A New Adaptive Image Denoising Method Based on Neighboring Coefficients
NASA Astrophysics Data System (ADS)
Biswas, Mantosh; Om, Hari
2016-03-01
Many good techniques have been discussed for image denoising that include NeighShrink, improved adaptive wavelet denoising method based on neighboring coefficients (IAWDMBNC), improved wavelet shrinkage technique for image denoising (IWST), local adaptive wiener filter (LAWF), wavelet packet thresholding using median and wiener filters (WPTMWF), adaptive image denoising method based on thresholding (AIDMT). These techniques are based on local statistical description of the neighboring coefficients in a window. These methods however do not give good quality of the images since they cannot modify and remove too many small wavelet coefficients simultaneously due to the threshold. In this paper, a new image denoising method is proposed that shrinks the noisy coefficients using an adaptive threshold. Our method overcomes these drawbacks and it has better performance than the NeighShrink, IAWDMBNC, IWST, LAWF, WPTMWF, and AIDMT denoising methods.
Adaptive reconnection-based arbitrary Lagrangian Eulerian method
Bo, Wurigen; Shashkov, Mikhail
2015-07-21
We present a new adaptive Arbitrary Lagrangian Eulerian (ALE) method. This method is based on the reconnection-based ALE (ReALE) methodology of Refs. [35], [34] and [6]. The main elements in a standard ReALE method are: an explicit Lagrangian phase on an arbitrary polygonal (in 2D) mesh in which the solution and positions of grid nodes are updated; a rezoning phase in which a new grid is defined by changing the connectivity (using Voronoi tessellation) but not the number of cells; and a remapping phase in which the Lagrangian solution is transferred onto the new grid. Furthermore, in the standard ReALE method, the rezoned mesh is smoothed by using one or several steps toward centroidal Voronoi tessellation, but it is not adapted to the solution in any way.
Adaptive reconnection-based arbitrary Lagrangian Eulerian method
Bo, Wurigen; Shashkov, Mikhail
2015-07-21
We present a new adaptive Arbitrary Lagrangian Eulerian (ALE) method. This method is based on the reconnection-based ALE (ReALE) methodology of Refs. [35], [34] and [6]. The main elements in a standard ReALE method are: an explicit Lagrangian phase on an arbitrary polygonal (in 2D) mesh in which the solution and positions of grid nodes are updated; a rezoning phase in which a new grid is defined by changing the connectivity (using Voronoi tessellation) but not the number of cells; and a remapping phase in which the Lagrangian solution is transferred onto the new grid. Furthermore, in the standard ReALEmore » method, the rezoned mesh is smoothed by using one or several steps toward centroidal Voronoi tessellation, but it is not adapted to the solution in any way.« less
Comparing Anisotropic Output-Based Grid Adaptation Methods by Decomposition
NASA Technical Reports Server (NTRS)
Park, Michael A.; Loseille, Adrien; Krakos, Joshua A.; Michal, Todd
2015-01-01
Anisotropic grid adaptation is examined by decomposing the steps of flow solution, ad- joint solution, error estimation, metric construction, and simplex grid adaptation. Multiple implementations of each of these steps are evaluated by comparison to each other and expected analytic results when available. For example, grids are adapted to analytic metric fields and grid measures are computed to illustrate the properties of multiple independent implementations of grid adaptation mechanics. Different implementations of each step in the adaptation process can be evaluated in a system where the other components of the adaptive cycle are fixed. Detailed examination of these properties allows comparison of different methods to identify the current state of the art and where further development should be targeted.
An Adaptive Derivative-based Method for Function Approximation
Tong, C
2008-10-22
To alleviate the high computational cost of large-scale multi-physics simulations to study the relationships between the model parameters and the outputs of interest, response surfaces are often used in place of the exact functional relationships. This report explores a method for response surface construction using adaptive sampling guided by derivative information at each selected sample point. This method is especially suitable for applications that can readily provide added information such as gradients and Hessian with respect to the input parameters under study. When higher order terms (third and above) in the Taylor series are negligible, the approximation error for this method can be controlled. We present details of the adaptive algorithm and numerical results on a few test problems.
An adaptive unsupervised hyperspectral classification method based on Gaussian distribution
NASA Astrophysics Data System (ADS)
Yue, Jiang; Wu, Jing-wei; Zhang, Yi; Bai, Lian-fa
2014-11-01
In order to achieve adaptive unsupervised clustering in the high precision, a method using Gaussian distribution to fit the similarity of the inter-class and the noise distribution is proposed in this paper, and then the automatic segmentation threshold is determined by the fitting result. First, according with the similarity measure of the spectral curve, this method assumes that the target and the background both in Gaussian distribution, the distribution characteristics is obtained through fitting the similarity measure of minimum related windows and center pixels with Gaussian function, and then the adaptive threshold is achieved. Second, make use of the pixel minimum related windows to merge adjacent similar pixels into a picture-block, then the dimensionality reduction is completed and the non-supervised classification is realized. AVIRIS data and a set of hyperspectral data we caught are used to evaluate the performance of the proposed method. Experimental results show that the proposed algorithm not only realizes the adaptive but also outperforms K-MEANS and ISODATA on the classification accuracy, edge recognition and robustness.
Hwang, Wei-Chin
2010-01-01
How do we culturally adapt psychotherapy for ethnic minorities? Although there has been growing interest in doing so, few therapy adaptation frameworks have been developed. The majority of these frameworks take a top-down theoretical approach to adapting psychotherapy. The purpose of this paper is to introduce a community-based developmental approach to modifying psychotherapy for ethnic minorities. The Formative Method for Adapting Psychotherapy (FMAP) is a bottom-up approach that involves collaborating with consumers to generate and support ideas for therapy adaptation. It involves 5-phases that target developing, testing, and reformulating therapy modifications. These phases include: (a) generating knowledge and collaborating with stakeholders (b) integrating generated information with theory and empirical and clinical knowledge, (c) reviewing the initial culturally adapted clinical intervention with stakeholders and revising the culturally adapted intervention, (d) testing the culturally adapted intervention, and (e) finalizing the culturally adapted intervention. Application of the FMAP is illustrated using examples from a study adapting psychotherapy for Chinese Americans, but can also be readily applied to modify therapy for other ethnic groups. PMID:20625458
Multiscale Simulation of Microcrack Based on a New Adaptive Finite Element Method
NASA Astrophysics Data System (ADS)
Xu, Yun; Chen, Jun; Chen, Dong Quan; Sun, Jin Shan
In this paper, a new adaptive finite element (FE) framework based on the variational multiscale method is proposed and applied to simulate the dynamic behaviors of metal under loadings. First, the extended bridging scale method is used to couple molecular dynamics and FE. Then, macro damages evolvements of those micro defects are simulated by the adaptive FE method. Some auxiliary strategies, such as the conservative mesh remapping, failure mechanism and mesh splitting technique are also included in the adaptive FE computation. Efficiency of our method is validated by numerical experiments.
Quantification of organ motion based on an adaptive image-based scale invariant feature method
Paganelli, Chiara; Peroni, Marta
2013-11-15
Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT
Wavelet-based acoustic emission detection method with adaptive thresholding
NASA Astrophysics Data System (ADS)
Menon, Sunil; Schoess, Jeffrey N.; Hamza, Rida; Busch, Darryl
2000-06-01
Reductions in Navy maintenance budgets and available personnel have dictated the need to transition from time-based to 'condition-based' maintenance. Achieving this will require new enabling diagnostic technologies. One such technology, the use of acoustic emission for the early detection of helicopter rotor head dynamic component faults, has been investigated by Honeywell Technology Center for its rotor acoustic monitoring system (RAMS). This ambitious, 38-month, proof-of-concept effort, which was a part of the Naval Surface Warfare Center Air Vehicle Diagnostics System program, culminated in a successful three-week flight test of the RAMS system at Patuxent River Flight Test Center in September 1997. The flight test results demonstrated that stress-wave acoustic emission technology can detect signals equivalent to small fatigue cracks in rotor head components and can do so across the rotating articulated rotor head joints and in the presence of other background acoustic noise generated during flight operation. This paper presents the results of stress wave data analysis of the flight-test dataset using wavelet-based techniques to assess background operational noise vs. machinery failure detection results.
Method for reducing the drag of blunt-based vehicles by adaptively increasing forebody roughness
NASA Technical Reports Server (NTRS)
Whitmore, Stephen A. (Inventor); Saltzman, Edwin J. (Inventor); Moes, Timothy R. (Inventor); Iliff, Kenneth W. (Inventor)
2005-01-01
A method for reducing drag upon a blunt-based vehicle by adaptively increasing forebody roughness to increase drag at the roughened area of the forebody, which results in a decrease in drag at the base of this vehicle, and in total vehicle drag.
Adaptive Algebraic Multigrid Methods
Brezina, M; Falgout, R; MacLachlan, S; Manteuffel, T; McCormick, S; Ruge, J
2004-04-09
Our ability to simulate physical processes numerically is constrained by our ability to solve the resulting linear systems, prompting substantial research into the development of multiscale iterative methods capable of solving these linear systems with an optimal amount of effort. Overcoming the limitations of geometric multigrid methods to simple geometries and differential equations, algebraic multigrid methods construct the multigrid hierarchy based only on the given matrix. While this allows for efficient black-box solution of the linear systems associated with discretizations of many elliptic differential equations, it also results in a lack of robustness due to assumptions made on the near-null spaces of these matrices. This paper introduces an extension to algebraic multigrid methods that removes the need to make such assumptions by utilizing an adaptive process. The principles which guide the adaptivity are highlighted, as well as their application to algebraic multigrid solution of certain symmetric positive-definite linear systems.
A density-based adaptive quantum mechanical/molecular mechanical method.
Waller, Mark P; Kumbhar, Sadhana; Yang, Jack
2014-10-20
We present a density-based adaptive quantum mechanical/molecular mechanical (DBA-QM/MM) method, whereby molecules can switch layers from the QM to the MM region and vice versa. The adaptive partitioning of the molecular system ensures that the layer assignment can change during the optimization procedure, that is, on the fly. The switch from a QM molecule to a MM molecule is determined if there is an absence of noncovalent interactions to any atom of the QM core region. The presence/absence of noncovalent interactions is determined by analysis of the reduced density gradient. Therefore, the location of the QM/MM boundary is based on physical arguments, and this neatly removes some empiricism inherent in previous adaptive QM/MM partitioning schemes. The DBA-QM/MM method is validated by using a water-in-water setup and an explicitly solvated L-alanyl-L-alanine dipeptide. PMID:24954803
Xia, Kelin; Zhan, Meng; Wan, Decheng; Wei, Guo-Wei
2012-02-01
Mesh deformation methods are a versatile strategy for solving partial differential equations (PDEs) with a vast variety of practical applications. However, these methods break down for elliptic PDEs with discontinuous coefficients, namely, elliptic interface problems. For this class of problems, the additional interface jump conditions are required to maintain the well-posedness of the governing equation. Consequently, in order to achieve high accuracy and high order convergence, additional numerical algorithms are required to enforce the interface jump conditions in solving elliptic interface problems. The present work introduces an interface technique based adaptively deformed mesh strategy for resolving elliptic interface problems. We take the advantages of the high accuracy, flexibility and robustness of the matched interface and boundary (MIB) method to construct an adaptively deformed mesh based interface method for elliptic equations with discontinuous coefficients. The proposed method generates deformed meshes in the physical domain and solves the transformed governed equations in the computational domain, which maintains regular Cartesian meshes. The mesh deformation is realized by a mesh transformation PDE, which controls the mesh redistribution by a source term. The source term consists of a monitor function, which builds in mesh contraction rules. Both interface geometry based deformed meshes and solution gradient based deformed meshes are constructed to reduce the L(∞) and L(2) errors in solving elliptic interface problems. The proposed adaptively deformed mesh based interface method is extensively validated by many numerical experiments. Numerical results indicate that the adaptively deformed mesh based interface method outperforms the original MIB method for dealing with elliptic interface problems. PMID:22586356
Xia, Kelin; Zhan, Meng; Wan, Decheng; Wei, Guo-Wei
2011-01-01
Mesh deformation methods are a versatile strategy for solving partial differential equations (PDEs) with a vast variety of practical applications. However, these methods break down for elliptic PDEs with discontinuous coefficients, namely, elliptic interface problems. For this class of problems, the additional interface jump conditions are required to maintain the well-posedness of the governing equation. Consequently, in order to achieve high accuracy and high order convergence, additional numerical algorithms are required to enforce the interface jump conditions in solving elliptic interface problems. The present work introduces an interface technique based adaptively deformed mesh strategy for resolving elliptic interface problems. We take the advantages of the high accuracy, flexibility and robustness of the matched interface and boundary (MIB) method to construct an adaptively deformed mesh based interface method for elliptic equations with discontinuous coefficients. The proposed method generates deformed meshes in the physical domain and solves the transformed governed equations in the computational domain, which maintains regular Cartesian meshes. The mesh deformation is realized by a mesh transformation PDE, which controls the mesh redistribution by a source term. The source term consists of a monitor function, which builds in mesh contraction rules. Both interface geometry based deformed meshes and solution gradient based deformed meshes are constructed to reduce the L∞ and L2 errors in solving elliptic interface problems. The proposed adaptively deformed mesh based interface method is extensively validated by many numerical experiments. Numerical results indicate that the adaptively deformed mesh based interface method outperforms the original MIB method for dealing with elliptic interface problems. PMID:22586356
NASA Astrophysics Data System (ADS)
Tang, Qiuyan; Wang, Jing; Lv, Pin; Sun, Quan
2015-10-01
Propagation simulation method and choosing mesh grid are both very important to get the correct propagation results in wave optics simulation. A new angular spectrum propagation method with alterable mesh grid based on the traditional angular spectrum method and the direct FFT method is introduced. With this method, the sampling space after propagation is not limited to propagation methods no more, but freely alterable. However, choosing mesh grid on target board influences the validity of simulation results directly. So an adaptive mesh choosing method based on wave characteristics is proposed with the introduced propagation method. We can calculate appropriate mesh grids on target board to get satisfying results. And for complex initial wave field or propagation through inhomogeneous media, we can also calculate and set the mesh grid rationally according to above method. Finally, though comparing with theoretical results, it's shown that the simulation result with the proposed method coinciding with theory. And by comparing with the traditional angular spectrum method and the direct FFT method, it's known that the proposed method is able to adapt to a wider range of Fresnel number conditions. That is to say, the method can simulate propagation results efficiently and correctly with propagation distance of almost zero to infinity. So it can provide better support for more wave propagation applications such as atmospheric optics, laser propagation and so on.
NASA Astrophysics Data System (ADS)
Shi, Lei; Wang, Z. J.
2015-08-01
Adjoint-based mesh adaptive methods are capable of distributing computational resources to areas which are important for predicting an engineering output. In this paper, we develop an adjoint-based h-adaptation approach based on the high-order correction procedure via reconstruction formulation (CPR) to minimize the output or functional error. A dual-consistent CPR formulation of hyperbolic conservation laws is developed and its dual consistency is analyzed. Super-convergent functional and error estimate for the output with the CPR method are obtained. Factors affecting the dual consistency, such as the solution point distribution, correction functions, boundary conditions and the discretization approach for the non-linear flux divergence term, are studied. The presented method is then used to perform simulations for the 2D Euler and Navier-Stokes equations with mesh adaptation driven by the adjoint-based error estimate. Several numerical examples demonstrate the ability of the presented method to dramatically reduce the computational cost comparing with uniform grid refinement.
NASA Astrophysics Data System (ADS)
Chai, Runqi; Savvaris, Al; Tsourdos, Antonios
2016-06-01
In this paper, a fuzzy physical programming (FPP) method has been introduced for solving multi-objective Space Manoeuvre Vehicles (SMV) skip trajectory optimization problem based on hp-adaptive pseudospectral methods. The dynamic model of SMV is elaborated and then, by employing hp-adaptive pseudospectral methods, the problem has been transformed to nonlinear programming (NLP) problem. According to the mission requirements, the solutions were calculated for each single-objective scenario. To get a compromised solution for each target, the fuzzy physical programming (FPP) model is proposed. The preference function is established with considering the fuzzy factor of the system such that a proper compromised trajectory can be acquired. In addition, the NSGA-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the FPP solution. Simulation results indicate that the proposed method is effective and feasible in terms of dealing with the multi-objective skip trajectory optimization for the SMV.
A novel timestamp based adaptive clock method for circuit emulation service over packet network
NASA Astrophysics Data System (ADS)
Dai, Jin-you; Yu, Shao-hua
2007-11-01
It is necessary to transport TDM (time division multiplexing) over packet network such as IP and Ethernet, and synchronization is a problem when carrying TDM over the packet network. Clock methods for TDM over packet network are introduced. A new adaptive clock method is presented. The method is a kind of timestamp based adaptive method, but no timestamp needs transporting over packet network. By using the local oscillator and a counter, the timestamp information (local timestamp) related to the service clock of the remote PE (provide edge) and the near PE can be attained. By using D-EWMA filter algorithm, the noise caused by packet network can be filtered and the useful timestamp can be extracted out. With the timestamp and a voltage-controlled oscillator, clock frequency of near PE can be adjusted the same as clock frequency of the remote PE. A kind of simulation device is designed and a test network topology is set up to test and verify the method. The experiment result shows that synthetical performance of the new method is better than ordinary buffer based method and ordinary timestamp based method.
Adaptation strategies for high order discontinuous Galerkin methods based on Tau-estimation
NASA Astrophysics Data System (ADS)
Kompenhans, Moritz; Rubio, Gonzalo; Ferrer, Esteban; Valero, Eusebio
2016-02-01
In this paper three p-adaptation strategies based on the minimization of the truncation error are presented for high order discontinuous Galerkin methods. The truncation error is approximated by means of a τ-estimation procedure and enables the identification of mesh regions that require adaptation. Three adaptation strategies are developed and termed a posteriori, quasi-a priori and quasi-a priori corrected. All strategies require fine solutions, which are obtained by enriching the polynomial order, but while the former needs time converged solutions, the last two rely on non-converged solutions, which lead to faster computations. In addition, the high order method permits the spatial decoupling for the estimated errors and enables anisotropic p-adaptation. These strategies are verified and compared in terms of accuracy and computational cost for the Euler and the compressible Navier-Stokes equations. It is shown that the two quasi-a priori methods achieve a significant reduction in computational cost when compared to a uniform polynomial enrichment. Namely, for a viscous boundary layer flow, we obtain a speedup of 6.6 and 7.6 for the quasi-a priori and quasi-a priori corrected approaches, respectively.
NASA Astrophysics Data System (ADS)
Bu, Guochao; Wang, Pei
2016-04-01
Terrestrial laser scanning (TLS) has been used to extract accurate forest biophysical parameters for inventory purposes. The diameter at breast height (DBH) is a key parameter for individual trees because it has the potential for modeling the height, volume, biomass, and carbon sequestration potential of the tree based on empirical allometric scaling equations. In order to extract the DBH from the single-scan data of TLS automatically and accurately within a certain range, we proposed an adaptive circle-ellipse fitting method based on the point cloud transect. This proposed method can correct the error caused by the simple circle fitting method when a tree is slanted. A slanted tree was detected by the circle-ellipse fitting analysis, then the corresponding slant angle was found based on the ellipse fitting result. With this information, the DBH of the trees could be recalculated based on reslicing the point cloud data at breast height. Artificial stem data simulated by a cylindrical model of leaning trees and the scanning data acquired with the RIEGL VZ-400 were used to test the proposed adaptive fitting method. The results shown that the proposed method can detect the trees and accurately estimate the DBH for leaning trees.
Adaptive non-uniformity correction method based on temperature for infrared detector array
NASA Astrophysics Data System (ADS)
Zhang, Zhijie; Yue, Song; Hong, Pu; Jia, Guowei; Lei, Bo
2013-09-01
The existence of non-uniformities in the responsitivity of the element array is a severe problem typical to common infrared detector. These non-uniformities result in a "curtain'' like fixed pattern noises (FPN) that appear in the image. Some random noise can be restrained by the method kind of equalization method. But the fixed pattern noise can only be removed by .non uniformity correction method. The produce of non uniformities of detector array is the combined action of infrared detector array, readout circuit, semiconductor device performance, the amplifier circuit and optical system. Conventional linear correction techniques require costly recalibration due to the drift of the detector or changes in temperature. Therefore, an adaptive non-uniformity method is needed to solve this problem. A lot factors including detectors and environment conditions variety are considered to analyze and conduct the cause of detector drift. Several experiments are designed to verify the guess. Based on the experiments, an adaptive non-uniformity correction method is put forward in this paper. The strength of this method lies in its simplicity and low computational complexity. Extensive experimental results demonstrate the disadvantage of traditional non-uniformity correct method is conquered by the proposed scheme.
Adaptive f-k deghosting method based on non-Gaussianity
NASA Astrophysics Data System (ADS)
Liu, Lei; Lu, Wenkai
2016-04-01
For conventional horizontal towed streamer data, the f-k deghosting method is widely used to remove receiver ghosts. In the traditional f-k deghosting method, the depth of the streamer and the sea surface reflection coefficient are two key ghost parameters. In general, for one seismic line, these two parameters are fixed for all shot gathers and given by the users. In practice, these two parameters often vary during acquisition because of the rough sea condition. This paper proposes an automatic method to adaptively obtain these two ghost parameters for every shot gather. Since the proposed method is based on the non-Gaussianity of the deghosting result, it is important to choose a proper non-Gaussian criterion to ensure high accuracy of the parameter estimation. We evaluate six non-Gaussian criteria by synthetic experiment. The conclusion of our experiment is expected to provide a reference for choosing the most appropriate criterion. We apply the proposed method on a 2D real field example. Experimental results show that the optimal parameters vary among shot gathers and validate effectiveness of the parameter estimation process. Moreover, despite that this method ignores the parameter variation within one shot, the adaptive deghosting results show improvements when compared with the deghosting results obtained by using constant parameters for the whole line.
Comparative adaptation accuracy of acrylic denture bases evaluated by two different methods.
Lee, Chung-Jae; Bok, Sung-Bem; Bae, Ji-Young; Lee, Hae-Hyoung
2010-08-01
This study examined the adaptation accuracy of acrylic denture base processed using fluid-resin (PERform), injection-moldings (SR-Ivocap, Success, Mak Press), and two compression-molding techniques. The adaptation accuracy was measured primarily by the posterior border gaps at the mid-palatal area using a microscope and subsequently by weighing of the weight of the impression material between the denture base and master cast using hand-mixed and automixed silicone. The correlation between the data measured using these two test methods was examined. The PERform and Mak Press produced significantly smaller maximum palatal gap dimensions than the other groups (p<0.05). Mak Press also showed a significantly smaller weight of automixed silicone material than the other groups (p<0.05), while SR-Ivocap and Success showed similar adaptation accuracy to the compression-molding denture. The correlationship between the magnitude of the posterior border gap and the weight of the silicone impression materials was affected by either the material or mixing variables. PMID:20675954
Wavefront detection method of a single-sensor based adaptive optics system.
Wang, Chongchong; Hu, Lifa; Xu, Huanyu; Wang, Yukun; Li, Dayu; Wang, Shaoxin; Mu, Quanquan; Yang, Chengliang; Cao, Zhaoliang; Lu, Xinghai; Xuan, Li
2015-08-10
In adaptive optics system (AOS) for optical telescopes, the reported wavefront sensing strategy consists of two parts: a specific sensor for tip-tilt (TT) detection and another wavefront sensor for other distortions detection. Thus, a part of incident light has to be used for TT detection, which decreases the light energy used by wavefront sensor and eventually reduces the precision of wavefront correction. In this paper, a single Shack-Hartmann wavefront sensor based wavefront measurement method is presented for both large amplitude TT and other distortions' measurement. Experiments were performed for testing the presented wavefront method and validating the wavefront detection and correction ability of the single-sensor based AOS. With adaptive correction, the root-mean-square of residual TT was less than 0.2 λ, and a clear image was obtained in the lab. Equipped on a 1.23-meter optical telescope, the binary stars with angle distance of 0.6″ were clearly resolved using the AOS. This wavefront measurement method removes the separate TT sensor, which not only simplifies the AOS but also saves light energy for subsequent wavefront sensing and imaging, and eventually improves the detection and imaging capability of the AOS. PMID:26367988
Patched based methods for adaptive mesh refinement solutions of partial differential equations
Saltzman, J.
1997-09-02
This manuscript contains the lecture notes for a course taught from July 7th through July 11th at the 1997 Numerical Analysis Summer School sponsored by C.E.A., I.N.R.I.A., and E.D.F. The subject area was chosen to support the general theme of that year`s school which is ``Multiscale Methods and Wavelets in Numerical Simulation.`` The first topic covered in these notes is a description of the problem domain. This coverage is limited to classical PDEs with a heavier emphasis on hyperbolic systems and constrained hyperbolic systems. The next topic is difference schemes. These schemes are the foundation for the adaptive methods. After the background material is covered, attention is focused on a simple patched based adaptive algorithm and its associated data structures for square grids and hyperbolic conservation laws. Embellishments include curvilinear meshes, embedded boundary and overset meshes. Next, several strategies for parallel implementations are examined. The remainder of the notes contains descriptions of elliptic solutions on the mesh hierarchy, elliptically constrained flow solution methods and elliptically constrained flow solution methods with diffusion.
NASA Astrophysics Data System (ADS)
Lei, Yu; Lei, Jianming; Guo, Junhui; Zou, Xuecheng; Li, Bin; Lu, Li
2014-02-01
A new autocorrelation matrix eigenvalue based digital signal processing (DSP) chromatic dispersion (CD) adaptive monitoring and compensation method is proposed. It employs the average of the autocorrelation matrix eigenvalue instead of eigenvalue spread to be the metric of scanning. The average calculation has been effective in relieving the degradation of performance caused by the fluctuation of autocorrelation matrix eigenvalue. Compare with the eigenvalue spread scanning algorithm, this method reduces the monitoring errors to below 10 ps/nm from more than 200 ps/nm, while not increasing its computation complexity. Simulation results show that in 100 Gbit/s polarization division multiplexing (PDM) quadrature phase shift keying (QPSK) coherent optical transmission system, this method improves the bit error rate (BER) performance and the system robustness against the amplified-spontaneous-emission noise.
Hejč, Jakub; Vítek, Martin; Ronzhina, Marina; Nováková, Marie; Kolářová, Jana
2015-09-01
We present a novel wavelet-based ECG delineation method with robust classification of P wave and T wave. The work is aimed on an adaptation of the method to long-term experimental electrograms (EGs) measured on isolated rabbit heart and to evaluate the effect of global ischemia in experimental EGs on delineation performance. The algorithm was tested on a set of 263 rabbit EGs with established reference points and on human signals using standard Common Standards for Quantitative Electrocardiography Standard Database (CSEDB). On CSEDB, standard deviation (SD) of measured errors satisfies given criterions in each point and the results are comparable to other published works. In rabbit signals, our QRS detector reached sensitivity of 99.87% and positive predictivity of 99.89% despite an overlay of spectral components of QRS complex, P wave and power line noise. The algorithm shows great performance in suppressing J-point elevation and reached low overall error in both, QRS onset (SD = 2.8 ms) and QRS offset (SD = 4.3 ms) delineation. T wave offset is detected with acceptable error (SD = 12.9 ms) and sensitivity nearly 99%. Variance of the errors during global ischemia remains relatively stable, however more failures in detection of T wave and P wave occur. Due to differences in spectral and timing characteristics parameters of rabbit based algorithm have to be highly adaptable and set more precisely than in human ECG signals to reach acceptable performance. PMID:26577367
Zhao, Guoliang; Li, Hongxing
2013-01-01
This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model. PMID:24453897
An adaptive distance-based group contribution method for thermodynamic property prediction.
He, Tanjin; Li, Shuang; Chi, Yawei; Zhang, Hong-Bo; Wang, Zhi; Yang, Bin; He, Xin; You, Xiaoqing
2016-09-14
In the search for an accurate yet inexpensive method to predict thermodynamic properties of large hydrocarbon molecules, we have developed an automatic and adaptive distance-based group contribution (DBGC) method. The method characterizes the group interaction within a molecule with an exponential decay function of the group-to-group distance, defined as the number of bonds between the groups. A database containing the molecular bonding information and the standard enthalpy of formation (Hf,298K) for alkanes, alkenes, and their radicals at the M06-2X/def2-TZVP//B3LYP/6-31G(d) level of theory was constructed. Multiple linear regression (MLR) and artificial neural network (ANN) fitting were used to obtain the contributions from individual groups and group interactions for further predictions. Compared with the conventional group additivity (GA) method, the DBGC method predicts Hf,298K for alkanes more accurately using the same training sets. Particularly for some highly branched large hydrocarbons, the discrepancy with the literature data is smaller for the DBGC method than the conventional GA method. When extended to other molecular classes, including alkenes and radicals, the overall accuracy level of this new method is still satisfactory. PMID:27522953
Adaptive model-based control systems and methods for controlling a gas turbine
NASA Technical Reports Server (NTRS)
Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)
2004-01-01
Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).
Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing
2016-01-01
A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006
Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing
2016-01-01
A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006
A Star Recognition Method Based on the Adaptive Ant Colony Algorithm for Star Sensors
Quan, Wei; Fang, Jiancheng
2010-01-01
A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms. PMID:22294908
A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.
Quan, Wei; Fang, Jiancheng
2010-01-01
A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50″, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms. PMID:22294908
Accelerated adaptive integration method.
Kaus, Joseph W; Arrar, Mehrnoosh; McCammon, J Andrew
2014-05-15
Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value of λ seed the conformational space sampled at another λ value. Adapting the value of λ throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the λ value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of λ, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors. PMID:24780083
Accelerated Adaptive Integration Method
2015-01-01
Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value of λ seed the conformational space sampled at another λ value. Adapting the value of λ throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the λ value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of λ, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors. PMID:24780083
Simple method for model reference adaptive control
NASA Technical Reports Server (NTRS)
Seraji, H.
1989-01-01
A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.
Development and evaluation of a method of calibrating medical displays based on fixed adaptation
Sund, Patrik Månsson, Lars Gunnar; Båth, Magnus
2015-04-15
Purpose: The purpose of this work was to develop and evaluate a new method for calibration of medical displays that includes the effect of fixed adaptation and by using equipment and luminance levels typical for a modern radiology department. Methods: Low contrast sinusoidal test patterns were derived at nine luminance levels from 2 to 600 cd/m{sup 2} and used in a two alternative forced choice observer study, where the adaptation level was fixed at the logarithmic average of 35 cd/m{sup 2}. The contrast sensitivity at each luminance level was derived by establishing a linear relationship between the ten pattern contrast levels used at every luminance level and a detectability index (d′) calculated from the fraction of correct responses. A Gaussian function was fitted to the data and normalized to the adaptation level. The corresponding equation was used in a display calibration method that included the grayscale standard display function (GSDF) but compensated for fixed adaptation. In the evaluation study, the contrast of circular objects with a fixed pixel contrast was displayed using both calibration methods and was rated on a five-grade scale. Results were calculated using a visual grading characteristics method. Error estimations in both observer studies were derived using a bootstrap method. Results: The contrast sensitivities for the darkest and brightest patterns compared to the contrast sensitivity at the adaptation luminance were 37% and 56%, respectively. The obtained Gaussian fit corresponded well with similar studies. The evaluation study showed a higher degree of equally distributed contrast throughout the luminance range with the calibration method compensated for fixed adaptation than for the GSDF. The two lowest scores for the GSDF were obtained for the darkest and brightest patterns. These scores were significantly lower than the lowest score obtained for the compensated GSDF. For the GSDF, the scores for all luminance levels were statistically
Comparing Computer-Adaptive and Curriculum-Based Measurement Methods of Assessment
ERIC Educational Resources Information Center
Shapiro, Edward S.; Gebhardt, Sarah N.
