semi-implicit scheme in time, for solving nonlinear partial differential equations. These numerical schemes are unconditionally stable, fast and naturally parallelizable. The filtering results are evaluated and compared first using the Mean Hausdorff distance between a gold standard and different isosurfaces of original and filtered data. Then, the number of isosurface connected components in a region of interest (ROI) detected in original and after the filtering is compared with the corresponding correct number of nuclei in the gold standard. Such analysis proves the robustness and reliability of the edge preserving nonlinear diffusion filtering for this type of data and lead to finding the optimal filtering parameters for the studied models and numerical schemes. Further comparisons consist in ability of splitting the very close objects which

Quantum neural network-based EEG filtering for a brain-computer interface.

PubMed

Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

2014-02-01

A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Optimized digital filtering techniques for radiation detection with HPGe detectors

NASA Astrophysics Data System (ADS)

Salathe, Marco; Kihm, Thomas

2016-02-01

This paper describes state-of-the-art digital filtering techniques that are part of GEANA, an automatic data analysis software used for the GERDA experiment. The discussed filters include a novel, nonlinear correction method for ballistic deficits, which is combined with one of three shaping filters: a pseudo-Gaussian, a modified trapezoidal, or a modified cusp filter. The performance of the filters is demonstrated with a 762 g Broad Energy Germanium (BEGe) detector, produced by Canberra, that measures γ-ray lines from radioactive sources in an energy range between 59.5 and 2614.5 keV. At 1332.5 keV, together with the ballistic deficit correction method, all filters produce a comparable energy resolution of 1.61 keV FWHM. This value is superior to those measured by the manufacturer and those found in publications with detectors of a similar design and mass. At 59.5 keV, the modified cusp filter without a ballistic deficit correction produced the best result, with an energy resolution of 0.46 keV. It is observed that the loss in resolution by using a constant shaping time over the entire energy range is small when using the ballistic deficit correction method.

An optimal search filter for retrieving systematic reviews and meta-analyses

PubMed Central

2012-01-01

Background Health-evidence.ca is an online registry of systematic reviews evaluating the effectiveness of public health interventions. Extensive searching of bibliographic databases is required to keep the registry up to date. However, search filters have been developed to assist in searching the extensive amount of published literature indexed. Search filters can be designed to find literature related to a certain subject (i.e. content-specific filter) or particular study designs (i.e. methodological filter). The objective of this paper is to describe the development and validation of the health-evidence.ca Systematic Review search filter and to compare its performance to other available systematic review filters. Methods This analysis of search filters was conducted in MEDLINE, EMBASE, and CINAHL. The performance of thirty-one search filters in total was assessed. A validation data set of 219 articles indexed between January 2004 and December 2005 was used to evaluate performance on sensitivity, specificity, precision and the number needed to read for each filter. Results Nineteen of 31 search filters were effective in retrieving a high level of relevant articles (sensitivity scores greater than 85%). The majority achieved a high degree of sensitivity at the expense of precision and yielded large result sets. The main advantage of the health-evidence.ca Systematic Review search filter in comparison to the other filters was that it maintained the same level of sensitivity while reducing the number of articles that needed to be screened. Conclusions The health-evidence.ca Systematic Review search filter is a useful tool for identifying published systematic reviews, with further screening to identify those evaluating the effectiveness of public health interventions. The filter that narrows the focus saves considerable time and resources during updates of this online resource, without sacrificing sensitivity. PMID:22512835

Optimization of hydrolysis and volatile fatty acids production from sugarcane filter cake: Effects of urea supplementation and sodium hydroxide pretreatment.

PubMed

Janke, Leandro; Leite, Athaydes; Batista, Karla; Weinrich, Sören; Sträuber, Heike; Nikolausz, Marcell; Nelles, Michael; Stinner, Walter

2016-01-01

Different methods for optimization the anaerobic digestion (AD) of sugarcane filter cake (FC) with a special focus on volatile fatty acids (VFA) production were studied. Sodium hydroxide (NaOH) pretreatment at different concentrations was investigated in batch experiments and the cumulative methane yields fitted to a dual-pool two-step model to provide an initial assessment on AD. The effects of nitrogen supplementation in form of urea and NaOH pretreatment for improved VFA production were evaluated in a semi-continuously operated reactor as well. The results indicated that higher NaOH concentrations during pretreatment accelerated the AD process and increased methane production in batch experiments. Nitrogen supplementation resulted in a VFA loss due to methane formation by buffering the pH value at nearly neutral conditions (∼ 6.7). However, the alkaline pretreatment with 6g NaOH/100g FCFM improved both the COD solubilization and the VFA yield by 37%, mainly consisted by n-butyric and acetic acids. Copyright © 2015 Elsevier Ltd. All rights reserved.

Designing a composite correlation filter based on iterative optimization of training images for distortion invariant face recognition

NASA Astrophysics Data System (ADS)

Wang, Q.; Elbouz, M.; Alfalou, A.; Brosseau, C.

2017-06-01

We present a novel method to optimize the discrimination ability and noise robustness of composite filters. This method is based on the iterative preprocessing of training images which can extract boundary and detailed feature information of authentic training faces, thereby improving the peak-to-correlation energy (PCE) ratio of authentic faces and to be immune to intra-class variance and noise interference. By adding the training images directly, one can obtain a composite template with high discrimination ability and robustness for face recognition task. The proposed composite correlation filter does not involve any complicated mathematical analysis and computation which are often required in the design of correlation algorithms. Simulation tests have been conducted to check the effectiveness and feasibility of our proposal. Moreover, to assess robustness of composite filters using receiver operating characteristic (ROC) curves, we devise a new method to count the true positive and false positive rates for which the difference between PCE and threshold is involved.

Recursive Implementations of the Consider Filter

NASA Technical Reports Server (NTRS)

Zanetti, Renato; DSouza, Chris

2012-01-01

One method to account for parameters errors in the Kalman filter is to consider their effect in the so-called Schmidt-Kalman filter. This work addresses issues that arise when implementing a consider Kalman filter as a real-time, recursive algorithm. A favorite implementation of the Kalman filter as an onboard navigation subsystem is the UDU formulation. A new way to implement a UDU consider filter is proposed. The non-optimality of the recursive consider filter is also analyzed, and a modified algorithm is proposed to overcome this limitation.

Design of two-channel filter bank using nature inspired optimization based fractional derivative constraints.

PubMed

Kuldeep, B; Singh, V K; Kumar, A; Singh, G K

2015-01-01

In this article, a novel approach for 2-channel linear phase quadrature mirror filter (QMF) bank design based on a hybrid of gradient based optimization and optimization of fractional derivative constraints is introduced. For the purpose of this work, recently proposed nature inspired optimization techniques such as cuckoo search (CS), modified cuckoo search (MCS) and wind driven optimization (WDO) are explored for the design of QMF bank. 2-Channel QMF is also designed with particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization techniques. The design problem is formulated in frequency domain as sum of L2 norm of error in passband, stopband and transition band at quadrature frequency. The contribution of this work is the novel hybrid combination of gradient based optimization (Lagrange multiplier method) and nature inspired optimization (CS, MCS, WDO, PSO and ABC) and its usage for optimizing the design problem. Performance of the proposed method is evaluated by passband error (ϕp), stopband error (ϕs), transition band error (ϕt), peak reconstruction error (PRE), stopband attenuation (As) and computational time. The design examples illustrate the ingenuity of the proposed method. Results are also compared with the other existing algorithms, and it was found that the proposed method gives best result in terms of peak reconstruction error and transition band error while it is comparable in terms of passband and stopband error. Results show that the proposed method is successful for both lower and higher order 2-channel QMF bank design. A comparative study of various nature inspired optimization techniques is also presented, and the study singles out CS as a best QMF optimization technique. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A generalized adaptive mathematical morphological filter for LIDAR data

NASA Astrophysics Data System (ADS)

Cui, Zheng

Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in

Carbon nanotube filters

NASA Astrophysics Data System (ADS)

Srivastava, A.; Srivastava, O. N.; Talapatra, S.; Vajtai, R.; Ajayan, P. M.

2004-09-01

Over the past decade of nanotube research, a variety of organized nanotube architectures have been fabricated using chemical vapour deposition. The idea of using nanotube structures in separation technology has been proposed, but building macroscopic structures that have controlled geometric shapes, density and dimensions for specific applications still remains a challenge. Here we report the fabrication of freestanding monolithic uniform macroscopic hollow cylinders having radially aligned carbon nanotube walls, with diameters and lengths up to several centimetres. These cylindrical membranes are used as filters to demonstrate their utility in two important settings: the elimination of multiple components of heavy hydrocarbons from petroleum-a crucial step in post-distillation of crude oil-with a single-step filtering process, and the filtration of bacterial contaminants such as Escherichia coli or the nanometre-sized poliovirus (~25 nm) from water. These macro filters can be cleaned for repeated filtration through ultrasonication and autoclaving. The exceptional thermal and mechanical stability of nanotubes, and the high surface area, ease and cost-effective fabrication of the nanotube membranes may allow them to compete with ceramic- and polymer-based separation membranes used commercially.

Carbon nanotube filters.

PubMed

Srivastava, A; Srivastava, O N; Talapatra, S; Vajtai, R; Ajayan, P M

2004-09-01

Over the past decade of nanotube research, a variety of organized nanotube architectures have been fabricated using chemical vapour deposition. The idea of using nanotube structures in separation technology has been proposed, but building macroscopic structures that have controlled geometric shapes, density and dimensions for specific applications still remains a challenge. Here we report the fabrication of freestanding monolithic uniform macroscopic hollow cylinders having radially aligned carbon nanotube walls, with diameters and lengths up to several centimetres. These cylindrical membranes are used as filters to demonstrate their utility in two important settings: the elimination of multiple components of heavy hydrocarbons from petroleum-a crucial step in post-distillation of crude oil-with a single-step filtering process, and the filtration of bacterial contaminants such as Escherichia coli or the nanometre-sized poliovirus ( approximately 25 nm) from water. These macro filters can be cleaned for repeated filtration through ultrasonication and autoclaving. The exceptional thermal and mechanical stability of nanotubes, and the high surface area, ease and cost-effective fabrication of the nanotube membranes may allow them to compete with ceramic- and polymer-based separation membranes used commercially.

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Rod-filter-field optimization of the J-PARC RF-driven H{sup −} ion source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueno, A., E-mail: akira.ueno@j-parc.jp; Ohkoshi, K.; Ikegami, K.

2015-04-08

In order to satisfy the Japan Proton Accelerator Research Complex (J-PARC) second-stage requirements of an H{sup −} ion beam of 60mA within normalized emittances of 1.5πmm•mrad both horizontally and vertically, a flat top beam duty factor of 1.25% (500μs×25Hz) and a life-time of longer than 1month, the J-PARC cesiated RF-driven H{sup −} ion source was developed by using an internal-antenna developed at the Spallation Neutron Source (SNS). Although rod-filter-field (RFF) is indispensable and one of the most beam performance dominative parameters for the RF-driven H{sup −} ion source with the internal-antenna, the procedure to optimize it is not established. Inmore » order to optimize the RFF and establish the procedure, the beam performances of the J-PARC source with various types of rod-filter-magnets (RFMs) were measured. By changing RFM’s gap length and gap number inside of the region projecting the antenna inner-diameter along the beam axis, the dependence of the H{sup −} ion beam intensity on the net 2MHz-RF power was optimized. Furthermore, the fine-tuning of RFM’s cross-section (magnetmotive force) was indispensable for easy operation with the temperature (T{sub PE}) of the plasma electrode (PE) lower than 70°C, which minimizes the transverse emittances. The 5% reduction of RFM’s cross-section decreased the time-constant to recover the cesium effects after an slightly excessive cesiation on the PE from several 10 minutes to several minutes for T{sub PE} around 60°C.« less

An optimized time varying filtering based empirical mode decomposition method with grey wolf optimizer for machinery fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei

2018-03-01

A time varying filtering based empirical mode decomposition (EMD) (TVF-EMD) method was proposed recently to solve the mode mixing problem of EMD method. Compared with the classical EMD, TVF-EMD was proven to improve the frequency separation performance and be robust to noise interference. However, the decomposition parameters (i.e., bandwidth threshold and B-spline order) significantly affect the decomposition results of this method. In original TVF-EMD method, the parameter values are assigned in advance, which makes it difficult to achieve satisfactory analysis results. To solve this problem, this paper develops an optimized TVF-EMD method based on grey wolf optimizer (GWO) algorithm for fault diagnosis of rotating machinery. Firstly, a measurement index termed weighted kurtosis index is constructed by using kurtosis index and correlation coefficient. Subsequently, the optimal TVF-EMD parameters that match with the input signal can be obtained by GWO algorithm using the maximum weighted kurtosis index as objective function. Finally, fault features can be extracted by analyzing the sensitive intrinsic mode function (IMF) owning the maximum weighted kurtosis index. Simulations and comparisons highlight the performance of TVF-EMD method for signal decomposition, and meanwhile verify the fact that bandwidth threshold and B-spline order are critical to the decomposition results. Two case studies on rotating machinery fault diagnosis demonstrate the effectiveness and advantages of the proposed method.

Design of order statistics filters using feedforward neural networks

NASA Astrophysics Data System (ADS)

Maslennikova, Yu. S.; Bochkarev, V. V.

2016-08-01

In recent years significant progress have been made in the development of nonlinear data processing techniques. Such techniques are widely used in digital data filtering and image enhancement. Many of the most effective nonlinear filters based on order statistics. The widely used median filter is the best known order statistic filter. Generalized form of these filters could be presented based on Lloyd's statistics. Filters based on order statistics have excellent robustness properties in the presence of impulsive noise. In this paper, we present special approach for synthesis of order statistics filters using artificial neural networks. Optimal Lloyd's statistics are used for selecting of initial weights for the neural network. Adaptive properties of neural networks provide opportunities to optimize order statistics filters for data with asymmetric distribution function. Different examples demonstrate the properties and performance of presented approach.

A two-step parameter optimization algorithm for improving estimation of optical properties using spatial frequency domain imaging

NASA Astrophysics Data System (ADS)

Hu, Dong; Lu, Renfu; Ying, Yibin

2018-03-01

This research was aimed at optimizing the inverse algorithm for estimating the optical absorption (μa) and reduced scattering (μs‧) coefficients from spatial frequency domain diffuse reflectance. Studies were first conducted to determine the optimal frequency resolution and start and end frequencies in terms of the reciprocal of mean free path (1/mfp‧). The results showed that the optimal frequency resolution increased with μs‧ and remained stable when μs‧ was larger than 2 mm-1. The optimal end frequency decreased from 0.3/mfp‧ to 0.16/mfp‧ with μs‧ ranging from 0.4 mm-1 to 3 mm-1, while the optimal start frequency remained at 0 mm-1. A two-step parameter estimation method was proposed based on the optimized frequency parameters, which improved estimation accuracies by 37.5% and 9.8% for μa and μs‧, respectively, compared with the conventional one-step method. Experimental validations with seven liquid optical phantoms showed that the optimized algorithm resulted in the mean absolute errors of 15.4%, 7.6%, 5.0% for μa and 16.4%, 18.0%, 18.3% for μs‧ at the wavelengths of 675 nm, 700 nm, and 715 nm, respectively. Hence, implementation of the optimized parameter estimation method should be considered in order to improve the measurement of optical properties of biological materials when using spatial frequency domain imaging technique.

Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Armstrong, Jeffrey B.; Garg, Sanjay

2012-01-01

An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.

Aircraft Recirculation Filter for Air-Quality and Incident Assessment

PubMed Central

Eckels, Steven J.; Jones, Byron; Mann, Garrett; Mohan, Krishnan R.; Weisel, Clifford P.

2015-01-01

The current research examines the possibility of using recirculation filters from aircraft to document the nature of air-quality incidents on aircraft. These filters are highly effective at collecting solid and liquid particulates. Identification of engine oil contaminants arriving through the bleed air system on the filter was chosen as the initial focus. A two-step study was undertaken. First, a compressor/bleed air simulator was developed to simulate an engine oil leak, and samples were analyzed with gas chromatograph-mass spectrometry. These samples provided a concrete link between tricresyl phosphates and a homologous series of synthetic pentaerythritol esters from oil and contaminants found on the sample paper. The second step was to test 184 used aircraft filters with the same gas chromatograph-mass spectrometry system; of that total, 107 were standard filters, and 77 were nonstandard. Four of the standard filters had both markers for oil, with the homologous series synthetic pentaerythritol esters being the less common marker. It was also found that 90% of the filters had some detectable level of tricresyl phosphates. Of the 77 nonstandard filters, 30 had both markers for oil, a significantly higher percent than the standard filters. PMID:25641977

Aircraft Recirculation Filter for Air-Quality and Incident Assessment.

PubMed

Eckels, Steven J; Jones, Byron; Mann, Garrett; Mohan, Krishnan R; Weisel, Clifford P

The current research examines the possibility of using recirculation filters from aircraft to document the nature of air-quality incidents on aircraft. These filters are highly effective at collecting solid and liquid particulates. Identification of engine oil contaminants arriving through the bleed air system on the filter was chosen as the initial focus. A two-step study was undertaken. First, a compressor/bleed air simulator was developed to simulate an engine oil leak, and samples were analyzed with gas chromatograph-mass spectrometry. These samples provided a concrete link between tricresyl phosphates and a homologous series of synthetic pentaerythritol esters from oil and contaminants found on the sample paper. The second step was to test 184 used aircraft filters with the same gas chromatograph-mass spectrometry system; of that total, 107 were standard filters, and 77 were nonstandard. Four of the standard filters had both markers for oil, with the homologous series synthetic pentaerythritol esters being the less common marker. It was also found that 90% of the filters had some detectable level of tricresyl phosphates. Of the 77 nonstandard filters, 30 had both markers for oil, a significantly higher percent than the standard filters.

Importance of Adjunct Delivery Techniques to Optimize Deployment Success of Distal Protection Filters During Vein Graft Intervention.

PubMed

Kaliyadan, Antony G; Chawla, Harnish; Fischman, David L; Ruggiero, Nicholas; Gannon, Michael; Walinsky, Paul; Savage, Michael P

2017-02-01

technically difficult with complex SVG disease. Adjunct delivery techniques are important to optimize deployment success of distal protection filters during SVG intervention.

The Lockheed alternate partial polarizer universal filter

NASA Technical Reports Server (NTRS)

Title, A. M.

1976-01-01

A tunable birefringent filter using an alternate partial polarizer design has been built. The filter has a transmission of 38% in polarized light. Its full width at half maximum is .09A at 5500A. It is tunable from 4500 to 8500A by means of stepping motor actuated rotating half wave plates and polarizers. Wave length commands and thermal compensation commands are generated by a PPD 11/10 minicomputer. The alternate partial polarizer universal filter is compared with the universal birefringent filter and the design techniques, construction methods, and filter performance are discussed in some detail. Based on the experience of this filter some conclusions regarding the future of birefringent filters are elaborated.

Denitrifying woodchip bioreactor and phosphorus filter pairing to minimize pollution swapping

USGS Publications Warehouse

Christianson, Laura E.; Lepine, Christine; Sibrell, Philip; Penn, Chad J.; Summerfelt, Steven T.

2017-01-01

Pairing denitrifying woodchip bioreactors and phosphorus-sorbing filters provides a unique, engineered approach for dual nutrient removal from waters impaired with both nitrogen (N) and phosphorus (P). This column study aimed to test placement of two P-filter media (acid mine drainage treatment residuals and steel slag) relative to a denitrifying system to maximize N and P removal and minimize pollution swapping under varying flow conditions (i.e., woodchip column hydraulic retention times (HRTs) of 7.2, 18, and 51 h; P-filter HRTs of 7.6–59 min). Woodchip denitrification columns were placed either upstream or downstream of P-filters filled with either medium. The configuration with woodchip denitrifying systems placed upstream of the P-filters generally provided optimized dissolved P removal efficiencies and removal rates. The P-filters placed upstream of the woodchip columns exhibited better P removal than downstream-placed P-filters only under overly long (i.e., N-limited) retention times when highly reduced effluent exited the woodchip bioreactors. The paired configurations using mine drainage residuals provided significantly greater P removal than the steel slag P-filters (e.g., 25–133 versus 8.8–48 g P removed m−3 filter media d−1, respectively), but there were no significant differences in N removal between treatments (removal rates: 8.0–18 g N removed m−3 woodchips d−1; N removal efficiencies: 18–95% across all HRTs). The range of HRTs tested here resulted in various undesirable pollution swapping by-products from the denitrifying bioreactors: nitrite production when nitrate removal was not complete and sulfate reduction, chemical oxygen demand production and decreased pH during overly long retention times. The downstream P-filter placement provided a polishing step for removal of chemical oxygen demand and nitrite.

Denitrifying woodchip bioreactor and phosphorus filter pairing to minimize pollution swapping.