2012-01-01
This article reported the concurrent, predictive, and diagnostic accuracy of a computer-adaptive test (CAT) and curriculum-based measurements (CBM; both computation and concepts/application measures) for universal screening in mathematics among students in first through fourth grade. Correlational analyses indicated moderate to strong…
NASA Technical Reports Server (NTRS)
Whitmore, Stephen A. (Inventor); Saltzman, Edwin J. (Inventor); Moes, Timothy R. (Inventor); Iliff, Kenneth W. (Inventor)
2005-01-01
A method for reducing drag upon a blunt-based vehicle by adaptively increasing forebody roughness to increase drag at the roughened area of the forebody, which results in a decrease in drag at the base of this vehicle, and in total vehicle drag.
An edge-based solution-adaptive method applied to the AIRPLANE code
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Thomas, Scott D.; Cliff, Susan E.
1995-01-01
Computational methods to solve large-scale realistic problems in fluid flow can be made more efficient and cost effective by using them in conjunction with dynamic mesh adaption procedures that perform simultaneous coarsening and refinement to capture flow features of interest. This work couples the tetrahedral mesh adaption scheme, 3D_TAG, with the AIRPLANE code to solve complete aircraft configuration problems in transonic and supersonic flow regimes. Results indicate that the near-field sonic boom pressure signature of a cone-cylinder is improved, the oblique and normal shocks are better resolved on a transonic wing, and the bow shock ahead of an unstarted inlet is better defined.
A Digitalized Gyroscope System Based on a Modified Adaptive Control Method
Xia, Dunzhu; Hu, Yiwei; Ni, Peizhen
2016-01-01
In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm. PMID:26959019
A Digitalized Gyroscope System Based on a Modified Adaptive Control Method.
Xia, Dunzhu; Hu, Yiwei; Ni, Peizhen
2016-01-01
In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm. PMID:26959019
Robust Optimal Adaptive Control Method with Large Adaptive Gain
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2009-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
NASA Astrophysics Data System (ADS)
Ma, Xibo; Tian, Jie; Zhang, Bo; Zhang, Xing; Xue, Zhenwen; Dong, Di; Han, Dong
2011-03-01
Among many optical molecular imaging modalities, bioluminescence imaging (BLI) has more and more wide application in tumor detection and evaluation of pharmacodynamics, toxicity, pharmacokinetics because of its noninvasive molecular and cellular level detection ability, high sensitivity and low cost in comparison with other imaging technologies. However, BLI can not present the accurate location and intensity of the inner bioluminescence sources such as in the bone, liver or lung etc. Bioluminescent tomography (BLT) shows its advantage in determining the bioluminescence source distribution inside a small animal or phantom. Considering the deficiency of two-dimensional imaging modality, we developed three-dimensional tomography to reconstruct the information of the bioluminescence source distribution in transgenic mOC-Luc mice bone with the boundary measured data. In this paper, to study the osteocalcin (OC) accumulation in transgenic mOC-Luc mice bone, a BLT reconstruction method based on multilevel adaptive finite element (FEM) algorithm was used for localizing and quantifying multi bioluminescence sources. Optical and anatomical information of the tissues are incorporated as a priori knowledge in this method, which can reduce the ill-posedness of BLT. The data was acquired by the dual modality BLT and Micro CT prototype system that was developed by us. Through temperature control and absolute intensity calibration, a relative accurate intensity can be calculated. The location of the OC accumulation was reconstructed, which was coherent with the principle of bone differentiation. This result also was testified by ex vivo experiment in the black 96-plate well using the BLI system and the chemiluminescence apparatus.
H∞ Adaptive tracking control for switched systems based on an average dwell-time method
NASA Astrophysics Data System (ADS)
Wu, Caiyun; Zhao, Jun
2015-10-01
This paper investigates the H∞ state tracking model reference adaptive control (MRAC) problem for a class of switched systems using an average dwell-time method. First, a stability criterion is established for a switched reference model. Then, an adaptive controller is designed and the state tracking control problem is converted into the stability analysis. The global practical stability of the error switched system can be guaranteed under a class of switching signals characterised by an average dwell time. Consequently, sufficient conditions for the solvability of the H∞ state tracking MRAC problem are derived. An example of highly manoeuvrable aircraft technology vehicle is given to demonstrate the feasibility and effectiveness of the proposed design method.
Thickness-based adaptive mesh refinement methods for multi-phase flow simulations with thin regions
Chen, Xiaodong; Yang, Vigor
2014-07-15
In numerical simulations of multi-scale, multi-phase flows, grid refinement is required to resolve regions with small scales. A notable example is liquid-jet atomization and subsequent droplet dynamics. It is essential to characterize the detailed flow physics with variable length scales with high fidelity, in order to elucidate the underlying mechanisms. In this paper, two thickness-based mesh refinement schemes are developed based on distance- and topology-oriented criteria for thin regions with confining wall/plane of symmetry and in any situation, respectively. Both techniques are implemented in a general framework with a volume-of-fluid formulation and an adaptive-mesh-refinement capability. The distance-oriented technique compares against a critical value, the ratio of an interfacial cell size to the distance between the mass center of the cell and a reference plane. The topology-oriented technique is developed from digital topology theories to handle more general conditions. The requirement for interfacial mesh refinement can be detected swiftly, without the need of thickness information, equation solving, variable averaging or mesh repairing. The mesh refinement level increases smoothly on demand in thin regions. The schemes have been verified and validated against several benchmark cases to demonstrate their effectiveness and robustness. These include the dynamics of colliding droplets, droplet motions in a microchannel, and atomization of liquid impinging jets. Overall, the thickness-based refinement technique provides highly adaptive meshes for problems with thin regions in an efficient and fully automatic manner.
NASA Astrophysics Data System (ADS)
Hasegawa, Takemitsu; Hibino, Susumu; Hosoda, Yohsuke; Ninomiya, Ichizo
2007-08-01
An improvement is made to an automatic quadrature due to Ninomiya (J. Inf. Process. 3:162?170, 1980) of adaptive type based on the Newton?Cotes rule by incorporating a doubly-adaptive algorithm due to Favati, Lotti and Romani (ACM Trans. Math. Softw. 17:207?217, 1991; ACM Trans. Math. Softw. 17:218?232, 1991). We compare the present method in performance with some others by using various test problems including Kahaner?s ones (Computation of numerical quadrature formulas. In: Rice, J.R. (ed.) Mathematical Software, 229?259. Academic, Orlando, FL, 1971).
Adaptive neural network nonlinear control for BTT missile based on the differential geometry method
NASA Astrophysics Data System (ADS)
Wu, Hao; Wang, Yongji; Xu, Jiangsheng
2007-11-01
A new nonlinear control strategy incorporated the differential geometry method with adaptive neural networks is presented for the nonlinear coupling system of Bank-to-Turn missile in reentry phase. The basic control law is designed using the differential geometry feedback linearization method, and the online learning neural networks are used to compensate the system errors due to aerodynamic parameter errors and external disturbance in view of the arbitrary nonlinear mapping and rapid online learning ability for multi-layer neural networks. The online weights and thresholds tuning rules are deduced according to the tracking error performance functions by Levenberg-Marquardt algorithm, which will make the learning process faster and more stable. The six degree of freedom simulation results show that the attitude angles can track the desired trajectory precisely. It means that the proposed strategy effectively enhance the stability, the tracking performance and the robustness of the control system.
A wavelet-MRA-based adaptive semi-Lagrangian method for the relativistic Vlasov-Maxwell system
Besse, Nicolas Latu, Guillaume Ghizzo, Alain Sonnendruecker, Eric Bertrand, Pierre
2008-08-10
In this paper we present a new method for the numerical solution of the relativistic Vlasov-Maxwell system on a phase-space grid using an adaptive semi-Lagrangian method. The adaptivity is performed through a wavelet multiresolution analysis, which gives a powerful and natural refinement criterion based on the local measurement of the approximation error and regularity of the distribution function. Therefore, the multiscale expansion of the distribution function allows to get a sparse representation of the data and thus save memory space and CPU time. We apply this numerical scheme to reduced Vlasov-Maxwell systems arising in laser-plasma physics. Interaction of relativistically strong laser pulses with overdense plasma slabs is investigated. These Vlasov simulations revealed a rich variety of phenomena associated with the fast particle dynamics induced by electromagnetic waves as electron trapping, particle acceleration, and electron plasma wavebreaking. However, the wavelet based adaptive method that we developed here, does not yield significant improvements compared to Vlasov solvers on a uniform mesh due to the substantial overhead that the method introduces. Nonetheless they might be a first step towards more efficient adaptive solvers based on different ideas for the grid refinement or on a more efficient implementation. Here the Vlasov simulations are performed in a two-dimensional phase-space where the development of thin filaments, strongly amplified by relativistic effects requires an important increase of the total number of points of the phase-space grid as they get finer as time goes on. The adaptive method could be more useful in cases where these thin filaments that need to be resolved are a very small fraction of the hyper-volume, which arises in higher dimensions because of the surface-to-volume scaling and the essentially one-dimensional structure of the filaments. Moreover, the main way to improve the efficiency of the adaptive method is to
NASA Astrophysics Data System (ADS)
Ma, Xiang; Zabaras, Nicholas
2009-03-01
A new approach to modeling inverse problems using a Bayesian inference method is introduced. The Bayesian approach considers the unknown parameters as random variables and seeks the probabilistic distribution of the unknowns. By introducing the concept of the stochastic prior state space to the Bayesian formulation, we reformulate the deterministic forward problem as a stochastic one. The adaptive hierarchical sparse grid collocation (ASGC) method is used for constructing an interpolant to the solution of the forward model in this prior space which is large enough to capture all the variability/uncertainty in the posterior distribution of the unknown parameters. This solution can be considered as a function of the random unknowns and serves as a stochastic surrogate model for the likelihood calculation. Hierarchical Bayesian formulation is used to derive the posterior probability density function (PPDF). The spatial model is represented as a convolution of a smooth kernel and a Markov random field. The state space of the PPDF is explored using Markov chain Monte Carlo algorithms to obtain statistics of the unknowns. The likelihood calculation is performed by directly sampling the approximate stochastic solution obtained through the ASGC method. The technique is assessed on two nonlinear inverse problems: source inversion and permeability estimation in flow through porous media.
Wang, Han; Du, Wencai; Xu, Lingwei
2016-01-01
The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS) problem to improve the estimation performance. In this paper, an AdaptiveRegularized Compressive Sampling Matching Pursuit (ARCoSaMP) algorithm is proposed. Unlike anterior greedy algorithms, the new algorithm can achieve the accuracy of reconstruction by choosing the support set adaptively, and exploiting the regularization process, which realizes the second selecting of atoms in the support set although the sparsity of the channel is unknown. Simulation results show that CS-based methods obtain significant channel estimation performance improvement compared to that of conventional preamble-based methods. The proposed ARCoSaMP algorithm outperforms the conventional sparse adaptive matching pursuit (SAMP) algorithm. ARCoSaMP provides even more interesting results than the mostadvanced greedy compressive sampling matching pursuit (CoSaMP) algorithm without a prior sparse knowledge of the channel. PMID:27347967
Wang, Han; Du, Wencai; Xu, Lingwei
2016-01-01
The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS) problem to improve the estimation performance. In this paper, an AdaptiveRegularized Compressive Sampling Matching Pursuit (ARCoSaMP) algorithm is proposed. Unlike anterior greedy algorithms, the new algorithm can achieve the accuracy of reconstruction by choosing the support set adaptively, and exploiting the regularization process, which realizes the second selecting of atoms in the support set although the sparsity of the channel is unknown. Simulation results show that CS-based methods obtain significant channel estimation performance improvement compared to that of conventional preamble-based methods. The proposed ARCoSaMP algorithm outperforms the conventional sparse adaptive matching pursuit (SAMP) algorithm. ARCoSaMP provides even more interesting results than the mostadvanced greedy compressive sampling matching pursuit (CoSaMP) algorithm without a prior sparse knowledge of the channel. PMID:27347967
Methods for correcting tilt anisoplanatism in laser-guide-star-based multiconjugate adaptive optics.
Ellerbroek, B L; Rigaut, F
2001-10-01
Multiconjugate adaptive optics (MCAO) is a technique for correcting turbulence-induced phase distortions in three dimensions instead of two, thereby greatly expanding the corrected field of view of an adaptive optics system. This is accomplished with use of multiple deformable mirrors conjugate to distinct ranges in the atmosphere, with actuator commands computed from wave-front sensor (WFS) measurements from multiple guide stars. Laser guide stars (LGSs) must be used (at least for the forseeable future) to achieve a useful degree of sky coverage in an astronomical MCAO system. Much as a single LGS cannot be used to measure overall wave-front tilt, a constellation of multiple LGSs at a common range cannot detect tilt anisoplanatism. This error alone will significantly degrade the performance of a MCAO system based on a single tilt-only natural guide star (NGS) and multiple tilt-removed LGSs at a common altitude. We present a heuristic, low-order model for the principal source of tilt anisoplanatism that suggests four possible approaches to eliminating this defect in LGS MCAO: (i) tip/tilt measurements from multiple NGS, (ii) a solution to the LGS tilt uncertainty problem, (iii) additional higher-order WFS measurements from a single NGS, or (iv) higher-order WFS measurements from both sodium and Rayleigh LGSs at different ranges. Sample numerical results for one particular MCAO system configuration indicate that approach (ii), if feasible, would provide the highest degree of tilt anisoplanatism compensation. Approaches (i) and (iv) also provide very useful levels of performance and do not require unrealistically low levels of WFS measurement noise. For a representative set of parameters for an 8-m telescope, the additional laser power required for approach (iv) is on the order of 2 W per Rayleigh LGS. PMID:11583271
Oh, Won-suk; Park, Ju-mi
2014-08-01
The base of a partial overdenture prosthesis should be fitted intraorally against the supporting element of a tooth root. Chairside relining is a common method; however, an autopolymerizing acrylic resin presents high porosity when polymerized intraorally. This article describes an indirect method where an impression is made with a silicone occlusion registration material to create a replica of the supporting elements of the residual ridge and the tooth root in a high-viscosity polyvinyl siloxane impression material. PMID:24412183
NASA Astrophysics Data System (ADS)
Wang, Cheng; Dong, XinZhuang; Shu, Chi-Wang
2015-10-01
For numerical simulation of detonation, computational cost using uniform meshes is large due to the vast separation in both time and space scales. Adaptive mesh refinement (AMR) is advantageous for problems with vastly different scales. This paper aims to propose an AMR method with high order accuracy for numerical investigation of multi-dimensional detonation. A well-designed AMR method based on finite difference weighted essentially non-oscillatory (WENO) scheme, named as AMR&WENO is proposed. A new cell-based data structure is used to organize the adaptive meshes. The new data structure makes it possible for cells to communicate with each other quickly and easily. In order to develop an AMR method with high order accuracy, high order prolongations in both space and time are utilized in the data prolongation procedure. Based on the message passing interface (MPI) platform, we have developed a workload balancing parallel AMR&WENO code using the Hilbert space-filling curve algorithm. Our numerical experiments with detonation simulations indicate that the AMR&WENO is accurate and has a high resolution. Moreover, we evaluate and compare the performance of the uniform mesh WENO scheme and the parallel AMR&WENO method. The comparison results provide us further insight into the high performance of the parallel AMR&WENO method.
NASA Astrophysics Data System (ADS)
Xin, Yizhong; Ren, Xiangshi
Continuous pen pressure can be used to operate multi-state widgets such as menus in pen based user interfaces. The number of levels into which the pen pressure space is divided determines the number of states in the multi-state widgets. To increase the optimal number of divisions of the pen pressure space and achieve greater pen pressure usability, we propose a new discretization method which divides the pen pressure space according to a personal pen pressure use profile. We present here four variations of the method: discretization according to personal/aggregation pen pressure use profile with/without visual feedback of uniform level widths and the traditional even discretization method. Two experiments were conducted respectively to investigate pen pressure use profile and to comparatively evaluate the performance of these methods. Results indicate that the subjects performed fastest and with the fewest errors when the pen pressure space was divided according to personal profile with visual feedback of uniform level widths (PU) and performed worst when the pen pressure space was divided evenly. With PU method, the optimal number of divisions of the pen pressure space was 8. Visual feedback of uniform level widths enhanced performance of uneven discretization. The findings of this study have implications for human-oriented pen pressure use in pen pressure based user interface designs.
Pipek, János; Nagy, Szilvia
2013-03-01
The wave function of a many electron system contains inhomogeneously distributed spatial details, which allows to reduce the number of fine detail wavelets in multiresolution analysis approximations. Finding a method for decimating the unnecessary basis functions plays an essential role in avoiding an exponential increase of computational demand in wavelet-based calculations. We describe an effective prediction algorithm for the next resolution level wavelet coefficients, based on the approximate wave function expanded up to a given level. The prediction results in a reasonable approximation of the wave function and allows to sort out the unnecessary wavelets with a great reliability. PMID:23115109
NASA Astrophysics Data System (ADS)
Huang, Rongzong; Wu, Huiying
2016-06-01
A total enthalpy-based lattice Boltzmann (LB) method with adaptive mesh refinement (AMR) is developed in this paper to efficiently simulate solid-liquid phase change problem where variables vary significantly near the phase interface and thus finer grid is required. For the total enthalpy-based LB method, the velocity field is solved by an incompressible LB model with multiple-relaxation-time (MRT) collision scheme, and the temperature field is solved by a total enthalpy-based MRT LB model with the phase interface effects considered and the deviation term eliminated. With a kinetic assumption that the density distribution function for solid phase is at equilibrium state, a volumetric LB scheme is proposed to accurately realize the nonslip velocity condition on the diffusive phase interface and in the solid phase. As compared with the previous schemes, this scheme can avoid nonphysical flow in the solid phase. As for the AMR approach, it is developed based on multiblock grids. An indicator function is introduced to control the adaptive generation of multiblock grids, which can guarantee the existence of overlap area between adjacent blocks for information exchange. Since MRT collision schemes are used, the information exchange is directly carried out in the moment space. Numerical tests are firstly performed to validate the strict satisfaction of the nonslip velocity condition, and then melting problems in a square cavity with different Prandtl numbers and Rayleigh numbers are simulated, which demonstrate that the present method can handle solid-liquid phase change problem with high efficiency and accuracy.
Feedback in Videogame-Based Adaptive Training
ERIC Educational Resources Information Center
Rivera, Iris Daliz
2010-01-01
The field of training has been changing rapidly due to advances in technology such as videogame-based adaptive training. Videogame-based adaptive training has provided flexibility and adaptability for training in cost-effective ways. Although this method of training may have many benefits for the trainee, current research has not kept up to pace…
NASA Astrophysics Data System (ADS)
Masoudi, Rasoul; Kabiri, Peyman
2014-01-01
Pansharpening aims to fuse a low-resolution multispectral image with a high-resolution panchromatic image to create a multispectral image with high spatial and spectral resolution. The intensity-hue-saturation (IHS) fusion method transforms an image from RGB space to IHS space. This paper reports a method to improve the spectral resolution of a final multispectral image. The proposed method implies two modifications on the basic IHS method to improve the sharpness of the final image. First, the paper proposes a method based on a genetic algorithm to find the weight of each band of multispectral image in the fusion process. Later on, a texture-based technique is proposed to save the spectral information of the final image with respect to the texture boundaries. Spectral quality metrics in terms of SAM, SID, Q-average, RASE, RMSE, CC, ERGAS and UIQI are used in our experiments. Experimental results on IKONOS and QuickBird data show that the proposed method is more efficient than the original IHS-based fusion approach and some of its extensions, such as IKONOS IHS, edge-adaptive IHS and explicit band coefficient IHS, in preserving spectral information of multispectral images.
NASA Astrophysics Data System (ADS)
Vu, Duc; Guo, Bin; Xu, Luzhou; Li, Jian
2010-04-01
We consider ground moving target indication (GMTI) and target velocity estimation based on multi-channel synthetic aperture radar (SAR) images. Via forming velocity versus cross-range images, we show that small moving targets can be detected even in the presence of strong stationary ground clutter. Moreover, the velocities of the moving targets can be estimated, and the misplaced moving targets can be placed back to their original locations based on the estimated velocities. Adaptive beamforming techniques, including Capon and generalizedlikelihood ratio test (GLRT), are used to form velocity versus cross-range images for each range bin of interest. The velocity estimation ambiguities caused by the multi-channel array geometry are analyzed. We also demonstrate the effectiveness of our approaches using the Air Force Research Laboratory (AFRL) publicly-released Gotcha SAR based GMTI data set.
Method For Model-Reference Adaptive Control
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1990-01-01
Relatively simple method of model-reference adaptive control (MRAC) developed from two prior classes of MRAC techniques: signal-synthesis method and parameter-adaption method. Incorporated into unified theory, which yields more general adaptation scheme.
SU-D-207-04: GPU-Based 4D Cone-Beam CT Reconstruction Using Adaptive Meshing Method
Zhong, Z; Gu, X; Iyengar, P; Mao, W; Wang, J; Guo, X
2015-06-15
Purpose: Due to the limited number of projections at each phase, the image quality of a four-dimensional cone-beam CT (4D-CBCT) is often degraded, which decreases the accuracy of subsequent motion modeling. One of the promising methods is the simultaneous motion estimation and image reconstruction (SMEIR) approach. The objective of this work is to enhance the computational speed of the SMEIR algorithm using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step is to generate the tetrahedral mesh based on the features of a reference phase 4D-CBCT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. After the mesh generation, the updated motion model and other phases of 4D-CBCT can be obtained by matching the 4D-CBCT projection images at each phase with the corresponding forward projections of the deformed reference phase of 4D-CBCT. The entire process of this 4D-CBCT reconstruction method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its tremendous parallel computing ability. Results: A 4D XCAT digital phantom was used to test the proposed mesh-based image reconstruction algorithm. The image Result shows both bone structures and inside of the lung are well-preserved and the tumor position can be well captured. Compared to the previous voxel-based CPU implementation of SMEIR, the proposed method is about 157 times faster for reconstructing a 10 -phase 4D-CBCT with dimension 256×256×150. Conclusion: The GPU-based parallel 4D CBCT reconstruction method uses the feature-based mesh for estimating motion model and demonstrates equivalent image Result with previous voxel-based SMEIR approach, with significantly improved computational speed.
ERIC Educational Resources Information Center
Debevc, Matjaž; Stjepanovic, Zoran; Holzinger, Andreas
2014-01-01
Web-based and adapted e-learning materials provide alternative methods of learning to those used in a traditional classroom. Within the study described in this article, deaf and hard of hearing people used an adaptive e-learning environment to improve their computer literacy. This environment included streaming video with sign language interpreter…
NASA Astrophysics Data System (ADS)
Pantano, Carlos
2005-11-01
We describe a hybrid finite difference method for large-eddy simulation (LES) of compressible flows with a low-numerical dissipation scheme and structured adaptive mesh refinement (SAMR). Numerical experiments and validation calculations are presented including a turbulent jet and the strongly shock-driven mixing of a Richtmyer-Meshkov instability. The approach is a conservative flux-based SAMR formulation and as such, it utilizes refinement to computational advantage. The numerical method for the resolved scale terms encompasses the cases of scheme alternation and internal mesh interfaces resulting from SAMR. An explicit centered scheme that is consistent with a skew-symmetric finite difference formulation is used in turbulent flow regions while a weighted essentially non-oscillatory (WENO) scheme is employed to capture shocks. The subgrid stresses and transports are calculated by means of the streched-vortex model, Misra & Pullin (1997)
NASA Astrophysics Data System (ADS)
Pantano, C.; Deiterding, R.; Hill, D. J.; Pullin, D. I.
2007-01-01
We present a methodology for the large-eddy simulation of compressible flows with a low-numerical dissipation scheme and structured adaptive mesh refinement (SAMR). A description of a conservative, flux-based hybrid numerical method that uses both centered finite-difference and a weighted essentially non-oscillatory (WENO) scheme is given, encompassing the cases of scheme alternation and internal mesh interfaces resulting from SAMR. In this method, the centered scheme is used in turbulent flow regions while WENO is employed to capture shocks. One-, two- and three-dimensional numerical experiments and example simulations are presented including homogeneous shock-free turbulence, a turbulent jet and the strongly shock-driven mixing of a Richtmyer-Meshkov instability.
NASA Astrophysics Data System (ADS)
Liu, Jiaqi; Han, Jing; Zhang, Yi; Bai, Lianfa
2015-10-01
Locally adaptive regression kernels model can describe the edge shape of images accurately and graphic trend of images integrally, but it did not consider images' color information while the color is an important element of an image. Therefore, we present a novel method of target recognition based on 3-D-color-space locally adaptive regression kernels model. Different from the general additional color information, this method directly calculate the local similarity features of 3-D data from the color image. The proposed method uses a few examples of an object as a query to detect generic objects with incompact, complex and changeable shapes. Our method involves three phases: First, calculating the novel color-space descriptors from the RGB color space of query image which measure the likeness of a voxel to its surroundings. Salient features which include spatial- dimensional and color -dimensional information are extracted from said descriptors, and simplifying them to construct a non-similar local structure feature set of the object class by principal components analysis (PCA). Second, we compare the salient features with analogous features from the target image. This comparison is done using a matrix generalization of the cosine similarity measure. Then the similar structures in the target image are obtained using local similarity structure statistical matching. Finally, we use the method of non-maxima suppression in the similarity image to extract the object position and mark the object in the test image. Experimental results demonstrate that our approach is effective and accurate in improving the ability to identify targets.
Milne, R.B.
1995-12-01
This thesis describes a new method for the numerical solution of partial differential equations of the parabolic type on an adaptively refined mesh in two or more spatial dimensions. The method is motivated and developed in the context of the level set formulation for the curvature dependent propagation of surfaces in three dimensions. In that setting, it realizes the multiple advantages of decreased computational effort, localized accuracy enhancement, and compatibility with problems containing a range of length scales.
NASA Astrophysics Data System (ADS)
Ding, Nenggen; Taheri, Saied
2010-10-01
In this article, an adaptive integrated control algorithm based on active front steering and direct yaw moment control using direct Lyapunov method is proposed. Variation of cornering stiffness is considered through adaptation laws in the algorithm to ensure robustness of the integrated controller. A simple two degrees of freedom (DOF) vehicle model is used to develop the control algorithm. To evaluate the control algorithm developed here, a nonlinear eight-DOF vehicle model along with a combined-slip tyre model and a single-point preview driver model are used. Control commands are executed through correction steering angle on front wheels and braking torque applied on one of the four wheels. Simulation of a double lane change manoeuvre using Matlab®/Simulink is used for evaluation of the control algorithm. Simulation results show that the integrated control algorithm can significantly enhance vehicle stability during emergency evasive manoeuvres on various road conditions ranging from dry asphalt to very slippery packed snow road surfaces.
Adaptive Finite Element Methods in Geodynamics
NASA Astrophysics Data System (ADS)
Davies, R.; Davies, H.; Hassan, O.; Morgan, K.; Nithiarasu, P.
2006-12-01
Adaptive finite element methods are presented for improving the quality of solutions to two-dimensional (2D) and three-dimensional (3D) convection dominated problems in geodynamics. The methods demonstrate the application of existing technology in the engineering community to problems within the `solid' Earth sciences. Two-Dimensional `Adaptive Remeshing': The `remeshing' strategy introduced in 2D adapts the mesh automatically around regions of high solution gradient, yielding enhanced resolution of the associated flow features. The approach requires the coupling of an automatic mesh generator, a finite element flow solver and an error estimator. In this study, the procedure is implemented in conjunction with the well-known geodynamical finite element code `ConMan'. An unstructured quadrilateral mesh generator is utilised, with mesh adaptation accomplished through regeneration. This regeneration employs information provided by an interpolation based local error estimator, obtained from the computed solution on an existing mesh. The technique is validated by solving thermal and thermo-chemical problems with known benchmark solutions. In a purely thermal context, results illustrate that the method is highly successful, improving solution accuracy whilst increasing computational efficiency. For thermo-chemical simulations the same conclusions can be drawn. However, results also demonstrate that the grid based methods employed for simulating the compositional field are not competitive with the other methods (tracer particle and marker chain) currently employed in this field, even at the higher spatial resolutions allowed by the adaptive grid strategies. Three-Dimensional Adaptive Multigrid: We extend the ideas from our 2D work into the 3D realm in the context of a pre-existing 3D-spherical mantle dynamics code, `TERRA'. In its original format, `TERRA' is computationally highly efficient since it employs a multigrid solver that depends upon a grid utilizing a clever
NASA Technical Reports Server (NTRS)
Militello, Carmelo; Felippa, Carlos A.
1992-01-01
The formulation and application of element-level error indicators based on parametrized variational principles are investigated. These indicators are ideally suited to drive adaptive mesh refinment on parallel computers where access to neighboring elements resident on different processors may incur significant computational overhead. Furthermore, such estimators are not affected by physical jumps at wavefronts or interfaces. An estimator derived from the higher-order element energy is applied to r adaptation of meshes in plates and shell structures where the exact solution is known.
NASA Astrophysics Data System (ADS)
Ye, Xianzhi; Jing, Lei; Kansen, Mizuo; Wang, Junbo; Ota, Kaoru; Cheng, Zixue
With the progress of ubiquitous technology, ubiquitous learning presents new opportunities to learners. Situations of a learner can be grasped through analyzing the learner's actions collected by sensors, RF-IDs, or cameras in order to provide support at proper time, proper place, and proper situation. Training for acquiring skills and enhancing physical abilities through exercise and experience in the real world is an important domain in u-learning. A training program may last for several days and has one or more training units (exercises) for a day. A learner's performance in a unit is considered as short term state. The performance in a series of units may change with patterns: progress, plateau, and decline. Long term state in a series of units is accumulatively computed based on short term states. In a learning/training program, it is necessary to apply different support strategies to adapt to different states of the learner. Adaptation in learning support is significant, because a learner loses his/her interests easily without adaptation. Systems with the adaptive support usually provide stimulators to a learner, and a learner can have a great motivation in learning at beginning. However, when the stimulators reach some levels, the learner may lose his/her motivation, because the long term state of the learner changes dynamically, which means a progress state may change to a plateau state or a decline state. In different long term learning states, different types of stimulators are needed. However, the stimulators and advice provided by the existing systems are monotonic without changeable support strategies. We propose a mutual adaptive support. The mutual adaptation means each of the system and the learner has their own states. On one hand, the system tries to change its state to adapt to the learner's state for providing adaptive support. On the other hand, the learner can change its performance following the advice given based on the state of the system
Domain adaptive boosting method and its applications
NASA Astrophysics Data System (ADS)
Geng, Jie; Miao, Zhenjiang
2015-03-01
Differences of data distributions widely exist among datasets, i.e., domains. For many pattern recognition, nature language processing, and content-based analysis systems, a decrease in performance caused by the domain differences between the training and testing datasets is still a notable problem. We propose a domain adaptation method called domain adaptive boosting (DAB). It is based on the AdaBoost approach with extensions to cover the domain differences between the source and target domains. Two main stages are contained in this approach: source-domain clustering and source-domain sample selection. By iteratively adding the selected training samples from the source domain, the discrimination model is able to achieve better domain adaptation performance based on a small validation set. The DAB algorithm is suitable for the domains with large scale samples and easy to extend for multisource adaptation. We implement this method on three computer vision systems: the skin detection model in single images, the video concept detection model, and the object classification model. In the experiments, we compare the performances of several commonly used methods and the proposed DAB. Under most situations, the DAB is superior.
NASA Astrophysics Data System (ADS)
Chen, Peng; Quarteroni, Alfio
2015-10-01
In this work we develop an adaptive and reduced computational algorithm based on dimension-adaptive sparse grid approximation and reduced basis methods for solving high-dimensional uncertainty quantification (UQ) problems. In order to tackle the computational challenge of "curse of dimensionality" commonly faced by these problems, we employ a dimension-adaptive tensor-product algorithm [16] and propose a verified version to enable effective removal of the stagnation phenomenon besides automatically detecting the importance and interaction of different dimensions. To reduce the heavy computational cost of UQ problems modelled by partial differential equations (PDE), we adopt a weighted reduced basis method [7] and develop an adaptive greedy algorithm in combination with the previous verified algorithm for efficient construction of an accurate reduced basis approximation. The efficiency and accuracy of the proposed algorithm are demonstrated by several numerical experiments.