PubMed

Christianson, Laura E; Lepine, Christine; Sibrell, Philip L; Penn, Chad; Summerfelt, Steven T

2017-09-15

Pairing denitrifying woodchip bioreactors and phosphorus-sorbing filters provides a unique, engineered approach for dual nutrient removal from waters impaired with both nitrogen (N) and phosphorus (P). This column study aimed to test placement of two P-filter media (acid mine drainage treatment residuals and steel slag) relative to a denitrifying system to maximize N and P removal and minimize pollution swapping under varying flow conditions (i.e., woodchip column hydraulic retention times (HRTs) of 7.2, 18, and 51 h; P-filter HRTs of 7.6-59 min). Woodchip denitrification columns were placed either upstream or downstream of P-filters filled with either medium. The configuration with woodchip denitrifying systems placed upstream of the P-filters generally provided optimized dissolved P removal efficiencies and removal rates. The P-filters placed upstream of the woodchip columns exhibited better P removal than downstream-placed P-filters only under overly long (i.e., N-limited) retention times when highly reduced effluent exited the woodchip bioreactors. The paired configurations using mine drainage residuals provided significantly greater P removal than the steel slag P-filters (e.g., 25-133 versus 8.8-48 g P removed m -3 filter media d -1 , respectively), but there were no significant differences in N removal between treatments (removal rates: 8.0-18 g N removed m -3 woodchips d -1 ; N removal efficiencies: 18-95% across all HRTs). The range of HRTs tested here resulted in various undesirable pollution swapping by-products from the denitrifying bioreactors: nitrite production when nitrate removal was not complete and sulfate reduction, chemical oxygen demand production and decreased pH during overly long retention times. The downstream P-filter placement provided a polishing step for removal of chemical oxygen demand and nitrite. Copyright © 2017 The Conservation Fund. Published by Elsevier Ltd.. All rights reserved.

Aquatic Plants Aid Sewage Filter

NASA Technical Reports Server (NTRS)

Wolverton, B. C.

1985-01-01

Method of wastewater treatment combines micro-organisms and aquatic plant roots in filter bed. Treatment occurs as liquid flows up through system. Micro-organisms, attached themselves to rocky base material of filter, act in several steps to decompose organic matter in wastewater. Vascular aquatic plants (typically, reeds, rushes, cattails, or water hyacinths) absorb nitrogen, phosphorus, other nutrients, and heavy metals from water through finely divided roots.

Pilonidal Sinus Disease: 10 Steps to Optimize Care.

PubMed

Harris, Connie; Sibbald, R Gary; Mufti, Asfandyar; Somayaji, Ranjani

2016-10-01

To present a 10-step approach to the assessment and treatment of pilonidal sinus disease (PSD) and related wounds based on the Harris protocol, expert opinion, and a current literature review. This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. After participating in this educational activity, the participant should be better able to: Pilonidal sinus disease (PSD) is a common problem in young adults and particularly in males with a deep natal or intergluteal cleft and coarse body hair. An approach to an individual with PSD includes the assessment of pain, activities of daily living, the pilonidal sinus, and natal cleft. Local wound care includes the management of infection (if present), along with appropriate debridement and moisture management. Treatment is optimized with patient empowerment to manage the wound and periwound environment (cleansing, dressing changes, decontamination, hair removal, minimizing friction). Self-care education includes the recognition of recurrences or infection. Early surgical intervention of these wounds is often necessary for successful outcomes. Pilonidal sinus healing by secondary intention often takes weeks to months; however, the use of the Harris protocol may decrease healing times. A number of new surgical approaches may accelerate healing. Surgical closure by primary intention is often associated with higher recurrence rates. Expert opinion in this article is combined with an evidence-based literature review. The authors have tabulated 10 key steps from the Harris protocol, including a review of the surgical techniques to improve PSD patient outcomes.

A high-throughput semi-automated preparation for filtered synaptoneurosomes.

PubMed

Murphy, Kathryn M; Balsor, Justin; Beshara, Simon; Siu, Caitlin; Pinto, Joshua G A

2014-09-30

Synaptoneurosomes have become an important tool for studying synaptic proteins. The filtered synaptoneurosomes preparation originally developed by Hollingsworth et al. (1985) is widely used and is an easy method to prepare synaptoneurosomes. The hand processing steps in that preparation, however, are labor intensive and have become a bottleneck for current proteomic studies using synaptoneurosomes. For this reason, we developed new steps for tissue homogenization and filtration that transform the preparation of synaptoneurosomes to a high-throughput, semi-automated process. We implemented a standardized protocol with easy to follow steps for homogenizing multiple samples simultaneously using a FastPrep tissue homogenizer (MP Biomedicals, LLC) and then filtering all of the samples in centrifugal filter units (EMD Millipore, Corp). The new steps dramatically reduce the time to prepare synaptoneurosomes from hours to minutes, increase sample recovery, and nearly double enrichment for synaptic proteins. These steps are also compatible with biosafety requirements for working with pathogen infected brain tissue. The new high-throughput semi-automated steps to prepare synaptoneurosomes are timely technical advances for studies of low abundance synaptic proteins in valuable tissue samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling error analysis of stationary linear discrete-time filters

NASA Technical Reports Server (NTRS)

Patel, R.; Toda, M.

1977-01-01

The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal and optimal (Kalman) filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a design can easily compare the performance of a suboptimal filter with that of the optimal filter, when only the range of errors in the elements of the model matrices is available.

The use of filter media to determine filter cleanliness

NASA Astrophysics Data System (ADS)

Van Staden, S. J.; Haarhoff, J.

It is general believed that a sand filter starts its life with new, perfectly clean media, which becomes gradually clogged with each filtration cycle, eventually getting to a point where either head loss or filtrate quality starts to deteriorate. At this point the backwash cycle is initiated and, through the combined action of air and water, returns the media to its original perfectly clean state. Reality, however, dictates otherwise. Many treatment plants visited a decade or more after commissioning are found to have unacceptably dirty filter sand and backwash systems incapable of returning the filter media to a desired state of cleanliness. In some cases, these problems are common ones encountered in filtration plants but many reasons for media deterioration remain elusive, falling outside of these common problems. The South African conditions of highly eutrophic surface waters at high temperatures, however, exacerbate the problems with dirty filter media. Such conditions often lead to the formation of biofilm in the filter media, which is shown to inhibit the effective backwashing of sand and carbon filters. A systematic investigation into filter media cleanliness was therefore started in 2002, ending in 2005, at the University of Johannesburg (the then Rand Afrikaans University). This involved media from eight South African Water Treatment Plants, varying between sand and sand-anthracite combinations and raw water types from eutrophic through turbid to low-turbidity waters. Five states of cleanliness and four fractions of specific deposit were identified relating to in situ washing, column washing, cylinder inversion and acid-immersion techniques. These were measured and the results compared to acceptable limits for specific deposit, as determined in previous studies, though expressed in kg/m 3. These values were used to determine the state of the filters. In order to gain greater insight into the composition of the specific deposits stripped from the media, a

Selection vector filter framework

NASA Astrophysics Data System (ADS)

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

2003-10-01

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

An optimized strain demodulation method for PZT driven fiber Fabry-Perot tunable filter

NASA Astrophysics Data System (ADS)

Sheng, Wenjuan; Peng, G. D.; Liu, Yang; Yang, Ning

2015-08-01

An optimized strain-demodulation-method based on piezo-electrical transducer (PZT) driven fiber Fabry-Perot (FFP) filter is proposed and experimentally demonstrated. Using a parallel processing mode to drive the PZT continuously, the hysteresis effect is eliminated, and the system demodulation rate is increased. Furthermore, an AC-DC compensation method is developed to address the intrinsic nonlinear relationship between the displacement and voltage of PZT. The experimental results show that the actual demodulation rate is improved from 15 Hz to 30 Hz, the random error of the strain measurement is decreased by 95%, and the deviation between the test values after compensation and the theoretical values is less than 1 pm/με.

Picking Deep Filter Responses for Fine-Grained Image Recognition (Open Access Author’s Manuscript)

DTIC Science & Technology

2016-12-16

stages. Our method explores a unified framework based on two steps of deep filter response picking. The first picking step is to find distinctive... filters which respond to specific patterns significantly and consistently, and learn a set of part detectors via iteratively alternating between new...positive sample mining and part model retraining. The second picking step is to pool deep filter responses via spatially weighted combination of Fisher

MR image reconstruction via guided filter.

PubMed

Huang, Heyan; Yang, Hang; Wang, Kang

2018-04-01

Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.

Performance evaluation of an asynchronous multisensor track fusion filter

NASA Astrophysics Data System (ADS)

Alouani, Ali T.; Gray, John E.; McCabe, D. H.

2003-08-01

Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

Design-Filter Selection for H2 Control of Microgravity Isolation Systems: A Single-Degree-of-Freedom Case Study

NASA Technical Reports Server (NTRS)

Hampton, R. David; Whorton, Mark S.

2000-01-01

Many microgravity space-science experiments require active vibration isolation, to attain suitably low levels of background acceleration for useful experimental results. The design of state-space controllers by optimal control methods requires judicious choices of frequency-weighting design filters. Kinematic coupling among states greatly clouds designer intuition in the choices of these filters, and the masking effects of the state observations cloud the process further. Recent research into the practical application of H2 synthesis methods to such problems, indicates that certain steps can lead to state frequency-weighting design-filter choices with substantially improved promise of usefulness, even in the face of these difficulties. In choosing these filters on the states, one considers their relationships to corresponding design filters on appropriate pseudo-sensitivity- and pseudo-complementary-sensitivity functions. This paper investigates the application of these considerations to a single-degree-of-freedom microgravity vibration-isolation test case. Significant observations that were noted during the design process are presented. along with explanations based on the existent theory for such problems.

An application of PSO algorithm for multi-criteria geometry optimization of printed low-pass filters based on conductive periodic structures

NASA Astrophysics Data System (ADS)

Steckiewicz, Adam; Butrylo, Boguslaw

2017-08-01

In this paper we discussed the results of a multi-criteria optimization scheme as well as numerical calculations of periodic conductive structures with selected geometry. Thin printed structures embedded on a flexible dielectric substrate may be applied as simple, cheap, passive low-pass filters with an adjustable cutoff frequency in low (up to 1 MHz) radio frequency range. The analysis of an electromagnetic phenomena in presented structures was realized on the basis of a three-dimensional numerical model of three proposed geometries of periodic elements. The finite element method (FEM) was used to obtain a solution of an electromagnetic harmonic field. Equivalent lumped electrical parameters of printed cells obtained in such manner determine the shape of an amplitude transmission characteristic of a low-pass filter. A nonlinear influence of a printed cell geometry on equivalent parameters of cells electric model, makes it difficult to find the desired optimal solution. Therefore an optimization problem of optimal cell geometry estimation with regard to an approximation of the determined amplitude transmission characteristic with an adjusted cutoff frequency, was obtained by the particle swarm optimization (PSO) algorithm. A dynamically suitable inertia factor was also introduced into the algorithm to improve a convergence to a global extremity of a multimodal objective function. Numerical results as well as PSO simulation results were characterized in terms of approximation accuracy of predefined amplitude characteristics in a pass-band, stop-band and cutoff frequency. Three geometries of varying degrees of complexity were considered and their use in signal processing systems was evaluated.

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2005-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration.

NASA Astrophysics Data System (ADS)

Uzunoglu, B.; Hussaini, Y.

2017-12-01

Implicit Particle Filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability by an implicit step . It optimizes a nonlinear cost function which can be inherited from legacy assimilation routines . Dynamic state estimation for almost real-time applications in power systems are becomingly increasingly more important with integration of variable wind and solar power generation. New advanced state estimation tools that will replace the old generation state estimation in addition to having a general framework of complexities should be able to address the legacy software and able to integrate the old software in a mathematical framework while allowing the power industry need for a cautious and evolutionary change in comparison to a complete revolutionary approach while addressing nonlinearity and non-normal behaviour. This work implements implicit particle filter as a state estimation tool for the estimation of the states of a power system and presents the first implicit particle filter application study on a power system state estimation. The implicit particle filter is introduced into power systems and the simulations are presented for a three-node benchmark power system . The performance of the filter on the presented problem is analyzed and the results are presented.

Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

PubMed Central

Cervantes-Sanchez, Fernando; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Ornelas-Rodriguez, Manuel; Torres-Cisneros, Miguel

2016-01-01

This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA) in X-ray angiograms. Since the single-scale Gabor filters (SSG) are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (A z) under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with A z = 0.9502 over a training set of 40 images and A z = 0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms. PMID:27738422

Noise reduction and functional maps image quality improvement in dynamic CT perfusion using a new k-means clustering guided bilateral filter (KMGB).

PubMed

Pisana, Francesco; Henzler, Thomas; Schönberg, Stefan; Klotz, Ernst; Schmidt, Bernhard; Kachelrieß, Marc

2017-07-01

Dynamic CT perfusion (CTP) consists in repeated acquisitions of the same volume in different time steps, slightly before, during and slightly afterwards the injection of contrast media. Important functional information can be derived for each voxel, which reflect the local hemodynamic properties and hence the metabolism of the tissue. Different approaches are being investigated to exploit data redundancy and prior knowledge for noise reduction of such datasets, ranging from iterative reconstruction schemes to high dimensional filters. We propose a new spatial bilateral filter which makes use of the k-means clustering algorithm and of an optimal calculated guiding image. We named the proposed filter as k-means clustering guided bilateral filter (KMGB). In this study, the KMGB filter is compared with the partial temporal non-local means filter (PATEN), with the time-intensity profile similarity (TIPS) filter, and with a new version derived from it, by introducing the guiding image (GB-TIPS). All the filters were tested on a digital in-house developed brain CTP phantom, were noise was added to simulate 80 kV and 200 mAs (default scanning parameters), 100 mAs and 30 mAs. Moreover, the filters performances were tested on 7 noisy clinical datasets with different pathologies in different body regions. The original contribution of our work is two-fold: first we propose an efficient algorithm to calculate a guiding image to improve the results of the TIPS filter, secondly we propose the introduction of the k-means clustering step and demonstrate how this can potentially replace the TIPS part of the filter obtaining better results at lower computational efforts. As expected, in the GB-TIPS, the introduction of the guiding image limits the over-smoothing of the TIPS filter, improving spatial resolution by more than 50%. Furthermore, replacing the time-intensity profile similarity calculation with a fuzzy k-means clustering strategy (KMGB) allows to control the edge preserving

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

NASA Astrophysics Data System (ADS)

Wang, Ershen; Jia, Chaoying; Tong, Gang; Qu, Pingping; Lan, Xiaoyu; Pang, Tao

2018-03-01

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.

Improved Goldstein Interferogram Filter Based on Local Fringe Frequency Estimation.

PubMed

Feng, Qingqing; Xu, Huaping; Wu, Zhefeng; You, Yanan; Liu, Wei; Ge, Shiqi

2016-11-23

The quality of an interferogram, which is limited by various phase noise, will greatly affect the further processes of InSAR, such as phase unwrapping. Interferometric SAR (InSAR) geophysical measurements', such as height or displacement, phase filtering is therefore an essential step. In this work, an improved Goldstein interferogram filter is proposed to suppress the phase noise while preserving the fringe edges. First, the proposed adaptive filter step, performed before frequency estimation, is employed to improve the estimation accuracy. Subsequently, to preserve the fringe characteristics, the estimated fringe frequency in each fixed filtering patch is removed from the original noisy phase. Then, the residual phase is smoothed based on the modified Goldstein filter with its parameter alpha dependent on both the coherence map and the residual phase frequency. Finally, the filtered residual phase and the removed fringe frequency are combined to generate the filtered interferogram, with the loss of signal minimized while reducing the noise level. The effectiveness of the proposed method is verified by experimental results based on both simulated and real data.

Improved Goldstein Interferogram Filter Based on Local Fringe Frequency Estimation

PubMed Central

Feng, Qingqing; Xu, Huaping; Wu, Zhefeng; You, Yanan; Liu, Wei; Ge, Shiqi

2016-01-01

The quality of an interferogram, which is limited by various phase noise, will greatly affect the further processes of InSAR, such as phase unwrapping. Interferometric SAR (InSAR) geophysical measurements’, such as height or displacement, phase filtering is therefore an essential step. In this work, an improved Goldstein interferogram filter is proposed to suppress the phase noise while preserving the fringe edges. First, the proposed adaptive filter step, performed before frequency estimation, is employed to improve the estimation accuracy. Subsequently, to preserve the fringe characteristics, the estimated fringe frequency in each fixed filtering patch is removed from the original noisy phase. Then, the residual phase is smoothed based on the modified Goldstein filter with its parameter alpha dependent on both the coherence map and the residual phase frequency. Finally, the filtered residual phase and the removed fringe frequency are combined to generate the filtered interferogram, with the loss of signal minimized while reducing the noise level. The effectiveness of the proposed method is verified by experimental results based on both simulated and real data. PMID:27886081

Progress in navigation filter estimate fusion and its application to spacecraft rendezvous

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

1994-01-01

A new derivation of an algorithm which fuses the outputs of two Kalman filters is presented within the context of previous research in this field. Unlike other works, this derivation clearly shows the combination of estimates to be optimal, minimizing the trace of the fused covariance matrix. The algorithm assumes that the filters use identical models, and are stable and operating optimally with respect to their own local measurements. Evidence is presented which indicates that the error ellipsoid derived from the covariance of the optimally fused estimate is contained within the intersections of the error ellipsoids of the two filters being fused. Modifications which reduce the algorithm's data transmission requirements are also presented, including a scalar gain approximation, a cross-covariance update formula which employs only the two contributing filters' autocovariances, and a form of the algorithm which can be used to reinitialize the two Kalman filters. A sufficient condition for using the optimally fused estimates to periodically reinitialize the Kalman filters in this fashion is presented and proved as a theorem. When these results are applied to an optimal spacecraft rendezvous problem, simulated performance results indicate that the use of optimally fused data leads to significantly improved robustness to initial target vehicle state errors. The following applications of estimate fusion methods to spacecraft rendezvous are also described: state vector differencing, and redundancy management.

Robotic fish tracking method based on suboptimal interval Kalman filter

NASA Astrophysics Data System (ADS)

Tong, Xiaohong; Tang, Chao

2017-11-01

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

The optimal design of stepped wedge trials with equal allocation to sequences and a comparison to other trial designs.

PubMed

Thompson, Jennifer A; Fielding, Katherine; Hargreaves, James; Copas, Andrew

2017-12-01

Background/Aims We sought to optimise the design of stepped wedge trials with an equal allocation of clusters to sequences and explored sample size comparisons with alternative trial designs. Methods We developed a new expression for the design effect for a stepped wedge trial, assuming that observations are equally correlated within clusters and an equal number of observations in each period between sequences switching to the intervention. We minimised the design effect with respect to (1) the fraction of observations before the first and after the final sequence switches (the periods with all clusters in the control or intervention condition, respectively) and (2) the number of sequences. We compared the design effect of this optimised stepped wedge trial to the design effects of a parallel cluster-randomised trial, a cluster-randomised trial with baseline observations, and a hybrid trial design (a mixture of cluster-randomised trial and stepped wedge trial) with the same total cluster size for all designs. Results We found that a stepped wedge trial with an equal allocation to sequences is optimised by obtaining all observations after the first sequence switches and before the final sequence switches to the intervention; this means that the first sequence remains in the control condition and the last sequence remains in the intervention condition for the duration of the trial. With this design, the optimal number of sequences is [Formula: see text], where [Formula: see text] is the cluster-mean correlation, [Formula: see text] is the intracluster correlation coefficient, and m is the total cluster size. The optimal number of sequences is small when the intracluster correlation coefficient and cluster size are small and large when the intracluster correlation coefficient or cluster size is large. A cluster-randomised trial remains more efficient than the optimised stepped wedge trial when the intracluster correlation coefficient or cluster size is small. A

Reflective Filters Design for Self-Filtering Narrowband Ultraviolet Imaging Experiment Wide-Field Surveys (NUVIEWS) Project

NASA Technical Reports Server (NTRS)

Park, Jung- Ho; Kim, Jongmin; Zukic, Muamer; Torr, Douglas G.

1994-01-01

We report the design of multilayer reflective filters for the self-filtering cameras of the NUVIEWS project. Wide angle self-filtering cameras were designed to image the C IV (154.9 nm) line emission, and H2 Lyman band fluorescence (centered at 161 nm) over a 20 deg x 30 deg field of view. A key element of the filter design includes the development of pi-multilayers optimized to provide maximum reflectance at 154.9 nm and 161 nm for the respective cameras without significant spectral sensitivity to the large cone angle of the incident radiation. We applied self-filtering concepts to design NUVIEWS telescope filters that are composed of three reflective mirrors and one folding mirror. The filters with narrowband widths of 6 and 8 rim at 154.9 and 161 nm, respectively, have net throughputs of more than 50 % with average blocking of out-of-band wavelengths better than 3 x 10(exp -4)%.

Simplification of the Kalman filter for meteorological data assimilation

NASA Technical Reports Server (NTRS)

Dee, Dick P.

1991-01-01

The paper proposes a new statistical method of data assimilation that is based on a simplification of the Kalman filter equations. The forecast error covariance evolution is approximated simply by advecting the mass-error covariance field, deriving the remaining covariances geostrophically, and accounting for external model-error forcing only at the end of each forecast cycle. This greatly reduces the cost of computation of the forecast error covariance. In simulations with a linear, one-dimensional shallow-water model and data generated artificially, the performance of the simplified filter is compared with that of the Kalman filter and the optimal interpolation (OI) method. The simplified filter produces analyses that are nearly optimal, and represents a significant improvement over OI.