Structured adaptive grid generation using algebraic methods
NASA Technical Reports Server (NTRS)
Yang, Jiann-Cherng; Soni, Bharat K.; Roger, R. P.; Chan, Stephen C.
1993-01-01
The accuracy of the numerical algorithm depends not only on the formal order of approximation but also on the distribution of grid points in the computational domain. Grid adaptation is a procedure which allows optimal grid redistribution as the solution progresses. It offers the prospect of accurate flow field simulations without the use of an excessively timely, computationally expensive, grid. Grid adaptive schemes are divided into two basic categories: differential and algebraic. The differential method is based on a variational approach where a function which contains a measure of grid smoothness, orthogonality and volume variation is minimized by using a variational principle. This approach provided a solid mathematical basis for the adaptive method, but the Euler-Lagrange equations must be solved in addition to the original governing equations. On the other hand, the algebraic method requires much less computational effort, but the grid may not be smooth. The algebraic techniques are based on devising an algorithm where the grid movement is governed by estimates of the local error in the numerical solution. This is achieved by requiring the points in the large error regions to attract other points and points in the low error region to repel other points. The development of a fast, efficient, and robust algebraic adaptive algorithm for structured flow simulation applications is presented. This development is accomplished in a three step process. The first step is to define an adaptive weighting mesh (distribution mesh) on the basis of the equidistribution law applied to the flow field solution. The second, and probably the most crucial step, is to redistribute grid points in the computational domain according to the aforementioned weighting mesh. The third and the last step is to reevaluate the flow property by an appropriate search/interpolate scheme at the new grid locations. The adaptive weighting mesh provides the information on the desired concentration
NASA Astrophysics Data System (ADS)
Wang, Chuanyun; Qin, Shiyin
2015-03-01
Motivated by the robust principal component analysis, infrared small target image is regarded as low-rank background matrix corrupted by sparse target and noise matrices, thus a new target-background separation model is designed, subsequently, an adaptive detection method of infrared small target is presented. Firstly, multi-scale transform and patch transform are used to generate an image patch set for infrared small target detection; secondly, target-background separation of each patch is achieved by recovering the low-rank and sparse matrices using adaptive weighting parameter; thirdly, the image reconstruction and fusion are carried out to obtain the entire separated background and target images; finally, the infrared small target detection is realized by threshold segmentation of template matching similarity measurement. In order to validate the performance of the proposed method, three experiments: target-background separation, background clutter suppression and infrared small target detection, are performed over different clutter background with real infrared small targets in single-frame or sequence images. A series of experiment results demonstrate that the proposed method can not only suppress background clutter effectively even if with strong noise interference but also detect targets accurately with low false alarm rate.
Parallel adaptive wavelet collocation method for PDEs
Nejadmalayeri, Alireza; Vezolainen, Alexei; Brown-Dymkoski, Eric; Vasilyev, Oleg V.
2015-10-01
A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allows fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 2048{sup 3} using as many as 2048 CPU cores.
Dowling, Jason A.; Lambert, Jonathan; Parker, Joel; Salvado, Olivier; Fripp, Jurgen; Capp, Anne; Wratten, Chris; Denham, James W.; Greer, Peter B.
2012-05-01
Purpose: Prostate radiation therapy dose planning directly on magnetic resonance imaging (MRI) scans would reduce costs and uncertainties due to multimodality image registration. Adaptive planning using a combined MRI-linear accelerator approach will also require dose calculations to be performed using MRI data. The aim of this work was to develop an atlas-based method to map realistic electron densities to MRI scans for dose calculations and digitally reconstructed radiograph (DRR) generation. Methods and Materials: Whole-pelvis MRI and CT scan data were collected from 39 prostate patients. Scans from 2 patients showed significantly different anatomy from that of the remaining patient population, and these patients were excluded. A whole-pelvis MRI atlas was generated based on the manually delineated MRI scans. In addition, a conjugate electron-density atlas was generated from the coregistered computed tomography (CT)-MRI scans. Pseudo-CT scans for each patient were automatically generated by global and nonrigid registration of the MRI atlas to the patient MRI scan, followed by application of the same transformations to the electron-density atlas. Comparisons were made between organ segmentations by using the Dice similarity coefficient (DSC) and point dose calculations for 26 patients on planning CT and pseudo-CT scans. Results: The agreement between pseudo-CT and planning CT was quantified by differences in the point dose at isocenter and distance to agreement in corresponding voxels. Dose differences were found to be less than 2%. Chi-squared values indicated that the planning CT and pseudo-CT dose distributions were equivalent. No significant differences (p > 0.9) were found between CT and pseudo-CT Hounsfield units for organs of interest. Mean {+-} standard deviation DSC scores for the atlas-based segmentation of the pelvic bones were 0.79 {+-} 0.12, 0.70 {+-} 0.14 for the prostate, 0.64 {+-} 0.16 for the bladder, and 0.63 {+-} 0.16 for the rectum
An adaptive selective frequency damping method
NASA Astrophysics Data System (ADS)
Jordi, Bastien; Cotter, Colin; Sherwin, Spencer
2015-03-01
The selective frequency damping (SFD) method is used to obtain unstable steady-state solutions of dynamical systems. The stability of this method is governed by two parameters that are the control coefficient and the filter width. Convergence is not guaranteed for arbitrary choice of these parameters. Even when the method does converge, the time necessary to reach a steady-state solution may be very long. We present an adaptive SFD method. We show that by modifying the control coefficient and the filter width all along the solver execution, we can reach an optimum convergence rate. This method is based on successive approximations of the dominant eigenvalue of the flow studied. We design a one-dimensional model to select SFD parameters that enable us to control the evolution of the least stable eigenvalue of the system. These parameters are then used for the application of the SFD method to the multi-dimensional flow problem. We apply this adaptive method to a set of classical test cases of computational fluid dynamics and show that the steady-state solutions obtained are similar to what can be found in the literature. Then we apply it to a specific vortex dominated flow (of interest for the automotive industry) whose stability had never been studied before. Seventh Framework Programme of the European Commission - ANADE project under Grant Contract PITN-GA-289428.
NASA Astrophysics Data System (ADS)
Pantano, C.; Deiterding, R.; Hill, D. J.; Pullin, D. I.
2006-09-01
This paper describes a hybrid finite-difference method for the large-eddy simulation of compressible flows with low-numerical dissipation and structured adaptive mesh refinement (SAMR). A conservative flux-based approach is described with an explicit centered scheme used in turbulent flow regions while a weighted essentially non-oscillatory (WENO) scheme is employed to capture shocks. Three-dimensional numerical simulations of a Richtmyer-Meshkov instability are presented.
Avci, Derya; Leblebicioglu, Mehmet Kemal; Poyraz, Mustafa; Dogantekin, Esin
2014-02-01
So far, analysis and classification of urine cells number has become an important topic for medical diagnosis of some diseases. Therefore, in this study, we suggest a new technique based on Adaptive Discrete Wavelet Entropy Energy and Neural Network Classifier (ADWEENN) for Recognition of Urine Cells from Microscopic Images Independent of Rotation and Scaling. Some digital image processing methods such as noise reduction, contrast enhancement, segmentation, and morphological process are used for feature extraction stage of this ADWEENN in this study. Nowadays, the image processing and pattern recognition topics have come into prominence. The image processing concludes operation and design of systems that recognize patterns in data sets. In the past years, very difficulty in classification of microscopic images was the deficiency of enough methods to characterize. Lately, it is seen that, multi-resolution image analysis methods such as Gabor filters, discrete wavelet decompositions are superior to other classic methods for analysis of these microscopic images. In this study, the structure of the ADWEENN method composes of four stages. These are preprocessing stage, feature extraction stage, classification stage and testing stage. The Discrete Wavelet Transform (DWT) and adaptive wavelet entropy and energy is used for adaptive feature extraction in feature extraction stage to strengthen the premium features of the Artificial Neural Network (ANN) classifier in this study. Efficiency of the developed ADWEENN method was tested showing that an avarage of 97.58% recognition succes was obtained. PMID:24493072
Lei, Xusheng; Zou, Ying; Dong, Fei
2015-11-01
Due to the nonlinearity and time variation of a two-axis inertially stabilized platform (ISP) system, the conventional feedback control cannot be utilized directly. To realize the control performance with fast dynamic response and high stabilization precision, the dynamic model of the ISP system is expected to match the ideal model which satisfies the desired control performance. Therefore, a composite control method based on the adaptive radial basis function neural network (RBFNN) feedback control and the extended state observer (ESO), is proposed for ISP. The adaptive RBFNN is proposed to generate the feedback control parameters online. Based on the state error information in the working process, the adaptive RBFNN can be constructed and optimized directly. Therefore, no priori training data is needed for the construction of the RBFNN. Furthermore, a linear second-order ESO is constructed to compensate for the composite disturbance. The asymptotic stability of the proposed control method has been proven by the Lyapunov stability theory. The applicability of the proposed method is validated by a series of simulations and flight tests. PMID:26434418
Perceptually-Based Adaptive JPEG Coding
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Rosenholtz, Ruth; Null, Cynthia H. (Technical Monitor)
1996-01-01
An extension to the JPEG standard (ISO/IEC DIS 10918-3) allows spatial adaptive coding of still images. As with baseline JPEG coding, one quantization matrix applies to an entire image channel, but in addition the user may specify a multiplier for each 8 x 8 block, which multiplies the quantization matrix, yielding the new matrix for the block. MPEG 1 and 2 use much the same scheme, except there the multiplier changes only on macroblock boundaries. We propose a method for perceptual optimization of the set of multipliers. We compute the perceptual error for each block based upon DCT quantization error adjusted according to contrast sensitivity, light adaptation, and contrast masking, and pick the set of multipliers which yield maximally flat perceptual error over the blocks of the image. We investigate the bitrate savings due to this adaptive coding scheme and the relative importance of the different sorts of masking on adaptive coding.
Burattini, Laura; Zareba, Wojciech; Burattini, Roberto
2008-09-01
To develop a new method for non-invasive identification of patients prone to ventricular tachyarrhythmia and sudden cardiac death, an adaptive match-filter (AMF) was applied to detect and characterize T-wave alternans (TWA) in 200 coronary artery diseased (CAD) patients compared with 176 healthy (H) subjects. TWA was characterized in terms of duration (TWAD), amplitude (TWAA), and magnitude (TWAM, defined as the product of TWAD times TWAA). A criterion derived from these parameters, estimated over the H-population, allowed discrimination between a risk (TWA+) and a normality (NO TWA) zone in the TWAD-TWAA plane. To gain further ability to discriminate among different risk levels, the TWA+ zone was divided into four sub-zones respectively characterized by low duration and low amplitude (LDLA), low duration and high amplitude (LDHA), high duration and low amplitude (HDLA), and high duration and high amplitude (HDHA). With our methodology, 21 CAD-patients (10.5%) were identified as TWA+, 9 falling in the LDLA zone, 4 in the HDLA, 7 in the LDHA, and 1 in the HDHA. These results are in agreement with clinical expectations and pave the way to further clinical follow-up studies finalized to analyze pathophysiological implications and risk factors associated to each TWA+ zone. PMID:18618261
A new orientation-adaptive interpolation method.
Wang, Qing; Ward, Rabab Kreidieh
2007-04-01
We propose an isophote-oriented, orientation-adaptive interpolation method. The proposed method employs an interpolation kernel that adapts to the local orientation of isophotes, and the pixel values are obtained through an oriented, bilinear interpolation. We show that, by doing so, the curvature of the interpolated isophotes is reduced, and, thus, zigzagging artifacts are largely suppressed. Analysis and experiments show that images interpolated using the proposed method are visually pleasing and almost artifact free. PMID:17405424
Ensemble transform sensitivity method for adaptive observations
NASA Astrophysics Data System (ADS)
Zhang, Yu; Xie, Yuanfu; Wang, Hongli; Chen, Dehui; Toth, Zoltan
2016-01-01
The Ensemble Transform (ET) method has been shown to be useful in providing guidance for adaptive observation deployment. It predicts forecast error variance reduction for each possible deployment using its corresponding transformation matrix in an ensemble subspace. In this paper, a new ET-based sensitivity (ETS) method, which calculates the gradient of forecast error variance reduction in terms of analysis error variance reduction, is proposed to specify regions for possible adaptive observations. ETS is a first order approximation of the ET; it requires just one calculation of a transformation matrix, increasing computational efficiency (60%-80% reduction in computational cost). An explicit mathematical formulation of the ETS gradient is derived and described. Both the ET and ETS methods are applied to the Hurricane Irene (2011) case and a heavy rainfall case for comparison. The numerical results imply that the sensitive areas estimated by the ETS and ET are similar. However, ETS is much more efficient, particularly when the resolution is higher and the number of ensemble members is larger.
The Method of Adaptive Comparative Judgement
ERIC Educational Resources Information Center
Pollitt, Alastair
2012-01-01
Adaptive Comparative Judgement (ACJ) is a modification of Thurstone's method of comparative judgement that exploits the power of adaptivity, but in scoring rather than testing. Professional judgement by teachers replaces the marking of tests; a judge is asked to compare the work of two students and simply to decide which of them is the better.…
Adaptive characterization method for desktop color printers
NASA Astrophysics Data System (ADS)
Shen, Hui-Liang; Zheng, Zhi-Huan; Jin, Chong-Chao; Du, Xin; Shao, Si-Jie; Xin, John H.
2013-04-01
With the rapid development of multispectral imaging technique, it is desired that the spectral color can be accurately reproduced using desktop color printers. However, due to the specific spectral gamuts determined by printer inks, it is almost impossible to exactly replicate the reflectance spectra in other media. In addition, as ink densities can not be individually controlled, desktop printers can only be regarded as red-green-blue devices, making physical models unfeasible. We propose a locally adaptive method, which consists of both forward and inverse models, for desktop printer characterization. In the forward model, we establish the adaptive transform between control values and reflectance spectrum on individual cellular subsets by using weighted polynomial regression. In the inverse model, we first determine the candidate space of the control values based on global inverse regression and then compute the optimal control values by minimizing the color difference between the actual spectrum and the predicted spectrum via forward transform. Experimental results show that the proposed method can reproduce colors accurately for different media under multiple illuminants.
Variational method for adaptive grid generation
Brackbill, J.U.
1983-01-01
A variational method for generating adaptive meshes is described. Functionals measuring smoothness, skewness, orientation, and the Jacobian are minimized to generate a mapping from a rectilinear domain in natural coordinate to an arbitrary domain in physical coordinates. From the mapping, a mesh is easily constructed. In using the method to adaptively zone computational problems, as few as one third the number of mesh points are required in each coordinate direction compared with a uniformly zoned mesh.
Online Adaptive Replanning Method for Prostate Radiotherapy
Ahunbay, Ergun E.; Peng Cheng; Holmes, Shannon; Godley, Andrew; Lawton, Colleen; Li, X. Allen
2010-08-01
Purpose: To report the application of an adaptive replanning technique for prostate cancer radiotherapy (RT), consisting of two steps: (1) segment aperture morphing (SAM), and (2) segment weight optimization (SWO), to account for interfraction variations. Methods and Materials: The new 'SAM+SWO' scheme was retroactively applied to the daily CT images acquired for 10 prostate cancer patients on a linear accelerator and CT-on-Rails combination during the course of RT. Doses generated by the SAM+SWO scheme based on the daily CT images were compared with doses generated after patient repositioning using the current planning target volume (PTV) margin (5 mm, 3 mm toward rectum) and a reduced margin (2 mm), along with full reoptimization scans based on the daily CT images to evaluate dosimetry benefits. Results: For all cases studied, the online replanning method provided significantly better target coverage when compared with repositioning with reduced PTV (13% increase in minimum prostate dose) and improved organ sparing when compared with repositioning with regular PTV (13% decrease in the generalized equivalent uniform dose of rectum). The time required to complete the online replanning process was 6 {+-} 2 minutes. Conclusion: The proposed online replanning method can be used to account for interfraction variations for prostate RT with a practically acceptable time frame (5-10 min) and with significant dosimetric benefits. On the basis of this study, the developed online replanning scheme is being implemented in the clinic for prostate RT.
Adaptive control of a Stewart platform-based manipulator
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.
1993-01-01
A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
NASA Astrophysics Data System (ADS)
Lee, Michael S.; Olson, Mark A.
2011-06-01
Temperature-based replica exchange (T-ReX) enhances sampling of molecular dynamics simulations by autonomously heating and cooling simulation clients via a Metropolis exchange criterion. A pathological case for T-ReX can occur when a change in state (e.g., folding to unfolding of a protein) has a large energetic difference over a short temperature interval leading to insufficient exchanges amongst replica clients near the transition temperature. One solution is to allow the temperature set to dynamically adapt in the temperature space, thereby enriching the population of clients near the transition temperature. In this work, we evaluated two approaches for adapting the temperature set: a method that equalizes exchange rates over all neighbor temperature pairs and a method that attempts to induce clients to visit all temperatures (dubbed "current maximization") by positioning many clients at or near the transition temperature. As a test case, we simulated the 57-residue SH3 domain of alpha-spectrin. Exchange rate equalization yielded the same unfolding-folding transition temperature as fixed-temperature ReX with much smoother convergence of this value. Surprisingly, the current maximization method yielded a significantly lower transition temperature, in close agreement with experimental observation, likely due to more extensive sampling of the transition state.
Adaptive learning based heartbeat classification.
Srinivas, M; Basil, Tony; Mohan, C Krishna
2015-01-01
Cardiovascular diseases (CVD) are a leading cause of unnecessary hospital admissions as well as fatalities placing an immense burden on the healthcare industry. A process to provide timely intervention can reduce the morbidity rate as well as control rising costs. Patients with cardiovascular diseases require quick intervention. Towards that end, automated detection of abnormal heartbeats captured by electronic cardiogram (ECG) signals is vital. While cardiologists can identify different heartbeat morphologies quite accurately among different patients, the manual evaluation is tedious and time consuming. In this chapter, we propose new features from the time and frequency domains and furthermore, feature normalization techniques to reduce inter-patient and intra-patient variations in heartbeat cycles. Our results using the adaptive learning based classifier emulate those reported in existing literature and in most cases deliver improved performance, while eliminating the need for labeling of signals by domain experts. PMID:26484555
A New Adaptive Image Denoising Method
NASA Astrophysics Data System (ADS)
Biswas, Mantosh; Om, Hari
2016-03-01
In this paper, a new adaptive image denoising method is proposed that follows the soft-thresholding technique. In our method, a new threshold function is also proposed, which is determined by taking the various combinations of noise level, noise-free signal variance, subband size, and decomposition level. It is simple and adaptive as it depends on the data-driven parameters estimation in each subband. The state-of-the-art denoising methods viz. VisuShrink, SureShrink, BayesShrink, WIDNTF and IDTVWT are not able to modify the coefficients in an efficient manner to provide the good quality of image. Our method removes the noise from the noisy image significantly and provides better visual quality of an image.
Adaptive multiscale method for two-dimensional nanoscale adhesive contacts
NASA Astrophysics Data System (ADS)
Tong, Ruiting; Liu, Geng; Liu, Lan; Wu, Liyan
2013-05-01
There are two separate traditional approaches to model contact problems: continuum and atomistic theory. Continuum theory is successfully used in many domains, but when the scale of the model comes to nanometer, continuum approximation meets challenges. Atomistic theory can catch the detailed behaviors of an individual atom by using molecular dynamics (MD) or quantum mechanics, although accurately, it is usually time-consuming. A multiscale method coupled MD and finite element (FE) is presented. To mesh the FE region automatically, an adaptive method based on the strain energy gradient is introduced to the multiscale method to constitute an adaptive multiscale method. Utilizing the proposed method, adhesive contacts between a rigid cylinder and an elastic substrate are studied, and the results are compared with full MD simulations. The process of FE meshes refinement shows that adaptive multiscale method can make FE mesh generation more flexible. Comparison of the displacements of boundary atoms in the overlap region with the results from full MD simulations indicates that adaptive multiscale method can transfer displacements effectively. Displacements of atoms and FE nodes on the center line of the multiscale model agree well with that of atoms in full MD simulations, which shows the continuity in the overlap region. Furthermore, the Von Mises stress contours and contact force distributions in the contact region are almost same as full MD simulations. The method presented combines multiscale method and adaptive technique, and can provide a more effective way to multiscale method and to the investigation on nanoscale contact problems.
NASA Astrophysics Data System (ADS)
Cockburn, Bernardo; Kao, Chiu-Yen; Reitich, Fernando
2014-02-01
We present an adaptive spectral/discontinuous Galerkin (DG) method on curved elements to simulate high-frequency wavefronts within a reduced phase-space formulation of geometrical optics. Following recent work, the approach is based on the use of level sets defined by functions satisfying the Liouville equations in reduced phase-space and, in particular, it relies on the smoothness of these functions to represent them by rapidly convergent spectral expansions in the phase variables. The resulting (hyperbolic) system of equations for the coefficients in these expansions are then amenable to a high-order accurate treatment via DG approximations. In the present work, we significantly expand on the applicability and efficiency of the approach by incorporating mechanisms that allow for its use in scattering simulations and for a reduced overall computational cost. With regards to the former we demonstrate that the incorporation of curved elements is necessary to attain any kind of accuracy in calculations that involve scattering off non-flat interfaces. With regards to efficiency, on the other hand, we also show that the level-set formulation allows for a space p-adaptive scheme that under-resolves the level-set functions away from the wavefront without incurring in a loss of accuracy in the approximation of its location. As we show, these improvements enable simulations that are beyond the capabilities of previous implementations of these numerical procedures.
NASA Astrophysics Data System (ADS)
Wang, Chongchong; Wang, Yukun; Hu, Lifa; Wang, Shaoxin; Cao, Zhaoliang; Mu, Quanquan; Li, Dayu; Yang, Chengliang; Xuan, Li
2016-05-01
The intrinsic hysteresis nonlinearity of the piezo-actuators can severely degrade the positioning accuracy of a tip-tilt mirror (TTM) in an adaptive optics system. This paper focuses on compensating this hysteresis nonlinearity by feed-forward linearization with an inverse hysteresis model. This inverse hysteresis model is based on the classical Presiach model, and the neural network (NN) is used to describe the hysteresis loop. In order to apply it in the real-time adaptive correction, an analytical nonlinear function derived from the NN is introduced to compute the inverse hysteresis model output instead of the time-consuming NN simulation process. Experimental results show that the proposed method effectively linearized the TTM behavior with the static hysteresis nonlinearity of TTM reducing from 15.6% to 1.4%. In addition, the tip-tilt tracking experiments using the integrator with and without hysteresis compensation are conducted. The wavefront tip-tilt aberration rejection ability of the TTM control system is significantly improved with the -3 dB error rejection bandwidth increasing from 46 to 62 Hz.
NASA Astrophysics Data System (ADS)
Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming
2013-03-01
The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.
Adaptive control of space based robot manipulators
NASA Technical Reports Server (NTRS)
Walker, Michael W.; Wee, Liang-Boon
1991-01-01
For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.
Jackowski, Konrad; Krawczyk, Bartosz; Woźniak, Michał
2014-05-01
Currently, methods of combined classification are the focus of intense research. A properly designed group of combined classifiers exploiting knowledge gathered in a pool of elementary classifiers can successfully outperform a single classifier. There are two essential issues to consider when creating combined classifiers: how to establish the most comprehensive pool and how to design a fusion model that allows for taking full advantage of the collected knowledge. In this work, we address the issues and propose an AdaSS+, training algorithm dedicated for the compound classifier system that effectively exploits local specialization of the elementary classifiers. An effective training procedure consists of two phases. The first phase detects the classifier competencies and adjusts the respective fusion parameters. The second phase boosts classification accuracy by elevating the degree of local specialization. The quality of the proposed algorithms are evaluated on the basis of a wide range of computer experiments that show that AdaSS+ can outperform the original method and several reference classifiers. PMID:24552506
Adaptive Finite Element Methods for Continuum Damage Modeling
NASA Technical Reports Server (NTRS)
Min, J. B.; Tworzydlo, W. W.; Xiques, K. E.
1995-01-01
The paper presents an application of adaptive finite element methods to the modeling of low-cycle continuum damage and life prediction of high-temperature components. The major objective is to provide automated and accurate modeling of damaged zones through adaptive mesh refinement and adaptive time-stepping methods. The damage modeling methodology is implemented in an usual way by embedding damage evolution in the transient nonlinear solution of elasto-viscoplastic deformation problems. This nonlinear boundary-value problem is discretized by adaptive finite element methods. The automated h-adaptive mesh refinements are driven by error indicators, based on selected principal variables in the problem (stresses, non-elastic strains, damage, etc.). In the time domain, adaptive time-stepping is used, combined with a predictor-corrector time marching algorithm. The time selection is controlled by required time accuracy. In order to take into account strong temperature dependency of material parameters, the nonlinear structural solution a coupled with thermal analyses (one-way coupling). Several test examples illustrate the importance and benefits of adaptive mesh refinements in accurate prediction of damage levels and failure time.
NASA Astrophysics Data System (ADS)
Valdivia, Valeska; Hennebelle, Patrick
2014-11-01
Context. Ultraviolet radiation plays a crucial role in molecular clouds. Radiation and matter are tightly coupled and their interplay influences the physical and chemical properties of gas. In particular, modeling the radiation propagation requires calculating column densities, which can be numerically expensive in high-resolution multidimensional simulations. Aims: Developing fast methods for estimating column densities is mandatory if we are interested in the dynamical influence of the radiative transfer. In particular, we focus on the effect of the UV screening on the dynamics and on the statistical properties of molecular clouds. Methods: We have developed a tree-based method for a fast estimate of column densities, implemented in the adaptive mesh refinement code RAMSES. We performed numerical simulations using this method in order to analyze the influence of the screening on the clump formation. Results: We find that the accuracy for the extinction of the tree-based method is better than 10%, while the relative error for the column density can be much more. We describe the implementation of a method based on precalculating the geometrical terms that noticeably reduces the calculation time. To study the influence of the screening on the statistical properties of molecular clouds we present the probability distribution function of gas and the associated temperature per density bin and the mass spectra for different density thresholds. Conclusions: The tree-based method is fast and accurate enough to be used during numerical simulations since no communication is needed between CPUs when using a fully threaded tree. It is then suitable to parallel computing. We show that the screening for far UV radiation mainly affects the dense gas, thereby favoring low temperatures and affecting the fragmentation. We show that when we include the screening, more structures are formed with higher densities in comparison to the case that does not include this effect. We
Scaled norm-based Euclidean projection for sparse speaker adaptation
NASA Astrophysics Data System (ADS)
Kim, Younggwan; Kim, Myung Jong; Kim, Hoirin
2015-12-01
To reduce data storage for speaker adaptive (SA) models, in our previous work, we proposed a sparse speaker adaptation method which can efficiently reduce the number of adapted parameters by using Euclidean projection onto the L 1-ball (EPL1) while maintaining recognition performance comparable to maximum a posteriori (MAP) adaptation. In the EPL1-based sparse speaker adaptation framework, however, the adapted Gaussian mean vectors are mostly concentrated on dimensions having large variances because of assuming unit variance for all dimensions. To make EPL1 more flexible, in this paper, we propose scaled norm-based Euclidean projection (SNEP) which can consider dimension-specific variances. By using SNEP, we also propose a new sparse speaker adaptation method which can consider the variances of a speaker-independent model. Our experiments show that the adapted components of mean vectors are evenly distributed in all dimensions, and we can obtain sparsely adapted models with no loss of phone recognition performance from the proposed method compared with MAP adaptation.
Method and system for environmentally adaptive fault tolerant computing
NASA Technical Reports Server (NTRS)
Copenhaver, Jason L. (Inventor); Jeremy, Ramos (Inventor); Wolfe, Jeffrey M. (Inventor); Brenner, Dean (Inventor)
2010-01-01
A method and system for adapting fault tolerant computing. The method includes the steps of measuring an environmental condition representative of an environment. An on-board processing system's sensitivity to the measured environmental condition is measured. It is determined whether to reconfigure a fault tolerance of the on-board processing system based in part on the measured environmental condition. The fault tolerance of the on-board processing system may be reconfigured based in part on the measured environmental condition.
Adaptive multiscale model reduction with Generalized Multiscale Finite Element Methods
NASA Astrophysics Data System (ADS)
Chung, Eric; Efendiev, Yalchin; Hou, Thomas Y.
2016-09-01
In this paper, we discuss a general multiscale model reduction framework based on multiscale finite element methods. We give a brief overview of related multiscale methods. Due to page limitations, the overview focuses on a few related methods and is not intended to be comprehensive. We present a general adaptive multiscale model reduction framework, the Generalized Multiscale Finite Element Method. Besides the method's basic outline, we discuss some important ingredients needed for the method's success. We also discuss several applications. The proposed method allows performing local model reduction in the presence of high contrast and no scale separation.
Ahmed, Awad A.; Egleston, Brian; Alcantara, Pino; Li, Linna; Pollack, Alan; Horwitz, Eric M.; Buyyounouski, Mark K.
2013-07-15
Background: There are no well-established normal tissue sparing dose–volume histogram (DVH) criteria that limit the risk of urinary toxicity from prostate radiation therapy (RT). The aim of this study was to determine which criteria predict late toxicity among various DVH parameters when contouring the entire solid bladder and its contents versus the bladder wall. The area under the histogram curve (AUHC) was also analyzed. Methods and Materials: From 1993 to 2000, 503 men with prostate cancer received 3-dimensional conformal RT (median follow-up time, 71 months). The whole bladder and the bladder wall were contoured in all patients. The primary endpoint was grade ≥2 genitourinary (GU) toxicity occurring ≥3 months after completion of RT. Cox regressions of time to grade ≥2 toxicity were estimated separately for the entire bladder and bladder wall. Concordance probability estimates (CPE) assessed model discriminative ability. Before training the models, an external random test group of 100 men was set aside for testing. Separate analyses were performed based on the mean age (≤ 68 vs >68 years). Results: Age, pretreatment urinary symptoms, mean dose (entire bladder and bladder wall), and AUHC (entire bladder and bladder wall) were significant (P<.05) in multivariable analysis. Overall, bladder wall CPE values were higher than solid bladder values. The AUHC for bladder wall provided the greatest discrimination for late bladder toxicity when compared with alternative DVH points, with CPE values of 0.68 for age ≤68 years and 0.81 for age >68 years. Conclusion: The AUHC method based on bladder wall volumes was superior for predicting late GU toxicity. Age >68 years was associated with late grade ≥2 GU toxicity, which suggests that risk-adapted dose constraints based on age should be explored.
Design of Pel Adaptive DPCM coding based upon image partition
NASA Astrophysics Data System (ADS)
Saitoh, T.; Harashima, H.; Miyakawa, H.
1982-01-01
A Pel Adaptive DPCM coding system based on image partition is developed which possesses coding characteristics superior to those of the Block Adaptive DPCM coding system. This method uses multiple DPCM coding loops and nonhierarchical cluster analysis. It is found that the coding performances of the Pel Adaptive DPCM coding method differ depending on the subject images. The Pel Adaptive DPCM designed using these methods is shown to yield a maximum performance advantage of 2.9 dB for the Girl and Couple images and 1.5 dB for the Aerial image, although no advantage was obtained for the moon image. These results show an improvement over the optimally designed Block Adaptive DPCM coding method proposed by Saito et al. (1981).
An Adaptive VOF Method on Unstructured Grid
NASA Astrophysics Data System (ADS)
Wu, L. L.; Huang, M.; Chen, B.