Optimal hydrograph separation using a recursive digital filter constrained by chemical mass balance, with application to selected Chesapeake Bay watersheds

USGS Publications Warehouse

Raffensperger, Jeff P.; Baker, Anna C.; Blomquist, Joel D.; Hopple, Jessica A.

2017-06-26

Quantitative estimates of base flow are necessary to address questions concerning the vulnerability and response of the Nation’s water supply to natural and human-induced change in environmental conditions. An objective of the U.S. Geological Survey National Water-Quality Assessment Project is to determine how hydrologic systems are affected by watershed characteristics, including land use, land cover, water use, climate, and natural characteristics (geology, soil type, and topography). An important component of any hydrologic system is base flow, generally described as the part of streamflow that is sustained between precipitation events, fed to stream channels by delayed (usually subsurface) pathways, and more specifically as the volumetric discharge of water, estimated at a measurement site or gage at the watershed scale, which represents groundwater that discharges directly or indirectly to stream reaches and is then routed to the measurement point.Hydrograph separation using a recursive digital filter was applied to 225 sites in the Chesapeake Bay watershed. The recursive digital filter was chosen for the following reasons: it is based in part on the assumption that groundwater acts as a linear reservoir, and so has a physical basis; it has only two adjustable parameters (alpha, obtained directly from recession analysis, and beta, the maximum value of the base-flow index that can be modeled by the filter), which can be determined objectively and with the same physical basis of groundwater reservoir linearity, or that can be optimized by applying a chemical-mass-balance constraint. Base-flow estimates from the recursive digital filter were compared with those from five other hydrograph-separation methods with respect to two metrics: the long-term average fraction of streamflow that is base flow, or base-flow index, and the fraction of days where streamflow is entirely base flow. There was generally good correlation between the methods, with some biased

Kalman filter based control for Adaptive Optics

NASA Astrophysics Data System (ADS)

Petit, Cyril; Quiros-Pacheco, Fernando; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

2004-12-01

Classical Adaptive Optics suffer from a limitation of the corrected Field Of View. This drawback has lead to the development of MultiConjugated Adaptive Optics. While the first MCAO experimental set-ups are presently under construction, little attention has been paid to the control loop. This is however a key element in the optimization process especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications : simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering which seems a very promising solution. Following the work of Brice Leroux, we focus on a frequential characterization of kalman filters, computing a transfer matrix. The result brings much information about their behaviour and allows comparisons with classical controllers. It also appears that straightforward improvements of the system models can lead to static aberrations and vibrations filtering. Simulation results are proposed and analysed thanks to our frequential characterization. Related problems such as model errors, aliasing effect reduction or experimental implementation and testing of Kalman filter control loop on a simplified MCAO experimental set-up could be then discussed.

Evidence-Based Evaluation of Inferior Vena Cava Filter Complications Based on Filter Type

PubMed Central

Deso, Steven E.; Idakoji, Ibrahim A.; Kuo, William T.

2016-01-01

Many inferior vena cava (IVC) filter types, along with their specific risks and complications, are not recognized. The purpose of this study was to evaluate the various FDA-approved IVC filter types to determine device-specific risks, as a way to help identify patients who may benefit from ongoing follow-up versus prompt filter retrieval. An evidence-based electronic search (FDA Premarket Notification, MEDLINE, FDA MAUDE) was performed to identify all IVC filter types and device-specific complications from 1980 to 2014. Twenty-three IVC filter types (14 retrievable, 9 permanent) were identified. The devices were categorized as follows: conical (n = 14), conical with umbrella (n = 1), conical with cylindrical element (n = 2), biconical with cylindrical element (n = 2), helical (n = 1), spiral (n = 1), and complex (n = 1). Purely conical filters were associated with the highest reported risks of penetration (90–100%). Filters with cylindrical or umbrella elements were associated with the highest reported risk of IVC thrombosis (30–50%). Conical Bard filters were associated with the highest reported risks of fracture (40%). The various FDA-approved IVC filter types were evaluated for device-specific complications based on best current evidence. This information can be used to guide and optimize clinical management in patients with indwelling IVC filters. PMID:27247477

The invariant of the stiffness filter function with the weight filter function of the power function form

NASA Astrophysics Data System (ADS)

Shang, Zhen; Sui, Yun-Kang

2012-12-01

Based on the independent, continuous and mapping (ICM) method and homogenization method, a research model is constructed to propose and deduce a theorem and corollary from the invariant between the weight filter function and the corresponding stiffness filter function of the form of power function. The efficiency in searching for optimum solution will be raised via the choice of rational filter functions, so the above mentioned results are very important to the further study of structural topology optimization.

Reducing radiation dose by application of optimized low-energy x-ray filters to K-edge imaging with a photon counting detector.

PubMed

Choi, Yu-Na; Lee, Seungwan; Kim, Hee-Joung

2016-01-21

K-edge imaging with photon counting x-ray detectors (PCXDs) can improve image quality compared with conventional energy integrating detectors. However, low-energy x-ray photons below the K-edge absorption energy of a target material do not contribute to image formation in the K-edge imaging and are likely to be completely absorbed by an object. In this study, we applied x-ray filters to the K-edge imaging with a PCXD based on cadmium zinc telluride for reducing radiation dose induced by low-energy x-ray photons. We used aluminum (Al) filters with different thicknesses as the low-energy x-ray filters and implemented the iodine K-edge imaging with an energy bin of 34-48 keV at the tube voltages of 50, 70 and 90 kVp. The effects of the low-energy x-ray filters on the K-edge imaging were investigated with respect to signal-difference-to-noise ratio (SDNR), entrance surface air kerma (ESAK) and figure of merit (FOM). The highest value of SDNR was observed in the K-edge imaging with a 2 mm Al filter, and the SDNR decreased as a function of the filter thicknesses. Compared to the K-edge imaging with a 2 mm Al filter, the ESAK was reduced by 66%, 48% and 39% in the K-edge imaging with a 12 mm Al filter for 50 kVp, 70 kVp and 90 kVp, respectively. The FOM values, which took into account the ESAK and SDNR, were maximized for 8, 6 to 8 and 4 mm Al filters at 50 kVp, 70 kVp and 90 kVp, respectively. We concluded that the use of an optimal low-energy filter thickness, which was determined by maximizing the FOM, could significantly reduce radiation dose while maintaining image quality in the K-edge imaging with the PCXD.

An optimal modification of a Kalman filter for time scales

NASA Technical Reports Server (NTRS)

Greenhall, C. A.

2003-01-01

The Kalman filter in question, which was implemented in the time scale algorithm TA(NIST), produces time scales with poor short-term stability. A simple modification of the error covariance matrix allows the filter to produce time scales with good stability at all averaging times, as verified by simulations of clock ensembles.

Method of producing monolithic ceramic cross-flow filter

DOEpatents

Larsen, D.A.; Bacchi, D.P.; Connors, T.F.; Collins, E.L. III

1998-02-10

Ceramic filter of various configuration have been used to filter particulates from hot gases exhausted from coal-fired systems. Prior ceramic cross-flow filters have been favored over other types, but those previously have been assemblies of parts somehow fastened together and consequently subject often to distortion or delamination on exposure hot gas in normal use. The present new monolithic, seamless, cross-flow ceramic filters, being of one-piece construction, are not prone to such failure. Further, these new products are made by a novel casting process which involves the key steps of demolding the ceramic filter green body so that none of the fragile inner walls of the filter is cracked or broken. 2 figs.

Method of producing monolithic ceramic cross-flow filter

DOEpatents

Larsen, David A.; Bacchi, David P.; Connors, Timothy F.; Collins, III, Edwin L.

1998-01-01

Ceramic filter of various configuration have been used to filter particulates from hot gases exhausted from coal-fired systems. Prior ceramic cross-flow filters have been favored over other types, but those previously horn have been assemblies of parts somehow fastened together and consequently subject often to distortion or delamination on exposure hot gas in normal use. The present new monolithic, seamless, cross-flow ceramic filters, being of one-piece construction, are not prone to such failure. Further, these new products are made by novel casting process which involves the key steps of demolding the ceramic filter green body so that none of the fragile inner walls of the filter is cracked or broken.

Fish mouths as engineering structures for vortical cross-step filtration

NASA Astrophysics Data System (ADS)

Sanderson, S. Laurie; Roberts, Erin; Lineburg, Jillian; Brooks, Hannah

2016-03-01

Suspension-feeding fishes such as goldfish and whale sharks retain prey without clogging their oral filters, whereas clogging is a major expense in industrial crossflow filtration of beer, dairy foods and biotechnology products. Fishes' abilities to retain particles that are smaller than the pore size of the gill-raker filter, including extraction of particles despite large holes in the filter, also remain unexplained. Here we show that unexplored combinations of engineering structures (backward-facing steps forming d-type ribs on the porous surface of a cone) cause fluid dynamic phenomena distinct from current biological and industrial filter operations. This vortical cross-step filtration model prevents clogging and explains the transport of tiny concentrated particles to the oesophagus using a hydrodynamic tongue. Mass transfer caused by vortices along d-type ribs in crossflow is applicable to filter-feeding duck beak lamellae and whale baleen plates, as well as the fluid mechanics of ventilation at fish gill filaments.

An Explicit Linear Filtering Solution for the Optimization of Guidance Systems with Statistical Inputs

NASA Technical Reports Server (NTRS)

Stewart, Elwood C.

1961-01-01

The determination of optimum filtering characteristics for guidance system design is generally a tedious process which cannot usually be carried out in general terms. In this report a simple explicit solution is given which is applicable to many different types of problems. It is shown to be applicable to problems which involve optimization of constant-coefficient guidance systems and time-varying homing type systems for several stationary and nonstationary inputs. The solution is also applicable to off-design performance, that is, the evaluation of system performance for inputs for which the system was not specifically optimized. The solution is given in generalized form in terms of the minimum theoretical error, the optimum transfer functions, and the optimum transient response. The effects of input signal, contaminating noise, and limitations on the response are included. From the results given, it is possible in an interception problem, for example, to rapidly assess the effects on minimum theoretical error of such factors as target noise and missile acceleration. It is also possible to answer important questions regarding the effect of type of target maneuver on optimum performance.

Optimized FPGA Implementation of Multi-Rate FIR Filters Through Thread Decomposition

NASA Technical Reports Server (NTRS)

Kobayashi, Kayla N.; He, Yutao; Zheng, Jason X.

2011-01-01

Multi-rate finite impulse response (MRFIR) filters are among the essential signal-processing components in spaceborne instruments where finite impulse response filters are often used to minimize nonlinear group delay and finite precision effects. Cascaded (multistage) designs of MRFIR filters are further used for large rate change ratio in order to lower the required throughput, while simultaneously achieving comparable or better performance than single-stage designs. Traditional representation and implementation of MRFIR employ polyphase decomposition of the original filter structure, whose main purpose is to compute only the needed output at the lowest possible sampling rate. In this innovation, an alternative representation and implementation technique called TD-MRFIR (Thread Decomposition MRFIR) is presented. The basic idea is to decompose MRFIR into output computational threads, in contrast to a structural decomposition of the original filter as done in the polyphase decomposition. A naive implementation of a decimation filter consisting of a full FIR followed by a downsampling stage is very inefficient, as most of the computations performed by the FIR state are discarded through downsampling. In fact, only 1/M of the total computations are useful (M being the decimation factor). Polyphase decomposition provides an alternative view of decimation filters, where the downsampling occurs before the FIR stage, and the outputs are viewed as the sum of M sub-filters with length of N/M taps. Although this approach leads to more efficient filter designs, in general the implementation is not straightforward if the numbers of multipliers need to be minimized. In TD-MRFIR, each thread represents an instance of the finite convolution required to produce a single output of the MRFIR. The filter is thus viewed as a finite collection of concurrent threads. Each of the threads completes when a convolution result (filter output value) is computed, and activated when the first

Recent progress in plasmonic colour filters for image sensor and multispectral applications

NASA Astrophysics Data System (ADS)

Pinton, Nadia; Grant, James; Choubey, Bhaskar; Cumming, David; Collins, Steve

2016-04-01

Using nanostructured thin metal films as colour filters offers several important advantages, in particular high tunability across the entire visible spectrum and some of the infrared region, and also compatibility with conventional CMOS processes. Since 2003, the field of plasmonic colour filters has evolved rapidly and several different designs and materials, or combination of materials, have been proposed and studied. In this paper we present a simulation study for a single- step lithographically patterned multilayer structure able to provide competitive transmission efficiencies above 40% and contemporary FWHM of the order of 30 nm across the visible spectrum. The total thickness of the proposed filters is less than 200 nm and is constant for every wavelength, unlike e.g. resonant cavity-based filters such as Fabry-Perot that require a variable stack of several layers according to the working frequency, and their passband characteristics are entirely controlled by changing the lithographic pattern. It will also be shown that a key to obtaining narrow-band optical response lies in the dielectric environment of a nanostructure and that it is not necessary to have a symmetric structure to ensure good coupling between the SPPs at the top and bottom interfaces. Moreover, an analytical method to evaluate the periodicity, given a specific structure and a desirable working wavelength, will be proposed and its accuracy demonstrated. This method conveniently eliminate the need to optimize the design of a filter numerically, i.e. by running several time-consuming simulations with different periodicities.

Solving Assembly Sequence Planning using Angle Modulated Simulated Kalman Filter

NASA Astrophysics Data System (ADS)

Mustapa, Ainizar; Yusof, Zulkifli Md.; Adam, Asrul; Muhammad, Badaruddin; Ibrahim, Zuwairie

2018-03-01

This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. The SKF search strategy contains three simple steps; predict-measure-estimate. The main objective of the ASP is to determine the sequence of component installation to shorten assembly time or save assembly costs. Initially, permutation sequence is generated to represent each agent. Each agent is then subjected to a precedence matrix constraint to produce feasible assembly sequence. Next, the Angle Modulated SKF (AMSKF) is proposed for solving ASP problem. The main idea of the angle modulated approach in solving combinatorial optimization problem is to use a function, g(x), to create a continuous signal. The performance of the proposed AMSKF is compared against previous works in solving ASP by applying BGSA, BPSO, and MSPSO. Using a case study of ASP, the results show that AMSKF outperformed all the algorithms in obtaining the best solution.

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Washington University in St Louis, St Louis, MO; Li, H. Harlod

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The mostmore » important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.« less

Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

PubMed

Suleimanov, Yury V; Green, William H

2015-09-08

We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

NASA Astrophysics Data System (ADS)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

Genetically Engineered Microelectronic Infrared Filters

NASA Technical Reports Server (NTRS)

Cwik, Tom; Klimeck, Gerhard

1998-01-01

A genetic algorithm is used for design of infrared filters and in the understanding of the material structure of a resonant tunneling diode. These two components are examples of microdevices and nanodevices that can be numerically simulated using fundamental mathematical and physical models. Because the number of parameters that can be used in the design of one of these devices is large, and because experimental exploration of the design space is unfeasible, reliable software models integrated with global optimization methods are examined The genetic algorithm and engineering design codes have been implemented on massively parallel computers to exploit their high performance. Design results are presented for the infrared filter showing new and optimized device design. Results for nanodevices are presented in a companion paper at this workshop.

An Umeclidinium membrane sensor; Two-step optimization strategy for improved responses.

PubMed

Yehia, Ali M; Monir, Hany H

2017-09-01

In the scientific context of membrane sensors and improved experimentation, we devised an experimentally designed protocol for sensor optimization. Two-step strategy was implemented for Umeclidinium bromide (UMEC) analysis which is a novel quinuclidine-based muscarinic antagonist used for maintenance treatment of symptoms accompanied with chronic obstructive pulmonary disease. In the first place, membrane components were screened for ideal ion exchanger, ionophore and plasticizer using three categorical factors at three levels in Taguchi design. Secondly, experimentally designed optimization was followed in order to tune the sensor up for finest responses. Twelve experiments were randomly carried out in a continuous factor design. Nernstian response, detection limit and selectivity were assigned as responses in these designs. The optimized membrane sensor contained tetrakis-[3,5-bis(trifluoro- methyl)phenyl] borate (0.44wt%) and calix[6]arene (0.43wt%) in 50.00% PVC plasticized with 49.13wt% 2-ni-tro-phenyl octylether. This sensor, along with an optimum concentration of inner filling solution (2×10 -4 molL -1 UMEC) and 2h of soaking time, attained the design objectives. Nernstian response approached 59.7mV/decade and detection limit decreased by about two order of magnitude (8×10 -8 mol L -1 ) through this optimization protocol. The proposed sensor was validated for UMEC determination in its linear range (3.16×10 -7 -1×10 -3 mol L -1 ) and challenged for selective discrimination of other congeners and inorganic cations. Results of INCRUSE ELLIPTA ® inhalation powder analyses obtained from the proposed sensor and manufacturer's UPLC were statistically compared. Moreover the proposed sensor was successfully used for the determination of UMEC in plasma samples. Copyright © 2017 Elsevier B.V. All rights reserved.

[Research on engine remaining useful life prediction based on oil spectrum analysis and particle filtering].

PubMed

Sun, Lei; Jia, Yun-xian; Cai, Li-ying; Lin, Guo-yu; Zhao, Jin-song

2013-09-01

The spectrometric oil analysis(SOA) is an important technique for machine state monitoring, fault diagnosis and prognosis, and SOA based remaining useful life(RUL) prediction has an advantage of finding out the optimal maintenance strategy for machine system. Because the complexity of machine system, its health state degradation process can't be simply characterized by linear model, while particle filtering(PF) possesses obvious advantages over traditional Kalman filtering for dealing nonlinear and non-Gaussian system, the PF approach was applied to state forecasting by SOA, and the RUL prediction technique based on SOA and PF algorithm is proposed. In the prediction model, according to the estimating result of system's posterior probability, its prior probability distribution is realized, and the multi-step ahead prediction model based on PF algorithm is established. Finally, the practical SOA data of some engine was analyzed and forecasted by the above method, and the forecasting result was compared with that of traditional Kalman filtering method. The result fully shows the superiority and effectivity of the

Design and experimentally measure a high performance metamaterial filter

NASA Astrophysics Data System (ADS)

Xu, Ya-wen; Xu, Jing-cheng

2018-03-01

Metamaterial filter is a kind of expecting optoelectronic device. In this paper, a metal/dielectric/metal (M/D/M) structure metamaterial filter is simulated and measured. Simulated results indicate that the perfect impedance matching condition between the metamaterial filter and the free space leads to the transmission band. Measured results show that the proposed metamaterial filter achieves high performance transmission on TM and TE polarization directions. Moreover, the high transmission rate is also can be obtained when the incident angle reaches to 45°. Further measured results show that the transmission band can be expanded through optimizing structural parameters. The central frequency of the transmission band is also can be adjusted through optimizing structural parameters. The physical mechanism behind the central frequency shifted is solved through establishing an equivalent resonant circuit model.

Proposed hardware architectures of particle filter for object tracking

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Underwater single beam circumferentially scanning detection system using range-gated receiver and adaptive filter

NASA Astrophysics Data System (ADS)

Tan, Yayun; Zhang, He; Zha, Bingting

2017-09-01

Underwater target detection and ranging in seawater are of interest in unmanned underwater vehicles. This study presents an underwater detection system that synchronously scans a collimated laser beam and a narrow field of view to circumferentially detect an underwater target. Hybrid methods of range-gated and variable step-size least mean squares (VSS-LMS) adaptive filter are proposed to suppress water backscattering. The range-gated receiver eliminates the backscattering of near-field water. The VSS-LMS filter extracts the target echo in the remaining backscattering and the constant fraction discriminator timing method is used to improve ranging accuracy. The optimal constant fraction is selected by analysing the jitter noise and slope of the target echo. The prototype of the underwater detection system is constructed and tested in coastal seawater, then the effectiveness of backscattering suppression and high-ranging accuracy is verified through experimental results and analysis discussed in this paper.

Are consistent equal-weight particle filters possible?

NASA Astrophysics Data System (ADS)

van Leeuwen, P. J.

2017-12-01

Particle filters are fully nonlinear data-assimilation methods that could potentially change the way we do data-assimilation in highly nonlinear high-dimensional geophysical systems. However, the standard particle filter in which the observations come in by changing the relative weights of the particles is degenerate. This means that one particle obtains weight one, and all other particles obtain a very small weight, effectively meaning that the ensemble of particles reduces to that one particle. For over 10 years now scientists have searched for solutions to this problem. One obvious solution seems to be localisation, in which each part of the state only sees a limited number of observations. However, for a realistic localisation radius based on physical arguments, the number of observations is typically too large, and the filter is still degenerate. Another route taken is trying to find proposal densities that lead to more similar particle weights. There is a simple proof, however, that shows that there is an optimum, the so-called optimal proposal density, and that optimum will lead to a degenerate filter. On the other hand, it is easy to come up with a counter example of a particle filter that is not degenerate in high-dimensional systems. Furthermore, several particle filters have been developed recently that claim to have equal or equivalent weights. In this presentation I will show how to construct a particle filter that is never degenerate in high-dimensional systems, and how that is still consistent with the proof that one cannot do better than the optimal proposal density. Furthermore, it will be shown how equal- and equivalent-weights particle filters fit within this framework. This insight will then lead to new ways to generate particle filters that are non-degenerate, opening up the field of nonlinear filtering in high-dimensional systems.