2011-09-01
In order to improve the accuracy of interface capturing and keeping the computational efficiency, an adaptive VOF method on unstructured grid is proposed in this paper. The volume fraction in each cell is regarded as the criterion to locally refine the interface cell. With the movement of interface, new interface cells (0 ≤ f ≤ 1) are subdivided into child cells, while those child cells that no longer contain interface will be merged back into the original parent cell. In order to avoid the complicated redistribution of volume fraction during the subdivision and amalgamation procedure, a predictor-corrector algorithm is proposed to implement the subdivision and amalgamation procedures only in empty or full cell ( f = 0 or 1). Thus volume fraction in the new cell can take the value from the original cell directly, and the interpolation of the interface is avoided. The advantage of this method is that the re-generation of the whole grid system is not necessary, so its implementation is very efficient. Moreover, an advection flow test of a hollow square was performed, and the relative shape error of the result obtained by adaptive mesh is smaller than those by non-refined grid, which verifies the validation of our method.
Adaptive wavelet collocation method simulations of Rayleigh-Taylor instability
NASA Astrophysics Data System (ADS)
Reckinger, S. J.; Livescu, D.; Vasilyev, O. V.
2010-12-01
Numerical simulations of single-mode, compressible Rayleigh-Taylor instability are performed using the adaptive wavelet collocation method (AWCM), which utilizes wavelets for dynamic grid adaptation. Due to the physics-based adaptivity and direct error control of the method, AWCM is ideal for resolving the wide range of scales present in the development of the instability. The problem is initialized consistent with the solutions from linear stability theory. Non-reflecting boundary conditions are applied to prevent the contamination of the instability growth by pressure waves created at the interface. AWCM is used to perform direct numerical simulations that match the early-time linear growth, the terminal bubble velocity and a reacceleration region.
Workshop on adaptive grid methods for fusion plasmas
Wiley, J.C.
1995-07-01
The author describes a general `hp` finite element method with adaptive grids. The code was based on the work of Oden, et al. The term `hp` refers to the method of spatial refinement (h), in conjunction with the order of polynomials used as a part of the finite element discretization (p). This finite element code seems to handle well the different mesh grid sizes occuring between abuted grids with different resolutions.
Solving Chemical Master Equations by an Adaptive Wavelet Method
Jahnke, Tobias; Galan, Steffen
2008-09-01
Solving chemical master equations is notoriously difficult due to the tremendous number of degrees of freedom. We present a new numerical method which efficiently reduces the size of the problem in an adaptive way. The method is based on a sparse wavelet representation and an algorithm which, in each time step, detects the essential degrees of freedom required to approximate the solution up to the desired accuracy.
ERIC Educational Resources Information Center
Melaragno, Ralph J.
The two-phase study compared two methods of adapting self-instructional materials to individual differences among learners. The methods were compared with each other and with a control condition involving only minimal adaptation. The first adaptation procedure was based on subjects' performances on a learning task in Phase I of the study; the…
Adaptive method with intercessory feedback control for an intelligent agent
Goldsmith, Steven Y.
2004-06-22
An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.
Gradient-based adaptation of continuous dynamic model structures
NASA Astrophysics Data System (ADS)
La Cava, William G.; Danai, Kourosh
2016-01-01
A gradient-based method of symbolic adaptation is introduced for a class of continuous dynamic models. The proposed model structure adaptation method starts with the first-principles model of the system and adapts its structure after adjusting its individual components in symbolic form. A key contribution of this work is its introduction of the model's parameter sensitivity as the measure of symbolic changes to the model. This measure, which is essential to defining the structural sensitivity of the model, not only accommodates algebraic evaluation of candidate models in lieu of more computationally expensive simulation-based evaluation, but also makes possible the implementation of gradient-based optimisation in symbolic adaptation. The proposed method is applied to models of several virtual and real-world systems that demonstrate its potential utility.
Adaptive Accommodation Control Method for Complex Assembly
NASA Astrophysics Data System (ADS)
Kang, Sungchul; Kim, Munsang; Park, Shinsuk
Robotic systems have been used to automate assembly tasks in manufacturing and in teleoperation. Conventional robotic systems, however, have been ineffective in controlling contact force in multiple contact states of complex assemblythat involves interactions between complex-shaped parts. Unlike robots, humans excel at complex assembly tasks by utilizing their intrinsic impedance, forces and torque sensation, and tactile contact clues. By examining the human behavior in assembling complex parts, this study proposes a novel geometry-independent control method for robotic assembly using adaptive accommodation (or damping) algorithm. Two important conditions for complex assembly, target approachability and bounded contact force, can be met by the proposed control scheme. It generates target approachable motion that leads the object to move closer to a desired target position, while contact force is kept under a predetermined value. Experimental results from complex assembly tests have confirmed the feasibility and applicability of the proposed method.
Adaptable state based control system
NASA Technical Reports Server (NTRS)
Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)
2004-01-01
An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.
Adapting implicit methods to parallel processors
Reeves, L.; McMillin, B.; Okunbor, D.; Riggins, D.
1994-12-31
When numerically solving many types of partial differential equations, it is advantageous to use implicit methods because of their better stability and more flexible parameter choice, (e.g. larger time steps). However, since implicit methods usually require simultaneous knowledge of the entire computational domain, these methods axe difficult to implement directly on distributed memory parallel processors. This leads to infrequent use of implicit methods on parallel/distributed systems. The usual implementation of implicit methods is inefficient due to the nature of parallel systems where it is common to take the computational domain and distribute the grid points over the processors so as to maintain a relatively even workload per processor. This creates a problem at the locations in the domain where adjacent points are not on the same processor. In order for the values at these points to be calculated, messages have to be exchanged between the corresponding processors. Without special adaptation, this will result in idle processors during part of the computation, and as the number of idle processors increases, the lower the effective speed improvement by using a parallel processor.
NASA Astrophysics Data System (ADS)
Kopera, Michal A.; Giraldo, Francis X.
2015-09-01
We perform a comparison of mass conservation properties of the continuous (CG) and discontinuous (DG) Galerkin methods on non-conforming, dynamically adaptive meshes for two atmospheric test cases. The two methods are implemented in a unified way which allows for a direct comparison of the non-conforming edge treatment. We outline the implementation details of the non-conforming direct stiffness summation algorithm for the CG method and show that the mass conservation error is similar to the DG method. Both methods conserve to machine precision, regardless of the presence of the non-conforming edges. For lower order polynomials the CG method requires additional stabilization to run for very long simulation times. We addressed this issue by using filters and/or additional artificial viscosity. The mathematical proof of mass conservation for CG with non-conforming meshes is presented in Appendix B.
Linearly-Constrained Adaptive Signal Processing Methods
NASA Astrophysics Data System (ADS)
Griffiths, Lloyd J.
1988-01-01
In adaptive least-squares estimation problems, a desired signal d(n) is estimated using a linear combination of L observation values samples xi (n), x2(n), . . . , xL-1(n) and denoted by the vector X(n). The estimate is formed as the inner product of this vector with a corresponding L-dimensional weight vector W. One particular weight vector of interest is Wopt which minimizes the mean-square between d(n) and the estimate. In this context, the term `mean-square difference' is a quadratic measure such as statistical expectation or time average. The specific value of W which achieves the minimum is given by the prod-uct of the inverse data covariance matrix and the cross-correlation between the data vector and the desired signal. The latter is often referred to as the P-vector. For those cases in which time samples of both the desired and data vector signals are available, a variety of adaptive methods have been proposed which will guarantee that an iterative weight vector Wa(n) converges (in some sense) to the op-timal solution. Two which have been extensively studied are the recursive least-squares (RLS) method and the LMS gradient approximation approach. There are several problems of interest in the communication and radar environment in which the optimal least-squares weight set is of interest and in which time samples of the desired signal are not available. Examples can be found in array processing in which only the direction of arrival of the desired signal is known and in single channel filtering where the spectrum of the desired response is known a priori. One approach to these problems which has been suggested is the P-vector algorithm which is an LMS-like approximate gradient method. Although it is easy to derive the mean and variance of the weights which result with this algorithm, there has never been an identification of the corresponding underlying error surface which the procedure searches. The purpose of this paper is to suggest an alternative
An adaptive SPH method for strong shocks
NASA Astrophysics Data System (ADS)
Sigalotti, Leonardo Di G.; López, Hender; Trujillo, Leonardo
2009-09-01
We propose an alternative SPH scheme to usual SPH Godunov-type methods for simulating supersonic compressible flows with sharp discontinuities. The method relies on an adaptive density kernel estimation (ADKE) algorithm, which allows the width of the kernel interpolant to vary locally in space and time so that the minimum necessary smoothing is applied in regions of low density. We have performed a von Neumann stability analysis of the SPH equations for an ideal gas and derived the corresponding dispersion relation in terms of the local width of the kernel. Solution of the dispersion relation in the short wavelength limit shows that stability is achieved for a wide range of the ADKE parameters. Application of the method to high Mach number shocks confirms the predictions of the linear analysis. Examples of the resolving power of the method are given for a set of difficult problems, involving the collision of two strong shocks, the strong shock-tube test, and the interaction of two blast waves.
Adaptive frequency estimation by MUSIC (Multiple Signal Classification) method
NASA Astrophysics Data System (ADS)
Karhunen, Juha; Nieminen, Esko; Joutsensalo, Jyrki
During the last years, the eigenvector-based method called MUSIC has become very popular in estimating the frequencies of sinusoids in additive white noise. Adaptive realizations of the MUSIC method are studied using simulated data. Several of the adaptive realizations seem to give in practice equally good results as the nonadaptive standard realization. The only exceptions are instantaneous gradient type algorithms that need considerably more samples to achieve a comparable performance. A new method is proposed for constructing initial estimates to the signal subspace. The method improves often dramatically the performance of instantaneous gradient type algorithms. The new signal subspace estimate can also be used to define a frequency estimator directly or to simplify eigenvector computation.
Adaptive wavelet methods - Matrix-vector multiplication
NASA Astrophysics Data System (ADS)
Černá, Dana; Finěk, Václav
2012-12-01
The design of most adaptive wavelet methods for elliptic partial differential equations follows a general concept proposed by A. Cohen, W. Dahmen and R. DeVore in [3, 4]. The essential steps are: transformation of the variational formulation into the well-conditioned infinite-dimensional l2 problem, finding of the convergent iteration process for the l2 problem and finally derivation of its finite dimensional version which works with an inexact right hand side and approximate matrix-vector multiplications. In our contribution, we shortly review all these parts and wemainly pay attention to approximate matrix-vector multiplications. Effective approximation of matrix-vector multiplications is enabled by an off-diagonal decay of entries of the wavelet stiffness matrix. We propose here a new approach which better utilize actual decay of matrix entries.
Adaptive model training system and method
Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo
2014-04-15
An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.
Adaptive model training system and method
Bickford, Randall L; Palnitkar, Rahul M
2014-11-18
An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.
An Adaptive Cross-Architecture Combination Method for Graph Traversal
You, Yang; Song, Shuaiwen; Kerbyson, Darren J.
2014-06-18
Breadth-First Search (BFS) is widely used in many real-world applications including computational biology, social networks, and electronic design automation. The combination method, using both top-down and bottom-up techniques, is the most effective BFS approach. However, current combination methods rely on trial-and-error and exhaustive search to locate the optimal switching point, which may cause significant runtime overhead. To solve this problem, we design an adaptive method based on regression analysis to predict an optimal switching point for the combination method at runtime within less than 0.1% of the BFS execution time.
Koh, Doo-Yeol; Kim, Young-Kook; Kim, Kyung-Soo; Kim, Soohyun
2013-08-01
In mobile robotics, obtaining stable image of a mounted camera is crucial for operating a mobile system to complete given tasks. This note presents the development of a high-speed image stabilizing device using linear shaft actuator, and a new image stabilization method inspired by human gaze stabilization process known as vestibulo-ocular reflex (VOR). In the proposed control, the reference is adaptively adjusted by the VOR adaptation control to reject residual vibration of a camera as the VOR gain converges to optimal state. Through experiments on a pneumatic vibrator, it will be shown that the proposed system is capable of stabilizing 10 Hz platform vibration, which shows potential applicability of the device to a high-speed mobile robot. PMID:24007125
NASA Astrophysics Data System (ADS)
Koh, Doo-Yeol; Kim, Young-Kook; Kim, Kyung-Soo; Kim, Soohyun
2013-08-01
In mobile robotics, obtaining stable image of a mounted camera is crucial for operating a mobile system to complete given tasks. This note presents the development of a high-speed image stabilizing device using linear shaft actuator, and a new image stabilization method inspired by human gaze stabilization process known as vestibulo-ocular reflex (VOR). In the proposed control, the reference is adaptively adjusted by the VOR adaptation control to reject residual vibration of a camera as the VOR gain converges to optimal state. Through experiments on a pneumatic vibrator, it will be shown that the proposed system is capable of stabilizing 10 Hz platform vibration, which shows potential applicability of the device to a high-speed mobile robot.
Development of a dynamically adaptive grid method for multidimensional problems
NASA Astrophysics Data System (ADS)
Holcomb, J. E.; Hindman, R. G.
1984-06-01
An approach to solution adaptive grid generation for use with finite difference techniques, previously demonstrated on model problems in one space dimension, has been extended to multidimensional problems. The method is based on the popular elliptic steady grid generators, but is 'dynamically' adaptive in the sense that a grid is maintained at all times satisfying the steady grid law driven by a solution-dependent source term. Testing has been carried out on Burgers' equation in one and two space dimensions. Results appear encouraging both for inviscid wave propagation cases and viscous boundary layer cases, suggesting that application to practical flow problems is now possible. In the course of the work, obstacles relating to grid correction, smoothing of the solution, and elliptic equation solvers have been largely overcome. Concern remains, however, about grid skewness, boundary layer resolution and the need for implicit integration methods. Also, the method in 3-D is expected to be very demanding of computer resources.
Advanced numerical methods in mesh generation and mesh adaptation
Lipnikov, Konstantine; Danilov, A; Vassilevski, Y; Agonzal, A
2010-01-01
Numerical solution of partial differential equations requires appropriate meshes, efficient solvers and robust and reliable error estimates. Generation of high-quality meshes for complex engineering models is a non-trivial task. This task is made more difficult when the mesh has to be adapted to a problem solution. This article is focused on a synergistic approach to the mesh generation and mesh adaptation, where best properties of various mesh generation methods are combined to build efficiently simplicial meshes. First, the advancing front technique (AFT) is combined with the incremental Delaunay triangulation (DT) to build an initial mesh. Second, the metric-based mesh adaptation (MBA) method is employed to improve quality of the generated mesh and/or to adapt it to a problem solution. We demonstrate with numerical experiments that combination of all three methods is required for robust meshing of complex engineering models. The key to successful mesh generation is the high-quality of the triangles in the initial front. We use a black-box technique to improve surface meshes exported from an unattainable CAD system. The initial surface mesh is refined into a shape-regular triangulation which approximates the boundary with the same accuracy as the CAD mesh. The DT method adds robustness to the AFT. The resulting mesh is topologically correct but may contain a few slivers. The MBA uses seven local operations to modify the mesh topology. It improves significantly the mesh quality. The MBA method is also used to adapt the mesh to a problem solution to minimize computational resources required for solving the problem. The MBA has a solid theoretical background. In the first two experiments, we consider the convection-diffusion and elasticity problems. We demonstrate the optimal reduction rate of the discretization error on a sequence of adaptive strongly anisotropic meshes. The key element of the MBA method is construction of a tensor metric from hierarchical edge-based
Optimal and adaptive methods of processing hydroacoustic signals (review)
NASA Astrophysics Data System (ADS)
Malyshkin, G. S.; Sidel'nikov, G. B.
2014-09-01
Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.
QPSO-Based Adaptive DNA Computing Algorithm
Karakose, Mehmet; Cigdem, Ugur
2013-01-01
DNA (deoxyribonucleic acid) computing that is a new computation model based on DNA molecules for information storage has been increasingly used for optimization and data analysis in recent years. However, DNA computing algorithm has some limitations in terms of convergence speed, adaptability, and effectiveness. In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). Some contributions provided by the proposed QPSO based on adaptive DNA computing algorithm are as follows: (1) parameters of population size, crossover rate, maximum number of operations, enzyme and virus mutation rate, and fitness function of DNA computing algorithm are simultaneously tuned for adaptive process, (2) adaptive algorithm is performed using QPSO algorithm for goal-driven progress, faster operation, and flexibility in data, and (3) numerical realization of DNA computing algorithm with proposed approach is implemented in system identification. Two experiments with different systems were carried out to evaluate the performance of the proposed approach with comparative results. Experimental results obtained with Matlab and FPGA demonstrate ability to provide effective optimization, considerable convergence speed, and high accuracy according to DNA computing algorithm. PMID:23935409
Vortical Flow Prediction Using an Adaptive Unstructured Grid Method
NASA Technical Reports Server (NTRS)
Pirzadeh, Shahyar Z.
2003-01-01
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65 delta wing with different values of leading-edge radius. Although the geometry is quite simple, it poses a challenging problem for computing vortices originating from blunt leading edges. The second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the wind-tunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
Vortical Flow Prediction Using an Adaptive Unstructured Grid Method
NASA Technical Reports Server (NTRS)
Pirzadeh, Shahyar Z.
2001-01-01
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
Space-time adaptive numerical methods for geophysical applications.
Castro, C E; Käser, M; Toro, E F
2009-11-28
In this paper we present high-order formulations of the finite volume and discontinuous Galerkin finite-element methods for wave propagation problems with a space-time adaptation technique using unstructured meshes in order to reduce computational cost without reducing accuracy. Both methods can be derived in a similar mathematical framework and are identical in their first-order version. In their extension to higher order accuracy in space and time, both methods use spatial polynomials of higher degree inside each element, a high-order solution of the generalized Riemann problem and a high-order time integration method based on the Taylor series expansion. The static adaptation strategy uses locally refined high-resolution meshes in areas with low wave speeds to improve the approximation quality. Furthermore, the time step length is chosen locally adaptive such that the solution is evolved explicitly in time by an optimal time step determined by a local stability criterion. After validating the numerical approach, both schemes are applied to geophysical wave propagation problems such as tsunami waves and seismic waves comparing the new approach with the classical global time-stepping technique. The problem of mesh partitioning for large-scale applications on multi-processor architectures is discussed and a new mesh partition approach is proposed and tested to further reduce computational cost. PMID:19840984
Eigenanalysis-based adaptive interference suppression for source localization
NASA Astrophysics Data System (ADS)
Ren, Suiling; Ge, Fengxiang; Guo, Xin; Guo, Lianghao
2012-11-01
Passive sonar detection in shallow water environments is very difficult due to strong interference. In this paper, an eigenanalysis-based adaptive interference suppression method (EAAIS) is presented for source localization. First, using beamforming for each eigenvector of the cross-spectral density matrix (CSDM) and a priori knowledge of the target's bearing interval, the proposed method constructs an appropriate rule to adaptively and robustly identify which eigenvector does not contain dominant contributions from the target of interest (TOI). Then, the identified eigenvectors are subtracted from the CSDM for interference suppression and source location. Numerical simulation results show that the proposed method could effectively detect the TOI even in the presence of strong interference. In comparison with other adaptive interference suppression methods, the proposed method has better interference rejection capability and wider range of applications without a priori knowledge of the interference's position.
Adaptive numerical methods for partial differential equations
Cololla, P.
1995-07-01
This review describes a structured approach to adaptivity. The Automated Mesh Refinement (ARM) algorithms developed by M Berger are described, touching on hyperbolic and parabolic applications. Adaptivity is achieved by overlaying finer grids only in areas flagged by a generalized error criterion. The author discusses some of the issues involved in abutting disparate-resolution grids, and demonstrates that suitable algorithms exist for dissipative as well as hyperbolic systems.
Extremum seeking-based adaptive control for electromagnetic actuators
NASA Astrophysics Data System (ADS)
Benosman, Mouhacine; Atınç, Gökhan M.
2015-03-01
In this paper, we present a learning-based adaptive method to solve the problem of robust trajectory tracking for electromagnetic actuators. We merge a nonlinear backstepping controller that ensures bounded input/bounded states stability, with a multi-variable extremum seeking model-free learning algorithm. The learning algorithm is used to estimate online the uncertain parameters of the model, in this sense, we propose a learning-based adaptive controller. We present a proof of stability of this learning-based nonlinear controller when considering uncertainties with linear parametrisation. The efficiency of this approach is shown on a numerical example.
A novel adaptive force control method for IPMC manipulation
NASA Astrophysics Data System (ADS)
Hao, Lina; Sun, Zhiyong; Li, Zhi; Su, Yunquan; Gao, Jianchao
2012-07-01
IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable.
Principles and Methods of Adapted Physical Education.
ERIC Educational Resources Information Center
Arnheim, Daniel D.; And Others
Programs in adapted physical education are presented preceded by a background of services for the handicapped, by the psychosocial implications of disability, and by the growth and development of the handicapped. Elements of conducting programs discussed are organization and administration, class organization, facilities, exercise programs…
QUEST - A Bayesian adaptive psychometric method
NASA Technical Reports Server (NTRS)
Watson, A. B.; Pelli, D. G.
1983-01-01
An adaptive psychometric procedure that places each trial at the current most probable Bayesian estimate of threshold is described. The procedure takes advantage of the common finding that the human psychometric function is invariant in form when expressed as a function of log intensity. The procedure is simple, fast, and efficient, and may be easily implemented on any computer.
Adaptive method of realizing natural gradient learning for multilayer perceptrons.
Amari, S; Park, H; Fukumizu, K
2000-06-01
The natural gradient learning method is known to have ideal performances for on-line training of multilayer perceptrons. It avoids plateaus, which give rise to slow convergence of the backpropagation method. It is Fisher efficient, whereas the conventional method is not. However, for implementing the method, it is necessary to calculate the Fisher information matrix and its inverse, which is practically very difficult. This article proposes an adaptive method of directly obtaining the inverse of the Fisher information matrix. It generalizes the adaptive Gauss-Newton algorithms and provides a solid theoretical justification of them. Simulations show that the proposed adaptive method works very well for realizing natural gradient learning. PMID:10935719
Adaptive skin detection based on online training
NASA Astrophysics Data System (ADS)
Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang
2007-11-01
Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.
Adaptive Maximum Marginal Relevance Based Multi-email Summarization
NASA Astrophysics Data System (ADS)
Wang, Baoxun; Liu, Bingquan; Sun, Chengjie; Wang, Xiaolong; Li, Bo
By analyzing the inherent relationship between the maximum marginal relevance (MMR) model and the content cohesion of emails with the same subject, this paper presents an adaptive maximum marginal relevance based multi-email summarization method. Due to the adoption of approximate computing of email content cohesion, the adaptive MMR is able to automatically adjust the parameters according to the changing of the email sets. The experimental results have shown that the email summarizing system based on this technique can increase the precision while reducing the redundancy of the automatic summary results, consequently improve the average quality of email summaries.
Spatially-Anisotropic Parallel Adaptive Wavelet Collocation Method
NASA Astrophysics Data System (ADS)
Vasilyev, Oleg V.; Brown-Dymkoski, Eric
2015-11-01
Despite latest advancements in development of robust wavelet-based adaptive numerical methodologies to solve partial differential equations, they all suffer from two major ``curses'': 1) the reliance on rectangular domain and 2) the ``curse of anisotropy'' (i.e. homogeneous wavelet refinement and inability to have spatially varying aspect ratio of the mesh elements). The new method addresses both of these challenges by utilizing an adaptive anisotropic wavelet transform on curvilinear meshes that can be either algebraically prescribed or calculated on the fly using PDE-based mesh generation. In order to ensure accurate representation of spatial operators in physical space, an additional adaptation on spatial physical coordinates is also performed. It is important to note that when new nodes are added in computational space, the physical coordinates can be approximated by interpolation of the existing solution and additional local iterations to ensure that the solution of coordinate mapping PDEs is converged on the new mesh. In contrast to traditional mesh generation approaches, the cost of adding additional nodes is minimal, mainly due to localized nature of iterative mesh generation PDE solver requiring local iterations in the vicinity of newly introduced points. This work was supported by ONR MURI under grant N00014-11-1-069.
Solution-adaptive finite element method in computational fracture mechanics
NASA Technical Reports Server (NTRS)
Min, J. B.; Bass, J. M.; Spradley, L. W.
1993-01-01
Some recent results obtained using solution-adaptive finite element method in linear elastic two-dimensional fracture mechanics problems are presented. The focus is on the basic issue of adaptive finite element method for validating the applications of new methodology to fracture mechanics problems by computing demonstration problems and comparing the stress intensity factors to analytical results.
Adaptive method for electron bunch profile prediction
NASA Astrophysics Data System (ADS)
Scheinker, Alexander; Gessner, Spencer
2015-10-01
We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial control system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.
Adaptive method for electron bunch profile prediction
Scheinker, Alexander; Gessner, Spencer
2015-10-01
We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial control system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.
Adaptive Cognitive-Based Selection of Learning Objects
ERIC Educational Resources Information Center
Karampiperis, Pythagoras; Lin, Taiyu; Sampson, Demetrios G.; Kinshuk
2006-01-01
Adaptive cognitive-based selection is recognized as among the most significant open issues in adaptive web-based learning systems. In order to adaptively select learning resources, the definition of adaptation rules according to the cognitive style or learning preferences of the learners is required. Although some efforts have been reported in…
A multilevel adaptive projection method for unsteady incompressible flow
NASA Technical Reports Server (NTRS)
Howell, Louis H.
1993-01-01
There are two main requirements for practical simulation of unsteady flow at high Reynolds number: the algorithm must accurately propagate discontinuous flow fields without excessive artificial viscosity, and it must have some adaptive capability to concentrate computational effort where it is most needed. We satisfy the first of these requirements with a second-order Godunov method similar to those used for high-speed flows with shocks, and the second with a grid-based refinement scheme which avoids some of the drawbacks associated with unstructured meshes. These two features of our algorithm place certain constraints on the projection method used to enforce incompressibility. Velocities are cell-based, leading to a Laplacian stencil for the projection which decouples adjacent grid points. We discuss features of the multigrid and multilevel iteration schemes required for solution of the resulting decoupled problem. Variable-density flows require use of a modified projection operator--we have found a multigrid method for this modified projection that successfully handles density jumps of thousands to one. Numerical results are shown for the 2D adaptive and 3D variable-density algorithms.
NASA Astrophysics Data System (ADS)
Kong, Weiwei; Lei, Yang; Zhao, Huaixun
2014-11-01
The issue of visible light and infrared images fusion has been an active topic in both military and civilian areas, and a great many relevant algorithms and techniques have been developed accordingly. This paper addresses a novel adaptive approach to the above two patterns of images fusion problem, employing multi-scale geometry analysis (MGA) of non-subsampled shearlet transform (NSST) and fast non-negative matrix factorization (FNMF) together. Compared with other existing conventional MGA tools, NSST owns not only better feature-capturing capabilities, but also much lower computational complexities. As a modification version of the classic NMF model, FNMF overcomes the local optimum property inherent in NMF to a large extent. Furthermore, use of the FNMF with a less complex structure and much fewer iteration numbers required leads to the enhancement of the overall computational efficiency, which is undoubtedly meaningful and promising in so many real-time applications especially the military and medical technologies. Experimental results indicate that the proposed method is superior to other current popular ones in both aspects of subjective visual and objective performance.
Robust time and frequency domain estimation methods in adaptive control
NASA Technical Reports Server (NTRS)
Lamaire, Richard Orville
1987-01-01
A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.
Revenue-maximization-based adaptive WFQ
NASA Astrophysics Data System (ADS)
Joutsensalo, Jyrki; Hamalainen, Timo; Zhang, Jian
2002-09-01
In the future Internet, different applications such as Voice over IP (VoIP) and Video-on-Demand (VoD) arise with different Quality of Service (QoS) parameters including e.g. guaranteed bandwidth, delay jitter, and latency. Different kinds of service classes (e.g. gold, silver, bronze) arise. The customers of different classes pay different prices to the service provider, who must share resources in a plausible way. In a router, packets are queued using a multi-queue system, where each queue corresponds to one service class. In this paper, an adaptive Weighted Fair Queue based algorithm for traffic allocation is presented and studied. The weights in gradient type WFQ algorithm are adapted using revenue as a target function.
Assessing Adaptive Instructional Design Tools and Methods in ADAPT[IT].
ERIC Educational Resources Information Center
Eseryel, Deniz; Spector, J. Michael
ADAPT[IT] (Advanced Design Approach for Personalized Training - Interactive Tools) is a European project within the Information Society Technologies program that is providing design methods and tools to guide a training designer according to the latest cognitive science and standardization principles. ADAPT[IT] addresses users in two significantly…
Design of an adaptive neural network based power system stabilizer.
Liu, Wenxin; Venayagamoorthy, Ganesh K; Wunsch, Donald C
2003-01-01
Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp the low frequency power system oscillations. To overcome the drawbacks of conventional PSS (CPSS), numerous techniques have been proposed in the literature. Based on the analysis of existing techniques, this paper presents an indirect adaptive neural network based power system stabilizer (IDNC) design. The proposed IDNC consists of a neuro-controller, which is used to generate a supplementary control signal to the excitation system, and a neuro-identifier, which is used to model the dynamics of the power system and to adapt the neuro-controller parameters. The proposed method has the features of a simple structure, adaptivity and fast response. The proposed IDNC is evaluated on a single machine infinite bus power system under different operating conditions and disturbances to demonstrate its effectiveness and robustness. PMID:12850048
Roy’s Adaptation Model-Based Patient Education for Promoting the Adaptation of Hemodialysis Patients
Afrasiabifar, Ardashir; Karimi, Zohreh; Hassani, Parkhideh
2013-01-01
Background In addition to physical adaptation and psychosocial adjustment to chronic renal disease, hemodialysis (HD) patients must also adapt to dialysis therapy plan. Objectives The aim of the present study was to examine the effect of Roy’s adaptation model-based patient education on adaptation of HD patients. Patients and Methods This study is a semi-experimental research that was conducted with the participation of all patients with end-stage renal disease referred to the dialysis unit of Shahid Beheshti Hospital of Yasuj city, 2010. A total of 59 HD patients were randomly allocated to two groups of test and control. Data were collected by a questionnaire based on the Roy’s Adaptation Model (RAM). Validity and reliability of the questionnaire were approved. Patient education was determined by eight one-hour sessions over eight weeks. At the end of the education plan, the patients were given an educational booklet containing the main points of self-care for HD patients. The effectiveness of education plan was assessed two months after plan completion and data were compared with the pre-education scores. All analyses were conducted using the SPSS software (version 16) through descriptive and inferential statistics including correlation, t-test, ANOVA and ANCOVA tests. Results The results showed significant differences in the mean scores of physiological and self-concept models between the test and control groups (P = 0.01 and P = 0.03 respectively). Also a statistical difference (P = 0.04) was observed in the mean scores of the role function mode of both groups. There was no significant difference in the mean scores of interdependence modes between the two groups. Conclusions RAM based patient education could improve the patients’ adaptation in physiologic and self-concept modes. In addition to suggesting further research in this area, nurses are recommended to pay more attention in applying RAM in dialysis centers. PMID:24396575
Moving and adaptive grid methods for compressible flows
NASA Technical Reports Server (NTRS)
Trepanier, Jean-Yves; Camarero, Ricardo
1995-01-01
This paper describes adaptive grid methods developed specifically for compressible flow computations. The basic flow solver is a finite-volume implementation of Roe's flux difference splitting scheme or arbitrarily moving unstructured triangular meshes. The grid adaptation is performed according to geometric and flow requirements. Some results are included to illustrate the potential of the methodology.
An adaptive pseudospectral method for discontinuous problems
NASA Technical Reports Server (NTRS)
Augenbaum, Jeffrey M.
1988-01-01
The accuracy of adaptively chosen, mapped polynomial approximations is studied for functions with steep gradients or discontinuities. It is shown that, for steep gradient functions, one can obtain spectral accuracy in the original coordinate system by using polynomial approximations in a transformed coordinate system with substantially fewer collocation points than are necessary using polynomial expansion directly in the original, physical, coordinate system. It is also shown that one can avoid the usual Gibbs oscillation associated with steep gradient solutions of hyperbolic pde's by approximation in suitably chosen coordinate systems. Continuous, high gradient solutions are computed with spectral accuracy (as measured in the physical coordinate system). Discontinuous solutions associated with nonlinear hyperbolic equations can be accurately computed by using an artificial viscosity chosen to smooth out the solution in the mapped, computational domain. Thus, shocks can be effectively resolved on a scale that is subgrid to the resolution available with collocation only in the physical domain. Examples with Fourier and Chebyshev collocation are given.
Adaptable radiation monitoring system and method
Archer, Daniel E.; Beauchamp, Brock R.; Mauger, G. Joseph; Nelson, Karl E.; Mercer, Michael B.; Pletcher, David C.; Riot, Vincent J.; Schek, James L.; Knapp, David A.
2006-06-20
A portable radioactive-material detection system capable of detecting radioactive sources moving at high speeds. The system has at least one radiation detector capable of detecting gamma-radiation and coupled to an MCA capable of collecting spectral data in very small time bins of less than about 150 msec. A computer processor is connected to the MCA for determining from the spectral data if a triggering event has occurred. Spectral data is stored on a data storage device, and a power source supplies power to the detection system. Various configurations of the detection system may be adaptably arranged for various radiation detection scenarios. In a preferred embodiment, the computer processor operates as a server which receives spectral data from other networked detection systems, and communicates the collected data to a central data reporting system.
Adaptive computational methods for aerothermal heating analysis
NASA Technical Reports Server (NTRS)
Price, John M.; Oden, J. Tinsley
1988-01-01
The development of adaptive gridding techniques for finite-element analysis of fluid dynamics equations is described. The developmental work was done with the Euler equations with concentration on shock and inviscid flow field capturing. Ultimately this methodology is to be applied to a viscous analysis for the purpose of predicting accurate aerothermal loads on complex shapes subjected to high speed flow environments. The development of local error estimate strategies as a basis for refinement strategies is discussed, as well as the refinement strategies themselves. The application of the strategies to triangular elements and a finite-element flux-corrected-transport numerical scheme are presented. The implementation of these strategies in the GIM/PAGE code for 2-D and 3-D applications is documented and demonstrated.
Zhao, Qian; Jia, Xiaobo; Xia, Rui; Lin, Jianing; Zhang, Yuan
2016-09-01
Ionic mixtures, measured as specific conductivity, have been increasingly concerned because of their toxicities to aquatic organisms. However, identifying protective values of specific conductivity for aquatic organisms is challenging given that laboratory test systems cannot examine more salt-intolerant species nor effects occurring in streams. Large data sets used for deriving field-based benchmarks are rarely available. In this study, a field-based method for small data sets was used to derive specific conductivity benchmark, which is expected to prevent the extirpation of 95% of local taxa from circum-neutral to alkaline waters dominated by a mixture of SO4(2-) and HCO3(-) anions and other dissolved ions. To compensate for the smaller sample size, species level analyses were combined with genus level analyses. The benchmark is based on extirpation concentration (XC95) values of specific conductivity for 60 macroinvertebrate genera estimated from 296 sampling sites in the Hun-Tai River Basin. We derived the specific conductivity benchmark by using a 2-point interpolation method, which yielded the benchmark of 249 μS/cm. Our study tailored the method that was developed by USEPA to derive aquatic life benchmark for specific conductivity for basin scale application, and may provide useful information for water pollution control and management. PMID:27389551
Adaptive mesh strategies for the spectral element method
NASA Technical Reports Server (NTRS)
Mavriplis, Catherine
1992-01-01
An adaptive spectral method was developed for the efficient solution of time dependent partial differential equations. Adaptive mesh strategies that include resolution refinement and coarsening by three different methods are illustrated on solutions to the 1-D viscous Burger equation and the 2-D Navier-Stokes equations for driven flow in a cavity. Sharp gradients, singularities, and regions of poor resolution are resolved optimally as they develop in time using error estimators which indicate the choice of refinement to be used. The adaptive formulation presents significant increases in efficiency, flexibility, and general capabilities for high order spectral methods.
SU-E-J-153: MRI Based, Daily Adaptive Radiotherapy for Rectal Cancer: Contour Adaptation
Kleijnen, J; Burbach, M; Verbraeken, T; Weggers, R; Zoetelief, A; Reerink, O; Lagendijk, J; Raaymakers, B; Asselen, B
2014-06-01
Purpose: A major hurdle in adaptive radiotherapy is the adaptation of the planning MRI's delineations to the daily anatomy. We therefore investigate the accuracy and time needed for online clinical target volume (CTV) adaptation by radiation therapists (RTT), to be used in MRI-guided adaptive treatments on a MRI-Linac (MRL). Methods: Sixteen patients, diagnosed with early stage rectal cancer, underwent a T2-weighted MRI prior to each fraction of short-course radiotherapy, resulting in 4–5 scans per patient. On these scans, the CTV was delineated according to guidelines by an experienced radiation oncologist (RO) and considered to be the gold standard. For each patient, the first MRI was considered as the planning MRI and matched on bony anatomy to the 3–4 daily MRIs. The planning MRI's CTV delineation was rigidly propagated to the daily MRI scans as a proposal for adaptation. Three RTTs in training started the adaptation of the CTV conform guidelines, after a two hour training lecture and a two patient (n=7) training set. To assess the inter-therapist variation, all three RTTs altered delineations of 3 patients (n=12). One RTT altered the CTV delineations (n=53) of the remaining 11 patients. Time needed for adaptation of the CTV to guidelines was registered.As a measure of agreement, the conformity index (CI) was determined between the RTTs' delineations as a group. Dice similarity coefficients were determined between delineations of the RTT and the RO. Results: We found good agreement between RTTs' and RO's delineations (average Dice=0.91, SD=0.03). Furthermore, the inter-observer agreement between the RTTs was high (average CI=0.94, SD=0.02). Adaptation time reduced from 10:33 min (SD= 3:46) to 2:56 min (SD=1:06) between the first and last ten delineations, respectively. Conclusion: Daily CTV adaptation by RTTs, seems a feasible and safe way to introduce daily, online MRI-based plan adaptation for a MRL.
Adaptive script based animations for intervention planning.
Muehler, Konrad; Bade, Ragnar; Preim, Bernhard
2006-01-01
We describe scripting facilities to create medical animations for intervention planning based on medical volume data and derived segmentation information. A data independent scripting language has been developed to separate animation scripts from imaging data. The scripting facilities are adaptive and allow to reuse one script to create animations for many different patients. With expressive animations, we support the individual planning process, the preoperative documentation as well as discussions between medical doctors, for example in a tumor board. We also discuss the enhancement of interactive explorations with animations generated on the fly. PMID:17354925
Investigation of the Multiple Model Adaptive Control (MMAC) method for flight control systems
NASA Technical Reports Server (NTRS)
1975-01-01
The application was investigated of control theoretic ideas to the design of flight control systems for the F-8 aircraft. The design of an adaptive control system based upon the so-called multiple model adaptive control (MMAC) method is considered. Progress is reported.
Adaptive sequential methods for detecting network intrusions
NASA Astrophysics Data System (ADS)
Chen, Xinjia; Walker, Ernest
2013-06-01
In this paper, we propose new sequential methods for detecting port-scan attackers which routinely perform random "portscans" of IP addresses to find vulnerable servers to compromise. In addition to rigorously control the probability of falsely implicating benign remote hosts as malicious, our method performs significantly faster than other current solutions. Moreover, our method guarantees that the maximum amount of observational time is bounded. In contrast to the previous most effective method, Threshold Random Walk Algorithm, which is explicit and analytical in nature, our proposed algorithm involve parameters to be determined by numerical methods. We have introduced computational techniques such as iterative minimax optimization for quick determination of the parameters of the new detection algorithm. A framework of multi-valued decision for detecting portscanners and DoS attacks is also proposed.
Adaptive finite-element method for diffraction gratings
NASA Astrophysics Data System (ADS)
Bao, Gang; Chen, Zhiming; Wu, Haijun
2005-06-01
A second-order finite-element adaptive strategy with error control for one-dimensional grating problems is developed. The unbounded computational domain is truncated to a bounded one by a perfectly-matched-layer (PML) technique. The PML parameters, such as the thickness of the layer and the medium properties, are determined through sharp a posteriori error estimates. The adaptive finite-element method is expected to increase significantly the accuracy and efficiency of the discretization as well as reduce the computation cost. Numerical experiments are included to illustrate the competitiveness of the proposed adaptive method.
Fast adaptive composite grid methods on distributed parallel architectures
NASA Technical Reports Server (NTRS)
Lemke, Max; Quinlan, Daniel
1992-01-01
The fast adaptive composite (FAC) grid method is compared with the adaptive composite method (AFAC) under variety of conditions including vectorization and parallelization. Results are given for distributed memory multiprocessor architectures (SUPRENUM, Intel iPSC/2 and iPSC/860). It is shown that the good performance of AFAC and its superiority over FAC in a parallel environment is a property of the algorithm and not dependent on peculiarities of any machine.
ERIC Educational Resources Information Center
Kara, Bülent; Mukaddes, Nahit Motavalli; Altinkaya, Isilay; Güntepe, Dilek; Gökçay, Gülbin; Özmen, Meral
2014-01-01
We aimed to adapt the Modified Checklist for Autism in Toddlers to Turkish culture. The Modified Checklist for Autism in Toddlers was filled out independently by 191 parents while they were waiting for the well-child examination of their child. A high screen-positive rate was found. Because of this high false-positive rate, a second study was done…
ERIC Educational Resources Information Center
Ho, Tsung-Han
2010-01-01
Computerized adaptive testing (CAT) provides a highly efficient alternative to the paper-and-pencil test. By selecting items that match examinees' ability levels, CAT not only can shorten test length and administration time but it can also increase measurement precision and reduce measurement error. In CAT, maximum information (MI) is the most…
Adaptive wavefront sensor based on the Talbot effect
NASA Astrophysics Data System (ADS)
Podanchuk, Dmytro V.; Kurashov, Vitaliy N.; Kovalenko, Andrey V.; Dan'ko, Volodymyr P.; Kotov, Myhailo M.; Goloborodko, Nataliya S.
2015-11-01
The possibilities of wavefront curvature measuring by Talbot sensor are theoretically and experimentally investigated. A new method of wavefront aberrations measurement is proposed and demonstrated. It is based on the observation of the Talbot effect when the diffraction grating is adapted to the wavefront curvature of the analyzed wave. Herewith, the observation plane stay fixed and corresponds to the Talbot length for a plane wave. It is shown that the measurement range can be made several times wider, with the help of the adaptive Talbot sensor, by retaining the required angular sensitivity. A possibility of self-reproduction of the rectangular grating (with different periods along the axes) by the astigmatic wavefront is experimentally demonstrated. The possibility of the experimental realization of the adaptive Talbot sensor using the dynamic spatial light modulator is demonstrated.
Latent subspace sparse representation-based unsupervised domain adaptation
NASA Astrophysics Data System (ADS)
Shuai, Liu; Sun, Hao; Zhao, Fumin; Zhou, Shilin
2015-12-01
In this paper, we introduce and study a novel unsupervised domain adaptation (DA) algorithm, called latent subspace sparse representation based domain adaptation, based on the fact that source and target data that lie in different but related low-dimension subspaces. The key idea is that each point in a union of subspaces can be constructed by a combination of other points in the dataset. In this method, we propose to project the source and target data onto a common latent generalized subspace which is a union of subspaces of source and target domains and learn the sparse representation in the latent generalized subspace. By employing the minimum reconstruction error and maximum mean discrepancy (MMD) constraints, the structure of source and target domain are preserved and the discrepancy is reduced between the source and target domains and thus reflected in the sparse representation. We then utilize the sparse representation to build a weighted graph which reflect the relationship of points from the different domains (source-source, source- target, and target-target) to predict the labels of the target domain. We also proposed an efficient optimization method for the algorithm. Our method does not need to combine with any classifiers and therefore does not need train the test procedures. Various experiments show that the proposed method perform better than the competitive state of art subspace-based domain adaptation.
Adaptive DFT-based Interferometer Fringe Tracking
NASA Technical Reports Server (NTRS)
Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.
2004-01-01
An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA) observatory at Mt. Hopkins, Arizona. The system can minimize the optical path differences (OPDs) for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse.
Adaptive upscaling with the dual mesh method
Guerillot, D.; Verdiere, S.
1997-08-01
The objective of this paper is to demonstrate that upscaling should be calculated during the flow simulation instead of trying to enhance the a priori upscaling methods. Hence, counter-examples are given to motivate our approach, the so-called Dual Mesh Method. The main steps of this numerical algorithm are recalled. Applications illustrate the necessity to consider different average relative permeability values depending on the direction in space. Moreover, these values could be different for the same average saturation. This proves that an a priori upscaling cannot be the answer even in homogeneous cases because of the {open_quotes}dynamical heterogeneity{close_quotes} created by the saturation profile. Other examples show the efficiency of the Dual Mesh Method applied to heterogeneous medium and to an actual field case in South America.
Adaptive grid methods for RLV environment assessment and nozzle analysis
NASA Technical Reports Server (NTRS)
Thornburg, Hugh J.
1996-01-01
, forcing functions to attract/repel points in an elliptic system, or to trigger local refinement, based upon application of an equidistribution principle. The popularity of solution-adaptive techniques is growing in tandem with unstructured methods. The difficultly of precisely controlling mesh densities and orientations with current unstructured grid generation systems has driven the use of solution-adaptive meshing. Use of derivatives of density or pressure are widely used for construction of such weight functions, and have been proven very successful for inviscid flows with shocks. However, less success has been realized for flowfields with viscous layers, vortices or shocks of disparate strength. It is difficult to maintain the appropriate mesh point spacing in the various regions which require a fine spacing for adequate resolution. Mesh points often migrate from important regions due to refinement of dominant features. An example of this is the well know tendency of adaptive methods to increase the resolution of shocks in the flowfield around airfoils, but in the incorrect location due to inadequate resolution of the stagnation region. This problem has been the motivation for this research.
Efficient Combustion Simulation via the Adaptive Wavelet Collocation Method
NASA Astrophysics Data System (ADS)
Lung, Kevin; Brown-Dymkoski, Eric; Guerrero, Victor; Doran, Eric; Museth, Ken; Balme, Jo; Urberger, Bob; Kessler, Andre; Jones, Stephen; Moses, Billy; Crognale, Anthony
Rocket engine development continues to be driven by the intuition and experience of designers, progressing through extensive trial-and-error test campaigns. Extreme temperatures and pressures frustrate direct observation, while high-fidelity simulation can be impractically expensive owing to the inherent muti-scale, multi-physics nature of the problem. To address this cost, an adaptive multi-resolution PDE solver has been designed which targets the high performance, many-core architecture of GPUs. The adaptive wavelet collocation method is used to maintain a sparse-data representation of the high resolution simulation, greatly reducing the memory footprint while tightly controlling physical fidelity. The tensorial, stencil topology of wavelet-based grids lends itself to highly vectorized algorithms which are necessary to exploit the performance of GPUs. This approach permits efficient implementation of direct finite-rate kinetics, and improved resolution of steep thermodynamic gradients and the smaller mixing scales that drive combustion dynamics. Resolving these scales is crucial for accurate chemical kinetics, which are typically degraded or lost in statistical modeling approaches.
An auto-adaptive background subtraction method for Raman spectra.
Xie, Yi; Yang, Lidong; Sun, Xilong; Wu, Dewen; Chen, Qizhen; Zeng, Yongming; Liu, Guokun
2016-05-15
Background subtraction is a crucial step in the preprocessing of Raman spectrum. Usually, parameter manipulating of the background subtraction method is necessary for the efficient removal of the background, which makes the quality of the spectrum empirically dependent. In order to avoid artificial bias, we proposed an auto-adaptive background subtraction method without parameter adjustment. The main procedure is: (1) select the local minima of spectrum while preserving major peaks, (2) apply an interpolation scheme to estimate background, (3) and design an iteration scheme to improve the adaptability of background subtraction. Both simulated data and Raman spectra have been used to evaluate the proposed method. By comparing the backgrounds obtained from three widely applied methods: the polynomial, the Baek's and the airPLS, the auto-adaptive method meets the demand of practical applications in terms of efficiency and accuracy. PMID:26950502
An auto-adaptive background subtraction method for Raman spectra
NASA Astrophysics Data System (ADS)
Xie, Yi; Yang, Lidong; Sun, Xilong; Wu, Dewen; Chen, Qizhen; Zeng, Yongming; Liu, Guokun
2016-05-01
Background subtraction is a crucial step in the preprocessing of Raman spectrum. Usually, parameter manipulating of the background subtraction method is necessary for the efficient removal of the background, which makes the quality of the spectrum empirically dependent. In order to avoid artificial bias, we proposed an auto-adaptive background subtraction method without parameter adjustment. The main procedure is: (1) select the local minima of spectrum while preserving major peaks, (2) apply an interpolation scheme to estimate background, (3) and design an iteration scheme to improve the adaptability of background subtraction. Both simulated data and Raman spectra have been used to evaluate the proposed method. By comparing the backgrounds obtained from three widely applied methods: the polynomial, the Baek's and the airPLS, the auto-adaptive method meets the demand of practical applications in terms of efficiency and accuracy.
Adaptive responses to antibody based therapy.
Rodems, Tamara S; Iida, Mari; Brand, Toni M; Pearson, Hannah E; Orbuch, Rachel A; Flanigan, Bailey G; Wheeler, Deric L
2016-02-01
Receptor tyrosine kinases (RTKs) represent a large class of protein kinases that span the cellular membrane. There are 58 human RTKs identified which are grouped into 20 distinct families based upon their ligand binding, sequence homology and structure. They are controlled by ligand binding which activates intrinsic tyrosine-kinase activity. This activity leads to the phosphorylation of distinct tyrosines on the cytoplasmic tail, leading to the activation of cell signaling cascades. These signaling cascades ultimately regulate cellular proliferation, apoptosis, migration, survival and homeostasis of the cell. The vast majority of RTKs have been directly tied to the etiology and progression of cancer. Thus, using antibodies to target RTKs as a cancer therapeutic strategy has been intensely pursued. Although antibodies against the epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2) have shown promise in the clinical arena, the development of both intrinsic and acquired resistance to antibody-based therapies is now well appreciated. In this review we provide an overview of the RTK family, the biology of EGFR and HER2, as well as an in-depth review of the adaptive responses undertaken by cells in response to antibody based therapies directed against these receptors. A greater understanding of these mechanisms and their relevance in human models will lead to molecular insights in overcoming and circumventing resistance to antibody based therapy. PMID:26808665
Adaptive control with an expert system based supervisory level. Thesis
NASA Technical Reports Server (NTRS)
Sullivan, Gerald A.
1991-01-01
Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up
Locally adaptive method to define coordination shell.
Higham, Jonathan; Henchman, Richard H
2016-08-28
An algorithm is presented to define a particle's coordination shell for any collection of particles. It requires only the particles' positions and no pre-existing knowledge or parameters beyond those already in the force field. A particle's shell is taken to be all particles that are not blocked by any other particle and not further away than a blocked particle. Because blocking is based on two distances and an angle for triplets of particles, it is called the relative angular distance (RAD) algorithm. RAD is applied to Lennard-Jones particles in molecular dynamics simulations of crystalline, liquid, and gaseous phases at various temperatures and densities. RAD coordination shells agree well with those from a cut-off in the radial distribution function for the crystals and liquids and are slightly higher for the gas. PMID:27586905
Track and vertex reconstruction: From classical to adaptive methods
Strandlie, Are; Fruehwirth, Rudolf
2010-04-15
This paper reviews classical and adaptive methods of track and vertex reconstruction in particle physics experiments. Adaptive methods have been developed to meet the experimental challenges at high-energy colliders, in particular, the CERN Large Hadron Collider. They can be characterized by the obliteration of the traditional boundaries between pattern recognition and statistical estimation, by the competition between different hypotheses about what constitutes a track or a vertex, and by a high level of flexibility and robustness achieved with a minimum of assumptions about the data. The theoretical background of some of the adaptive methods is described, and it is shown that there is a close connection between the two main branches of adaptive methods: neural networks and deformable templates, on the one hand, and robust stochastic filters with annealing, on the other hand. As both classical and adaptive methods of track and vertex reconstruction presuppose precise knowledge of the positions of the sensitive detector elements, the paper includes an overview of detector alignment methods and a survey of the alignment strategies employed by past and current experiments.
A massively parallel adaptive finite element method with dynamic load balancing
Devine, K.D.; Flaherty, J.E.; Wheat, S.R.; Maccabe, A.B.
1993-05-01
We construct massively parallel, adaptive finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We demonstrate parallel efficiency through computations on a 1024-processor nCUBE/2 hypercube. We also present results using adaptive p-refinement to reduce the computational cost of the method. We describe tiling, a dynamic, element-based data migration system. Tiling dynamically maintains global load balance in the adaptive method by overlapping neighborhoods of processors, where each neighborhood performs local load balancing. We demonstrate the effectiveness of the dynamic load balancing with adaptive p-refinement examples.
Introduction to Adaptive Methods for Differential Equations
NASA Astrophysics Data System (ADS)
Eriksson, Kenneth; Estep, Don; Hansbo, Peter; Johnson, Claes
Knowing thus the Algorithm of this calculus, which I call Differential Calculus, all differential equations can be solved by a common method (Gottfried Wilhelm von Leibniz, 1646-1719).When, several years ago, I saw for the first time an instrument which, when carried, automatically records the number of steps taken by a pedestrian, it occurred to me at once that the entire arithmetic could be subjected to a similar kind of machinery so that not only addition and subtraction, but also multiplication and division, could be accomplished by a suitably arranged machine easily, promptly and with sure results. For it is unworthy of excellent men to lose hours like slaves in the labour of calculations, which could safely be left to anyone else if the machine was used. And now that we may give final praise to the machine, we may say that it will be desirable to all who are engaged in computations which, as is well known, are the managers of financial affairs, the administrators of others estates, merchants, surveyors, navigators, astronomers, and those connected with any of the crafts that use mathematics (Leibniz).
A locally adaptive kernel regression method for facies delineation
NASA Astrophysics Data System (ADS)
Fernàndez-Garcia, D.; Barahona-Palomo, M.; Henri, C. V.; Sanchez-Vila, X.
2015-12-01
Facies delineation is defined as the separation of geological units with distinct intrinsic characteristics (grain size, hydraulic conductivity, mineralogical composition). A major challenge in this area stems from the fact that only a few scattered pieces of hydrogeological information are available to delineate geological facies. Several methods to delineate facies are available in the literature, ranging from those based only on existing hard data, to those including secondary data or external knowledge about sedimentological patterns. This paper describes a methodology to use kernel regression methods as an effective tool for facies delineation. The method uses both the spatial and the actual sampled values to produce, for each individual hard data point, a locally adaptive steering kernel function, self-adjusting the principal directions of the local anisotropic kernels to the direction of highest local spatial correlation. The method is shown to outperform the nearest neighbor classification method in a number of synthetic aquifers whenever the available number of hard data is small and randomly distributed in space. In the case of exhaustive sampling, the steering kernel regression method converges to the true solution. Simulations ran in a suite of synthetic examples are used to explore the selection of kernel parameters in typical field settings. It is shown that, in practice, a rule of thumb can be used to obtain suboptimal results. The performance of the method is demonstrated to significantly improve when external information regarding facies proportions is incorporated. Remarkably, the method allows for a reasonable reconstruction of the facies connectivity patterns, shown in terms of breakthrough curves performance.
Fabrication Methods for Adaptive Deformable Mirrors
NASA Technical Reports Server (NTRS)
Toda, Risaku; White, Victor E.; Manohara, Harish; Patterson, Keith D.; Yamamoto, Namiko; Gdoutos, Eleftherios; Steeves, John B.; Daraio, Chiara; Pellegrino, Sergio
2013-01-01
Previously, it was difficult to fabricate deformable mirrors made by piezoelectric actuators. This is because numerous actuators need to be precisely assembled to control the surface shape of the mirror. Two approaches have been developed. Both approaches begin by depositing a stack of piezoelectric films and electrodes over a silicon wafer substrate. In the first approach, the silicon wafer is removed initially by plasmabased reactive ion etching (RIE), and non-plasma dry etching with xenon difluoride (XeF2). In the second approach, the actuator film stack is immersed in a liquid such as deionized water. The adhesion between the actuator film stack and the substrate is relatively weak. Simply by seeping liquid between the film and the substrate, the actuator film stack is gently released from the substrate. The deformable mirror contains multiple piezoelectric membrane layers as well as multiple electrode layers (some are patterned and some are unpatterned). At the piezolectric layer, polyvinylidene fluoride (PVDF), or its co-polymer, poly(vinylidene fluoride trifluoroethylene P(VDF-TrFE) is used. The surface of the mirror is coated with a reflective coating. The actuator film stack is fabricated on silicon, or silicon on insulator (SOI) substrate, by repeatedly spin-coating the PVDF or P(VDFTrFE) solution and patterned metal (electrode) deposition. In the first approach, the actuator film stack is prepared on SOI substrate. Then, the thick silicon (typically 500-micron thick and called handle silicon) of the SOI wafer is etched by a deep reactive ion etching process tool (SF6-based plasma etching). This deep RIE stops at the middle SiO2 layer. The middle SiO2 layer is etched by either HF-based wet etching or dry plasma etch. The thin silicon layer (generally called a device layer) of SOI is removed by XeF2 dry etch. This XeF2 etch is very gentle and extremely selective, so the released mirror membrane is not damaged. It is possible to replace SOI with silicon
Stability and error estimation for Component Adaptive Grid methods
NASA Technical Reports Server (NTRS)
Oliger, Joseph; Zhu, Xiaolei
1994-01-01
Component adaptive grid (CAG) methods for solving hyperbolic partial differential equations (PDE's) are discussed in this paper. Applying recent stability results for a class of numerical methods on uniform grids. The convergence of these methods for linear problems on component adaptive grids is established here. Furthermore, the computational error can be estimated on CAG's using the stability results. Using these estimates, the error can be controlled on CAG's. Thus, the solution can be computed efficiently on CAG's within a given error tolerance. Computational results for time dependent linear problems in one and two space dimensions are presented.
Contrast-based sensorless adaptive optics for retinal imaging.
Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew
2015-09-01
Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes. PMID:26417525
An Adaptive De-Aliasing Strategy for Discontinuous Galerkin methods
NASA Astrophysics Data System (ADS)
Beck, Andrea; Flad, David; Frank, Hannes; Munz, Claus-Dieter
2015-11-01
Discontinuous Galerkin methods combine the accuracy of a local polynomial representation with the geometrical flexibility of an element-based discretization. In combination with their excellent parallel scalability, these methods are currently of great interest for DNS and LES. For high order schemes, the dissipation error approaches a cut-off behavior, which allows an efficient wave resolution per degree of freedom, but also reduces robustness against numerical errors. One important source of numerical error is the inconsistent discretization of the non-linear convective terms, which results in aliasing of kinetic energy and solver instability. Consistent evaluation of the inner products prevents this form of error, but is computationally very expensive. In this talk, we discuss the need for a consistent de-aliasing to achieve a neutrally stable scheme, and present a novel strategy for recovering a part of the incurred computational costs. By implementing the de-aliasing operation through a cell-local projection filter, we can perform adaptive de-aliasing in space and time, based on physically motivated indicators. We will present results for a homogeneous isotropic turbulence and the Taylor-Green vortex flow, and discuss implementation details, accuracy and efficiency.
Analyzing Hedges in Verbal Communication: An Adaptation-Based Approach
ERIC Educational Resources Information Center
Wang, Yuling
2010-01-01
Based on Adaptation Theory, the article analyzes the production process of hedges. The procedure consists of the continuous making of choices in linguistic forms and communicative strategies. These choices are made just for adaptation to the contextual correlates. Besides, the adaptation process is dynamic, intentional and bidirectional.
Adaptive DFT-Based Interferometer Fringe Tracking
NASA Astrophysics Data System (ADS)
Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.
An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA) Observatory at Mount Hopkins, Arizona. The system can minimize the optical path differences (OPDs) for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier-transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on offline data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse. One example of such an application might be to the field of thin-film measurement by ellipsometry, using a broadband light source and a Fourier-transform spectrometer to detect the resulting fringe patterns.
On Accuracy of Adaptive Grid Methods for Captured Shocks
NASA Technical Reports Server (NTRS)
Yamaleev, Nail K.; Carpenter, Mark H.
2002-01-01
The accuracy of two grid adaptation strategies, grid redistribution and local grid refinement, is examined by solving the 2-D Euler equations for the supersonic steady flow around a cylinder. Second- and fourth-order linear finite difference shock-capturing schemes, based on the Lax-Friedrichs flux splitting, are used to discretize the governing equations. The grid refinement study shows that for the second-order scheme, neither grid adaptation strategy improves the numerical solution accuracy compared to that calculated on a uniform grid with the same number of grid points. For the fourth-order scheme, the dominant first-order error component is reduced by the grid adaptation, while the design-order error component drastically increases because of the grid nonuniformity. As a result, both grid adaptation techniques improve the numerical solution accuracy only on the coarsest mesh or on very fine grids that are seldom found in practical applications because of the computational cost involved. Similar error behavior has been obtained for the pressure integral across the shock. A simple analysis shows that both grid adaptation strategies are not without penalties in the numerical solution accuracy. Based on these results, a new grid adaptation criterion for captured shocks is proposed.
Evaluation of Adaptive Subdivision Method on Mobile Device
NASA Astrophysics Data System (ADS)
Rahim, Mohd Shafry Mohd; Isa, Siti Aida Mohd; Rehman, Amjad; Saba, Tanzila
2013-06-01
Recently, there are significant improvements in the capabilities of mobile devices; but rendering large 3D object is still tedious because of the constraint in resources of mobile devices. To reduce storage requirement, 3D object is simplified but certain area of curvature is compromised and the surface will not be smooth. Therefore a method to smoother selected area of a curvature is implemented. One of the popular methods is adaptive subdivision method. Experiments are performed using two data with results based on processing time, rendering speed and the appearance of the object on the devices. The result shows a downfall in frame rate performance due to the increase in the number of triangles with each level of iteration while the processing time of generating the new mesh also significantly increase. Since there is a difference in screen size between the devices the surface on the iPhone appears to have more triangles and more compact than the surface displayed on the iPad. [Figure not available: see fulltext.
NASA Astrophysics Data System (ADS)
Liu, Hong; Mo, Yu L.
1998-08-01
There are many textures such as woven fabrics having repeating Textron. In order to handle the textural characteristics of images with defects, this paper proposes a new method based on 2D wavelet transform. In the method, a new concept of different adaptive wavelet bases is used to match the texture pattern. The 2D wavelet transform has two different adaptive orthonormal wavelet bases for rows and columns which differ from Daubechies wavelet bases. The orthonormal wavelet bases for rows and columns are generated by genetic algorithm. The experiment result demonstrate the ability of the different adaptive wavelet bases to characterize the texture and locate the defects in the texture.
Adaptive, Model-Based Monitoring and Threat Detection
NASA Astrophysics Data System (ADS)
Valdes, Alfonso; Skinner, Keith
2002-09-01
We explore the suitability of model-based probabilistic techniques, such as Bayes networks, to the field of intrusion detection and alert report correlation. We describe a network intrusion detection system (IDS) using Bayes inference, wherein the knowledge base is encoded not as rules but as conditional probability relations between observables and hypotheses of normal and malicious usage. The same high-performance Bayes inference library was employed in a component of the Mission-Based Correlation effort, using an initial knowledge base that adaptively learns the security administrator's preference for alert priority and rank. Another major effort demonstrated probabilistic techniques in heterogeneous sensor correlation. We provide results for simulated attack data, live traffic, and the CyberPanel Grand Challenge Problem. Our results establish that model-based probabilistic techniques are an important complementary capability to signature-based methods in detection and correlation.