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

PubMed

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

2017-11-01

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

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

Optimum color filters for CCD digital cameras

NASA Astrophysics Data System (ADS)

Engelhardt, Kai; Kunz, Rino E.; Seitz, Peter; Brunner, Harald; Knop, Karl

1993-12-01

As part of the ESPRIT II project No. 2103 (MASCOT) a high performance prototype color CCD still video camera was developed. Intended for professional usage such as in the graphic arts, the camera provides a maximum resolution of 3k X 3k full color pixels. A high colorimetric performance was achieved through specially designed dielectric filters and optimized matrixing. The color transformation was obtained by computer simulation of the camera system and non-linear optimization which minimized the perceivable color errors as measured in the 1976 CIELUV uniform color space for a set of about 200 carefully selected test colors. The color filters were designed to allow perfect colorimetric reproduction in principle and at the same time with imperceptible color noise and with special attention to fabrication tolerances. The camera system includes a special real-time digital color processor which carries out the color transformation. The transformation can be selected from a set of sixteen matrices optimized for different illuminants and output devices. Because the actual filter design was based on slightly incorrect data the prototype camera showed a mean colorimetric error of 2.7 j.n.d. (CIELUV) in experiments. Using correct input data in the redesign of the filters, a mean colorimetric error of only 1 j.n.d. (CIELUV) seems to be feasible, implying that it is possible with such an optimized color camera to achieve such a high colorimetric performance that the reproduced colors in an image cannot be distinguished from the original colors in a scene, even in direct comparison.

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

High-latitude filtering in a global grid-point model using model normal modes. [Fourier filters for synoptic weather forecasting

NASA Technical Reports Server (NTRS)

Takacs, L. L.; Kalnay, E.; Navon, I. M.

1985-01-01

A normal modes expansion technique is applied to perform high latitude filtering in the GLAS fourth order global shallow water model with orography. The maximum permissible time step in the solution code is controlled by the frequency of the fastest propagating mode, which can be a gravity wave. Numerical methods are defined for filtering the data to identify the number of gravity modes to be included in the computations in order to obtain the appropriate zonal wavenumbers. The performances of the model with and without the filter, and with a time tendency and a prognostic field filter are tested with simulations of the Northern Hemisphere winter. The normal modes expansion technique is shown to leave the Rossby modes intact and permit 3-5 day predictions, a range not possible with the other high-latitude filters.

Principal Component Noise Filtering for NAST-I Radiometric Calibration

NASA Technical Reports Server (NTRS)

Tian, Jialin; Smith, William L., Sr.

2011-01-01

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed- Interferometer (NAST-I) instrument is a high-resolution scanning interferometer that measures emitted thermal radiation between 3.3 and 18 microns. The NAST-I radiometric calibration is achieved using internal blackbody calibration references at ambient and hot temperatures. In this paper, we introduce a refined calibration technique that utilizes a principal component (PC) noise filter to compensate for instrument distortions and artifacts, therefore, further improve the absolute radiometric calibration accuracy. To test the procedure and estimate the PC filter noise performance, we form dependent and independent test samples using odd and even sets of blackbody spectra. To determine the optimal number of eigenvectors, the PC filter algorithm is applied to both dependent and independent blackbody spectra with a varying number of eigenvectors. The optimal number of PCs is selected so that the total root-mean-square (RMS) error is minimized. To estimate the filter noise performance, we examine four different scenarios: apply PC filtering to both dependent and independent datasets, apply PC filtering to dependent calibration data only, apply PC filtering to independent data only, and no PC filters. The independent blackbody radiances are predicted for each case and comparisons are made. The results show significant reduction in noise in the final calibrated radiances with the implementation of the PC filtering algorithm.

Two-step reconstruction method using global optimization and conjugate gradient for ultrasound-guided diffuse optical tomography.

PubMed

Tavakoli, Behnoosh; Zhu, Quing

2013-01-01

Ultrasound-guided diffuse optical tomography (DOT) is a promising method for characterizing malignant and benign lesions in the female breast. We introduce a new two-step algorithm for DOT inversion in which the optical parameters are estimated with the global optimization method, genetic algorithm. The estimation result is applied as an initial guess to the conjugate gradient (CG) optimization method to obtain the absorption and scattering distributions simultaneously. Simulations and phantom experiments have shown that the maximum absorption and reduced scattering coefficients are reconstructed with less than 10% and 25% errors, respectively. This is in contrast with the CG method alone, which generates about 20% error for the absorption coefficient and does not accurately recover the scattering distribution. A new measure of scattering contrast has been introduced to characterize benign and malignant breast lesions. The results of 16 clinical cases reconstructed with the two-step method demonstrates that, on average, the absorption coefficient and scattering contrast of malignant lesions are about 1.8 and 3.32 times higher than the benign cases, respectively.

An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

NASA Astrophysics Data System (ADS)

Zhang, Yan; Tang, Baoping; Liu, Ziran; Chen, Rengxiang

2016-02-01

Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses

Ensemble Data Assimilation for Streamflow Forecasting: Experiments with Ensemble Kalman Filter and Particle Filter

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Gebremichael, M.; Hopson, T. M.; Wojick, R.

2011-12-01

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 Filter (EnKF) and Particle Filter (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 filter 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.

Prediction-Correction Algorithms for Time-Varying Constrained Optimization

DOE PAGES

Simonetto, Andrea; Dall'Anese, Emiliano

2017-07-26

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

Investigation on filter method for smoothing spiral phase plate

NASA Astrophysics Data System (ADS)

Zhang, Yuanhang; Wen, Shenglin; Luo, Zijian; Tang, Caixue; Yan, Hao; Yang, Chunlin; Liu, Mincai; Zhang, Qinghua; Wang, Jian

2018-03-01

Spiral phase plate (SPP) for generating vortex hollow beams has high efficiency in various applications. However, it is difficult to obtain an ideal spiral phase plate because of its continuous-varying helical phase and discontinued phase step. This paper describes the demonstration of continuous spiral phase plate using filter methods. The numerical simulations indicate that different filter method including spatial domain filter, frequency domain filter has unique impact on surface topography of SPP and optical vortex characteristics. The experimental results reveal that the spatial Gaussian filter method for smoothing SPP is suitable for Computer Controlled Optical Surfacing (CCOS) technique and obtains good optical properties.

Implicit LES using adaptive filtering

NASA Astrophysics Data System (ADS)

Sun, Guangrui; Domaradzki, Julian A.

2018-04-01

In implicit large eddy simulations (ILES) numerical dissipation prevents buildup of small scale energy in a manner similar to the explicit subgrid scale (SGS) models. If spectral methods are used the numerical dissipation is negligible but it can be introduced by applying a low-pass filter in the physical space, resulting in an effective ILES. In the present work we provide a comprehensive analysis of the numerical dissipation produced by different filtering operations in a turbulent channel flow simulated using a non-dissipative, pseudo-spectral Navier-Stokes solver. The amount of numerical dissipation imparted by filtering can be easily adjusted by changing how often a filter is applied. We show that when the additional numerical dissipation is close to the subgrid-scale (SGS) dissipation of an explicit LES the overall accuracy of ILES is also comparable, indicating that periodic filtering can replace explicit SGS models. A new method is proposed, which does not require any prior knowledge of a flow, to determine the filtering period adaptively. Once an optimal filtering period is found, the accuracy of ILES is significantly improved at low implementation complexity and computational cost. The method is general, performing well for different Reynolds numbers, grid resolutions, and filter shapes.

Rapid analysis of ultraviolet filters using dispersive liquid-liquid microextraction coupled to headspace gas chromatography and mass spectrometry.

PubMed

Pierson, Stephen A; Trujillo-Rodríguez, María J; Anderson, Jared L

2018-05-29

An ionic-liquid-based in situ dispersive liquid-liquid microextraction method coupled to headspace gas chromatography and mass spectrometry was developed for the rapid analysis of ultraviolet filters. The chemical structures of five ionic liquids were specifically designed to incorporate various functional groups for the favorable extraction of the target analytes. Extraction parameters including ionic liquid mass, molar ratio of ionic liquid to metathesis reagent, vortex time, ionic strength, pH, and total sample volume were studied and optimized. The effect of the headspace temperature and volume during the headspace sampling step was also evaluated to increase the sensitivity of the method. The optimized procedure is fast as it only required ∼7-10 min per extraction and allowed for multiple extractions to be performed simultaneously. In addition, the method exhibited high precision, good linearity, and low limits of detection for six ultraviolet filters in aqueous samples. The developed method was applied to both pool and lake water samples attaining acceptable relative recovery values. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An adaptive surface filter for airborne laser scanning point clouds by means of regularization and bending energy

NASA Astrophysics Data System (ADS)

Hu, Han; Ding, Yulin; Zhu, Qing; Wu, Bo; Lin, Hui; Du, Zhiqiang; Zhang, Yeting; Zhang, Yunsheng

2014-06-01

The filtering of point clouds is a ubiquitous task in the processing of airborne laser scanning (ALS) data; however, such filtering processes are difficult because of the complex configuration of the terrain features. The classical filtering algorithms rely on the cautious tuning of parameters to handle various landforms. To address the challenge posed by the bundling of different terrain features into a single dataset and to surmount the sensitivity of the parameters, in this study, we propose an adaptive surface filter (ASF) for the classification of ALS point clouds. Based on the principle that the threshold should vary in accordance to the terrain smoothness, the ASF embeds bending energy, which quantitatively depicts the local terrain structure to self-adapt the filter threshold automatically. The ASF employs a step factor to control the data pyramid scheme in which the processing window sizes are reduced progressively, and the ASF gradually interpolates thin plate spline surfaces toward the ground with regularization to handle noise. Using the progressive densification strategy, regularization and self-adaption, both performance improvement and resilience to parameter tuning are achieved. When tested against the benchmark datasets provided by ISPRS, the ASF performs the best in comparison with all other filtering methods, yielding an average total error of 2.85% when optimized and 3.67% when using the same parameter set.

Transdermal film-loaded finasteride microplates to enhance drug skin permeation: Two-step optimization study.

PubMed

Ahmed, Tarek A; El-Say, Khalid M

2016-06-10

The goal was to develop an optimized transdermal finasteride (FNS) film loaded with drug microplates (MIC), utilizing two-step optimization, to decrease the dosing schedule and inconsistency in gastrointestinal absorption. First; 3-level factorial design was implemented to prepare optimized FNS-MIC of minimum particle size. Second; Box-Behnken design matrix was used to develop optimized transdermal FNS-MIC film. Interaction among MIC components was studied using physicochemical characterization tools. Film components namely; hydroxypropyl methyl cellulose (X1), dimethyl sulfoxide (X2) and propylene glycol (X3) were optimized for their effects on the film thickness (Y1) and elongation percent (Y2), and for FNS steady state flux (Y3), permeability coefficient (Y4), and diffusion coefficient (Y5) following ex-vivo permeation through the rat skin. Morphological study of the optimized MIC and transdermal film was also investigated. Results revealed that stabilizer concentration and anti-solvent percent were significantly affecting MIC formulation. Optimized FNS-MIC of particle size 0.93μm was successfully prepared in which there was no interaction observed among their components. An enhancement in the aqueous solubility of FNS-MIC by more than 23% was achieved. All the studied variables, most of their interaction and quadratic effects were significantly affecting the studied variables (Y1-Y5). Morphological observation illustrated non-spherical, short rods, flakes like small plates that were homogeneously distributed in the optimized transdermal film. Ex-vivo study showed enhanced FNS permeation from film loaded MIC when compared to that contains pure drug. So, MIC is a successful technique to enhance aqueous solubility and skin permeation of poor water soluble drug especially when loaded into transdermal films. Copyright © 2016 Elsevier B.V. All rights reserved.

Assessment of intermittently loaded woodchip and sand filters to treat dairy soiled water.

PubMed

Murnane, J G; Brennan, R B; Healy, M G; Fenton, O

2016-10-15

Land application of dairy soiled water (DSW) is expensive relative to its nutrient replacement value. The use of aerobic filters is an effective alternative method of treatment and potentially allows the final effluent to be reused on the farm. Knowledge gaps exist concerning the optimal design and operation of filters for the treatment of DSW. To address this, 18 laboratory-scale filters, with depths of either 0.6 m or 1 m, were intermittently loaded with DSW over periods of up to 220 days to evaluate the impacts of depth (0.6 m versus 1 m), organic loading rates (OLRs) (50 versus 155 g COD m(-2) d(-1)), and media type (woodchip versus sand) on organic, nutrient and suspended solids (SS) removals. The study found that media depth was important in contaminant removal in woodchip filters. Reductions of 78% chemical oxygen demand (COD), 95% SS, 85% total nitrogen (TN), 82% ammonium-nitrogen (NH4N), 50% total phosphorus (TP), and 54% dissolved reactive phosphorus (DRP) were measured in 1 m deep woodchip filters, which was greater than the reductions in 0.6 m deep woodchip filters. Woodchip filters also performed optimally when loaded at a high OLR (155 g COD m(-2) d(-1)), although the removal mechanism was primarily physical (i.e. straining) as opposed to biological. When operated at the same OLR and when of the same depth, the sand filters had better COD removals (96%) than woodchip (74%), but there was no significant difference between them in the removal of SS and NH4N. However, the likelihood of clogging makes sand filters less desirable than woodchip filters. Using the optimal designs of both configurations, the filter area required per cow for a woodchip filter is more than four times less than for a sand filter. Therefore, this study found that woodchip filters are more economically and environmentally effective in the treatment of DSW than sand filters, and optimal performance may be achieved using woodchip filters with a depth of at least 1�

Least Median of Squares Filtering of Locally Optimal Point Matches for Compressible Flow Image Registration

PubMed Central

Castillo, Edward; Castillo, Richard; White, Benjamin; Rojo, Javier; Guerrero, Thomas

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. PMID:22797602

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study.

PubMed

Hosseinyalamdary, Siavash

2018-04-24

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy.

[Optimization of one-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology].

PubMed

Zhang, Yan-jun; Liu, Li-li; Hu, Jun-hua; Wu, Yun; Chao, En-xiang; Xiao, Wei

2015-11-01

First with the qualified rate of granules as the evaluation index, significant influencing factors were firstly screened by Plackett-Burman design. Then, with the qualified rate and moisture content as the evaluation indexes, significant factors that affect one-step pelletization technology were further optimized by Box-Behnken design; experimental data were imitated by multiple regression and second-order polynomial equation; and response surface method was used for predictive analysis of optimal technology. The best conditions were as follows: inlet air temperature of 85 degrees C, sample introduction speed of 33 r x min(-1), density of concrete 1. 10. One-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology was stable and feasible with good predictability, which provided reliable basis for the industrialized production of Biqiu granules.

EXPLICIT LEAST-DEGREE BOUNDARY FILTERS FOR DISCONTINUOUS GALERKIN.

PubMed

Nguyen, Dang-Manh; Peters, Jörg

2017-01-01

Convolving the output of Discontinuous Galerkin (DG) computations using spline filters can improve both smoothness and accuracy of the output. At domain boundaries, these filters have to be one-sided for non-periodic boundary conditions. Recently, position-dependent smoothness-increasing accuracy-preserving (PSIAC) filters were shown to be a superset of the well-known one-sided RLKV and SRV filters. Since PSIAC filters can be formulated symbolically, PSIAC filtering amounts to forming linear products with local DG output and so offers a more stable and efficient implementation. The paper introduces a new class of PSIAC filters NP 0 that have small support and are piecewise constant. Extensive numerical experiments for the canonical hyperbolic test equation show NP 0 filters outperform the more complex known boundary filters. NP 0 filters typically reduce the L ∞ error in the boundary region below that of the interior where optimally superconvergent symmetric filters of the same support are applied. NP 0 filtering can be implemented as forming linear combinations of the data with short rational weights. Exact derivatives of the convolved output are easy to compute.

EXPLICIT LEAST-DEGREE BOUNDARY FILTERS FOR DISCONTINUOUS GALERKIN*

PubMed Central

Nguyen, Dang-Manh; Peters, Jörg

2017-01-01

Convolving the output of Discontinuous Galerkin (DG) computations using spline filters can improve both smoothness and accuracy of the output. At domain boundaries, these filters have to be one-sided for non-periodic boundary conditions. Recently, position-dependent smoothness-increasing accuracy-preserving (PSIAC) filters were shown to be a superset of the well-known one-sided RLKV and SRV filters. Since PSIAC filters can be formulated symbolically, PSIAC filtering amounts to forming linear products with local DG output and so offers a more stable and efficient implementation. The paper introduces a new class of PSIAC filters NP0 that have small support and are piecewise constant. Extensive numerical experiments for the canonical hyperbolic test equation show NP0 filters outperform the more complex known boundary filters. NP0 filters typically reduce the L∞ error in the boundary region below that of the interior where optimally superconvergent symmetric filters of the same support are applied. NP0 filtering can be implemented as forming linear combinations of the data with short rational weights. Exact derivatives of the convolved output are easy to compute. PMID:29081643

A simple new filter for nonlinear high-dimensional data assimilation

NASA Astrophysics Data System (ADS)

Tödter, Julian; Kirchgessner, Paul; Ahrens, Bodo

2015-04-01

The ensemble Kalman filter (EnKF) and its deterministic variants, mostly square root filters such as the ensemble transform Kalman filter (ETKF), represent a popular alternative to variational data assimilation schemes and are applied in a wide range of operational and research activities. Their forecast step employs an ensemble integration that fully respects the nonlinear nature of the analyzed system. In the analysis step, they implicitly assume the prior state and observation errors to be Gaussian. Consequently, in nonlinear systems, the analysis mean and covariance are biased, and these filters remain suboptimal. In contrast, the fully nonlinear, non-Gaussian particle filter (PF) only relies on Bayes' theorem, which guarantees an exact asymptotic behavior, but because of the so-called curse of dimensionality it is exposed to weight collapse. This work shows how to obtain a new analysis ensemble whose mean and covariance exactly match the Bayesian estimates. This is achieved by a deterministic matrix square root transformation of the forecast ensemble, and subsequently a suitable random rotation that significantly contributes to filter stability while preserving the required second-order statistics. The forecast step remains as in the ETKF. The proposed algorithm, which is fairly easy to implement and computationally efficient, is referred to as the nonlinear ensemble transform filter (NETF). The properties and performance of the proposed algorithm are investigated via a set of Lorenz experiments. They indicate that such a filter formulation can increase the analysis quality, even for relatively small ensemble sizes, compared to other ensemble filters in nonlinear, non-Gaussian scenarios. Furthermore, localization enhances the potential applicability of this PF-inspired scheme in larger-dimensional systems. Finally, the novel algorithm is coupled to a large-scale ocean general circulation model. The NETF is stable, behaves reasonably and shows a good

Investigation, development, and application of optimal output feedback theory. Volume 3: The relationship between dynamic compensators and observers and Kalman filters

NASA Technical Reports Server (NTRS)

Broussard, John R.

1987-01-01

Relationships between observers, Kalman Filters and dynamic compensators using feedforward control theory are investigated. In particular, the relationship, if any, between the dynamic compensator state and linear functions of a discrete plane state are investigated. It is shown that, in steady state, a dynamic compensator driven by the plant output can be expressed as the sum of two terms. The first term is a linear combination of the plant state. The second term depends on plant and measurement noise, and the plant control. Thus, the state of the dynamic compensator can be expressed as an estimator of the first term with additive error given by the second term. Conditions under which a dynamic compensator is a Kalman filter are presented, and reduced-order optimal estimaters are investigated.

A nonlinear generalization of the Savitzky-Golay filter and the quantitative analysis of saccades

PubMed Central

Dai, Weiwei; Selesnick, Ivan; Rizzo, John-Ross; Rucker, Janet; Hudson, Todd

2017-01-01

The Savitzky-Golay (SG) filter is widely used to smooth and differentiate time series, especially biomedical data. However, time series that exhibit abrupt departures from their typical trends, such as sharp waves or steps, which are of physiological interest, tend to be oversmoothed by the SG filter. Hence, the SG filter tends to systematically underestimate physiological parameters in certain situations. This article proposes a generalization of the SG filter to more accurately track abrupt deviations in time series, leading to more accurate parameter estimates (e.g., peak velocity of saccadic eye movements). The proposed filtering methodology models a time series as the sum of two component time series: a low-frequency time series for which the conventional SG filter is well suited, and a second time series that exhibits instantaneous deviations (e.g., sharp waves, steps, or more generally, discontinuities in a higher order derivative). The generalized SG filter is then applied to the quantitative analysis of saccadic eye movements. It is demonstrated that (a) the conventional SG filter underestimates the peak velocity of saccades, especially those of small amplitude, and (b) the generalized SG filter estimates peak saccadic velocity more accurately than the conventional filter. PMID:28813566

A nonlinear generalization of the Savitzky-Golay filter and the quantitative analysis of saccades.