Final Report: Symposium on Adaptive Methods for Partial Differential Equations
Pernice, M.; Johnson, C.R.; Smith, P.J.; Fogelson, A.
1998-12-10
OAK-B135 Final Report: Symposium on Adaptive Methods for Partial Differential Equations. Complex physical phenomena often include features that span a wide range of spatial and temporal scales. Accurate simulation of such phenomena can be difficult to obtain, and computations that are under-resolved can even exhibit spurious features. While it is possible to resolve small scale features by increasing the number of grid points, global grid refinement can quickly lead to problems that are intractable, even on the largest available computing facilities. These constraints are particularly severe for three dimensional problems that involve complex physics. One way to achieve the needed resolution is to refine the computational mesh locally, in only those regions where enhanced resolution is required. Adaptive solution methods concentrate computational effort in regions where it is most needed. These methods have been successfully applied to a wide variety of problems in computational science and engineering. Adaptive methods can be difficult to implement, prompting the development of tools and environments to facilitate their use. To ensure that the results of their efforts are useful, algorithm and tool developers must maintain close communication with application specialists. Conversely it remains difficult for application specialists who are unfamiliar with the methods to evaluate the trade-offs between the benefits of enhanced local resolution and the effort needed to implement an adaptive solution method.
Visual-adaptation-mechanism based underwater object extraction
NASA Astrophysics Data System (ADS)
Chen, Zhe; Wang, Huibin; Xu, Lizhong; Shen, Jie
2014-03-01
Due to the major obstacles originating from the strong light absorption and scattering in a dynamic underwater environment, underwater optical information acquisition and processing suffer from effects such as limited range, non-uniform lighting, low contrast, and diminished colors, causing it to become the bottleneck for marine scientific research and projects. After studying and generalizing the underwater biological visual mechanism, we explore its advantages in light adaption which helps animals to precisely sense the underwater scene and recognize their prey or enemies. Then, aiming to transform the significant advantage of the visual adaptation mechanism into underwater computer vision tasks, a novel knowledge-based information weighting fusion model is established for underwater object extraction. With this bionic model, the dynamical adaptability is given to the underwater object extraction task, making them more robust to the variability of the optical properties in different environments. The capability of the proposed method to adapt to the underwater optical environments is shown, and its outperformance for the object extraction is demonstrated by comparison experiments.
Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.
Zhang, Yanjun; Tao, Gang; Chen, Mou
2016-09-01
This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method. PMID:26285223
Goffin, Mark A.; Buchan, Andrew G.; Dargaville, Steven; Pain, Christopher C.; Smith, Paul N.; Smedley-Stevenson, Richard P.
2015-01-15
A method for applying goal-based adaptive methods to the angular resolution of the neutral particle transport equation is presented. The methods are applied to an octahedral wavelet discretisation of the spherical angular domain which allows for anisotropic resolution. The angular resolution is adapted across both the spatial and energy dimensions. The spatial domain is discretised using an inner-element sub-grid scale finite element method. The goal-based adaptive methods optimise the angular discretisation to minimise the error in a specific functional of the solution. The goal-based error estimators require the solution of an adjoint system to determine the importance to the specified functional. The error estimators and the novel methods to calculate them are described. Several examples are presented to demonstrate the effectiveness of the methods. It is shown that the methods can significantly reduce the number of unknowns and computational time required to obtain a given error. The novelty of the work is the use of goal-based adaptive methods to obtain anisotropic resolution in the angular domain for solving the transport equation. -- Highlights: •Wavelet angular discretisation used to solve transport equation. •Adaptive method developed for the wavelet discretisation. •Anisotropic angular resolution demonstrated through the adaptive method. •Adaptive method provides improvements in computational efficiency.
A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Hydrodynamics
Anderson, R W; Pember, R B; Elliott, N S
2004-01-28
A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the combined ALE-AMR method hinge upon the integration of traditional AMR techniques with both staggered grid Lagrangian operators as well as elliptic relaxation operators on moving, deforming mesh hierarchies. Numerical examples demonstrate the utility of the method in performing detailed three-dimensional shock-driven instability calculations.
A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Hydrodynamics
Anderson, R W; Pember, R B; Elliott, N S
2002-10-19
A new method that combines staggered grid Arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the combined ALE-AMR method hinge upon the integration of traditional AMR techniques with both staggered grid Lagrangian operators as well as elliptic relaxation operators on moving, deforming mesh hierarchies. Numerical examples demonstrate the utility of the method in performing detailed three-dimensional shock-driven instability calculations.
Speckle reduction in optical coherence tomography by adaptive total variation method
NASA Astrophysics Data System (ADS)
Wu, Tong; Shi, Yaoyao; Liu, Youwen; He, Chongjun
2015-12-01
An adaptive total variation method based on the combination of speckle statistics and total variation restoration is proposed and developed for reducing speckle noise in optical coherence tomography (OCT) images. The statistical distribution of the speckle noise in OCT image is investigated and measured. With the measured parameters such as the mean value and variance of the speckle noise, the OCT image is restored by the adaptive total variation restoration method. The adaptive total variation restoration algorithm was applied to the OCT images of a volunteer's hand skin, which showed effective speckle noise reduction and image quality improvement. For image quality comparison, the commonly used median filtering method was also applied to the same images to reduce the speckle noise. The measured results demonstrate the superior performance of the adaptive total variation restoration method in terms of image signal-to-noise ratio, equivalent number of looks, contrast-to-noise ratio, and mean square error.
Adaptive computational methods for SSME internal flow analysis
NASA Technical Reports Server (NTRS)
Oden, J. T.
1986-01-01
Adaptive finite element methods for the analysis of classes of problems in compressible and incompressible flow of interest in SSME (space shuttle main engine) analysis and design are described. The general objective of the adaptive methods is to improve and to quantify the quality of numerical solutions to the governing partial differential equations of fluid dynamics in two-dimensional cases. There are several different families of adaptive schemes that can be used to improve the quality of solutions in complex flow simulations. Among these are: (1) r-methods (node-redistribution or moving mesh methods) in which a fixed number of nodal points is allowed to migrate to points in the mesh where high error is detected; (2) h-methods, in which the mesh size h is automatically refined to reduce local error; and (3) p-methods, in which the local degree p of the finite element approximation is increased to reduce local error. Two of the three basic techniques have been studied in this project: an r-method for steady Euler equations in two dimensions and a p-method for transient, laminar, viscous incompressible flow. Numerical results are presented. A brief introduction to residual methods of a-posterior error estimation is also given and some pertinent conclusions of the study are listed.
Component-based handprint segmentation using adaptive writing style model
NASA Astrophysics Data System (ADS)
Garris, Michael D.
1997-04-01
Building upon the utility of connected components, NIST has designed a new character segmentor based on statistically modeling the style of a person's handwriting. Simple spatial features capture the characteristics of a particular writer's style of handprint, enabling the new method to maintain a traditional character-level segmentation philosophy without the integration of recognition or the use of oversegmentation and linguistic postprocessing. Estimates for stroke width and character height are used to compute aspect ratio and standard stroke count features that adapt to the writer's style at the field level. The new method has been developed with a predetermined set of fuzzy rules making the segmentor much less fragile and much more adaptive, and the new method successfully reconstructs fragmented characters as well as splits touching characters. The new segmentor was integrated into the NIST public domain form-based handprint recognition systems and then tested on a set of 490 handwriting sample forms found in NIST special database 19. When compared to a simple component-based segmentor, the new adaptable method improved the overall recognition of handprinted digits by 3.4 percent and field level recognition by 6.9 percent, while effectively reducing deletion errors by 82 percent. The same program code and set of parameters successfully segments sequences of uppercase and lowercase characters without any context-based tuning. While not as dramatic as digits, the recognition of uppercase and lowercase characters improved by 1.7 percent and 1.3 percent respectively. The segmentor maintains a relatively straight-forward and logical process flow avoiding convolutions of encoded exceptions as is common in expert systems. As a result, the new segmentor operates very efficiently, and throughput as high as 362 characters per second can be achieved. Letters and numbers are constructed from a predetermined configuration of a relatively small number of strokes. Results
Adaptive muffler based on controlled flow valves.
Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij
2015-06-01
An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462
Adaptive windowed range-constrained Otsu method using local information
NASA Astrophysics Data System (ADS)
Zheng, Jia; Zhang, Dinghua; Huang, Kuidong; Sun, Yuanxi; Tang, Shaojie
2016-01-01
An adaptive windowed range-constrained Otsu method using local information is proposed for improving the performance of image segmentation. First, the reason why traditional thresholding methods do not perform well in the segmentation of complicated images is analyzed. Therein, the influences of global and local thresholdings on the image segmentation are compared. Second, two methods that can adaptively change the size of the local window according to local information are proposed by us. The characteristics of the proposed methods are analyzed. Thereby, the information on the number of edge pixels in the local window of the binarized variance image is employed to adaptively change the local window size. Finally, the superiority of the proposed method over other methods such as the range-constrained Otsu, the active contour model, the double Otsu, the Bradley's, and the distance-regularized level set evolution is demonstrated. It is validated by the experiments that the proposed method can keep more details and acquire much more satisfying area overlap measure as compared with the other conventional methods.
Likelihood Methods for Adaptive Filtering and Smoothing. Technical Report #455.
ERIC Educational Resources Information Center
Butler, Ronald W.
The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…
A Conditional Exposure Control Method for Multidimensional Adaptive Testing
ERIC Educational Resources Information Center
Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A.
2009-01-01
In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…
ICASE/LaRC Workshop on Adaptive Grid Methods
NASA Technical Reports Server (NTRS)
South, Jerry C., Jr. (Editor); Thomas, James L. (Editor); Vanrosendale, John (Editor)
1995-01-01
Solution-adaptive grid techniques are essential to the attainment of practical, user friendly, computational fluid dynamics (CFD) applications. In this three-day workshop, experts gathered together to describe state-of-the-art methods in solution-adaptive grid refinement, analysis, and implementation; to assess the current practice; and to discuss future needs and directions for research. This was accomplished through a series of invited and contributed papers. The workshop focused on a set of two-dimensional test cases designed by the organizers to aid in assessing the current state of development of adaptive grid technology. In addition, a panel of experts from universities, industry, and government research laboratories discussed their views of needs and future directions in this field.
A massively parallel adaptive finite element method with dynamic load balancing
Devine, K.D.; Flaherty, J.E.; Wheat, S.R.; Maccabe, A.B.
1993-12-31
The authors construct massively parallel adaptive finite element methods for the solution of hyperbolic conservation laws. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. The resulting method is of high order and may be parallelized efficiently on MIMD computers. They demonstrate parallel efficiency through computations on a 1024-processor nCUBE/2 hypercube. They present results using adaptive p-refinement to reduce the computational cost of the method, and tiling, a dynamic, element-based data migration system that maintains global load balance of the adaptive method by overlapping neighborhoods of processors that each perform local balancing.
Creating Evidence-Based Research in Adapted Physical Activity
ERIC Educational Resources Information Center
Reid, Greg; Bouffard, Marcel; MacDonald, Catherine
2012-01-01
Professional practice guided by the best research evidence is a usually referred to as evidence-based practice. The aim of the present paper is to describe five fundamental beliefs of adapted physical activity practices that should be considered in an 8-step research model to create evidence-based research in adapted physical activity. The five…
Turbulent Output-Based Anisotropic Adaptation
NASA Technical Reports Server (NTRS)
Park, Michael A.; Carlson, Jan-Renee
2010-01-01
Controlling discretization error is a remaining challenge for computational fluid dynamics simulation. Grid adaptation is applied to reduce estimated discretization error in drag or pressure integral output functions. To enable application to high O(10(exp 7)) Reynolds number turbulent flows, a hybrid approach is utilized that freezes the near-wall boundary layer grids and adapts the grid away from the no slip boundaries. The hybrid approach is not applicable to problems with under resolved initial boundary layer grids, but is a powerful technique for problems with important off-body anisotropic features. Supersonic nozzle plume, turbulent flat plate, and shock-boundary layer interaction examples are presented with comparisons to experimental measurements of pressure and velocity. Adapted grids are produced that resolve off-body features in locations that are not known a priori.
Adaptable Metadata Rich IO Methods for Portable High Performance IO
Lofstead, J.; Zheng, Fang; Klasky, Scott A; Schwan, Karsten
2009-01-01
Since IO performance on HPC machines strongly depends on machine characteristics and configuration, it is important to carefully tune IO libraries and make good use of appropriate library APIs. For instance, on current petascale machines, independent IO tends to outperform collective IO, in part due to bottlenecks at the metadata server. The problem is exacerbated by scaling issues, since each IO library scales differently on each machine, and typically, operates efficiently to different levels of scaling on different machines. With scientific codes being run on a variety of HPC resources, efficient code execution requires us to address three important issues: (1) end users should be able to select the most efficient IO methods for their codes, with minimal effort in terms of code updates or alterations; (2) such performance-driven choices should not prevent data from being stored in the desired file formats, since those are crucial for later data analysis; and (3) it is important to have efficient ways of identifying and selecting certain data for analysis, to help end users cope with the flood of data produced by high end codes. This paper employs ADIOS, the ADaptable IO System, as an IO API to address (1)-(3) above. Concerning (1), ADIOS makes it possible to independently select the IO methods being used by each grouping of data in an application, so that end users can use those IO methods that exhibit best performance based on both IO patterns and the underlying hardware. In this paper, we also use this facility of ADIOS to experimentally evaluate on petascale machines alternative methods for high performance IO. Specific examples studied include methods that use strong file consistency vs. delayed parallel data consistency, as that provided by MPI-IO or POSIX IO. Concerning (2), to avoid linking IO methods to specific file formats and attain high IO performance, ADIOS introduces an efficient intermediate file format, termed BP, which can be converted, at small
Tsunami modelling with adaptively refined finite volume methods
LeVeque, R.J.; George, D.L.; Berger, M.J.
2011-01-01
Numerical modelling of transoceanic tsunami propagation, together with the detailed modelling of inundation of small-scale coastal regions, poses a number of algorithmic challenges. The depth-averaged shallow water equations can be used to reduce this to a time-dependent problem in two space dimensions, but even so it is crucial to use adaptive mesh refinement in order to efficiently handle the vast differences in spatial scales. This must be done in a 'wellbalanced' manner that accurately captures very small perturbations to the steady state of the ocean at rest. Inundation can be modelled by allowing cells to dynamically change from dry to wet, but this must also be done carefully near refinement boundaries. We discuss these issues in the context of Riemann-solver-based finite volume methods for tsunami modelling. Several examples are presented using the GeoClaw software, and sample codes are available to accompany the paper. The techniques discussed also apply to a variety of other geophysical flows. ?? 2011 Cambridge University Press.
An adaptive over/under data combination method
NASA Astrophysics Data System (ADS)
He, Jian-Wei; Lu, Wen-Kai; Li, Zhong-Xiao
2013-12-01
The traditional "dephase and sum" algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm sea surface assumption. Hence, the traditional "dephase and sum" algorithms might produce poor-quality results in rough sea conditions. We propose an adaptive over/under data combination method, which adaptively estimates the amplitude spectrum of the ghost operator from the over/under data, and then over/under data combinations are implemented using the estimated ghost operators. A synthetic single shot gather is used to verify the performance of the proposed method in rough sea surface conditions and a real triple over/under dataset demonstrates the method performance.
Final Report: Symposium on Adaptive Methods for Partial Differential Equations
Pernice, Michael; Johnson, Christopher R.; Smith, Philip J.; Fogelson, Aaron
1998-12-08
Complex physical phenomena often include features that span a wide range of spatial and temporal scales. Accurate simulation of such phenomena can be difficult to obtain, and computations that are under-resolved can even exhibit spurious features. While it is possible to resolve small scale features by increasing the number of grid points, global grid refinement can quickly lead to problems that are intractable, even on the largest available computing facilities. These constraints are particularly severe for three dimensional problems that involve complex physics. One way to achieve the needed resolution is to refine the computational mesh locally, in only those regions where enhanced resolution is required. Adaptive solution methods concentrate computational effort in regions where it is most needed. These methods have been successfully applied to a wide variety of problems in computational science and engineering. Adaptive methods can be difficult to implement, prompting the development of tools and environments to facilitate their use. To ensure that the results of their efforts are useful, algorithm and tool developers must maintain close communication with application specialists. Conversely it remains difficult for application specialists who are unfamiliar with the methods to evaluate the trade-offs between the benefits of enhanced local resolution and the effort needed to implement an adaptive solution method.
NASA Astrophysics Data System (ADS)
Feng, Xiao; Tang, Rui-chun; Zhai, Yi-li; Feng, Yu-qing; Hong, Bo-hai
2013-07-01
Multimedia adaptation decision-taking techniques based on context are considered. Constraint satisfaction problem-Based Content Adaptation Algorithm (CBCAA) is proposed. First the algorithm obtains and classifies context information using MPEG-21; then it builds the constraint model according to different types of context information, constraint satisfaction method is used to acquire Media Description Decision Set (MDDS); finally a bit-stream adaptation engine performs the multimedia transcoding. Simulation results prove that the presented algorithm offers an efficient solution for personalized multimedia adaptation in heterogeneous environments.
Adaptive SVD-Based Digital Image Watermarking
NASA Astrophysics Data System (ADS)
Shirvanian, Maliheh; Torkamani Azar, Farah
Digital data utilization along with the increase popularity of the Internet has facilitated information sharing and distribution. However, such applications have also raised concern about copyright issues and unauthorized modification and distribution of digital data. Digital watermarking techniques which are proposed to solve these problems hide some information in digital media and extract it whenever needed to indicate the data owner. In this paper a new method of image watermarking based on singular value decomposition (SVD) of images is proposed which considers human visual system prior to embedding watermark by segmenting the original image into several blocks of different sizes, with more density in the edges of the image. In this way the original image quality is preserved in the watermarked image. Additional advantages of the proposed technique are large capacity of watermark embedding and robustness of the method against different types of image manipulation techniques.
Parallel 3D Mortar Element Method for Adaptive Nonconforming Meshes
NASA Technical Reports Server (NTRS)
Feng, Huiyu; Mavriplis, Catherine; VanderWijngaart, Rob; Biswas, Rupak
2004-01-01
High order methods are frequently used in computational simulation for their high accuracy. An efficient way to avoid unnecessary computation in smooth regions of the solution is to use adaptive meshes which employ fine grids only in areas where they are needed. Nonconforming spectral elements allow the grid to be flexibly adjusted to satisfy the computational accuracy requirements. The method is suitable for computational simulations of unsteady problems with very disparate length scales or unsteady moving features, such as heat transfer, fluid dynamics or flame combustion. In this work, we select the Mark Element Method (MEM) to handle the non-conforming interfaces between elements. A new technique is introduced to efficiently implement MEM in 3-D nonconforming meshes. By introducing an "intermediate mortar", the proposed method decomposes the projection between 3-D elements and mortars into two steps. In each step, projection matrices derived in 2-D are used. The two-step method avoids explicitly forming/deriving large projection matrices for 3-D meshes, and also helps to simplify the implementation. This new technique can be used for both h- and p-type adaptation. This method is applied to an unsteady 3-D moving heat source problem. With our new MEM implementation, mesh adaptation is able to efficiently refine the grid near the heat source and coarsen the grid once the heat source passes. The savings in computational work resulting from the dynamic mesh adaptation is demonstrated by the reduction of the the number of elements used and CPU time spent. MEM and mesh adaptation, respectively, bring irregularity and dynamics to the computer memory access pattern. Hence, they provide a good way to gauge the performance of computer systems when running scientific applications whose memory access patterns are irregular and unpredictable. We select a 3-D moving heat source problem as the Unstructured Adaptive (UA) grid benchmark, a new component of the NAS Parallel
Web-Based Adaptive Testing System (WATS) for Classifying Students Academic Ability
ERIC Educational Resources Information Center
Lee, Jaemu; Park, Sanghoon; Kim, Kwangho
2012-01-01
Computer Adaptive Testing (CAT) has been highlighted as a promising assessment method to fulfill two testing purposes: estimating student academic ability and classifying student academic level. In this paper, assessment for we introduced the Web-based Adaptive Testing System (WATS) developed to support a cost effective assessment for classifying…
Methods for prismatic/tetrahedral grid generation and adaptation
NASA Astrophysics Data System (ADS)
Kallinderis, Y.
1995-10-01
The present work involves generation of hybrid prismatic/tetrahedral grids for complex 3-D geometries including multi-body domains. The prisms cover the region close to each body's surface, while tetrahedra are created elsewhere. Two developments are presented for hybrid grid generation around complex 3-D geometries. The first is a new octree/advancing front type of method for generation of the tetrahedra of the hybrid mesh. The main feature of the present advancing front tetrahedra generator that is different from previous such methods is that it does not require the creation of a background mesh by the user for the determination of the grid-spacing and stretching parameters. These are determined via an automatically generated octree. The second development is a method for treating the narrow gaps in between different bodies in a multiply-connected domain. This method is applied to a two-element wing case. A High Speed Civil Transport (HSCT) type of aircraft geometry is considered. The generated hybrid grid required only 170 K tetrahedra instead of an estimated two million had a tetrahedral mesh been used in the prisms region as well. A solution adaptive scheme for viscous computations on hybrid grids is also presented. A hybrid grid adaptation scheme that employs both h-refinement and redistribution strategies is developed to provide optimum meshes for viscous flow computations. Grid refinement is a dual adaptation scheme that couples 3-D, isotropic division of tetrahedra and 2-D, directional division of prisms.
Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction
NASA Technical Reports Server (NTRS)
Campbell, Richard L.; Carter, Melissa B.; Deere, Karen A.; Waithe, Kenrick A.
2008-01-01
This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes.
Adaptive [theta]-methods for pricing American options
NASA Astrophysics Data System (ADS)
Khaliq, Abdul Q. M.; Voss, David A.; Kazmi, Kamran
2008-12-01
We develop adaptive [theta]-methods for solving the Black-Scholes PDE for American options. By adding a small, continuous term, the Black-Scholes PDE becomes an advection-diffusion-reaction equation on a fixed spatial domain. Standard implementation of [theta]-methods would require a Newton-type iterative procedure at each time step thereby increasing the computational complexity of the methods. Our linearly implicit approach avoids such complications. We establish a general framework under which [theta]-methods satisfy a discrete version of the positivity constraint characteristic of American options, and numerically demonstrate the sensitivity of the constraint. The positivity results are established for the single-asset and independent two-asset models. In addition, we have incorporated and analyzed an adaptive time-step control strategy to increase the computational efficiency. Numerical experiments are presented for one- and two-asset American options, using adaptive exponential splitting for two-asset problems. The approach is compared with an iterative solution of the two-asset problem in terms of computational efficiency.
An Adaptive Unstructured Grid Method by Grid Subdivision, Local Remeshing, and Grid Movement
NASA Technical Reports Server (NTRS)
Pirzadeh, Shahyar Z.
1999-01-01
An unstructured grid adaptation technique has been developed and successfully applied to several three dimensional inviscid flow test cases. The approach is based on a combination of grid subdivision, local remeshing, and grid movement. For solution adaptive grids, the surface triangulation is locally refined by grid subdivision, and the tetrahedral grid in the field is partially remeshed at locations of dominant flow features. A grid redistribution strategy is employed for geometric adaptation of volume grids to moving or deforming surfaces. The method is automatic and fast and is designed for modular coupling with different solvers. Several steady state test cases with different inviscid flow features were tested for grid/solution adaptation. In all cases, the dominant flow features, such as shocks and vortices, were accurately and efficiently predicted with the present approach. A new and robust method of moving tetrahedral "viscous" grids is also presented and demonstrated on a three-dimensional example.
Robust flicker evaluation method for low power adaptive dimming LCDs
NASA Astrophysics Data System (ADS)
Kim, Seul-Ki; Song, Seok-Jeong; Nam, Hyoungsik
2015-05-01
This paper describes a robust dimming flicker evaluation method of adaptive dimming algorithms for low power liquid crystal displays (LCDs). While the previous methods use sum of square difference (SSD) values without excluding the image sequence information, the proposed modified SSD (mSSD) values are obtained only with the dimming flicker effects by making use of differential images. The proposed scheme is verified for eight dimming configurations of two dimming level selection methods and four temporal filters over three test videos. Furthermore, a new figure of merit is introduced to cover the dimming flicker as well as image qualities and power consumption.
NASA Astrophysics Data System (ADS)
Cai, Xiaochun; Hu, Yihua; Wang, Peng; Sun, Dujuan; Hu, Guilan
2009-10-01
The paper presents an adaptive segmentation and activity classification method for filamentous fungi image. Firstly, an adaptive structuring element (SE) construction algorithm is proposed for image background suppression. Based on watershed transform method, the color labeled segmentation of fungi image is taken. Secondly, the fungi elements feature space is described and the feature set for fungi hyphae activity classification is extracted. The growth rate evaluation of fungi hyphae is achieved by using SVM classifier. Some experimental results demonstrate that the proposed method is effective for filamentous fungi image processing.
Adaptive domain decomposition methods for advection-diffusion problems
Carlenzoli, C.; Quarteroni, A.
1995-12-31
Domain decomposition methods can perform poorly on advection-diffusion equations if diffusion is dominated by advection. Indeed, the hyperpolic part of the equations could affect the behavior of iterative schemes among subdomains slowing down dramatically their rate of convergence. Taking into account the direction of the characteristic lines we introduce suitable adaptive algorithms which are stable with respect to the magnitude of the convective field in the equations and very effective on bear boundary value problems.
Adaptive control based on retrospective cost optimization
NASA Technical Reports Server (NTRS)
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
2012-01-01
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
NASA Astrophysics Data System (ADS)
Domingues, Margarete O.; Gomes, Anna Karina F.; Mendes, Odim; Schneider, Kai
2013-10-01
We present a new adaptive multiresoltion method for the numerical simulation of ideal magnetohydrodynamics. The governing equations, i.e., the compressible Euler equations coupled with the Maxwell equations are discretized using a finite volume scheme on a two-dimensional Cartesian mesh. Adaptivity in space is obtained via multiresolution analysis, which allows the reliable introduction of a locally refined mesh while controlling the error. The explicit time discretization uses a compact Runge-Kutta method for local time stepping and an embedded Runge-Kutta scheme for automatic time step control. An extended generalized Lagrangian multiplier approach with the mixed hyperbolic-parabolic correction type is used to control the incompressibility of the magnetic field. Applications to a two-dimensional problem illustrate the properties of the method. Memory savings and numerical divergences of the magnetic field are reported and the accuracy of the adaptive computations is assessed by comparing with the available exact solution. This work was supported by the contract SiCoMHD (ANR-Blanc 2011-045).
Image Watermarking Based on Adaptive Models of Human Visual Perception
NASA Astrophysics Data System (ADS)
Khawne, Amnach; Hamamoto, Kazuhiko; Chitsobhuk, Orachat
This paper proposes a digital image watermarking based on adaptive models of human visual perception. The algorithm exploits the local activities estimated from wavelet coefficients of each subband to adaptively control the luminance masking. The adaptive luminance is thus delicately combined with the contrast masking and edge detection and adopted as a visibility threshold. With the proposed combination of adaptive visual sensitivity parameters, the proposed perceptual model can be more appropriate to the different characteristics of various images. The weighting function is chosen such that the fidelity, imperceptibility and robustness could be preserved without making any perceptual difference to the image quality.
A New Online Calibration Method for Multidimensional Computerized Adaptive Testing.
Chen, Ping; Wang, Chun
2016-09-01
Multidimensional-Method A (M-Method A) has been proposed as an efficient and effective online calibration method for multidimensional computerized adaptive testing (MCAT) (Chen & Xin, Paper presented at the 78th Meeting of the Psychometric Society, Arnhem, The Netherlands, 2013). However, a key assumption of M-Method A is that it treats person parameter estimates as their true values, thus this method might yield erroneous item calibration when person parameter estimates contain non-ignorable measurement errors. To improve the performance of M-Method A, this paper proposes a new MCAT online calibration method, namely, the full functional MLE-M-Method A (FFMLE-M-Method A). This new method combines the full functional MLE (Jones & Jin in Psychometrika 59:59-75, 1994; Stefanski & Carroll in Annals of Statistics 13:1335-1351, 1985) with the original M-Method A in an effort to correct for the estimation error of ability vector that might otherwise adversely affect the precision of item calibration. Two correction schemes are also proposed when implementing the new method. A simulation study was conducted to show that the new method generated more accurate item parameter estimation than the original M-Method A in almost all conditions. PMID:26608960
Alimohammadi, Nasrollah; Maleki, Bibi; Shahriari, Mohsen; Chitsaz, Ahmad
2015-01-01
Background: Stroke is a stressful event with several functional, physical, psychological, social, and economic problems that affect individuals’ different living balances. With coping strategies, patients try to control these problems and return to their natural life. The aim of this study is to investigate the effect of a care plan based on Roy adaptation model biological dimension on stroke patients’ physiologic adaptation level. Materials and Methods: This study is a clinical trial in which 50 patients, affected by brain stroke and being admitted in the neurology ward of Kashani and Alzahra hospitals, were randomly assigned to control and study groups in Isfahan in 2013. Roy adaptation model care plan was administered in biological dimension in the form of four sessions and phone call follow-ups for 1 month. The forms related to Roy adaptation model were completed before and after intervention in the two groups. Chi-square test and t-test were used to analyze the data through SPSS 18. Results: There was a significant difference in mean score of adaptation in physiological dimension in the study group after intervention (P < 0.001) compared to before intervention. Comparison of the mean scores of changes of adaptation in the patients affected by brain stroke in the study and control groups showed a significant increase in physiological dimension in the study group by 47.30 after intervention (P < 0.001). Conclusions: The results of study showed that Roy adaptation model biological dimension care plan can result in an increase in adaptation in patients with stroke in physiological dimension. Nurses can use this model for increasing patients’ adaptation. PMID:25878708
A self-adaptive-grid method with application to airfoil flow
NASA Technical Reports Server (NTRS)
Nakahashi, K.; Deiwert, G. S.
1985-01-01
A self-adaptive-grid method is described that is suitable for multidimensional steady and unsteady computations. Based on variational principles, a spring analogy is used to redistribute grid points in an optimal sense to reduce the overall solution error. User-specified parameters, denoting both maximum and minimum permissible grid spacings, are used to define the all-important constants, thereby minimizing the empiricism and making the method self-adaptive. Operator splitting and one-sided controls for orthogonality and smoothness are used to make the method practical, robust, and efficient. Examples are included for both steady and unsteady viscous flow computations about airfoils in two dimensions, as well as for a steady inviscid flow computation and a one-dimensional case. These examples illustrate the precise control the user has with the self-adaptive method and demonstrate a significant improvement in accuracy and quality of the solutions.
McClarren, Ryan G. Urbatsch, Todd J.
2009-09-01
In this paper we develop a robust implicit Monte Carlo (IMC) algorithm based on more accurately updating the linearized equilibrium radiation energy density. The method does not introduce oscillations in the solution and has the same limit as {delta}t{yields}{infinity} as the standard Fleck and Cummings IMC method. Moreover, the approach we introduce can be trivially added to current implementations of IMC by changing the definition of the Fleck factor. Using this new method we develop an adaptive scheme that uses either standard IMC or the modified method basing the adaptation on a zero-dimensional problem solved in each cell. Numerical results demonstrate that the new method can avoid the nonphysical overheating that occurs in standard IMC when the time step is large. The method also leads to decreased noise in the material temperature at the cost of a potential increase in the radiation temperature noise.
Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems
NASA Technical Reports Server (NTRS)
Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.
1979-01-01
The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.
Adaptive wavefront sensor based on the Talbot phenomenon.
Podanchuk, Dmytro V; Goloborodko, Andrey A; Kotov, Myhailo M; Kovalenko, Andrey V; Kurashov, Vitalij N; Dan'ko, Volodymyr P
2016-04-20
A new adaptive method of wavefront sensing is proposed and demonstrated. The method is based on the Talbot self-imaging effect, which is observed in an illuminating light beam with strong second-order aberration. Compensation of defocus and astigmatism is achieved with an appropriate choice of size of the rectangular unit cell of the diffraction grating, which is performed iteratively. A liquid-crystal spatial light modulator is used for this purpose. Self-imaging of rectangular grating in the astigmatic light beam is demonstrated experimentally. High-order aberrations are detected with respect to the compensated second-order aberration. The comparative results of wavefront sensing with a Shack-Hartmann sensor and the proposed sensor are adduced. PMID:27140122
Parallel, adaptive finite element methods for conservation laws
NASA Technical Reports Server (NTRS)
Biswas, Rupak; Devine, Karen D.; Flaherty, Joseph E.
1994-01-01
We construct parallel finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. A posteriori estimates of spatial errors are obtained by a p-refinement technique using superconvergence at Radau points. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We compare results using different limiting schemes and demonstrate parallel efficiency through computations on an NCUBE/2 hypercube. We also present results using adaptive h- and p-refinement to reduce the computational cost of the method.
Xiao, Jinjun; Li, Min; Zhang, Haipeng
2015-01-01
This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, a novel RAPCA method is developed to capture the common structure patterns based on intergraph matrix of the objects. Secondly, the robust similarity measure is proposed based on adaptive principal component. Finally, the robust registration algorithm is derived based on the RAPCA. The experimental results show that the proposed method is very effective in capturing the common structure patterns for image registration on real-world images. PMID:25960739
A NOISE ADAPTIVE FUZZY EQUALIZATION METHOD FOR PROCESSING SOLAR EXTREME ULTRAVIOLET IMAGES
Druckmueller, M.
2013-08-15
A new image enhancement tool ideally suited for the visualization of fine structures in extreme ultraviolet images of the corona is presented in this paper. The Noise Adaptive Fuzzy Equalization method is particularly suited for the exceptionally high dynamic range images from the Atmospheric Imaging Assembly instrument on the Solar Dynamics Observatory. This method produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform which are often used for that purpose.
Smoothed aggregation adaptive spectral element-based algebraic multigrid
2015-01-20
SAAMGE provides parallel methods for building multilevel hierarchies and solvers that can be used for elliptic equations with highly heterogeneous coefficients. Additionally, hierarchy adaptation is implemented allowing solving multiple problems with close coefficients without rebuilding the hierarchy.
Beam shaping for laser-based adaptive optics in astronomy.
Béchet, Clémentine; Guesalaga, Andrés; Neichel, Benoit; Fesquet, Vincent; González-Núñez, Héctor; Zúñiga, Sebastián; Escarate, Pedro; Guzman, Dani
2014-06-01
The availability and performance of laser-based adaptive optics (AO) systems are strongly dependent on the power and quality of the laser beam before being projected to the sky. Frequent and time-consuming alignment procedures are usually required in the laser systems with free-space optics to optimize the beam. Despite these procedures, significant distortions of the laser beam have been observed during the first two years of operation of the Gemini South multi-conjugate adaptive optics system (GeMS). A beam shaping concept with two deformable mirrors is investigated in order to provide automated optimization of the laser quality for astronomical AO. This study aims at demonstrating the correction of quasi-static aberrations of the laser, in both amplitude and phase, testing a prototype of this two-deformable mirror concept on GeMS. The paper presents the results of the preparatory study before the experimental phase. An algorithm to control amplitude and phase correction, based on phase retrieval techniques, is presented with a novel unwrapping method. Its performance is assessed via numerical simulations, using aberrations measured at GeMS as reference. The results predict effective amplitude and phase correction of the laser distortions with about 120 actuators per mirror and a separation of 1.4 m between the mirrors. The spot size is estimated to be reduced by up to 15% thanks to the correction. In terms of AO noise level, this has the same benefit as increasing the photon flux by 40%. PMID:24921496
A comparison of locally adaptive multigrid methods: LDC, FAC and FIC
NASA Technical Reports Server (NTRS)
Khadra, Khodor; Angot, Philippe; Caltagirone, Jean-Paul
1993-01-01
This study is devoted to a comparative analysis of three 'Adaptive ZOOM' (ZOom Overlapping Multi-level) methods based on similar concepts of hierarchical multigrid local refinement: LDC (Local Defect Correction), FAC (Fast Adaptive Composite), and FIC (Flux Interface Correction)--which we proposed recently. These methods are tested on two examples of a bidimensional elliptic problem. We compare, for V-cycle procedures, the asymptotic evolution of the global error evaluated by discrete norms, the corresponding local errors, and the convergence rates of these algorithms.
Lei, Xusheng; Li, Jingjing
2012-01-01
This paper presents an adaptive information fusion method to improve the accuracy and reliability of the altitude measurement information for small unmanned aerial rotorcraft during the landing process. Focusing on the low measurement performance of sensors mounted on small unmanned aerial rotorcraft, a wavelet filter is applied as a pre-filter to attenuate the high frequency noises in the sensor output. Furthermore, to improve altitude information, an adaptive extended Kalman filter based on a maximum a posteriori criterion is proposed to estimate measurement noise covariance matrix in real time. Finally, the effectiveness of the proposed method is proved by static tests, hovering flight and autonomous landing flight tests. PMID:23201993
Adaptive methods for nonlinear structural dynamics and crashworthiness analysis
NASA Technical Reports Server (NTRS)
Belytschko, Ted
1993-01-01
The objective is to describe three research thrusts in crashworthiness analysis: adaptivity; mixed time integration, or subcycling, in which different timesteps are used for different parts of the mesh in explicit methods; and methods for contact-impact which are highly vectorizable. The techniques are being developed to improve the accuracy of calculations, ease-of-use of crashworthiness programs, and the speed of calculations. The latter is still of importance because crashworthiness calculations are often made with models of 20,000 to 50,000 elements using explicit time integration and require on the order of 20 to 100 hours on current supercomputers. The methodologies are briefly reviewed and then some example calculations employing these methods are described. The methods are also of value to other nonlinear transient computations.
Planetary gearbox fault diagnosis using an adaptive stochastic resonance method
NASA Astrophysics Data System (ADS)
Lei, Yaguo; Han, Dong; Lin, Jing; He, Zhengjia
2013-07-01
Planetary gearboxes are widely used in aerospace, automotive and heavy industry applications due to their large transmission ratio, strong load-bearing capacity and high transmission efficiency. The tough operation conditions of heavy duty and intensive impact load may cause gear tooth damage such as fatigue crack and teeth missed etc. The challenging issues in fault diagnosis of planetary gearboxes include selection of sensitive measurement locations, investigation of vibration transmission paths and weak feature extraction. One of them is how to effectively discover the weak characteristics from noisy signals of faulty components in planetary gearboxes. To address the issue in fault diagnosis of planetary gearboxes, an adaptive stochastic resonance (ASR) method is proposed in this paper. The ASR method utilizes the optimization ability of ant colony algorithms and adaptively realizes the optimal stochastic resonance system matching input signals. Using the ASR method, the noise may be weakened and weak characteristics highlighted, and therefore the faults can be diagnosed accurately. A planetary gearbox test rig is established and experiments with sun gear faults including a chipped tooth and a missing tooth are conducted. And the vibration signals are collected under the loaded condition and various motor speeds. The proposed method is used to process the collected signals and the results of feature extraction and fault diagnosis demonstrate its effectiveness.
Role-based adaptation for video conferencing in healthcare applications
NASA Astrophysics Data System (ADS)
Figuerola, Oscar; Kalva, Hari; Escudero, Antonio; Agarwal, Ankur
2014-02-01
A large number of health-related applications are being developed using web infrastructure. Video is increasingly used in healthcare applications to enable communications between patients and care providers. We present a video conferencing system designed for healthcare applications. In face of network congestion, the system uses role-based adaptation to ensure seamless service. A new web technology, WebRTC, is used to enable seamless conferencing applications. We present the video conferencing application and demonstrate the usefulness of role based adaptation.
Finite element error estimation and adaptivity based on projected stresses
Jung, J.
1990-08-01
This report investigates the behavior of a family of finite element error estimators based on projected stresses, i.e., continuous stresses that are a least squared error fit to the conventional Gauss point stresses. An error estimate based on element force equilibrium appears to be quite effective. Examples of adaptive mesh refinement for a one-dimensional problem are presented. Plans for two-dimensional adaptivity are discussed. 12 refs., 82 figs.
Deng, Hua; Li, Han-Xiong; Wu, Yi-Hu
2008-09-01
A new feedback-linearization-based neural network (NN) adaptive control is proposed for unknown nonaffine nonlinear discrete-time systems. An equivalent model in affine-like form is first derived for the original nonaffine discrete-time systems as feedback linearization methods cannot be implemented for such systems. Then, feedback linearization adaptive control is implemented based on the affine-like equivalent model identified with neural networks. Pretraining is not required and the weights of the neural networks used in adaptive control are directly updated online based on the input-output measurement. The dead-zone technique is used to remove the requirement of persistence excitation during the adaptation. With the proposed neural network adaptive control, stability and performance of the closed-loop system are rigorously established. Illustrated examples are provided to validate the theoretical findings. PMID:18779092
Adapting Document Similarity Measures for Ligand-Based Virtual Screening.
Himmat, Mubarak; Salim, Naomie; Al-Dabbagh, Mohammed Mumtaz; Saeed, Faisal; Ahmed, Ali
2016-01-01
Quantifying the similarity of molecules is considered one of the major tasks in virtual screening. There are many similarity measures that have been proposed for this purpose, some of which have been derived from document and text retrieving areas as most often these similarity methods give good results in document retrieval and can achieve good results in virtual screening. In this work, we propose a similarity measure for ligand-based virtual screening, which has been derived from a text processing similarity measure. It has been adopted to be suitable for virtual screening; we called this proposed measure the Adapted Similarity Measure of Text Processing (ASMTP). For evaluating and testing the proposed ASMTP we conducted several experiments on two different benchmark datasets: the Maximum Unbiased Validation (MUV) and the MDL Drug Data Report (MDDR). The experiments have been conducted by choosing 10 reference structures from each class randomly as queries and evaluate them in the recall of cut-offs at 1% and 5%. The overall obtained results are compared with some similarity methods including the Tanimoto coefficient, which are considered to be the conventional and standard similarity coefficients for fingerprint-based similarity calculations. The achieved results show that the performance of ligand-based virtual screening is better and outperforms the Tanimoto coefficients and other methods. PMID:27089312
Evaluation of an adaptive beamforming method for hearing aids.
Greenberg, J E; Zurek, P M
1992-03-01
In this paper evaluations of a two-microphone adaptive beamforming system for hearing aids are presented. The system, based on the constrained adaptive beamformer described by Griffiths and Jim [IEEE Trans. Antennas Propag. AP-30, 27-34 (1982)], adapts to preserve target signals from straight ahead and to minimize jammer signals arriving from other directions. Modifications of the basic Griffiths-Jim algorithm are proposed to alleviate problems of target cancellation and misadjustment that arise in the presence of strong target signals. The evaluations employ both computer simulations and a real-time hardware implementation and are restricted to the case of a single jammer. Performance is measured by the spectrally weighted gain in the target-to-jammer ratio in the steady state. Results show that in environments with relatively little reverberation: (1) the modifications allow good performance even with misaligned arrays and high input target-to-jammer ratios; and (2) performance is better with a broadside array with 7-cm spacing between microphones than with a 26-cm broadside or a 7-cm endfire configuration. Performance degrades in reverberant environments; at the critical distance of a room, improvement with a practical system is limited to a few dB. PMID:1564202
Creatively Adapting Mastery Learning and Outcome-Based Education to the Social Work Classroom.
ERIC Educational Resources Information Center
Aviles, Christopher B.
This workshop was presented on outcome-based education and described how the instructional method called mastery learning compliments it and can be adapted for social work education. Although outcome-based education involves creating clearly outlined expected student outcomes, by itself it is not an instructional method. Mastery learning is a…
The SMART CLUSTER METHOD - adaptive earthquake cluster analysis and declustering
NASA Astrophysics Data System (ADS)
Schaefer, Andreas; Daniell, James; Wenzel, Friedemann
2016-04-01
Earthquake declustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity with usual applications comprising of probabilistic seismic hazard assessments (PSHAs) and earthquake prediction methods. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation. Various methods have been developed to address this issue from other researchers. These have differing ranges of complexity ranging from rather simple statistical window methods to complex epidemic models. This study introduces the smart cluster method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal identification. Hereby, an adaptive search algorithm for data point clusters is adopted. It uses the earthquake density in the spatio-temporal neighbourhood of each event to adjust the search properties. The identified clusters are subsequently analysed to determine directional anisotropy, focussing on a strong correlation along the rupture plane and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010/2011 Darfield-Christchurch events, an adaptive classification procedure is applied to disassemble subsequent ruptures which may have been grouped into an individual cluster using near-field searches, support vector machines and temporal splitting. The steering parameters of the search behaviour are linked to local earthquake properties like magnitude of completeness, earthquake density and Gutenberg-Richter parameters. The method is capable of identifying and classifying earthquake clusters in space and time. It is tested and validated using earthquake data from California and New Zealand. As a result of the cluster identification process, each event in
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
An adaptive pseudo-spectral method for reaction diffusion problems
NASA Technical Reports Server (NTRS)
Bayliss, A.; Gottlieb, D.; Matkowsky, B. J.; Minkoff, M.
1987-01-01
The spectral interpolation error was considered for both the Chebyshev pseudo-spectral and Galerkin approximations. A family of functionals I sub r (u), with the property that the maximum norm of the error is bounded by I sub r (u)/J sub r, where r is an integer and J is the degree of the polynomial approximation, was developed. These functionals are used in the adaptive procedure whereby the problem is dynamically transformed to minimize I sub r (u). The number of collocation points is then chosen to maintain a prescribed error bound. The method is illustrated by various examples from combustion problems in one and two dimensions.
A parallel adaptive method for pseudo-arclength continuation
NASA Astrophysics Data System (ADS)
Aruliah, D. A.; van Veen, L.; Dubitski, A.
2012-10-01
Pseudo-arclength continuation is a well-established method for constructing a numerical curve comprising solutions of a system of nonlinear equations. In many complicated high-dimensional systems, the corrector steps within pseudo-arclength continuation are extremely costly to compute; as a result, the step-length of the preceding prediction step must be adapted carefully to avoid prohibitively many failed steps. We describe the essence of a parallel method for adapting the step-length of pseudo-arclength continuation. Our method employs several predictor-corrector sequences with differing step-lengths running concurrently on distinct processors. Our parallel framework permits intermediate results of correction sequences that have not yet converged to seed new predictor-corrector sequences with various step-lengths; the goal is to amortize the cost of corrector steps to make further progress along the underlying numerical curve. Results from numerical experiments suggest a three-fold speedup is attainable when the continuation curve sought has great topological complexity and the corrector steps require significant processor time.
An h-adaptive local discontinuous Galerkin method for the Navier-Stokes-Korteweg equations
NASA Astrophysics Data System (ADS)
Tian, Lulu; Xu, Yan; Kuerten, J. G. M.; van der Vegt, J. J. W.
2016-08-01
In this article, we develop a mesh adaptation algorithm for a local discontinuous Galerkin (LDG) discretization of the (non)-isothermal Navier-Stokes-Korteweg (NSK) equations modeling liquid-vapor flows with phase change. This work is a continuation of our previous research, where we proposed LDG discretizations for the (non)-isothermal NSK equations with a time-implicit Runge-Kutta method. To save computing time and to capture the thin interfaces more accurately, we extend the LDG discretization with a mesh adaptation method. Given the current adapted mesh, a criterion for selecting candidate elements for refinement and coarsening is adopted based on the locally largest value of the density gradient. A strategy to refine and coarsen the candidate elements is then provided. We emphasize that the adaptive LDG discretization is relatively simple and does not require additional stabilization. The use of a locally refined mesh in combination with an implicit Runge-Kutta time method is, however, non-trivial, but results in an efficient time integration method for the NSK equations. Computations, including cases with solid wall boundaries, are provided to demonstrate the accuracy, efficiency and capabilities of the adaptive LDG discretizations.
An adaptive response surface method for crashworthiness optimization
NASA Astrophysics Data System (ADS)
Shi, Lei; Yang, Ren-Jye; Zhu, Ping
2013-11-01
Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.
Scale-adaptive tensor algebra for local many-body methods of electronic structure theory
Liakh, Dmitry I
2014-01-01
While the formalism of multiresolution analysis (MRA), based on wavelets and adaptive integral representations of operators, is actively progressing in electronic structure theory (mostly on the independent-particle level and, recently, second-order perturbation theory), the concepts of multiresolution and adaptivity can also be utilized within the traditional formulation of correlated (many-particle) theory which is based on second quantization and the corresponding (generally nonorthogonal) tensor algebra. In this paper, we present a formalism called scale-adaptive tensor algebra (SATA) which exploits an adaptive representation of tensors of many-body operators via the local adjustment of the basis set quality. Given a series of locally supported fragment bases of a progressively lower quality, we formulate the explicit rules for tensor algebra operations dealing with adaptively resolved tensor operands. The formalism suggested is expected to enhance the applicability and reliability of local correlated many-body methods of electronic structure theory, especially those directly based on atomic orbitals (or any other localized basis functions).
Image quality-based adaptive illumination normalisation for face recognition
NASA Astrophysics Data System (ADS)
Sellahewa, Harin; Jassim, Sabah A.
2009-05-01
Automatic face recognition is a challenging task due to intra-class variations. Changes in lighting conditions during enrolment and identification stages contribute significantly to these intra-class variations. A common approach to address the effects such of varying conditions is to pre-process the biometric samples in order normalise intra-class variations. Histogram equalisation is a widely used illumination normalisation technique in face recognition. However, a recent study has shown that applying histogram equalisation on well-lit face images could lead to a decrease in recognition accuracy. This paper presents a dynamic approach to illumination normalisation, based on face image quality. The quality of a given face image is measured in terms of its luminance distortion by comparing this image against a known reference face image. Histogram equalisation is applied to a probe image if its luminance distortion is higher than a predefined threshold. We tested the proposed adaptive illumination normalisation method on the widely used Extended Yale Face Database B. Identification results demonstrate that our adaptive normalisation produces better identification accuracy compared to the conventional approach where every image is normalised, irrespective of the lighting condition they were acquired.
Generalization Bounds Derived IPM-Based Regularization for Domain Adaptation.
Meng, Juan; Hu, Guyu; Li, Dong; Zhang, Yanyan; Pan, Zhisong
2016-01-01
Domain adaptation has received much attention as a major form of transfer learning. One issue that should be considered in domain adaptation is the gap between source domain and target domain. In order to improve the generalization ability of domain adaption methods, we proposed a framework for domain adaptation combining source and target data, with a new regularizer which takes generalization bounds into account. This regularization term considers integral probability metric (IPM) as the distance between the source domain and the target domain and thus can bound up the testing error of an existing predictor from the formula. Since the computation of IPM only involves two distributions, this generalization term is independent with specific classifiers. With popular learning models, the empirical risk minimization is expressed as a general convex optimization problem and thus can be solved effectively by existing tools. Empirical studies on synthetic data for regression and real-world data for classification show the effectiveness of this method. PMID:26819589
Generalization Bounds Derived IPM-Based Regularization for Domain Adaptation
Meng, Juan; Hu, Guyu; Zhang, Yanyan
2016-01-01
Domain adaptation has received much attention as a major form of transfer learning. One issue that should be considered in domain adaptation is the gap between source domain and target domain. In order to improve the generalization ability of domain adaption methods, we proposed a framework for domain adaptation combining source and target data, with a new regularizer which takes generalization bounds into account. This regularization term considers integral probability metric (IPM) as the distance between the source domain and the target domain and thus can bound up the testing error of an existing predictor from the formula. Since the computation of IPM only involves two distributions, this generalization term is independent with specific classifiers. With popular learning models, the empirical risk minimization is expressed as a general convex optimization problem and thus can be solved effectively by existing tools. Empirical studies on synthetic data for regression and real-world data for classification show the effectiveness of this method. PMID:26819589
Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization
Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali
2014-01-01
Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584
Support vector machine based on adaptive acceleration particle swarm optimization.
Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali
2014-01-01
Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584
Simulation of nonpoint source contamination based on adaptive mesh refinement
NASA Astrophysics Data System (ADS)
Kourakos, G.; Harter, T.
2014-12-01
Contamination of groundwater aquifers from nonpoint sources is a worldwide problem. Typical agricultural groundwater basins receive contamination from a large array (in the order of ~10^5-6) of spatially and temporally heterogeneous sources such as fields, crops, dairies etc, while the received contaminants emerge at significantly uncertain time lags to a large array of discharge surfaces such as public supply, domestic and irrigation wells and streams. To support decision making in such complex regimes several approaches have been developed, which can be grouped into 3 categories: i) Index methods, ii)regression methods and iii) physically based methods. Among the three, physically based methods are considered more accurate, but at the cost of computational demand. In this work we present a physically based simulation framework which exploits the latest hardware and software developments to simulate large (>>1,000 km2) groundwater basins. First we simulate groundwater flow using a sufficiently detailed mesh to capture the spatial heterogeneity. To achieve optimal mesh quality we combine adaptive mesh refinement with the nonlinear solution for unconfined flow. Starting from a coarse grid the mesh is refined iteratively in the parts of the domain where the flow heterogeneity appears higher resulting in optimal grid. Secondly we simulate the nonpoint source pollution based on the detailed velocity field computed from the previous step. In our approach we use the streamline model where the 3D transport problem is decomposed into multiple 1D transport problems. The proposed framework is applied to simulate nonpoint source pollution in the Central Valley aquifer system, California.
Turbulence profiling methods applied to ESO's adaptive optics facility
NASA Astrophysics Data System (ADS)
Valenzuela, Javier; Béchet, Clémentine; Garcia-Rissmann, Aurea; Gonté, Frédéric; Kolb, Johann; Le Louarn, Miska; Neichel, Benoît; Madec, Pierre-Yves; Guesalaga, Andrés.
2014-07-01
Two algorithms were recently studied for C2n profiling from wide-field Adaptive Optics (AO) measurements on GeMS (Gemini Multi-Conjugate AO system). They both rely on the Slope Detection and Ranging (SLODAR) approach, using spatial covariances of the measurements issued from various wavefront sensors. The first algorithm estimates the C2n profile by applying the truncated least-squares inverse of a matrix modeling the response of slopes covariances to various turbulent layer heights. In the second method, the profile is estimated by deconvolution of these spatial cross-covariances of slopes. We compare these methods in the new configuration of ESO Adaptive Optics Facility (AOF), a high-order multiple laser system under integration. For this, we use measurements simulated by the AO cluster of ESO. The impact of the measurement noise and of the outer scale of the atmospheric turbulence is analyzed. The important influence of the outer scale on the results leads to the development of a new step for outer scale fitting included in each algorithm. This increases the reliability and robustness of the turbulence strength and profile estimations.
A GPU-accelerated adaptive discontinuous Galerkin method for level set equation
NASA Astrophysics Data System (ADS)
Karakus, A.; Warburton, T.; Aksel, M. H.; Sert, C.
2016-01-01
This paper presents a GPU-accelerated nodal discontinuous Galerkin method for the solution of two- and three-dimensional level set (LS) equation on unstructured adaptive meshes. Using adaptive mesh refinement, computations are localised mostly near the interface location to reduce the computational cost. Small global time step size resulting from the local adaptivity is avoided by local time-stepping based on a multi-rate Adams-Bashforth scheme. Platform independence of the solver is achieved with an extensible multi-threading programming API that allows runtime selection of different computing devices (GPU and CPU) and different threading interfaces (CUDA, OpenCL and OpenMP). Overall, a highly scalable, accurate and mass conservative numerical scheme that preserves the simplicity of LS formulation is obtained. Efficiency, performance and local high-order accuracy of the method are demonstrated through distinct numerical test cases.
An adaptive, formally second order accurate version of the immersed boundary method
NASA Astrophysics Data System (ADS)
Griffith, Boyce E.; Hornung, Richard D.; McQueen, David M.; Peskin, Charles S.
2007-04-01
Like many problems in biofluid mechanics, cardiac mechanics can be modeled as the dynamic interaction of a viscous incompressible fluid (the blood) and a (visco-)elastic structure (the muscular walls and the valves of the heart). The immersed boundary method is a mathematical formulation and numerical approach to such problems that was originally introduced to study blood flow through heart valves, and extensions of this work have yielded a three-dimensional model of the heart and great vessels. In the present work, we introduce a new adaptive version of the immersed boundary method. This adaptive scheme employs the same hierarchical structured grid approach (but a different numerical scheme) as the two-dimensional adaptive immersed boundary method of Roma et al. [A multilevel self adaptive version of the immersed boundary method, Ph.D. Thesis, Courant Institute of Mathematical Sciences, New York University, 1996; An adaptive version of the immersed boundary method, J. Comput. Phys. 153 (2) (1999) 509-534] and is based on a formally second order accurate (i.e., second order accurate for problems with sufficiently smooth solutions) version of the immersed boundary method that we have recently described [B.E. Griffith, C.S. Peskin, On the order of accuracy of the immersed boundary method: higher order convergence rates for sufficiently smooth problems, J. Comput. Phys. 208 (1) (2005) 75-105]. Actual second order convergence rates are obtained for both the uniform and adaptive methods by considering the interaction of a viscous incompressible flow and an anisotropic incompressible viscoelastic shell. We also present initial results from the application of this methodology to the three-dimensional simulation of blood flow in the heart and great vessels. The results obtained by the adaptive method show good qualitative agreement with simulation results obtained by earlier non-adaptive versions of the method, but the flow in the vicinity of the model heart valves
An adaptive PCA fusion method for remote sensing images
NASA Astrophysics Data System (ADS)
Guo, Qing; Li, An; Zhang, Hongqun; Feng, Zhongkui
2014-10-01
The principal component analysis (PCA) method is a popular fusion method used for its efficiency and high spatial resolution improvement. However, the spectral distortion is often found in PCA. In this paper, we propose an adaptive PCA method to enhance the spectral quality of the fused image. The amount of spatial details of the panchromatic (PAN) image injected into each band of the multi-spectral (MS) image is appropriately determined by a weighting matrix, which is defined by the edges of the PAN image, the edges of the MS image and the proportions between MS bands. In order to prove the effectiveness of the proposed method, the qualitative visual and quantitative analyses are introduced. The correlation coefficient (CC), the spectral discrepancy (SPD), and the spectral angle mapper (SAM) are used to measure the spectral quality of each fused band image. Q index is calculated to evaluate the global spectral quality of all the fused bands as a whole. The spatial quality is evaluated by the average gradient (AG) and the standard deviation (STD). Experimental results show that the proposed method improves the spectral quality very much comparing to the original PCA method while maintaining the high spatial quality of the original PCA.
A Dynamically Adaptive Arbitrary Lagrangian-Eulerian Method for Solution of the Euler Equations
Anderson, R W; Elliott, N S; Pember, R B
2003-02-14
A new method that combines staggered grid arbitrary Lagrangian-Eulerian (ALE) techniques with structured local adaptive mesh refinement (AMR) has been developed for solution of the Euler equations. The novel components of the methods are driven by the need to reconcile traditional AMR techniques with the staggered variables and moving, deforming meshes associated with Lagrange based ALE schemes. We develop interlevel solution transfer operators and interlevel boundary conditions first in the case of purely Lagrangian hydrodynamics, and then extend these ideas into an ALE method by developing adaptive extensions of elliptic mesh relaxation techniques. Conservation properties of the method are analyzed, and a series of test problem calculations are presented which demonstrate the utility and efficiency of the method.
Bergeron, Bryan; Cline, Andrew; Shipley, Jaime
2012-01-01
We have developed a distributed, standards-based architecture that enables simulation and simulator designers to leverage adaptive learning systems. Our approach, which incorporates an electronic competency record, open source LMS, and open source microcontroller hardware, is a low-cost, pragmatic option to integrating simulators with traditional courseware. PMID:22356955
NASA Technical Reports Server (NTRS)
Kantor, A. V.; Timonin, V. G.; Azarova, Y. S.
1974-01-01
The method of adaptive discretization is the most promising for elimination of redundancy from telemetry messages characterized by signal shape. Adaptive discretization with associative sorting was considered as a way to avoid the shortcomings of adaptive discretization with buffer smoothing and adaptive discretization with logical switching in on-board information compression devices (OICD) in spacecraft. Mathematical investigations of OICD are presented.
Adaptive Device Context Based Mobile Learning Systems
ERIC Educational Resources Information Center
Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng
2011-01-01
Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…
Adaptive Learning for ESL Based on Computation
ERIC Educational Resources Information Center
Wang, Ya-huei; Liao, Hung-Chang
2011-01-01
In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students' learning outcomes are to be maximised, it is…
A Spectral Adaptive Mesh Refinement Method for the Burgers equation
NASA Astrophysics Data System (ADS)
Nasr Azadani, Leila; Staples, Anne
2013-03-01
Adaptive mesh refinement (AMR) is a powerful technique in computational fluid dynamics (CFD). Many CFD problems have a wide range of scales which vary with time and space. In order to resolve all the scales numerically, high grid resolutions are required. The smaller the scales the higher the resolutions should be. However, small scales are usually formed in a small portion of the domain or in a special period of time. AMR is an efficient method to solve these types of problems, allowing high grid resolutions where and when they are needed and minimizing memory and CPU time. Here we formulate a spectral version of AMR in order to accelerate simulations of a 1D model for isotropic homogenous turbulence, the Burgers equation, as a first test of this method. Using pseudo spectral methods, we applied AMR in Fourier space. The spectral AMR (SAMR) method we present here is applied to the Burgers equation and the results are compared with the results obtained using standard solution methods performed using a fine mesh.
Robust image registration using adaptive coherent point drift method
NASA Astrophysics Data System (ADS)
Yang, Lijuan; Tian, Zheng; Zhao, Wei; Wen, Jinhuan; Yan, Weidong
2016-04-01
Coherent point drift (CPD) method is a powerful registration tool under the framework of the Gaussian mixture model (GMM). However, the global spatial structure of point sets is considered only without other forms of additional attribute information. The equivalent simplification of mixing parameters and the manual setting of the weight parameter in GMM make the CPD method less robust to outlier and have less flexibility. An adaptive CPD method is proposed to automatically determine the mixing parameters by embedding the local attribute information of features into the construction of GMM. In addition, the weight parameter is treated as an unknown parameter and automatically determined in the expectation-maximization algorithm. In image registration applications, the block-divided salient image disk extraction method is designed to detect sparse salient image features and local self-similarity is used as attribute information to describe the local neighborhood structure of each feature. The experimental results on optical images and remote sensing images show that the proposed method can significantly improve the matching performance.
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.
Combining Adaptive Hypermedia with Project and Case-Based Learning
ERIC Educational Resources Information Center
Papanikolaou, Kyparisia; Grigoriadou, Maria
2009-01-01
In this article we investigate the design of educational hypermedia based on constructivist learning theories. According to the principles of project and case-based learning we present the design rational of an Adaptive Educational Hypermedia system prototype named MyProject; learners working with MyProject undertake a project and the system…
Nonlinear mode decomposition: A noise-robust, adaptive decomposition method
NASA Astrophysics Data System (ADS)
Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta
2015-09-01
The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.
Nonlinear mode decomposition: a noise-robust, adaptive decomposition method.
Iatsenko, Dmytro; McClintock, Peter V E; Stefanovska, Aneta
2015-09-01
The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool-nonlinear mode decomposition (NMD)-which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques-which, together with the adaptive choice of their parameters, make it extremely noise robust-and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download. PMID:26465549
Developing the evidence base for mainstreaming adaptation of stormwater systems to climate change.