PubMed

Dai, Weiwei; Selesnick, Ivan; Rizzo, John-Ross; Rucker, Janet; Hudson, Todd

2017-08-01

The Savitzky-Golay (SG) filter is widely used to smooth and differentiate time series, especially biomedical data. However, time series that exhibit abrupt departures from their typical trends, such as sharp waves or steps, which are of physiological interest, tend to be oversmoothed by the SG filter. Hence, the SG filter tends to systematically underestimate physiological parameters in certain situations. This article proposes a generalization of the SG filter to more accurately track abrupt deviations in time series, leading to more accurate parameter estimates (e.g., peak velocity of saccadic eye movements). The proposed filtering methodology models a time series as the sum of two component time series: a low-frequency time series for which the conventional SG filter is well suited, and a second time series that exhibits instantaneous deviations (e.g., sharp waves, steps, or more generally, discontinuities in a higher order derivative). The generalized SG filter is then applied to the quantitative analysis of saccadic eye movements. It is demonstrated that (a) the conventional SG filter underestimates the peak velocity of saccades, especially those of small amplitude, and (b) the generalized SG filter estimates peak saccadic velocity more accurately than the conventional filter.

Chromotomography for a rotating-prism instrument using backprojection, then filtering.

PubMed

Deming, Ross W

2006-08-01

A simple closed-form solution is derived for reconstructing a 3D spatial-chromatic image cube from a set of chromatically dispersed 2D image frames. The algorithm is tailored for a particular instrument in which the dispersion element is a matching set of mechanically rotated direct vision prisms positioned between a lens and a focal plane array. By using a linear operator formalism to derive the Tikhonov-regularized pseudoinverse operator, it is found that the unique minimum-norm solution is obtained by applying the adjoint operator, followed by 1D filtering with respect to the chromatic variable. Thus the filtering and backprojection (adjoint) steps are applied in reverse order relative to an existing method. Computational efficiency is provided by use of the fast Fourier transform in the filtering step.

Design of efficient circularly symmetric two-dimensional variable digital FIR filters.

PubMed

Bindima, Thayyil; Elias, Elizabeth

2016-05-01

Circularly symmetric two-dimensional (2D) finite impulse response (FIR) filters find extensive use in image and medical applications, especially for isotropic filtering. Moreover, the design and implementation of 2D digital filters with variable fractional delay and variable magnitude responses without redesigning the filter has become a crucial topic of interest due to its significance in low-cost applications. Recently the design using fixed word length coefficients has gained importance due to the replacement of multipliers by shifters and adders, which reduces the hardware complexity. Among the various approaches to 2D design, transforming a one-dimensional (1D) filter to 2D by transformation, is reported to be an efficient technique. In this paper, 1D variable digital filters (VDFs) with tunable cut-off frequencies are designed using Farrow structure based interpolation approach, and the sub-filter coefficients in the Farrow structure are made multiplier-less using canonic signed digit (CSD) representation. The resulting performance degradation in the filters is overcome by using artificial bee colony (ABC) optimization. Finally, the optimized 1D VDFs are mapped to 2D using generalized McClellan transformation resulting in low complexity, circularly symmetric 2D VDFs with real-time tunability.

Wiener Chaos and Nonlinear Filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lototsky, S.V.

2006-11-15

The paper discusses two algorithms for solving the Zakai equation in the time-homogeneous diffusion filtering model with possible correlation between the state process and the observation noise. Both algorithms rely on the Cameron-Martin version of the Wiener chaos expansion, so that the approximate filter is a finite linear combination of the chaos elements generated by the observation process. The coefficients in the expansion depend only on the deterministic dynamics of the state and observation processes. For real-time applications, computing the coefficients in advance improves the performance of the algorithms in comparison with most other existing methods of nonlinear filtering. Themore » paper summarizes the main existing results about these Wiener chaos algorithms and resolves some open questions concerning the convergence of the algorithms in the noise-correlated setting. The presentation includes the necessary background on the Wiener chaos and optimal nonlinear filtering.« less

Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kao, Jim; Flicker, Dawn; Ide, Kayo

2006-05-20

This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from amore » single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand.« less

Deep Kalman Filter: Simultaneous Multi-Sensor Integration and Modelling; A GNSS/IMU Case Study

PubMed Central

Hosseinyalamdary, Siavash

2018-01-01

Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources. Therefore, IMU error modelling and the efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we developed deep Kalman filter to model and remove IMU errors and, consequently, improve the accuracy of IMU positioning. To achieve this, we added a modelling step to the prediction and update steps of the Kalman filter, so that the IMU error model is learned during integration. The results showed our deep Kalman filter outperformed the conventional Kalman filter and reached a higher level of accuracy. PMID:29695119

Multiple model cardinalized probability hypothesis density filter

NASA Astrophysics Data System (ADS)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

Combline designs improve mm-wave filter performance

NASA Astrophysics Data System (ADS)

Hey-Shipton, Gregory L.

1990-10-01

Combline filters with 2- to 75-percent bandwidths and orders up to 19 are discussed. They are realized as coupled rectangular coaxial transmission lines, since this type of transmission line is characterized by machinability and the wide variation in coupling coefficients that can be realized with rectangular bars. A broadband combline filter designed as a 19th-order, 0.01-dB equal-ripple Chebyshev type is presented, along with a third-order 0.001-dB equal-ripple Chebyshev filter with a 200-MHz bandwidth centered at 8.0 GHz. Interfaces to standard 50-ohm coaxial lines, as well as structures for waveguide interfaces are described, and focus is placed on a two-step impedance transformer matching a 538-ohm waveguide characteristic impedance to a 95-ohm filter terminal impedance.

Retrievable Inferior Vena Cava Filters in Trauma Patients: Prevalence and Management of Thrombus Within the Filter.

PubMed

Pan, Y; Zhao, J; Mei, J; Shao, M; Zhang, J; Wu, H

2016-12-01

The incidence of thrombus was investigated within retrievable filters placed in trauma patients with confirmed DVT at the time of retrieval and the optimal treatment for this clinical scenario was assessed. A technique called "filter retrieval with manual negative pressure aspiration thrombectomy" for management of filter thrombus was introduced and assessed. The retrievable filters referred for retrieval between January 2008 and December 2015 were retrospectively reviewed to determine the incidence of filter thrombus on a pre-retrieval cavogram. The clinical outcomes of different managements for thrombus within filters were recorded and analyzed. During the study 764 patients having Aegisy Filters implanted were referred for filter removal, from which 236 cases (134 male patients, mean age 50.2 years) of thrombus within the filter were observed on initial pre-retrieval IVC venogram 12-39 days after insertion (average 16.9 days). The incidence of infra-filter thrombus was 30.9%, and complete occlusion of the filter bearing IVC was seen in 2.4% (18) of cases. Retrieval was attempted in all 121 cases with small clots using a regular snare and sheath technique, and was successful in 120. A total of 116 cases with massive thrombus and IVC occlusion by thrombus were treated by CDT and/or the new retrieval technique. Overall, 213 cases (90.3%) of thrombus in the filter were removed successfully without PE. A small thrombus within the filter can be safely removed without additional management. CDT for reduction of the clot burden in filters was effective and safe. Filter retrieval with manual negative pressure aspiration thrombectomy seemed reasonable and valuable for management of massive thrombus within filters in some patients. Full assessment of the value and safety of this technique requires additional studies. Copyright © 2016 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Stochastic Adaptive Particle Beam Tracker Using Meer Filter Feedback.

DTIC Science & Technology

1986-12-01

breakthrough required in controlling the beam location. In 1983, Zicker (27] conducted a feasibility study of a simple proportional gain controller... Zicker synthesized his stochastic controller designs from a deterministic optimal LQ controller assuming full state feedback. An LQ controller is a...34Merge" Method 2.5 Simlifying the eer Filter a Zicker ran a performance analysis on the Meer filter and found the Meer filter virtually insensitive to

Texture classification of normal tissues in computed tomography using Gabor filters

NASA Astrophysics Data System (ADS)

Dettori, Lucia; Bashir, Alia; Hasemann, Julie

2007-03-01

The research presented in this article is aimed at developing an automated imaging system for classification of normal tissues in medical images obtained from Computed Tomography (CT) scans. Texture features based on a bank of Gabor filters are used to classify the following tissues of interests: liver, spleen, kidney, aorta, trabecular bone, lung, muscle, IP fat, and SQ fat. The approach consists of three steps: convolution of the regions of interest with a bank of 32 Gabor filters (4 frequencies and 8 orientations), extraction of two Gabor texture features per filter (mean and standard deviation), and creation of a Classification and Regression Tree-based classifier that automatically identifies the various tissues. The data set used consists of approximately 1000 DIACOM images from normal chest and abdominal CT scans of five patients. The regions of interest were labeled by expert radiologists. Optimal trees were generated using two techniques: 10-fold cross-validation and splitting of the data set into a training and a testing set. In both cases, perfect classification rules were obtained provided enough images were available for training (~65%). All performance measures (sensitivity, specificity, precision, and accuracy) for all regions of interest were at 100%. This significantly improves previous results that used Wavelet, Ridgelet, and Curvelet texture features, yielding accuracy values in the 85%-98% range The Gabor filters' ability to isolate features at different frequencies and orientations allows for a multi-resolution analysis of texture essential when dealing with, at times, very subtle differences in the texture of tissues in CT scans.

Correction of Bowtie-Filter Normalization and Crescent Artifacts for a Clinical CBCT System.

PubMed

Zhang, Hong; Kong, Vic; Huang, Ke; Jin, Jian-Yue

2017-02-01

To present our experiences in understanding and minimizing bowtie-filter crescent artifacts and bowtie-filter normalization artifacts in a clinical cone beam computed tomography system. Bowtie-filter position and profile variations during gantry rotation were studied. Two previously proposed strategies (A and B) were applied to the clinical cone beam computed tomography system to correct bowtie-filter crescent artifacts. Physical calibration and analytical approaches were used to minimize the norm phantom misalignment and to correct for bowtie-filter normalization artifacts. A combined procedure to reduce bowtie-filter crescent artifacts and bowtie-filter normalization artifacts was proposed and tested on a norm phantom, CatPhan, and a patient and evaluated using standard deviation of Hounsfield unit along a sampling line. The bowtie-filter exhibited not only a translational shift but also an amplitude variation in its projection profile during gantry rotation. Strategy B was better than strategy A slightly in minimizing bowtie-filter crescent artifacts, possibly because it corrected the amplitude variation, suggesting that the amplitude variation plays a role in bowtie-filter crescent artifacts. The physical calibration largely reduced the misalignment-induced bowtie-filter normalization artifacts, and the analytical approach further reduced bowtie-filter normalization artifacts. The combined procedure minimized both bowtie-filter crescent artifacts and bowtie-filter normalization artifacts, with Hounsfield unit standard deviation being 63.2, 45.0, 35.0, and 18.8 Hounsfield unit for the best correction approaches of none, bowtie-filter crescent artifacts, bowtie-filter normalization artifacts, and bowtie-filter normalization artifacts + bowtie-filter crescent artifacts, respectively. The combined procedure also demonstrated reduction of bowtie-filter crescent artifacts and bowtie-filter normalization artifacts in a CatPhan and a patient. We have developed a step-by-step

A novel two-step optimization method for tandem and ovoid high-dose-rate brachytherapy treatment for locally advanced cervical cancer.

PubMed

Sharma, Manju; Fields, Emma C; Todor, Dorin A

2015-01-01

To present a novel method allowing fast volumetric optimization of tandem and ovoid high-dose-rate treatments and to quantify its benefits. Twenty-seven CT-based treatment plans from 6 consecutive cervical cancer patients treated with four to five intracavitary tandem and ovoid insertions were used. Initial single-step optimized plans were manually optimized, approved, and delivered plans created with a goal to cover high-risk clinical target volume (HR-CTV) with D90 >90% and minimize rectum, bladder, and sigmoid D2cc. For the two-step optimized (TSO) plan, each single-step optimized plan was replanned adding a structure created from prescription isodose line to the existent physician delineated HR-CTV, rectum, bladder, and sigmoid. New, more rigorous dose-volume histogram constraints for the critical organs at risks (OARs) were used for the optimization. HR-CTV D90 and OAR D2ccs were evaluated in both plans. TSO plans had consistently smaller D2ccs for all three OARs while preserving HR-CTV D90. On plans with "excellent" CTV coverage, average D90 of 96% (91-102%), sigmoid, bladder, and rectum D2cc, respectively, reduced on average by 37% (16-73%), 28% (20-47%), and 27% (15-45%). Similar reductions were obtained on plans with "good" coverage, average D90 of 93% (90-99%). For plans with "inferior" coverage, average D90 of 81%, the coverage increased to 87% with concurrent D2cc reductions of 31%, 18%, and 11% for sigmoid, bladder, and rectum, respectively. The TSO can be added with minimal planning time increase but with the potential of dramatic and systematic reductions in OAR D2ccs and in some cases with concurrent increase in target dose coverage. These single-fraction modifications would be magnified over the course of four to five intracavitary insertions and may have real clinical implications in terms of decreasing both acute and late toxicities. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

PubMed Central

Ponomaryov, Volodymyr I.; Montenegro-Monroy, Hector; Nino-de-Rivera, Luis

2014-01-01

A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos. PMID:24688428

[Reduction of livestock-associated methicillin-resistant staphylococcus aureus (LA-MRSA) in the exhaust air of two piggeries by a bio-trickling filter and a biological three-step air cleaning system].

PubMed

Clauss, Marcus; Schulz, Jochen; Stratmann-Selke, Janin; Decius, Maja; Hartung, Jörg

2013-01-01

"Livestock-associated" Methicillin-resistent Staphylococcus aureus (LA-MRSA) are frequently found in the air of piggeries, are emitted into the ambient air of the piggeries and may also drift into residential areas or surrounding animal husbandries.. In order to reduce emissions from animal houses such as odour, gases and dust different biological air cleaning systems are commercially available. In this study the retention efficiencies for the culturable LA-MRSA of a bio-trickling filter and a combined three step system, both installed at two different piggeries, were investigated. Raw gas concentrations for LA-MRSA of 2.1 x 10(2) cfu/m3 (biotrickling filter) and 3.9 x 10(2) cfu/m3 (three step system) were found. The clean gas concentrations were in each case approximately one power of ten lower. Both systems were able to reduce the number of investigated bacteria in the air of piggeries on average about 90%. The investigated systems can contribute to protect nearby residents. However, considerable fluctuations of the emissions can occur.

A superior edge preserving filter with a systematic analysis

NASA Technical Reports Server (NTRS)

Holladay, Kenneth W.; Rickman, Doug

1991-01-01

A new, adaptive, edge preserving filter for use in image processing is presented. It had superior performance when compared to other filters. Termed the contiguous K-average, it aggregates pixels by examining all pixels contiguous to an existing cluster and adding the pixel closest to the mean of the existing cluster. The process is iterated until K pixels were accumulated. Rather than simply compare the visual results of processing with this operator to other filters, some approaches were developed which allow quantitative evaluation of how well and filter performs. Particular attention is given to the standard deviation of noise within a feature and the stability of imagery under iterative processing. Demonstrations illustrate the performance of several filters to discriminate against noise and retain edges, the effect of filtering as a preprocessing step, and the utility of the contiguous K-average filter when used with remote sensing data.

Input filter compensation for switching regulators

NASA Technical Reports Server (NTRS)

Kelkar, S. S.; Lee, F. C.

1983-01-01

A novel input filter compensation scheme for a buck regulator that eliminates the interaction between the input filter output impedance and the regulator control loop is presented. The scheme is implemented using a feedforward loop that senses the input filter state variables and uses this information to modulate the duty cycle signal. The feedforward design process presented is seen to be straightforward and the feedforward easy to implement. Extensive experimental data supported by analytical results show that significant performance improvement is achieved with the use of feedforward in the following performance categories: loop stability, audiosusceptibility, output impedance and transient response. The use of feedforward results in isolating the switching regulator from its power source thus eliminating all interaction between the regulator and equipment upstream. In addition the use of feedforward removes some of the input filter design constraints and makes the input filter design process simpler thus making it possible to optimize the input filter. The concept of feedforward compensation can also be extended to other types of switching regulators.

Stepped MS(All) Relied Transition (SMART): An approach to rapidly determine optimal multiple reaction monitoring mass spectrometry parameters for small molecules.

PubMed

Ye, Hui; Zhu, Lin; Wang, Lin; Liu, Huiying; Zhang, Jun; Wu, Mengqiu; Wang, Guangji; Hao, Haiping

2016-02-11

Multiple reaction monitoring (MRM) is a universal approach for quantitative analysis because of its high specificity and sensitivity. Nevertheless, optimization of MRM parameters remains as a time and labor-intensive task particularly in multiplexed quantitative analysis of small molecules in complex mixtures. In this study, we have developed an approach named Stepped MS(All) Relied Transition (SMART) to predict the optimal MRM parameters of small molecules. SMART requires firstly a rapid and high-throughput analysis of samples using a Stepped MS(All) technique (sMS(All)) on a Q-TOF, which consists of serial MS(All) events acquired from low CE to gradually stepped-up CE values in a cycle. The optimal CE values can then be determined by comparing the extracted ion chromatograms for the ion pairs of interest among serial scans. The SMART-predicted parameters were found to agree well with the parameters optimized on a triple quadrupole from the same vendor using a mixture of standards. The parameters optimized on a triple quadrupole from a different vendor was also employed for comparison, and found to be linearly correlated with the SMART-predicted parameters, suggesting the potential applications of the SMART approach among different instrumental platforms. This approach was further validated by applying to simultaneous quantification of 31 herbal components in the plasma of rats treated with a herbal prescription. Because the sMS(All) acquisition can be accomplished in a single run for multiple components independent of standards, the SMART approach are expected to find its wide application in the multiplexed quantitative analysis of complex mixtures. Copyright © 2015 Elsevier B.V. All rights reserved.

Triple-Quantum Filtered NMR Imaging of Sodium -23 in the Human Brain

NASA Astrophysics Data System (ADS)

Keltner, John Robinson

In the past multiple-quantum filtered imaging of biexponential relaxation sodium-23 nuclei in the human brain has been limited by low signal to noise ratios; this thesis demonstrates that such imaging is feasible when using a modified gradient-selected triple-quantum filter at a repetition time which maximizes the signal to noise ratio. Nuclear magnetic resonance imaging of biexponential relaxation sodium-23 (^{23}Na) nuclei in the human brain may be useful for detecting ischemia, cancer, and pathophysiology related to manic-depression. Multiple -quantum filters may be used to selectively image biexponential relaxation ^{23}Na signals since these filters suppress single-exponential relaxation ^{23}Na signals. In this thesis, the typical repetition times (200 -300 ms) used for in vivo multiple-quantum filtered ^{23}Na experiments are shown to be approximately 5 times greater than the optimal repetition time which maximizes multiple-quantum filtered SNR. Calculations and experimental verification show that the gradient-selected triple-quantum (GS3Q) filtered SNR for ^ {23}Na in a 4% agarose gel increases by a factor of two as the repetition time decreases from 300 ms to 55 ms. It is observed that a simple reduction of repetition time also increases spurious single-quantum signals from GS3Q filtered experiments. Irreducible superoperator calculations have been used to design a modified GS3Q filter which more effectively suppresses the spurious single-quantum signals. The modified GS3Q filter includes a preparatory crusher gradient and two-step-phase cycling. Using the modified GS3Q filter and a repetition time of 70 ms, a three dimensional triple-quantum filtered image of a phantom modelling ^{23} Na in the brain was obtained. The phantom consisted of two 4 cm diameter spheres inside of a 8.5 cm x 7 cm ellipsoid. The two spheres contained 0.012 and 0.024 M ^{23}Na in 4% agarose gel. Surrounding the spheres and inside the ellipsoid was 0.03 M aqueous ^{23}Na. The image

SIRT-FILTER v1.0.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

PELT, DANIEL

2017-04-21

Small Python package to compute tomographic reconstructions using a reconstruction method published in: Pelt, D.M., & De Andrade, V. (2017). Improved tomographic reconstruction of large-scale real-world data by filter optimization. Advanced Structural and Chemical Imaging 2: 17; and Pelt, D. M., & Batenburg, K. J. (2015). Accurately approximating algebraic tomographic reconstruction by filtered backprojection. In Proceedings of The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 158-161).

Broad application and optimization of a single wash-step for integrated endotoxin depletion during protein purification.

PubMed

Koziel, David; Michaelis, Uwe; Kruse, Tobias

2018-08-01

Endotoxins contaminate proteins that are produced in E. coli. High levels of endotoxins can influence cellular assays and cause severe adverse effects when administered to humans. Thus, endotoxin removal is important in protein purification for academic research and in GMP manufacturing of biopharmaceuticals. Several methods exist to remove endotoxin, but often require additional downstream-processing steps, decrease protein yield and are costly. These disadvantages can be avoided by using an integrated endotoxin depletion (iED) wash-step that utilizes Triton X-114 (TX114). In this paper, we show that the iED wash-step is broadly applicable in most commonly used chromatographies: it reduces endotoxin by a factor of 10 3 to 10 6 during NiNTA-, MBP-, SAC-, GST-, Protein A and CEX-chromatography but not during AEX or HIC-chromatography. We characterized the iED wash-step using Design of Experiments (DoE) and identified optimal experimental conditions for application scenarios that are relevant to academic research or industrial GMP manufacturing. A single iED wash-step with 0.75% (v/v) TX114 added to the feed and wash buffer can reduce endotoxin levels to below 2 EU/ml or deplete most endotoxin while keeping the manufacturing costs as low as possible. The comprehensive characterization enables academia and industry to widely adopt the iED wash-step for a routine, efficient and cost-effective depletion of endotoxin during protein purification at any scale. Copyright © 2018. Published by Elsevier B.V.

Analytically solvable chaotic oscillator based on a first-order filter.

PubMed

Corron, Ned J; Cooper, Roy M; Blakely, Jonathan N

2016-02-01

A chaotic hybrid dynamical system is introduced and its analytic solution is derived. The system is described as an unstable first order filter subject to occasional switching of a set point according to a feedback rule. The system qualitatively differs from other recently studied solvable chaotic hybrid systems in that the timing of the switching is regulated by an external clock. The chaotic analytic solution is an optimal waveform for communications in noise when a resistor-capacitor-integrate-and-dump filter is used as a receiver. As such, these results provide evidence in support of a recent conjecture that the optimal communication waveform for any stable infinite-impulse response filter is chaotic.

Analytically solvable chaotic oscillator based on a first-order filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corron, Ned J.; Cooper, Roy M.; Blakely, Jonathan N.

2016-02-15

A chaotic hybrid dynamical system is introduced and its analytic solution is derived. The system is described as an unstable first order filter subject to occasional switching of a set point according to a feedback rule. The system qualitatively differs from other recently studied solvable chaotic hybrid systems in that the timing of the switching is regulated by an external clock. The chaotic analytic solution is an optimal waveform for communications in noise when a resistor-capacitor-integrate-and-dump filter is used as a receiver. As such, these results provide evidence in support of a recent conjecture that the optimal communication waveform formore » any stable infinite-impulse response filter is chaotic.« less

Method and apparatus for selective filtering of ions

DOEpatents

Page, Jason S [Kennewick, WA; Tang, Keqi [Richland, WA; Smith, Richard D [Richland, WA

2009-04-07

An adjustable, low mass-to-charge (m/z) filter is disclosed employing electrospray ionization to block ions associated with unwanted low m/z species from entering the mass spectrometer and contributing their space charge to down-stream ion accumulation steps. The low-mass filter is made by using an adjustable potential energy barrier from the conductance limiting terminal electrode of an electrodynamic ion funnel, which prohibits species with higher ion mobilities from being transmitted. The filter provides a linear voltage adjustment of low-mass filtering from m/z values from about 50 to about 500. Mass filtering above m/z 500 can also be performed; however, higher m/z species are attenuated. The mass filter was evaluated with a liquid chromatography-mass spectrometry analysis of an albumin tryptic digest and resulted in the ability to block low-mass, "background" ions which account for 40-70% of the total ion current from the ESI source during peak elution.

AN ALTERNATIVE ELUENT TO BEEF EXTRACT FOR ELUTING POLIOVIRUS FROM ELECTROPOSITIVE FILTERS

EPA Science Inventory

Traditional methods for enteric virus removal from waters involve filtering the water through a positively charged filter followed by elution with beef extract, second step concentration by flocculation, and assay in cell culture. Two of the problems associated with this method ...

Analysis of multidimensional difference-of-Gaussians filters in terms of directly observable parameters.

PubMed

Cope, Davis; Blakeslee, Barbara; McCourt, Mark E

2013-05-01

The difference-of-Gaussians (DOG) filter is a widely used model for the receptive field of neurons in the retina and lateral geniculate nucleus (LGN) and is a potential model in general for responses modulated by an excitatory center with an inhibitory surrounding region. A DOG filter is defined by three standard parameters: the center and surround sigmas (which define the variance of the radially symmetric Gaussians) and the balance (which defines the linear combination of the two Gaussians). These parameters are not directly observable and are typically determined by nonlinear parameter estimation methods applied to the frequency response function. DOG filters show both low-pass (optimal response at zero frequency) and bandpass (optimal response at a nonzero frequency) behavior. This paper reformulates the DOG filter in terms of a directly observable parameter, the zero-crossing radius, and two new (but not directly observable) parameters. In the two-dimensional parameter space, the exact region corresponding to bandpass behavior is determined. A detailed description of the frequency response characteristics of the DOG filter is obtained. It is also found that the directly observable optimal frequency and optimal gain (the ratio of the response at optimal frequency to the response at zero frequency) provide an alternate coordinate system for the bandpass region. Altogether, the DOG filter and its three standard implicit parameters can be determined by three directly observable values. The two-dimensional bandpass region is a potential tool for the analysis of populations of DOG filters (for example, populations of neurons in the retina or LGN), because the clustering of points in this parameter space may indicate an underlying organizational principle. This paper concentrates on circular Gaussians, but the results generalize to multidimensional radially symmetric Gaussians and are given as an appendix.

Fluoride coatings for vacuum ultraviolet reflection filters.

PubMed

Guo, Chun; Kong, Mingdong; Lin, Dawei; Li, Bincheng

2015-12-10

LaF3/MgF2 reflection filters with a high spectral-discrimination capacity of the atomic-oxygen lines at 130.4 and 135.6 nm, which were employed in vacuum ultraviolet imagers, were prepared by molybdenum-boat thermal evaporation. The optical properties of reflection filters were characterized by a high-precision vacuum ultraviolet spectrophotometer. The vulnerability of the filter's microstructures to environmental contamination and the recovery of the optical properties of the stored filter samples with ultraviolet ozone cleaning were experimentally demonstrated. For reflection filters with the optimized nonquarter-wave multilayer structures, the reflectance ratios R135.6 nm/R130.4 nm of 92.7 and 20.6 were achieved for 7° and 45° angles of incidence, respectively. On the contrary, R135.6 nm/R130.4 nm ratio of 12.4 was obtained for a reflection filter with a standard π-stack multilayer structure with H/L=1/4 at 7° AOI.

Gabor filter based fingerprint image enhancement

NASA Astrophysics Data System (ADS)

Wang, Jin-Xiang

2013-03-01

Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

Design of efficient circularly symmetric two-dimensional variable digital FIR filters

PubMed Central

Bindima, Thayyil; Elias, Elizabeth

2016-01-01

Circularly symmetric two-dimensional (2D) finite impulse response (FIR) filters find extensive use in image and medical applications, especially for isotropic filtering. Moreover, the design and implementation of 2D digital filters with variable fractional delay and variable magnitude responses without redesigning the filter has become a crucial topic of interest due to its significance in low-cost applications. Recently the design using fixed word length coefficients has gained importance due to the replacement of multipliers by shifters and adders, which reduces the hardware complexity. Among the various approaches to 2D design, transforming a one-dimensional (1D) filter to 2D by transformation, is reported to be an efficient technique. In this paper, 1D variable digital filters (VDFs) with tunable cut-off frequencies are designed using Farrow structure based interpolation approach, and the sub-filter coefficients in the Farrow structure are made multiplier-less using canonic signed digit (CSD) representation. The resulting performance degradation in the filters is overcome by using artificial bee colony (ABC) optimization. Finally, the optimized 1D VDFs are mapped to 2D using generalized McClellan transformation resulting in low complexity, circularly symmetric 2D VDFs with real-time tunability. PMID:27222739

The Use of Daily Geodetic UT1 and LOD Data in the Optimal Estimation of UT1 and LOD With the JPL Kalman Earth Orientation Filter

NASA Technical Reports Server (NTRS)

Freedman, A. P.; Steppe, J. A.

1995-01-01

The Jet Propulsion Laboratory Kalman Earth Orientation Filter (KEOF) uses several of the Earth rotation data sets available to generate optimally interpolated UT1 and LOD series to support spacecraft navigation. This paper compares use of various data sets within KEOF.

Validation and implementation of Planova™ BioEX virus filters in the manufacture of a new liquid intravenous immunoglobulin in China.

PubMed

Ma, Shan; Pang, Guang Li; Shao, Yu Juan; Hongo-Hirasaki, Tomoko; Shang, Meng Xian; Inouye, Marcus; Jian, Chang Yong; Zhu, Meng Zhao; Yang, Hu Hu; Gao, Jian Feng; Xi, Zhi Ying; Song, Dian Wei

2018-03-01

There is a continuous need to improve the viral safety of plasma products, and we here report the development and optimization of a manufacturing-scale virus removal nanofiltration step for intravenous immunoglobulin (IVIG) using the recently introduced Planova™ BioEX filter. IVIG throughput was examined for various operating parameters: transmembrane pressure, temperature, protein concentration, and prefiltration methods. The developed procedure was based on filtering undiluted process solution (50.0 g/l IVIG) under constant transmembrane pressure filtration at 294 kPa and 25 °C following prefiltration with a 0.1 μm MILLEX VV filter. The recovery of IgG was approximately 98%, and no substantial changes in biochemical characteristics were observed before and after nanofiltration in scaled-up production. A viral clearance validation study with parvovirus under worst-case conditions performed at the National Institutes for Food and Drug Control of China (NIFDC) showed PPV logarithmic reduction value (LRV) > 4. Improved viral safety of IVIG can be assured by implementing a Planova BioEX nanofiltration step to ensure effective parvovirus clearance under conditions providing excellent protein recovery and no detectable impact on product biochemical properties. This plasma-derived IVIG product is the first to be certified for parvovirus safety by the NIFDC in China. Copyright © 2018 International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

Design of a composite filter realizable on practical spatial light modulators

NASA Technical Reports Server (NTRS)

Rajan, P. K.; Ramakrishnan, Ramachandran

1994-01-01

Hybrid optical correlator systems use two spatial light modulators (SLM's), one at the input plane and the other at the filter plane. Currently available SLM's such as the deformable mirror device (DMD) and liquid crystal television (LCTV) SLM's exhibit arbitrarily constrained operating characteristics. The pattern recognition filters designed with the assumption that the SLM's have ideal operating characteristic may not behave as expected when implemented on the DMD or LCTV SLM's. Therefore it is necessary to incorporate the SLM constraints in the design of the filters. In this report, an iterative method is developed for the design of an unconstrained minimum average correlation energy (MACE) filter. Then using this algorithm a new approach for the design of a SLM constrained distortion invariant filter in the presence of input SLM is developed. Two different optimization algorithms are used to maximize the objective function during filter synthesis, one based on the simplex method and the other based on the Hooke and Jeeves method. Also, the simulated annealing based filter design algorithm proposed by Khan and Rajan is refined and improved. The performance of the filter is evaluated in terms of its recognition/discrimination capabilities using computer simulations and the results are compared with a simulated annealing optimization based MACE filter. The filters are designed for different LCTV SLM's operating characteristics and the correlation responses are compared. The distortion tolerance and the false class image discrimination qualities of the filter are comparable to those of the simulated annealing based filter but the new filter design takes about 1/6 of the computer time taken by the simulated annealing filter design.

Spin-on bottom antireflective coating defect reduction by proper filter selection and process optimization

NASA Astrophysics Data System (ADS)

Brakensiek, Nickolas L.; Kidd, Brian; Mesawich, Michael; Stevens, Don, Jr.; Gotlinsky, Barry

2003-06-01

A design of experiment (DOE) was implemented to show the effects of various point of use filters on the coat process. The DOE takes into account the filter media, pore size, and pumping means, such as dispense pressure, time, and spin speed. The coating was executed on a TEL Mark 8 coat track, with an IDI M450 pump, and PALL 16 stack Falcon filters. A KLA 2112 set at 0.69 μm pixel size was used to scan the wafers to detect and identify the defects. The process found for DUV42P to maintain a low defect coating irrespective of the filter or pore size is a high start pressure, low end pressure, low dispense time, and high dispense speed. The IDI M450 pump has the capability to compensate for bubble type defects by venting the defects out of the filter before the defects are in the dispense line and the variable dispense rate allows the material in the dispense line to slow down at the end of dispense and not create microbubbles in the dispense line or tip. Also the differential pressure sensor will alarm if the pressure differential across the filter increases over a user-determined setpoint. The pleat design allows more surface area in the same footprint to reduce the differential pressure across the filter and transport defects to the vent tube. The correct low defect coating process will maximize the advantage of reducing filter pore size or changing the filter media.

Weighted finite impulse response filter for chromatic dispersion equalization in coherent optical fiber communication systems

NASA Astrophysics Data System (ADS)

Zeng, Ziyi; Yang, Aiying; Guo, Peng; Feng, Lihui

2018-01-01

Time-domain CD equalization using finite impulse response (FIR) filter is now a common approach for coherent optical fiber communication systems. The complex weights of FIR taps are calculated from a truncated impulse response of the CD transfer function, and the modulus of the complex weights is constant. In our work, we take the limited bandwidth of a single channel signal into account and propose weighted FIRs to improve the performance of CD equalization. The key in weighted FIR filters is the selection and optimization of weighted functions. In order to present the performance of different types of weighted FIR filters, a square-root raised cosine FIR (SRRC-FIR) and a Gaussian FIR (GS-FIR) are investigated. The optimization of square-root raised cosine FIR and Gaussian FIR are made in term of the bit rate error (BER) of QPSK and 16QAM coherent detection signal. The results demonstrate that the optimized parameters of the weighted filters are independent of the modulation format, symbol rate and the length of transmission fiber. With the optimized weighted FIRs, the BER of CD equalization signal is decreased significantly. Although this paper has investigated two types of weighted FIR filters, i.e. SRRC-FIR filter and GS-FIR filter, the principle of weighted FIR can also be extended to other symmetric functions super Gaussian function, hyperbolic secant function and etc.

Design considerations for a suboptimal Kalman filter

NASA Astrophysics Data System (ADS)

Difilippo, D. J.

1995-06-01

states. In Section 2, a high-level background description of a SAR motion compensation system that incorporates a TOA Kalman filter is given. The optimal TOA filter design is presented in Section 3 with some simulation results to indicate potential filter performance. In Section 4, the suboptimal Kalman filter configuration is derived. Simulation results are also shown in this section to allow comparision between suboptimal and optimal filter performances. Conclusions are contained in Section 5.

Optimal speckle noise reduction filter for range gated laser illuminated imaging

NASA Astrophysics Data System (ADS)

Dayton, David; Gonglewski, John; Lasche, James; Hassall, Arthur

2016-09-01

Laser illuminated imaging has a number of applications in the areas of night time air-to-ground target surveillance, ID, and pointing and tracking. Using a laser illuminator, the illumination intensity and thus the signal to noise ratio can be controlled. With the advent of high performance range gated cameras in the short-wave infra-red band, higher spatial resolution can be achieved over passive thermal night imaging cameras in the mid-wave infra-red due to the shorter wave-length. If a coherent illuminator is used the resulting imagery often suffers from speckle noise due to the scattering off of a rough target surface, which gives it a grainy "salt and pepper" appearance. The probability density function for the intensity of focal plane speckle is well understood to follow a negative exponential distribution. This can be exploited to develop a Bayesian speckle noise filter. The filter has the advantage over simple frame averaging approaches in that it preserves target features and motion while reducing speckle noise without smearing or blurring the images. The resulting filtered images have the appearance of passive imagery and so are more amenable to sensor fusion with simultaneous mid-wave infra-red thermal images for enhanced target ID. The noise filter improvement is demonstrated using examples from real world laser imaging tests on tactical targets.

Depth Filters Containing Diatomite Achieve More Efficient Particle Retention than Filters Solely Containing Cellulose Fibers.

PubMed

Buyel, Johannes F; Gruchow, Hannah M; Fischer, Rainer

2015-01-01

The clarification of biological feed stocks during the production of biopharmaceutical proteins is challenging when large quantities of particles must be removed, e.g., when processing crude plant extracts. Single-use depth filters are often preferred for clarification because they are simple to integrate and have a good safety profile. However, the combination of filter layers must be optimized in terms of nominal retention ratings to account for the unique particle size distribution in each feed stock. We have recently shown that predictive models can facilitate filter screening and the selection of appropriate filter layers. Here we expand our previous study by testing several filters with different retention ratings. The filters typically contain diatomite to facilitate the removal of fine particles. However, diatomite can interfere with the recovery of large biopharmaceutical molecules such as virus-like particles and aggregated proteins. Therefore, we also tested filtration devices composed solely of cellulose fibers and cohesive resin. The capacities of both filter types varied from 10 to 50 L m(-2) when challenged with tobacco leaf extracts, but the filtrate turbidity was ~500-fold lower (~3.5 NTU) when diatomite filters were used. We also tested pre-coat filtration with dispersed diatomite, which achieved capacities of up to 120 L m(-2) with turbidities of ~100 NTU using bulk plant extracts, and in contrast to the other depth filters did not require an upstream bag filter. Single pre-coat filtration devices can thus replace combinations of bag and depth filters to simplify the processing of plant extracts, potentially saving on time, labor and consumables. The protein concentrations of TSP, DsRed and antibody 2G12 were not affected by pre-coat filtration, indicating its general applicability during the manufacture of plant-derived biopharmaceutical proteins.

Depth Filters Containing Diatomite Achieve More Efficient Particle Retention than Filters Solely Containing Cellulose Fibers

PubMed Central

Buyel, Johannes F.; Gruchow, Hannah M.; Fischer, Rainer

2015-01-01

The clarification of biological feed stocks during the production of biopharmaceutical proteins is challenging when large quantities of particles must be removed, e.g., when processing crude plant extracts. Single-use depth filters are often preferred for clarification because they are simple to integrate and have a good safety profile. However, the combination of filter layers must be optimized in terms of nominal retention ratings to account for the unique particle size distribution in each feed stock. We have recently shown that predictive models can facilitate filter screening and the selection of appropriate filter layers. Here we expand our previous study by testing several filters with different retention ratings. The filters typically contain diatomite to facilitate the removal of fine particles. However, diatomite can interfere with the recovery of large biopharmaceutical molecules such as virus-like particles and aggregated proteins. Therefore, we also tested filtration devices composed solely of cellulose fibers and cohesive resin. The capacities of both filter types varied from 10 to 50 L m−2 when challenged with tobacco leaf extracts, but the filtrate turbidity was ~500-fold lower (~3.5 NTU) when diatomite filters were used. We also tested pre–coat filtration with dispersed diatomite, which achieved capacities of up to 120 L m−2 with turbidities of ~100 NTU using bulk plant extracts, and in contrast to the other depth filters did not require an upstream bag filter. Single pre-coat filtration devices can thus replace combinations of bag and depth filters to simplify the processing of plant extracts, potentially saving on time, labor and consumables. The protein concentrations of TSP, DsRed and antibody 2G12 were not affected by pre-coat filtration, indicating its general applicability during the manufacture of plant-derived biopharmaceutical proteins. PMID:26734037

Optimal Cut-Off Points of Fasting Plasma Glucose for Two-Step Strategy in Estimating Prevalence and Screening Undiagnosed Diabetes and Pre-Diabetes in Harbin, China

PubMed Central

Sun, Bo; Lan, Li; Cui, Wenxiu; Xu, Guohua; Sui, Conglan; Wang, Yibaina; Zhao, Yashuang; Wang, Jian; Li, Hongyuan

2015-01-01

To identify optimal cut-off points of fasting plasma glucose (FPG) for two-step strategy in screening abnormal glucose metabolism and estimating prevalence in general Chinese population. A population-based cross-sectional study was conducted on 7913 people aged 20 to 74 years in Harbin. Diabetes and pre-diabetes were determined by fasting and 2 hour post-load glucose from the oral glucose tolerance test in all participants. Screening potential of FPG, cost per case identified by two-step strategy, and optimal FPG cut-off points were described. The prevalence of diabetes was 12.7%, of which 65.2% was undiagnosed. Twelve percent or 9.0% of participants were diagnosed with pre-diabetes using 2003 ADA criteria or 1999 WHO criteria, respectively. The optimal FPG cut-off points for two-step strategy were 5.6 mmol/l for previously undiagnosed diabetes (area under the receiver-operating characteristic curve of FPG 0.93; sensitivity 82.0%; cost per case identified by two-step strategy ¥261), 5.3 mmol/l for both diabetes and pre-diabetes or pre-diabetes alone using 2003 ADA criteria (0.89 or 0.85; 72.4% or 62.9%; ¥110 or ¥258), 5.0 mmol/l for pre-diabetes using 1999 WHO criteria (0.78; 66.8%; ¥399), and 4.9 mmol/l for IGT alone (0.74; 62.2%; ¥502). Using the two-step strategy, the underestimates of prevalence reduced to nearly 38% for pre-diabetes or 18.7% for undiagnosed diabetes, respectively. Approximately a quarter of the general population in Harbin was in hyperglycemic condition. Using optimal FPG cut-off points for two-step strategy in Chinese population may be more effective and less costly for reducing the missed diagnosis of hyperglycemic condition. PMID:25785585

Testing the Stability of 2-D Recursive QP, NSHP and General Digital Filters of Second Order

NASA Astrophysics Data System (ADS)

Rathinam, Ananthanarayanan; Ramesh, Rengaswamy; Reddy, P. Subbarami; Ramaswami, Ramaswamy

Several methods for testing stability of first quadrant quarter-plane two dimensional (2-D) recursive digital filters have been suggested in 1970's and 80's. Though Jury's row and column algorithms, row and column concatenation stability tests have been considered as highly efficient mapping methods. They still fall short of accuracy as they need infinite number of steps to conclude about the exact stability of the filters and also the computational time required is enormous. In this paper, we present procedurally very simple algebraic method requiring only two steps when applied to the second order 2-D quarter - plane filter. We extend the same method to the second order Non-Symmetric Half-plane (NSHP) filters. Enough examples are given for both these types of filters as well as some lower order general recursive 2-D digital filters. We applied our method to barely stable or barely unstable filter examples available in the literature and got the same decisions thus showing that our method is accurate enough.

40 CFR 1065.590 - PM sampling media (e.g., filters) preconditioning and tare weighing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 32 2010-07-01 2010-07-01 false PM sampling media (e.g., filters... Specified Duty Cycles § 1065.590 PM sampling media (e.g., filters) preconditioning and tare weighing. Before an emission test, take the following steps to prepare PM sampling media (e.g., filters) and equipment...

40 CFR 1065.590 - PM sampling media (e.g., filters) preconditioning and tare weighing.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 34 2012-07-01 2012-07-01 false PM sampling media (e.g., filters... Specified Duty Cycles § 1065.590 PM sampling media (e.g., filters) preconditioning and tare weighing. Before an emission test, take the following steps to prepare PM sampling media (e.g., filters) and equipment...

40 CFR 1065.590 - PM sampling media (e.g., filters) preconditioning and tare weighing.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 34 2013-07-01 2013-07-01 false PM sampling media (e.g., filters... Specified Duty Cycles § 1065.590 PM sampling media (e.g., filters) preconditioning and tare weighing. Before an emission test, take the following steps to prepare PM sampling media (e.g., filters) and equipment...

40 CFR 1065.590 - PM sampling media (e.g., filters) preconditioning and tare weighing.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 33 2011-07-01 2011-07-01 false PM sampling media (e.g., filters... Specified Duty Cycles § 1065.590 PM sampling media (e.g., filters) preconditioning and tare weighing. Before an emission test, take the following steps to prepare PM sampling media (e.g., filters) and equipment...

40 CFR 1065.590 - PM sampling media (e.g., filters) preconditioning and tare weighing.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 33 2014-07-01 2014-07-01 false PM sampling media (e.g., filters... Specified Duty Cycles § 1065.590 PM sampling media (e.g., filters) preconditioning and tare weighing. Before an emission test, take the following steps to prepare PM sampling media (e.g., filters) and equipment...

Tunable Microwave Filter Design Using Thin-Film Ferroelectric Varactors

NASA Astrophysics Data System (ADS)

Haridasan, Vrinda

Military, space, and consumer-based communication markets alike are moving towards multi-functional, multi-mode, and portable transceiver units. Ferroelectric-based tunable filter designs in RF front-ends are a relatively new area of research that provides a potential solution to support wideband and compact transceiver units. This work presents design methodologies developed to optimize a tunable filter design for system-level integration, and to improve the performance of a ferroelectric-based tunable bandpass filter. An investigative approach to find the origins of high insertion loss exhibited by these filters is also undertaken. A system-aware design guideline and figure of merit for ferroelectric-based tunable band- pass filters is developed. The guideline does not constrain the filter bandwidth as long as it falls within the range of the analog bandwidth of a system's analog to digital converter. A figure of merit (FOM) that optimizes filter design for a specific application is presented. It considers the worst-case filter performance parameters and a tuning sensitivity term that captures the relation between frequency tunability and the underlying material tunability. A non-tunable parasitic fringe capacitance associated with ferroelectric-based planar capacitors is confirmed by simulated and measured results. The fringe capacitance is an appreciable proportion of the tunable capacitance at frequencies of X-band and higher. As ferroelectric-based tunable capac- itors form tunable resonators in the filter design, a proportionally higher fringe capacitance reduces the capacitance tunability which in turn reduces the frequency tunability of the filter. Methods to reduce the fringe capacitance can thus increase frequency tunability or indirectly reduce the filter insertion-loss by trading off the increased tunability achieved to lower loss. A new two-pole tunable filter topology with high frequency tunability (> 30%), steep filter skirts, wide stopband

MATCHED FILTER COMPUTATION ON FPGA, CELL, AND GPU

DOE Office of Scientific and Technical Information (OSTI.GOV)

BAKER, ZACHARY K.; GOKHALE, MAYA B.; TRIPP, JUSTIN L.

2007-01-08

The matched filter is an important kernel in the processing of hyperspectral data. The filter enables researchers to sift useful data from instruments that span large frequency bands. In this work, they evaluate the performance of a matched filter algorithm implementation on accelerated co-processor (XD1000), the IBM Cell microprocessor, and the NVIDIA GeForce 6900 GTX GPU graphics card. They provide extensive discussion of the challenges and opportunities afforded by each platform. In particular, they explore the problems of partitioning the filter most efficiently between the host CPU and the co-processor. Using their results, they derive several performance metrics that providemore » the optimal solution for a variety of application situations.« less

Rugate filter for light-trapping in solar cells.

PubMed

Fahr, Stephan; Ulbrich, Carolin; Kirchartz, Thomas; Rau, Uwe; Rockstuhl, Carsten; Lederer, Falk

2008-06-23

We suggest a design for a coating that could be applied on top of any solar cell having at least one diffusing surface. This coating acts as an angle and wavelength selective filter, which increases the average path length and absorptance at long wavelengths without altering the solar cell performance at short wavelengths. The filter design is based on a continuous variation of the refractive index in order to minimize undesired reflection losses. Numerical procedures are used to optimize the filter for a 10 microm thick monocrystalline silicon solar cell, which lifts the efficiency above the Auger limit for unconcentrated illumination. The feasibility to fabricate such filters is also discussed, considering a finite available refractive index range.

Use of astronomy filters in fluorescence microscopy.

PubMed

Piper, Jörg

2012-02-01

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

Glass wool filters for concentrating waterborne viruses and agricultural zoonotic pathogens

USGS Publications Warehouse

Millen, Hana T.; Gonnering, Jordan C.; Berg, Ryan K.; Spencer, Susan K.; Jokela, William E.; Pearce, John M.; Borchardt, Jackson S.; Borchardt, Mark A.

2012-01-01

The key first step in evaluating pathogen levels in suspected contaminated water is concentration. Concentration methods tend to be specific for a particular pathogen group, for example US Environmental Protection Agency Method 1623 for Giardia and Cryptosporidium1, which means multiple methods are required if the sampling program is targeting more than one pathogen group. Another drawback of current methods is the equipment can be complicated and expensive, for example the VIRADEL method with the 1MDS cartridge filter for concentrating viruses2. In this article we describe how to construct glass wool filters for concentrating waterborne pathogens. After filter elution, the concentrate is amenable to a second concentration step, such as centrifugation, followed by pathogen detection and enumeration by cultural or molecular methods. The filters have several advantages. Construction is easy and the filters can be built to any size for meeting specific sampling requirements. The filter parts are inexpensive, making it possible to collect a large number of samples without severely impacting a project budget. Large sample volumes (100s to 1,000s L) can be concentrated depending on the rate of clogging from sample turbidity. The filters are highly portable and with minimal equipment, such as a pump and flow meter, they can be implemented in the field for sampling finished drinking water, surface water, groundwater, and agricultural runoff. Lastly, glass wool filtration is effective for concentrating a variety of pathogen types so only one method is necessary. Here we report on filter effectiveness in concentrating waterborne human enterovirus, Salmonella enterica, Cryptosporidium parvum, and avian influenza virus.

Glass Wool Filters for Concentrating Waterborne Viruses and Agricultural Zoonotic Pathogens

PubMed Central

Millen, Hana T.; Gonnering, Jordan C.; Berg, Ryan K.; Spencer, Susan K.; Jokela, William E.; Pearce, John M.; Borchardt, Jackson S.; Borchardt, Mark A.

2012-01-01

The key first step in evaluating pathogen levels in suspected contaminated water is concentration. Concentration methods tend to be specific for a particular pathogen group, for example US Environmental Protection Agency Method 1623 for Giardia and Cryptosporidium1, which means multiple methods are required if the sampling program is targeting more than one pathogen group. Another drawback of current methods is the equipment can be complicated and expensive, for example the VIRADEL method with the 1MDS cartridge filter for concentrating viruses2. In this article we describe how to construct glass wool filters for concentrating waterborne pathogens. After filter elution, the concentrate is amenable to a second concentration step, such as centrifugation, followed by pathogen detection and enumeration by cultural or molecular methods. The filters have several advantages. Construction is easy and the filters can be built to any size for meeting specific sampling requirements. The filter parts are inexpensive, making it possible to collect a large number of samples without severely impacting a project budget. Large sample volumes (100s to 1,000s L) can be concentrated depending on the rate of clogging from sample turbidity. The filters are highly portable and with minimal equipment, such as a pump and flow meter, they can be implemented in the field for sampling finished drinking water, surface water, groundwater, and agricultural runoff. Lastly, glass wool filtration is effective for concentrating a variety of pathogen types so only one method is necessary. Here we report on filter effectiveness in concentrating waterborne human enterovirus, Salmonella enterica, Cryptosporidium parvum, and avian influenza virus. PMID:22415031

Phase Response Design of Recursive All-Pass Digital Filters Using a Modified PSO Algorithm

PubMed Central

2015-01-01

This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to improve the searching ability. In the proposed method, all of the designed filter coefficients are firstly collected to be a parameter vector and this vector is regarded as a particle of the algorithm. The MPSO with a modified velocity formula will force all particles into moving toward the optimal or near optimal solution by minimizing some defined objective function of the optimization problem. To show the effectiveness of the proposed method, two different kinds of linear phase response design examples are illustrated and the general PSO algorithm is compared as well. The obtained results show that the MPSO is superior to the general PSO for the phase response design of digital recursive all-pass filter. PMID:26366168

On the Performance of the Martin Digital Filter for High- and Low-pass Applications

NASA Technical Reports Server (NTRS)

Mcclain, C. R.

1979-01-01

A nonrecursive numerical filter is described in which the weighting sequence is optimized by minimizing the excursion from the ideal rectangular filter in a least squares sense over the entire domain of normalized frequency. Additional corrections to the weights in order to reduce overshoot oscillations (Gibbs phenomenon) and to insure unity gain at zero frequency for the low pass filter are incorporated. The filter is characterized by a zero phase shift for all frequencies (due to a symmetric weighting sequence), a finite memory and stability, and it may readily be transformed to a high pass filter. Equations for the filter weights and the frequency response function are presented, and applications to high and low pass filtering are examined. A discussion of optimization of high pass filter parameters for a rather stringent response requirement is given in an application to the removal of aircraft low frequency oscillations superimposed on remotely sensed ocean surface profiles. Several frequency response functions are displayed, both in normalized frequency space and in period space. A comparison of the performance of the Martin filter with some other commonly used low pass digital filters is provided in an application to oceanographic data.

Event-triggered resilient filtering with stochastic uncertainties and successive packet dropouts via variance-constrained approach

NASA Astrophysics Data System (ADS)

Jia, Chaoqing; Hu, Jun; Chen, Dongyan; Liu, Yurong; Alsaadi, Fuad E.

2018-07-01

In this paper, we discuss the event-triggered resilient filtering problem for a class of time-varying systems subject to stochastic uncertainties and successive packet dropouts. The event-triggered mechanism is employed with hope to reduce the communication burden and save network resources. The stochastic uncertainties are considered to describe the modelling errors and the phenomenon of successive packet dropouts is characterized by a random variable obeying the Bernoulli distribution. The aim of the paper is to provide a resilient event-based filtering approach for addressed time-varying systems such that, for all stochastic uncertainties, successive packet dropouts and filter gain perturbation, an optimized upper bound of the filtering error covariance is obtained by designing the filter gain. Finally, simulations are provided to demonstrate the effectiveness of the proposed robust optimal filtering strategy.

An Exploration of Trainer Filtering Approaches

NASA Technical Reports Server (NTRS)

Hester, Patrick; Tolk, Andreas; Gadi, Sandeep; Carver, Quinn; Roland, Philippe

2011-01-01

Simutator operators face a twofold entity management problem during Live-Virtual-Constructive (LVC) training events. They first must filter potentially hundreds of thousands of simulation entities in order 10 determine which elements are necessary for optimal trainee comprehension. Secondarily, they must manage the number of entities entering the simulation from those present in the object model in order to limit the computational burden on the simulation system and prevent unnecessary entities from entering the simulation, This paper focuses on the first filtering stage and describes a novel approach to entity filtering undertaken to maximize trainee awareness and learning. The feasibility of this novel approach is demonstrated on a case study and limitations to the proposed approach and future work are discussed.

GRIM-Filter: Fast seed location filtering in DNA read mapping using processing-in-memory technologies.

PubMed

Kim, Jeremie S; Senol Cali, Damla; Xin, Hongyi; Lee, Donghyuk; Ghose, Saugata; Alser, Mohammed; Hassan, Hasan; Ergin, Oguz; Alkan, Can; Mutlu, Onur

2018-05-09

Seed location filtering is critical in DNA read mapping, a process where billions of DNA fragments (reads) sampled from a donor are mapped onto a reference genome to identify genomic variants of the donor. State-of-the-art read mappers 1) quickly generate possible mapping locations for seeds (i.e., smaller segments) within each read, 2) extract reference sequences at each of the mapping locations, and 3) check similarity between each read and its associated reference sequences with a computationally-expensive algorithm (i.e., sequence alignment) to determine the origin of the read. A seed location filter comes into play before alignment, discarding seed locations that alignment would deem a poor match. The ideal seed location filter would discard all poor match locations prior to alignment such that there is no wasted computation on unnecessary alignments. We propose a novel seed location filtering algorithm, GRIM-Filter, optimized to exploit 3D-stacked memory systems that integrate computation within a logic layer stacked under memory layers, to perform processing-in-memory (PIM). GRIM-Filter quickly filters seed locations by 1) introducing a new representation of coarse-grained segments of the reference genome, and 2) using massively-parallel in-memory operations to identify read presence within each coarse-grained segment. Our evaluations show that for a sequence alignment error tolerance of 0.05, GRIM-Filter 1) reduces the false negative rate of filtering by 5.59x-6.41x, and 2) provides an end-to-end read mapper speedup of 1.81x-3.65x, compared to a state-of-the-art read mapper employing the best previous seed location filtering algorithm. GRIM-Filter exploits 3D-stacked memory, which enables the efficient use of processing-in-memory, to overcome the memory bandwidth bottleneck in seed location filtering. We show that GRIM-Filter significantly improves the performance of a state-of-the-art read mapper. GRIM-Filter is a universal seed location filter that can be

Complementary filter implementation in the dynamic language Lua

NASA Astrophysics Data System (ADS)

Sadowski, Damian; Sawicki, Aleksander; Lukšys, Donatas; Slanina, Zdenek

2017-08-01

The article presents the complementary filter implementation, that is used for the estimation of the pitch angle, in Lua script language. Inertial sensors as accelerometer and gyroscope were used in the study. Methods of angles estimation using acceleration and angular velocity sensors were presented in the theoretical part of the article. The operating principle of complementary filter has been presented. The prototype of Butterworth's analogue filter and its digital equivalent have been designed. Practical implementation of the issue was performed with the use of PC and DISCOVERY evaluation board equipped with STM32F01 processor, L3GD20 gyroscope and LS303DLHC accelerometer. Measurement data was transmitted by UART serial interface, then processed with the use of Lua software and luaRS232 programming library. Practical implementation was divided into two stages. In the first part, measurement data has been recorded and then processed with help of a complementary filter. In the second step, coroutines mechanism was used to filter data in real time.

Validation of search filters for identifying pediatric studies in PubMed.

PubMed

Leclercq, Edith; Leeflang, Mariska M G; van Dalen, Elvira C; Kremer, Leontien C M

2013-03-01

To identify and validate PubMed search filters for retrieving studies including children and to develop a new pediatric search filter for PubMed. We developed 2 different datasets of studies to evaluate the performance of the identified pediatric search filters, expressed in terms of sensitivity, precision, specificity, accuracy, and number needed to read (NNR). An optimal search filter will have a high sensitivity and high precision with a low NNR. In addition to the PubMed Limits: All Child: 0-18 years filter (in May 2012 renamed to PubMed Filter Child: 0-18 years), 6 search filters for identifying studies including children were identified: 3 developed by Kastner et al, 1 developed by BestBets, one by the Child Health Field, and 1 by the Cochrane Childhood Cancer Group. Three search filters (Cochrane Childhood Cancer Group, Child Health Field, and BestBets) had the highest sensitivity (99.3%, 99.5%, and 99.3%, respectively) but a lower precision (64.5%, 68.4%, and 66.6% respectively) compared with the other search filters. Two Kastner search filters had a high precision (93.0% and 93.7%, respectively) but a low sensitivity (58.5% and 44.8%, respectively). They failed to identify many pediatric studies in our datasets. The search terms responsible for false-positive results in the reference dataset were determined. With these data, we developed a new search filter for identifying studies with children in PubMed with an optimal sensitivity (99.5%) and precision (69.0%). Search filters to identify studies including children either have a low sensitivity or a low precision with a high NNR. A new pediatric search filter with a high sensitivity and a low NNR has been developed. Copyright © 2013 Mosby, Inc. All rights reserved.

LHCb Kalman Filter cross architecture studies

NASA Astrophysics Data System (ADS)

Cámpora Pérez, Daniel Hugo

2017-10-01

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

Spatial filters for high-peak-power multistage laser amplifiers.

PubMed

Potemkin, A K; Barmashova, T V; Kirsanov, A V; Martyanov, M A; Khazanov, E A; Shaykin, A A

2007-07-10

We describe spatial filters used in a Nd:glass laser with an output pulse energy up to 300 J and a pulse duration of 1 ns. This laser is designed for pumping of a chirped-pulse optical parametric amplifier. We present data required to choose the shape and diameter of a spatial filter lens, taking into account aberrations caused by spherical surfaces. Calculation of the optimal pinhole diameter is presented. Design features of the spatial filters and the procedure of their alignment are discussed in detail.

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Thermal control design of the Lightning Mapper Sensor narrow-band spectral filter

NASA Technical Reports Server (NTRS)

Flannery, Martin R.; Potter, John; Raab, Jeff R.; Manlief, Scott K.

1992-01-01

The performance of the Lightning Mapper Sensor is dependent on the temperature shifts of its narrowband spectral filter. To perform over a 10 degree FOV with an 0.8 nm bandwidth, the filter must be 15 cm in diameter and mounted externally to the telescope optics. The filter thermal control required a filter design optimized for minimum bandpass shift with temperature, a thermal analysis of substrate materials for maximum temperature uniformity, and a thermal radiation analysis to determine the parameter sensitivity of the radiation shield for the filter, the filter thermal recovery time after occultation, and heater power to maintain filter performance in the earth-staring geosynchronous environment.

Technical note: Improving the AWAT filter with interpolation schemes for advanced processing of high resolution data

NASA Astrophysics Data System (ADS)

Peters, Andre; Nehls, Thomas; Wessolek, Gerd

2016-06-01

Weighing lysimeters with appropriate data filtering yield the most precise and unbiased information for precipitation (P) and evapotranspiration (ET). A recently introduced filter scheme for such data is the AWAT (Adaptive Window and Adaptive Threshold) filter (Peters et al., 2014). The filter applies an adaptive threshold to separate significant from insignificant mass changes, guaranteeing that P and ET are not overestimated, and uses a step interpolation between the significant mass changes. In this contribution we show that the step interpolation scheme, which reflects the resolution of the measuring system, can lead to unrealistic prediction of P and ET, especially if they are required in high temporal resolution. We introduce linear and spline interpolation schemes to overcome these problems. To guarantee that medium to strong precipitation events abruptly following low or zero fluxes are not smoothed in an unfavourable way, a simple heuristic selection criterion is used, which attributes such precipitations to the step interpolation. The three interpolation schemes (step, linear and spline) are tested and compared using a data set from a grass-reference lysimeter with 1 min resolution, ranging from 1 January to 5 August 2014. The selected output resolutions for P and ET prediction are 1 day, 1 h and 10 min. As expected, the step scheme yielded reasonable flux rates only for a resolution of 1 day, whereas the other two schemes are well able to yield reasonable results for any resolution. The spline scheme returned slightly better results than the linear scheme concerning the differences between filtered values and raw data. Moreover, this scheme allows continuous differentiability of filtered data so that any output resolution for the fluxes is sound. Since computational burden is not problematic for any of the interpolation schemes, we suggest always using the spline scheme.

[Useful tools and methods for literature retrieval in pubmed: step-by-step guide for physicians].

PubMed

Hevia M, Joaquín; Huete G, Álvaro; Alfaro F, Sandra; Palominos V, Verónica

2017-12-01

Developing skills to search the medical literature has potential benefits on patient care and allow physicians to better orient their efforts when answering daily clinical questions. The objective of this paper is to share useful tools for optimizing medical literature retrieval in MEDLINE using PubMed including MeSH terms, filters and connectors.

Describing litho-constrained layout by a high-resolution model filter

NASA Astrophysics Data System (ADS)

Tsai, Min-Chun

2008-05-01

A novel high-resolution model (HRM) filtering technique was proposed to describe litho-constrained layouts. Litho-constrained layouts are layouts that have difficulties to pattern or are highly sensitive to process-fluctuations under current lithography technologies. HRM applies a short-wavelength (or high NA) model simulation directly on the pre-OPC, original design layout to filter out low spatial-frequency regions, and retain high spatial-frequency components which are litho-constrained. Since no OPC neither mask-synthesis steps are involved, this new technique is highly efficient in run time and can be used in design stage to detect and fix litho-constrained patterns. This method has successfully captured all the hot-spots with less than 15% overshoots on a realistic 80 mm2 full-chip M1 layout in 65nm technology node. A step by step derivation of this HRM technique is presented in this paper.

Iterative dip-steering median filter

NASA Astrophysics Data System (ADS)

Huo, Shoudong; Zhu, Weihong; Shi, Taikun

2017-09-01

Seismic data are always contaminated with high noise components, which present processing challenges especially for signal preservation and its true amplitude response. This paper deals with an extension of the conventional median filter, which is widely used in random noise attenuation. It is known that the standard median filter works well with laterally aligned coherent events but cannot handle steep events, especially events with conflicting dips. In this paper, an iterative dip-steering median filter is proposed for the attenuation of random noise in the presence of multiple dips. The filter first identifies the dominant dips inside an optimized processing window by a Fourier-radial transform in the frequency-wavenumber domain. The optimum size of the processing window depends on the intensity of random noise that needs to be attenuated and the amount of signal to be preserved. It then applies median filter along the dominant dip and retains the signals. Iterations are adopted to process the residual signals along the remaining dominant dips in a descending sequence, until all signals have been retained. The method is tested by both synthetic and field data gathers and also compared with the commonly used f-k least squares de-noising and f-x deconvolution.

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

Filtered epithermal quasi-monoenergetic neutron beams at research reactor facilities.

PubMed

Mansy, M S; Bashter, I I; El-Mesiry, M S; Habib, N; Adib, M

2015-03-01

Filtered neutron techniques were applied to produce quasi-monoenergetic neutron beams in the energy range of 1.5-133keV at research reactors. A simulation study was performed to characterize the filter components and transmitted beam lines. The filtered beams were characterized in terms of the optimal thickness of the main and additive components. The filtered neutron beams had high purity and intensity, with low contamination from the accompanying thermal emission, fast neutrons and γ-rays. A computer code named "QMNB" was developed in the "MATLAB" programming language to perform the required calculations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Design and fabrication of SiO2/TiO2 and MgO/TiO2 based high selective optical filters for diffuse reflectance and fluorescence signals extraction

PubMed Central

Pimenta, S.; Cardoso, S.; Miranda, A.; De Beule, P.; Castanheira, E.M.S.; Minas, G.

2015-01-01

This paper presents the design, optimization and fabrication of 16 MgO/TiO2 and SiO2/TiO2 based high selective narrow bandpass optical filters. Their performance to extract diffuse reflectance and fluorescence signals from gastrointestinal tissue phantoms was successfully evaluated. The obtained results prove their feasibility to correctly extract those spectroscopic signals, through a Spearman’s rank correlation test (Spearman’s correlation coefficient higher than 0.981) performed between the original spectra and the ones obtained using those 16 fabricated optical filters. These results are an important step for the implementation of a miniaturized, low-cost and minimal invasive microsystem that could help in the detection of gastrointestinal dysplasia. PMID:26309769

Design and fabrication of SiO2/TiO2 and MgO/TiO2 based high selective optical filters for diffuse reflectance and fluorescence signals extraction.

PubMed

Pimenta, S; Cardoso, S; Miranda, A; De Beule, P; Castanheira, E M S; Minas, G

2015-08-01

This paper presents the design, optimization and fabrication of 16 MgO/TiO2 and SiO2/TiO2 based high selective narrow bandpass optical filters. Their performance to extract diffuse reflectance and fluorescence signals from gastrointestinal tissue phantoms was successfully evaluated. The obtained results prove their feasibility to correctly extract those spectroscopic signals, through a Spearman's rank correlation test (Spearman's correlation coefficient higher than 0.981) performed between the original spectra and the ones obtained using those 16 fabricated optical filters. These results are an important step for the implementation of a miniaturized, low-cost and minimal invasive microsystem that could help in the detection of gastrointestinal dysplasia.

Adaptive interference cancel filter for evoked potential using high-order cumulants.

PubMed

Lin, Bor-Shyh; Lin, Bor-Shing; Chong, Fok-Ching; Lai, Feipei

2004-01-01

This paper is to present evoked potential (EP) processing using adaptive interference cancel (AIC) filter with second and high order cumulants. In conventional ensemble averaging method, people have to conduct repetitively experiments to record the required data. Recently, the use of AIC structure with second statistics in processing EP has proved more efficiency than traditional averaging method, but it is sensitive to both of the reference signal statistics and the choice of step size. Thus, we proposed higher order statistics-based AIC method to improve these disadvantages. This study was experimented in somatosensory EP corrupted with EEG. Gradient type algorithm is used in AIC method. Comparisons with AIC filter on second, third, fourth order statistics are also presented in this paper. We observed that AIC filter with third order statistics has better convergent performance for EP processing and is not sensitive to the selection of step size and reference input.

Sci-Thur PM - Colourful Interactions: Highlights 08: ARC TBI using Single-Step Optimized VMAT Fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hudson, Alana; Gordon, Deborah; Moore, Roseanne

Purpose: This work outlines a new TBI delivery technique to replace a lateral POP full bolus technique. The new technique is done with VMAT arc delivery, without bolus, treating the patient prone and supine. The benefits of the arc technique include: increased patient experience and safety, better dose conformity, better organ at risk sparing, decreased therapist time and reduction of therapist injuries. Methods: In this work we build on a technique developed by Jahnke et al. We use standard arc fields with gantry speeds corrected for varying distance to the patient followed by a single step VMAT optimization on amore » patient CT to increase dose inhomogeneity and to reduce dose to the lungs (vs. blocks). To compare the arc TBI technique to our full bolus technique, we produced plans on patient CTs for both techniques and evaluated several dosimetric parameters using an ANOVA test. Results and Conclusions: The arc technique is able reduce both the hot areas to the body (D2% reduced from 122.2% to 111.8% p<0.01) and the lungs (mean lung dose reduced from 107.5% to 99.1%, p<0.01), both statistically significant, while maintaining coverage (D98% = 97.8% vs. 94.6%, p=0.313, not statistically significant). We developed a more patient and therapist-friendly TBI treatment technique that utilizes single-step optimized VMAT plans. It was found that this technique was dosimetrically equivalent to our previous lateral technique in terms of coverage and statistically superior in terms of reduced lung dose.« less

Phase-step retrieval for tunable phase-shifting algorithms

NASA Astrophysics Data System (ADS)

Ayubi, Gastón A.; Duarte, Ignacio; Perciante, César D.; Flores, Jorge L.; Ferrari, José A.

2017-12-01

Phase-shifting (PS) is a well-known technique for phase retrieval in interferometry, with applications in deflectometry and 3D-profiling, which requires a series of intensity measurements with certain phase-steps. Usually the phase-steps are evenly spaced, and its knowledge is crucial for the phase retrieval. In this work we present a method to extract the phase-step between consecutive interferograms. We test the proposed technique with images corrupted by additive noise. The results were compared with other known methods. We also present experimental results showing the performance of the method when spatial filters are applied to the interferograms and the effect that they have on their relative phase-steps.

Model-Based Engine Control Architecture with an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Connolly, Joseph W.

2016-01-01

This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The non-linear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

Model-Based Engine Control Architecture with an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Connolly, Joseph W.

2016-01-01

This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The nonlinear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

Optimization of leaf margins for lung stereotactic body radiotherapy using a flattening filter-free beam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wakai, Nobuhide, E-mail: wakai@naramed-u.ac.jp; Sumida, Iori; Otani, Yuki

Purpose: The authors sought to determine the optimal collimator leaf margins which minimize normal tissue dose while achieving high conformity and to evaluate differences between the use of a flattening filter-free (FFF) beam and a flattening-filtered (FF) beam. Methods: Sixteen lung cancer patients scheduled for stereotactic body radiotherapy underwent treatment planning for a 7 MV FFF and a 6 MV FF beams to the planning target volume (PTV) with a range of leaf margins (−3 to 3 mm). Forty grays per four fractions were prescribed as a PTV D95. For PTV, the heterogeneity index (HI), conformity index, modified gradient indexmore » (GI), defined as the 50% isodose volume divided by target volume, maximum dose (Dmax), and mean dose (Dmean) were calculated. Mean lung dose (MLD), V20 Gy, and V5 Gy for the lung (defined as the volumes of lung receiving at least 20 and 5 Gy), mean heart dose, and Dmax to the spinal cord were measured as doses to organs at risk (OARs). Paired t-tests were used for statistical analysis. Results: HI was inversely related to changes in leaf margin. Conformity index and modified GI initially decreased as leaf margin width increased. After reaching a minimum, the two values then increased as leaf margin increased (“V” shape). The optimal leaf margins for conformity index and modified GI were −1.1 ± 0.3 mm (mean ± 1 SD) and −0.2 ± 0.9 mm, respectively, for 7 MV FFF compared to −1.0 ± 0.4 and −0.3 ± 0.9 mm, respectively, for 6 MV FF. Dmax and Dmean for 7 MV FFF were higher than those for 6 MV FF by 3.6% and 1.7%, respectively. There was a positive correlation between the ratios of HI, Dmax, and Dmean for 7 MV FFF to those for 6 MV FF and PTV size (R = 0.767, 0.809, and 0.643, respectively). The differences in MLD, V20 Gy, and V5 Gy for lung between FFF and FF beams were negligible. The optimal leaf margins for MLD, V20 Gy, and V5 Gy for lung were −0.9 ± 0.6, −1.1 ± 0.8, and −2.1 ± 1.2 mm, respectively, for 7 MV FFF

Mode-filtered large-core fiber for optical coherence tomography

PubMed Central

Moon, Sucbei; Chen, Zhongping

2013-01-01

We have investigated the use of multimode fiber in optical coherence tomography (OCT) with a mode filter that selectively suppresses the power of the high-order modes (HOMs). A large-core fiber (LCF) that has a moderate number of guiding modes was found to be an attractive alternative to the conventional single-mode fiber for its large mode area and the consequentially wide Rayleigh range of the output beam if the HOMs of the LCF were efficiently filtered out by a mode filter installed in the middle. For this, a simple mode filtering scheme of a fiber-coil mode filter was developed in this study. The LCF was uniformly coiled by an optimal bend radius with a fiber winder, specially devised for making a low-loss mode filter. The feasibility of the mode-filtered LCF in OCT imaging was tested with a common-path OCT system. It has been successfully demonstrated that our mode-filtered LCF can provide a useful imaging or sensing probe without an objective lens that greatly simplifies the structure of the probing optics. PMID:23207399

Desorption of micropollutant from spent carbon filters used for water purifier.

PubMed

Kwon, Da-Sol; Tak, So-Yeon; Lee, Jung-Eun; Kim, Moon-Kyung; Lee, Young Hwa; Han, Doo Won; Kang, Sanghyeon; Zoh, Kyung-Duk

2017-07-01

In this study, to examine the accumulated micropollutants in the spent carbon filter used in the water purifier, first, the method to desorb micropollutant from the activated carbon was developed and optimized. Then, using this optimized desorption conditions, we examined which micropollutants exist in spent carbon filters collected from houses in different regions in Korea where water purifiers were used. A total of 11 micropollutants (caffeine (CFF), acetaminophen (ACT), sulfamethazine (SMA), sulfamethoxazole (SMZ), metoprolol (MTP), carbamazepine (CBM), naproxen (NPX), bisphenol-A (BPA), ibuprofen (IBU), diclofenac (DCF), and triclocarban (TCB)) were analyzed using LC/MS-MS from the spent carbon filters. CFF, NPX, and DCF had the highest detection frequencies (>60%) in the carbon filters (n = 100), whereas SMA, SMZ, and MTP were only detected in the carbon filters, but not in the tap waters (n = 25), indicating that these micropollutants, which exist less than the detection limit in tap water, were accumulated in the carbon filters. The regional micropollutant detection patterns in the carbon filters showed higher levels of micropollutants, especially NPX, BPA, IBU, and DCF, in carbon filters collected in the Han River and Nakdong River basins where large cities exist. The levels of micropollutants in the carbon filter were generally lower in the regions where advanced oxidation processes (AOPs) were employed at nearby water treatment plants (WTPs), indicating that AOP process in WTP is quite effective in removing micropollutant. Our results suggest that desorption of micropollutant from the carbon filter used can be a tool to identify micropollutants present in tap water with trace amounts or below the detection limit.

Spin-filtering at COSY

NASA Astrophysics Data System (ADS)

Weidemann, Christian; PAX Collaboration

2011-05-01

The Spin Filtering experiments at COSY and AD at CERN within the framework of the Polarized Antiproton EXperiments (PAX) are proposed to determine the spin-dependent cross sections in bar pp scattering by observation of the buildup of polarization of an initially unpolarized stored antiproton beam after multiple passage through an internal polarized gas target. In order to commission the experimental setup for the AD and to understand the relevant machine parameters spin-filtering will first be done with protons at COSY. A first major step toward this goal has been achieved with the installation of the required mini-β section in summer 2009 and it's commissioning in January 2010. The target chamber together with the atomic beam source and the so-called Breit-Rabi polarimeter have been installed and commissioned in summer 2010. In addition an openable storage cell has been used. It provides a target thickness of 5·1013 atoms/cm2. We report on the status of spin-filtering experiments at COSY and the outcome of a recent beam time including studies on beam lifetime limitations like intra-beam scattering and the electron-cooling performance as well as machine acceptance studies.

Sinogram noise reduction for low-dose CT by statistics-based nonlinear filters

NASA Astrophysics Data System (ADS)

Wang, Jing; Lu, Hongbing; Li, Tianfang; Liang, Zhengrong

2005-04-01

Low-dose CT (computed tomography) sinogram data have been shown to be signal-dependent with an analytical relationship between the sample mean and sample variance. Spatially-invariant low-pass linear filters, such as the Butterworth and Hanning filters, could not adequately handle the data noise and statistics-based nonlinear filters may be an alternative choice, in addition to other choices of minimizing cost functions on the noisy data. Anisotropic diffusion filter and nonlinear Gaussian filters chain (NLGC) are two well-known classes of nonlinear filters based on local statistics for the purpose of edge-preserving noise reduction. These two filters can utilize the noise properties of the low-dose CT sinogram for adaptive noise reduction, but can not incorporate signal correlative information for an optimal regularized solution. Our previously-developed Karhunen-Loeve (KL) domain PWLS (penalized weighted least square) minimization considers the signal correlation via the KL strategy and seeks the PWLS cost function minimization for an optimal regularized solution for each KL component, i.e., adaptive to the KL components. This work compared the nonlinear filters with the KL-PWLS framework for low-dose CT application. Furthermore, we investigated the nonlinear filters for post KL-PWLS noise treatment in the sinogram space, where the filters were applied after ramp operation on the KL-PWLS treated sinogram data prior to backprojection operation (for image reconstruction). By both computer simulation and experimental low-dose CT data, the nonlinear filters could not outperform the KL-PWLS framework. The gain of post KL-PWLS edge-preserving noise filtering in the sinogram space is not significant, even the noise has been modulated by the ramp operation.

Waveform Analysis Optimization for the 45Ca Beta Decay Experiment

NASA Astrophysics Data System (ADS)

Whitehead, Ryan; ⁴⁵Ca Collaboration

2017-09-01

The 45Ca experiment is searching for a non-zero Fierz interference term, which would imply a tensor type contribution to the low-energy weak interaction, possibly signaling Beyond-the-Standard-Model (BSM) physics. Beta spectrum measurements are being performed at LANL, using the segmented, large area, Si detectors developed for the Nab and UCNB experiments. 109 events have been recorded, with 38 of the 254 pixels instrumented, during the summers of 2016 and 2017. An important step to extracting the energy spectra is the correction of the waveform for pile-up events. A set of analysis tools has been developed to address this issue. A trapezoidal filter has been characterized and optimized for the experimental waveforms. This filter is primarily used for energy extraction, but, by adjusting certain parameters, it has been modified to identify pile-up events. The efficiency varies with the total energy of the particle and the amount deposited with each detector interaction. Preliminary results of this analysis will be presented.

Normalised subband adaptive filtering with extended adaptiveness on degree of subband filters

NASA Astrophysics Data System (ADS)

Samuyelu, Bommu; Rajesh Kumar, Pullakura

2017-12-01

This paper proposes an adaptive normalised subband adaptive filtering (NSAF) to accomplish the betterment of NSAF performance. In the proposed NSAF, an extended adaptiveness is introduced from its variants in two ways. In the first way, the step-size is set adaptive, and in the second way, the selection of subbands is set adaptive. Hence, the proposed NSAF is termed here as variable step-size-based NSAF with selected subbands (VS-SNSAF). Experimental investigations are carried out to demonstrate the performance (in terms of convergence) of the VS-SNSAF against the conventional NSAF and its state-of-the-art adaptive variants. The results report the superior performance of VS-SNSAF over the traditional NSAF and its variants. It is also proved for its stability, robustness against noise and substantial computing complexity.

Optimization of a one-step heat-inducible in vivo mini DNA vector production system.

PubMed

Nafissi, Nafiseh; Sum, Chi Hong; Wettig, Shawn; Slavcev, Roderick A

2014-01-01

While safer than their viral counterparts, conventional circular covalently closed (CCC) plasmid DNA vectors offer a limited safety profile. They often result in the transfer of unwanted prokaryotic sequences, antibiotic resistance genes, and bacterial origins of replication that may lead to unwanted immunostimulatory responses. Furthermore, such vectors may impart the potential for chromosomal integration, thus potentiating oncogenesis. Linear covalently closed (LCC), bacterial sequence free DNA vectors have shown promising clinical improvements in vitro and in vivo. However, the generation of such minivectors has been limited by in vitro enzymatic reactions hindering their downstream application in clinical trials. We previously characterized an in vivo temperature-inducible expression system, governed by the phage λ pL promoter and regulated by the thermolabile λ CI[Ts]857 repressor to produce recombinant protelomerase enzymes in E. coli. In this expression system, induction of recombinant protelomerase was achieved by increasing culture temperature above the 37°C threshold temperature. Overexpression of protelomerase led to enzymatic reactions, acting on genetically engineered multi-target sites called "Super Sequences" that serve to convert conventional CCC plasmid DNA into LCC DNA minivectors. Temperature up-shift, however, can result in intracellular stress responses and may alter plasmid replication rates; both of which may be detrimental to LCC minivector production. We sought to optimize our one-step in vivo DNA minivector production system under various induction schedules in combination with genetic modifications influencing plasmid replication, processing rates, and cellular heat stress responses. We assessed different culture growth techniques, growth media compositions, heat induction scheduling and temperature, induction duration, post-induction temperature, and E. coli genetic background to improve the productivity and scalability of our system

EMG prediction from Motor Cortical Recordings via a Non-Negative Point Process Filter

PubMed Central

Nazarpour, Kianoush; Ethier, Christian; Paninski, Liam; Rebesco, James M.; Miall, R. Chris; Miller, Lee E.

2012-01-01

A constrained point process filtering mechanism for prediction of electromyogram (EMG) signals from multi-channel neural spike recordings is proposed here. Filters from the Kalman family are inherently sub-optimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model (GLM) that encapsulates covariates of neural activity, including the neurons’ own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter (KF) in an optimization framework and utilized a non-negativity constraint. This structure characterizes the non-linear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from twelve forearm and hand muscles of a behaving monkey during a grip-force task. For the case of limited training data, the constrained point process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static non-linearity) for different bin sizes and delays between input spikes and EMG output. For longer training data sets, results of the proposed filter and that of the Wiener cascade filter were comparable. PMID:21659018

Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.

PubMed

Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre

2003-03-01

A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

The intractable cigarette 'filter problem'.

PubMed

Harris, Bradford

2011-05-01

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

Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

NASA Astrophysics Data System (ADS)

Jena, D. P.; Panigrahi, S. N.

2016-03-01

Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

Stable Kalman filters for processing clock measurement data

NASA Technical Reports Server (NTRS)

Clements, P. A.; Gibbs, B. P.; Vandergraft, J. S.

1989-01-01

Kalman filters have been used for some time to process clock measurement data. Due to instabilities in the standard Kalman filter algorithms, the results have been unreliable and difficult to obtain. During the past several years, stable forms of the Kalman filter have been developed, implemented, and used in many diverse applications. These algorithms, while algebraically equivalent to the standard Kalman filter, exhibit excellent numerical properties. Two of these stable algorithms, the Upper triangular-Diagonal (UD) filter and the Square Root Information Filter (SRIF), have been implemented to replace the standard Kalman filter used to process data from the Deep Space Network (DSN) hydrogen maser clocks. The data are time offsets between the clocks in the DSN, the timescale at the National Institute of Standards and Technology (NIST), and two geographically intermediate clocks. The measurements are made by using the GPS navigation satellites in mutual view between clocks. The filter programs allow the user to easily modify the clock models, the GPS satellite dependent biases, and the random noise levels in order to compare different modeling assumptions. The results of this study show the usefulness of such software for processing clock data. The UD filter is indeed a stable, efficient, and flexible method for obtaining optimal estimates of clock offsets, offset rates, and drift rates. A brief overview of the UD filter is also given.

Multigrid one shot methods for optimal control problems: Infinite dimensional control

NASA Technical Reports Server (NTRS)

Arian, Eyal; Taasan, Shlomo

1994-01-01

The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.