Gersonius, B; Nasruddin, F; Ashley, R; Jeuken, A; Pathirana, A; Zevenbergen, C
2012-12-15
In a context of high uncertainty about hydro-climatic variables, the development of updated methods for climate impact and adaptation assessment is as important, if not more important than the provision of improved climate change data. In this paper, we introduce a hybrid method to facilitate mainstreaming adaptation of stormwater systems to climate change: i.e., the Mainstreaming method. The Mainstreaming method starts with an analysis of adaptation tipping points (ATPs), which is effect-based. These are points of reference where the magnitude of climate change is such that acceptable technical, environmental, societal or economic standards may be compromised. It extends the ATP analysis to include aspects from a bottom-up approach. The extension concerns the analysis of adaptation opportunities in the stormwater system. The results from both analyses are then used in combination to identify and exploit Adaptation Mainstreaming Moments (AMMs). Use of this method will enhance the understanding of the adaptive potential of stormwater systems. We have applied the proposed hybrid method to the management of flood risk for an urban stormwater system in Dordrecht (the Netherlands). The main finding of this case study is that the application of the Mainstreaming method helps to increase the no-/low-regret character of adaptation for several reasons: it focuses the attention on the most urgent effects of climate change; it is expected to lead to potential cost reductions, since adaptation options can be integrated into infrastructure and building design at an early stage instead of being applied separately; it will lead to the development of area-specific responses, which could not have been developed on a higher scale level; it makes it possible to take account of local values and sensibilities, which contributes to increased public and political support for the adaptive strategies. PMID:22575154
Probabilistic dual heuristic programming-based adaptive critic
NASA Astrophysics Data System (ADS)
Herzallah, Randa
2010-02-01
Adaptive critic (AC) methods have common roots as generalisations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, non-linear and non-stationary environments. In this study, a novel probabilistic dual heuristic programming (DHP)-based AC controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) AC method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterised by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the probabilistic critic network is then calculated and shown to be equal to the analytically derived correct value. Full derivation of the Riccati solution for this non-standard stochastic linear quadratic control problem is also provided. Moreover, the performance of the proposed probabilistic controller is demonstrated on linear and non-linear control examples.
An Evidence-Based Public Health Approach to Climate Change Adaptation
Eidson, Millicent; Tlumak, Jennifer E.; Raab, Kristin K.; Luber, George
2014-01-01
Background: Public health is committed to evidence-based practice, yet there has been minimal discussion of how to apply an evidence-based practice framework to climate change adaptation. Objectives: Our goal was to review the literature on evidence-based public health (EBPH), to determine whether it can be applied to climate change adaptation, and to consider how emphasizing evidence-based practice may influence research and practice decisions related to public health adaptation to climate change. Methods: We conducted a substantive review of EBPH, identified a consensus EBPH framework, and modified it to support an EBPH approach to climate change adaptation. We applied the framework to an example and considered implications for stakeholders. Discussion: A modified EBPH framework can accommodate the wide range of exposures, outcomes, and modes of inquiry associated with climate change adaptation and the variety of settings in which adaptation activities will be pursued. Several factors currently limit application of the framework, including a lack of higher-level evidence of intervention efficacy and a lack of guidelines for reporting climate change health impact projections. To enhance the evidence base, there must be increased attention to designing, evaluating, and reporting adaptation interventions; standardized health impact projection reporting; and increased attention to knowledge translation. This approach has implications for funders, researchers, journal editors, practitioners, and policy makers. Conclusions: The current approach to EBPH can, with modifications, support climate change adaptation activities, but there is little evidence regarding interventions and knowledge translation, and guidelines for projecting health impacts are lacking. Realizing the goal of an evidence-based approach will require systematic, coordinated efforts among various stakeholders. Citation: Hess JJ, Eidson M, Tlumak JE, Raab KK, Luber G. 2014. An evidence-based public
Applications of automatic mesh generation and adaptive methods in computational medicine
Schmidt, J.A.; Macleod, R.S.; Johnson, C.R.; Eason, J.C.
1995-12-31
Important problems in Computational Medicine exist that can benefit from the implementation of adaptive mesh refinement techniques. Biological systems are so inherently complex that only efficient models running on state of the art hardware can begin to simulate reality. To tackle the complex geometries associated with medical applications we present a general purpose mesh generation scheme based upon the Delaunay tessellation algorithm and an iterative point generator. In addition, automatic, two- and three-dimensional adaptive mesh refinement methods are presented that are derived from local and global estimates of the finite element error. Mesh generation and adaptive refinement techniques are utilized to obtain accurate approximations of bioelectric fields within anatomically correct models of the heart and human thorax. Specifically, we explore the simulation of cardiac defibrillation and the general forward and inverse problems in electrocardiography (ECG). Comparisons between uniform and adaptive refinement techniques are made to highlight the computational efficiency and accuracy of adaptive methods in the solution of field problems in computational medicine.
Adaptive neural network consensus based control of robot formations
NASA Astrophysics Data System (ADS)
Guzey, H. M.; Sarangapani, Jagannathan
2013-05-01
In this paper, adaptive consensus based formation control scheme is derived for mobile robots in a pre-defined formation when full dynamics of the robots which include inertia, Corolis, and friction vector are considered. It is shown that dynamic uncertainties of robots can make overall formation unstable when traditional consensus scheme is utilized. In order to estimate the affine nonlinear robot dynamics, a NN based adaptive scheme is utilized. In addition to this adaptive feedback control input, an additional control input is introduced based on the consensus approach to make the robots keep their desired formation. Subsequently, the outer consensus loop is redesigned for reduced communication. Lyapunov theory is used to show the stability of overall system. Simulation results are included at the end.
Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter.
Zhang, Zhen; Ma, Yaopeng
2016-01-01
A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively. PMID:26861349
Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter
Zhang, Zhen; Ma, Yaopeng
2016-01-01
A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively. PMID:26861349
A forward method for optimal stochastic nonlinear and adaptive control
NASA Technical Reports Server (NTRS)
Bayard, David S.
1988-01-01
A computational approach is taken to solve the optimal nonlinear stochastic control problem. The approach is to systematically solve the stochastic dynamic programming equations forward in time, using a nested stochastic approximation technique. Although computationally intensive, this provides a straightforward numerical solution for this class of problems and provides an alternative to the usual dimensionality problem associated with solving the dynamic programming equations backward in time. It is shown that the cost degrades monotonically as the complexity of the algorithm is reduced. This provides a strategy for suboptimal control with clear performance/computation tradeoffs. A numerical study focusing on a generic optimal stochastic adaptive control example is included to demonstrate the feasibility of the method.
Adaptive non-local means method for speckle reduction in ultrasound images
NASA Astrophysics Data System (ADS)
Ai, Ling; Ding, Mingyue; Zhang, Xuming
2016-03-01
Noise removal is a crucial step to enhance the quality of ultrasound images. However, some existing despeckling methods cannot ensure satisfactory restoration performance. In this paper, an adaptive non-local means (ANLM) filter is proposed for speckle noise reduction in ultrasound images. The distinctive property of the proposed method lies in that the decay parameter will not take the fixed value for the whole image but adapt itself to the variation of the local features in the ultrasound images. In the proposed method, the pre-filtered image will be obtained using the traditional NLM method. Based on the pre-filtered result, the local gradient will be computed and it will be utilized to determine the decay parameter adaptively for each image pixel. The final restored image will be produced by the ANLM method using the obtained decay parameters. Simulations on the synthetic image show that the proposed method can deliver sufficient speckle reduction while preserving image details very well and it outperforms the state-of-the-art despeckling filters in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). Experiments on the clinical ultrasound image further demonstrate the practicality and advantage of the proposed method over the compared filtering methods.
Adaptive control system having hedge unit and related apparatus and methods
NASA Technical Reports Server (NTRS)
Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)
2003-01-01
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Adaptive control system having hedge unit and related apparatus and methods
NASA Technical Reports Server (NTRS)
Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)
2007-01-01
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
Adaptive mesh refinement and adjoint methods in geophysics simulations
NASA Astrophysics Data System (ADS)
Burstedde, Carsten
2013-04-01
It is an ongoing challenge to increase the resolution that can be achieved by numerical geophysics simulations. This applies to considering sub-kilometer mesh spacings in global-scale mantle convection simulations as well as to using frequencies up to 1 Hz in seismic wave propagation simulations. One central issue is the numerical cost, since for three-dimensional space discretizations, possibly combined with time stepping schemes, a doubling of resolution can lead to an increase in storage requirements and run time by factors between 8 and 16. A related challenge lies in the fact that an increase in resolution also increases the dimensionality of the model space that is needed to fully parametrize the physical properties of the simulated object (a.k.a. earth). Systems that exhibit a multiscale structure in space are candidates for employing adaptive mesh refinement, which varies the resolution locally. An example that we found well suited is the mantle, where plate boundaries and fault zones require a resolution on the km scale, while deeper area can be treated with 50 or 100 km mesh spacings. This approach effectively reduces the number of computational variables by several orders of magnitude. While in this case it is possible to derive the local adaptation pattern from known physical parameters, it is often unclear what are the most suitable criteria for adaptation. We will present the goal-oriented error estimation procedure, where such criteria are derived from an objective functional that represents the observables to be computed most accurately. Even though this approach is well studied, it is rarely used in the geophysics community. A related strategy to make finer resolution manageable is to design methods that automate the inference of model parameters. Tweaking more than a handful of numbers and judging the quality of the simulation by adhoc comparisons to known facts and observations is a tedious task and fundamentally limited by the turnaround times
Adaptive conventional power system stabilizer based on artificial neural network
Kothari, M.L.; Segal, R.; Ghodki, B.K.
1995-12-31
This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.
A wavelet-optimized, very high order adaptive grid and order numerical method
NASA Technical Reports Server (NTRS)
Jameson, Leland
1996-01-01
Differencing operators of arbitrarily high order can be constructed by interpolating a polynomial through a set of data followed by differentiation of this polynomial and finally evaluation of the polynomial at the point where a derivative approximation is desired. Furthermore, the interpolating polynomial can be constructed from algebraic, trigonometric, or, perhaps exponential polynomials. This paper begins with a comparison of such differencing operator construction. Next, the issue of proper grids for high order polynomials is addressed. Finally, an adaptive numerical method is introduced which adapts the numerical grid and the order of the differencing operator depending on the data. The numerical grid adaptation is performed on a Chebyshev grid. That is, at each level of refinement the grid is a Chebvshev grid and this grid is refined locally based on wavelet analysis.
An Adaptive Feedback and Review Paradigm for Computer-Based Drills.
ERIC Educational Resources Information Center
Siegel, Martin A.; Misselt, A. Lynn
The Corrective Feedback Paradigm (CFP), which has been refined and expanded through use on the PLATO IV Computer-Based Education System, is based on instructional design strategies implied by stimulus-locus analyses, direct instruction, and instructional feedback methods. Features of the paradigm include adaptive feedback techniques with…
NASA Astrophysics Data System (ADS)
Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang; Zilan, Pan; Dawei, Zhang; Xiuhua, Ma
2016-04-01
In order to improve the reconstruction accuracy and reduce the workload, the algorithm of compressive sensing based on the iterative threshold is combined with the method of adaptive selection of the training sample, and a new algorithm of adaptive compressive sensing is put forward. The three kinds of training sample are used to reconstruct the spectral reflectance of the testing sample based on the compressive sensing algorithm and adaptive compressive sensing algorithm, and the color difference and error are compared. The experiment results show that spectral reconstruction precision based on the adaptive compressive sensing algorithm is better than that based on the algorithm of compressive sensing.
NASA Astrophysics Data System (ADS)
Nose, Takashi; Tachibana, Makoto; Kobayashi, Takao
This paper presents methods for controlling the intensity of emotional expressions and speaking styles of an arbitrary speaker's synthetic speech by using a small amount of his/her speech data in HMM-based speech synthesis. Model adaptation approaches are introduced into the style control technique based on the multiple-regression hidden semi-Markov model (MRHSMM). Two different approaches are proposed for training a target speaker's MRHSMMs. The first one is MRHSMM-based model adaptation in which the pretrained MRHSMM is adapted to the target speaker's model. For this purpose, we formulate the MLLR adaptation algorithm for the MRHSMM. The second method utilizes simultaneous adaptation of speaker and style from an average voice model to obtain the target speaker's style-dependent HSMMs which are used for the initialization of the MRHSMM. From the result of subjective evaluation using adaptation data of 50 sentences of each style, we show that the proposed methods outperform the conventional speaker-dependent model training when using the same size of speech data of the target speaker.
Earthquake Rupture Dynamics using Adaptive Mesh Refinement and High-Order Accurate Numerical Methods
NASA Astrophysics Data System (ADS)
Kozdon, J. E.; Wilcox, L.
2013-12-01
Our goal is to develop scalable and adaptive (spatial and temporal) numerical methods for coupled, multiphysics problems using high-order accurate numerical methods. To do so, we are developing an opensource, parallel library known as bfam (available at http://bfam.in). The first application to be developed on top of bfam is an earthquake rupture dynamics solver using high-order discontinuous Galerkin methods and summation-by-parts finite difference methods. In earthquake rupture dynamics, wave propagation in the Earth's crust is coupled to frictional sliding on fault interfaces. This coupling is two-way, required the simultaneous simulation of both processes. The use of laboratory-measured friction parameters requires near-fault resolution that is 4-5 orders of magnitude higher than that needed to resolve the frequencies of interest in the volume. This, along with earlier simulations using a low-order, finite volume based adaptive mesh refinement framework, suggest that adaptive mesh refinement is ideally suited for this problem. The use of high-order methods is motivated by the high level of resolution required off the fault in earlier the low-order finite volume simulations; we believe this need for resolution is a result of the excessive numerical dissipation of low-order methods. In bfam spatial adaptivity is handled using the p4est library and temporal adaptivity will be accomplished through local time stepping. In this presentation we will present the guiding principles behind the library as well as verification of code against the Southern California Earthquake Center dynamic rupture code validation test problems.
Sparse time-frequency decomposition based on dictionary adaptation.
Hou, Thomas Y; Shi, Zuoqiang
2016-04-13
In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. PMID:26953172
NASA Astrophysics Data System (ADS)
Roussel, Olivier; Schneider, Kai
2010-03-01
An adaptive mulitresolution method based on a second-order finite volume discretization is presented for solving the three-dimensional compressible Navier-Stokes equations in Cartesian geometry. The explicit time discretization is of second-order and for flux evaluation a 2-4 Mac Cormack scheme is used. Coherent Vortex Simulations (CVS) are performed by decomposing the flow variables into coherent and incoherent contributions. The coherent part is computed deterministically on a locally refined grid using the adaptive multiresolution method while the influence of the incoherent part is neglected to model turbulent dissipation. The computational efficiency of this approach in terms of memory and CPU time compression is illustrated for turbulent mixing layers in the weakly compressible regime and for Reynolds numbers based on the mixing layer thickness between 50 and 200. Comparisons with direct numerical simulations allow to assess the precision and efficiency of CVS.
Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling
NASA Technical Reports Server (NTRS)
Trujillo, Anna C.; Gregory, Irene M.
2012-01-01
Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Development of a Godunov method for Maxwell's equations with Adaptive Mesh Refinement
NASA Astrophysics Data System (ADS)
Barbas, Alfonso; Velarde, Pedro
2015-11-01
In this paper we present a second order 3D method for Maxwell's equations based on a Godunov scheme with Adaptive Mesh Refinement (AMR). In order to achieve it, we apply a limiter which better preserves extrema and boundary conditions based on a characteristic fields decomposition. Despite being more complex, simplifications in the boundary conditions make the resulting method competitive in computer time consumption and accuracy compared to FDTD. AMR allows us to simulate systems with a sharp step in material properties with negligible rebounds and also large domains with accuracy in small wavelengths.
Serial identification of EEG patterns using adaptive wavelet-based analysis
NASA Astrophysics Data System (ADS)
Nazimov, A. I.; Pavlov, A. N.; Nazimova, A. A.; Grubov, V. V.; Koronovskii, A. A.; Sitnikova, E.; Hramov, A. E.
2013-10-01
A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.
Method for removing tilt control in adaptive optics systems
Salmon, J.T.
1998-04-28
A new adaptive optics system and method of operation are disclosed, whereby the method removes tilt control, and includes the steps of using a steering mirror to steer a wavefront in the desired direction, for aiming an impinging aberrated light beam in the direction of a deformable mirror. The deformable mirror has its surface deformed selectively by means of a plurality of actuators, and compensates, at least partially, for existing aberrations in the light beam. The light beam is split into an output beam and a sample beam, and the sample beam is sampled using a wavefront sensor. The sampled signals are converted into corresponding electrical signals for driving a controller, which, in turn, drives the deformable mirror in a feedback loop in response to the sampled signals, for compensating for aberrations in the wavefront. To this purpose, a displacement error (gradient) of the wavefront is measured, and adjusted by a modified gain matrix, which satisfies the following equation: G{prime} = (I{minus}X(X{sup T} X){sup {minus}1}X{sup T})G(I{minus}A). 3 figs.
Method for removing tilt control in adaptive optics systems
Salmon, Joseph Thaddeus
1998-01-01
A new adaptive optics system and method of operation, whereby the method removes tilt control, and includes the steps of using a steering mirror to steer a wavefront in the desired direction, for aiming an impinging aberrated light beam in the direction of a deformable mirror. The deformable mirror has its surface deformed selectively by means of a plurality of actuators, and compensates, at least partially, for existing aberrations in the light beam. The light beam is split into an output beam and a sample beam, and the sample beam is sampled using a wavefront sensor. The sampled signals are converted into corresponding electrical signals for driving a controller, which, in turn, drives the deformable mirror in a feedback loop in response to the sampled signals, for compensating for aberrations in the wavefront. To this purpose, a displacement error (gradient) of the wavefront is measured, and adjusted by a modified gain matrix, which satisfies the following equation: G'=(I-X(X.sup.T X).sup.-1 X.sup.T)G(I-A)
Adapted G-mode Clustering Method applied to Asteroid Taxonomy
NASA Astrophysics Data System (ADS)
Hasselmann, Pedro H.; Carvano, Jorge M.; Lazzaro, D.
2013-11-01
The original G-mode was a clustering method developed by A. I. Gavrishin in the late 60's for geochemical classification of rocks, but was also applied to asteroid photometry, cosmic rays, lunar sample and planetary science spectroscopy data. In this work, we used an adapted version to classify the asteroid photometry from SDSS Moving Objects Catalog. The method works by identifying normal distributions in a multidimensional space of variables. The identification starts by locating a set of points with smallest mutual distance in the sample, which is a problem when data is not planar. Here we present a modified version of the G-mode algorithm, which was previously written in FORTRAN 77, in Python 2.7 and using NumPy, SciPy and Matplotlib packages. The NumPy was used for array and matrix manipulation and Matplotlib for plot control. The Scipy had a import role in speeding up G-mode, Scipy.spatial.distance.mahalanobis was chosen as distance estimator and Numpy.histogramdd was applied to find the initial seeds from which clusters are going to evolve. Scipy was also used to quickly produce dendrograms showing the distances among clusters. Finally, results for Asteroids Taxonomy and tests for different sample sizes and implementations are presented.
An h-adaptive finite element method for turbulent heat transfer
Carriington, David B
2009-01-01
A two-equation turbulence closure model (k-{omega}) using an h-adaptive grid technique and finite element method (FEM) has been developed to simulate low Mach flow and heat transfer. These flows are applicable to many flows in engineering and environmental sciences. Of particular interest in the engineering modeling areas are: combustion, solidification, and heat exchanger design. Flows for indoor air quality modeling and atmospheric pollution transport are typical types of environmental flows modeled with this method. The numerical method is based on a hybrid finite element model using an equal-order projection process. The model includes thermal and species transport, localized mesh refinement (h-adaptive) and Petrov-Galerkin weighting for the stabilizing the advection. This work develops the continuum model of a two-equation turbulence closure method. The fractional step solution method is stated along with the h-adaptive grid method (Carrington and Pepper, 2002). Solutions are presented for 2d flow over a backward-facing step.
Profiling Students' Adaptation Styles in Web-based Learning.
ERIC Educational Resources Information Center
Lee, Myung-Geun
2001-01-01
Discussion of Web-based instruction (WBI) focuses on a study of Korean universities that analyzed learners' adaptation styles and characteristics by retrospectively assessing the perceptions of various aspects of WBI. Considers computer literacy, interaction with instructor and students, difficulty of contents, and learners' perception of academic…
Adaptive NUC algorithm for uncooled IRFPA based on neural networks
NASA Astrophysics Data System (ADS)
Liu, Ziji; Jiang, Yadong; Lv, Jian; Zhu, Hongbin
2010-10-01
With developments in uncooled infrared plane array (UFPA) technology, many new advanced uncooled infrared sensors are used in defensive weapons, scientific research, industry and commercial applications. A major difference in imaging techniques between infrared IRFPA imaging system and a visible CCD camera is that, IRFPA need nonuniformity correction and dead pixel compensation, we usually called it infrared image pre-processing. Two-point or multi-point correction algorithms based on calibration commonly used may correct the non-uniformity of IRFPAs, but they are limited by pixel linearity and instability. Therefore, adaptive non-uniformity correction techniques are developed. Two of these adaptive non-uniformity correction algorithms are mostly discussed, one is based on temporal high-pass filter, and another is based on neural network. In this paper, a new NUC algorithm based on improved neural networks is introduced, and involves the compare result between improved neural networks and other adaptive correction techniques. A lot of different will discussed in different angle, like correction effects, calculation efficiency, hardware implementation and so on. According to the result and discussion, it could be concluding that the adaptive algorithm offers improved performance compared to traditional calibration mode techniques. This new algorithm not only provides better sensitivity, but also increases the system dynamic range. As the sensor application expended, it will be very useful in future infrared imaging systems.
Adaptive Knowledge Management of Project-Based Learning
ERIC Educational Resources Information Center
Tilchin, Oleg; Kittany, Mohamed
2016-01-01
The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…
Teaching a Biotechnology Curriculum Based on Adapted Primary Literature
ERIC Educational Resources Information Center
Falk, Hedda; Brill, Gilat; Yarden, Anat
2008-01-01
Adapted primary literature (APL) refers to an educational genre specifically designed to enable the use of research articles for learning biology in high school. The present investigation focuses on the pedagogical content knowledge (PCK) of four high-school biology teachers who enacted an APL-based curriculum in biotechnology. Using a…
Evidence-Based Practice in Adapted Physical Education
ERIC Educational Resources Information Center
Jin, Jooyeon; Yun, Joonkoo
2010-01-01
Although implementation of evidence-based practice (EBP) has been strongly advocated by federal legislation as well as school districts in recent years, the concept has not been well accepted in adapted physical education (APE), perhaps due to a lack of understanding of the central notion of EBP. The purpose of this article is to discuss how APE…
Frequency based design of modal controllers for adaptive optics systems.
Agapito, Guido; Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
2012-11-19
This paper addresses the problem of reducing the effects of wavefront distortions in ground-based telescopes within a "Modal-Control" framework. The proposed approach allows the designer to optimize the Youla parameter of a given modal controller with respect to a relevant adaptive optics performance criterion defined on a "sampled" frequency domain. This feature makes it possible to use turbulence/vibration profiles of arbitrary complexity (even empirical power spectral densities from data), while keeping the controller order at a moderate value. Effectiveness of the proposed solution is also illustrated through an adaptive optics numerical simulator. PMID:23187567
An Adaptive Digital Image Watermarking Algorithm Based on Morphological Haar Wavelet Transform
NASA Astrophysics Data System (ADS)
Huang, Xiaosheng; Zhao, Sujuan
At present, much more of the wavelet-based digital watermarking algorithms are based on linear wavelet transform and fewer on non-linear wavelet transform. In this paper, we propose an adaptive digital image watermarking algorithm based on non-linear wavelet transform--Morphological Haar Wavelet Transform. In the algorithm, the original image and the watermark image are decomposed with multi-scale morphological wavelet transform respectively. Then the watermark information is adaptively embedded into the original image in different resolutions, combining the features of Human Visual System (HVS). The experimental results show that our method is more robust and effective than the ordinary wavelet transform algorithms.
Image edge detection based on adaptive lifting scheme
NASA Astrophysics Data System (ADS)
Xia, Ping; Xiang, Xuejun; Wan, Junli
2009-10-01
Image edge is because the gradation is the result of not continuously, is image's information basic characteristic, is also one of hot topics in image processing. This paper analyzes traditional arithmetic of image edge detection and existing problem, uses adaptive lifting wavelet analysis, adaptive adjusts the predict filter and the update filter according to information's partial characteristic, thus realizes the processing information accurate match; at the same time, improves the wavelet edge detection operator, realizes one kind to be suitable for the adaptive lifting scheme image edge detection's algorithm, and applies this method in the medicine image edge detection. The experiment results show that this paper's algorithm is better than the traditional algorithm effect.
Cen, Guanjun; Zeng, Xianru; Long, Xiuzhen; Wei, Dewei; Gao, Xuyuan; Zeng, Tao
2015-01-01
In insects, the frequency distribution of the measurements of sclerotized body parts is generally used to classify larval instars and is characterized by a multimodal overlap between instar stages. Nonparametric methods with fixed bandwidths, such as histograms, have significant limitations when used to fit this type of distribution, making it difficult to identify divisions between instars. Fixed bandwidths have also been chosen somewhat subjectively in the past, which is another problem. In this study, we describe an adaptive kernel smoothing method to differentiate instars based on discontinuities in the growth rates of sclerotized insect body parts. From Brooks’ rule, we derived a new standard for assessing the quality of instar classification and a bandwidth selector that more accurately reflects the distributed character of specific variables. We used this method to classify the larvae of Austrosimulium tillyardianum (Diptera: Simuliidae) based on five different measurements. Based on head capsule width and head capsule length, the larvae were separated into nine instars. Based on head capsule postoccipital width and mandible length, the larvae were separated into 8 instars and 10 instars, respectively. No reasonable solution was found for antennal segment 3 length. Separation of the larvae into nine instars using head capsule width or head capsule length was most robust and agreed with Crosby’s growth rule. By strengthening the distributed character of the separation variable through the use of variable bandwidths, the adaptive kernel smoothing method could identify divisions between instars more effectively and accurately than previous methods. PMID:26546689
Imaging-Based Treatment Adaptation in Radiation Oncology.
Troost, Esther G C; Thorwarth, Daniela; Oyen, Wim J G
2015-12-01
In many tumor types, significant effort is being put into patient-tailored adaptation of treatment to improve outcome and preferably reduce toxicity. These opportunities first arose with the introduction of modern irradiation techniques (e.g., intensity-modulated radiotherapy) combined with functional imaging for more precise delineation of target volume. On the basis of functional CT, MRI, and PET results, radiation target volumes are altered during the course of treatment, or subvolumes inside the primary tumor are defined to enhance the dosing strategy. Moreover, the probability of complications to normal tissues is predicted using anatomic or functional imaging, such as in the use of CT or PET to predict radiation pneumonitis. Besides focusing, monitoring, and adapting photon therapy for solid tumors, PET also has a role in verifying proton-beam therapy. This article discusses the current state and remaining challenges of imaging-based treatment adaptation in radiation oncology. PMID:26429959
Searching for adaptive traits in genetic resources - phenology based approach
NASA Astrophysics Data System (ADS)
Bari, Abdallah
2015-04-01
Searching for adaptive traits in genetic resources - phenology based approach Abdallah Bari, Kenneth Street, Eddy De Pauw, Jalal Eddin Omari, and Chandra M. Biradar International Center for Agricultural Research in the Dry Areas, Rabat Institutes, Rabat, Morocco Phenology is an important plant trait not only for assessing and forecasting food production but also for searching in genebanks for adaptive traits. Among the phenological parameters we have been considering to search for such adaptive and rare traits are the onset (sowing period) and the seasonality (growing period). Currently an application is being developed as part of the focused identification of germplasm strategy (FIGS) approach to use climatic data in order to identify crop growing seasons and characterize them in terms of onset and duration. These approximations of growing period characteristics can then be used to estimate flowering and maturity dates for dryland crops, such as wheat, barley, faba bean, lentils and chickpea, and assess, among others, phenology-related traits such as days to heading [dhe] and grain filling period [gfp]. The approach followed here is based on first calculating long term average daily temperatures by fitting a curve to the monthly data over days from beginning of the year. Prior to the identification of these phenological stages the onset is extracted first from onset integer raster GIS layers developed based on a model of the growing period that considers both moisture and temperature limitations. The paper presents some examples of real applications of the approach to search for rare and adaptive traits.
Adaptive optics in digital micromirror based confocal microscopy
NASA Astrophysics Data System (ADS)
Pozzi, P.; Wilding, D.; Soloviev, O.; Vdovin, G.; Verhaegen, M.
2016-03-01
This proceeding reports early results in the development of a new technique for adaptive optics in confocal microscopy. The term adaptive optics refers to the branch of optics in which an active element in the optical system is used to correct inhomogeneities in the media through which light propagates. In its most classical form, mostly used in astronomical imaging, adaptive optics is achieved through a closed loop in which the actuators of a deformable mirror are driven by a wavefront sensor. This approach is severely limited in fluorescence microscopy, as the use of a wavefront sensor requires the presence of a bright, point like source in the field of view, a condition rarely satisfied in microscopy samples. Previously reported approaches to adaptive optics in fluorescence microscopy are therefore limited to the inclusion of fluorescent microspheres in the sample, to use as bright stars for wavefront sensors, or time consuming sensorless optimization procedures, requiring several seconds of optimization before the acquisition of a single image. We propose an alternative approach to the problem, implementing sensorless adaptive optics in a Programmable array microscope. A programmable array microscope is a microscope based on a digital micromirror device, in which the single elements of the micromirror act both as point sources and pinholes.
A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation
NASA Technical Reports Server (NTRS)
Bailey, Nathan R.; Scerbo, Mark W.; Freeman, Frederick G.; Mikulka, Peter J.; Scott, Lorissa A.
2004-01-01
Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed
Failure of Anisotropic Unstructured Mesh Adaption Based on Multidimensional Residual Minimization
NASA Technical Reports Server (NTRS)
Wood, William A.; Kleb, William L.
2003-01-01
An automated anisotropic unstructured mesh adaptation strategy is proposed, implemented, and assessed for the discretization of viscous flows. The adaption criteria is based upon the minimization of the residual fluctuations of a multidimensional upwind viscous flow solver. For scalar advection, this adaption strategy has been shown to use fewer grid points than gradient based adaption, naturally aligning mesh edges with discontinuities and characteristic lines. The adaption utilizes a compact stencil and is local in scope, with four fundamental operations: point insertion, point deletion, edge swapping, and nodal displacement. Evaluation of the solution-adaptive strategy is performed for a two-dimensional blunt body laminar wind tunnel case at Mach 10. The results demonstrate that the strategy suffers from a lack of robustness, particularly with regard to alignment of the bow shock in the vicinity of the stagnation streamline. In general, constraining the adaption to such a degree as to maintain robustness results in negligible improvement to the solution. Because the present method fails to consistently or significantly improve the flow solution, it is rejected in favor of simple uniform mesh refinement.
Effect of cooling procedure on final denture base adaptation.
Ganzarolli, S M; Rached, R N; Garcia, R C M R; Del Bel Cury, A A
2002-08-01
Well-fitted dentures prevent hyperplasic lesions, provide chewing efficiency and promote patient's comfort. Several factors may affect final adaptation of dentures, as the type of the acrylic resin, the flask cooling procedure and the water uptake. This investigation evaluated the effect of water storage and two different cooling procedures [bench cooling (BC) for 2 h; running water (RW) at 20 degrees C for 45 min] on the final adaptation of denture bases. A heat-cured acrylic resin (CL, Clássico, Clássico Artigos Odontológicos) and two microwave-cured acrylic resins [Acron MC, (AC) GC Dent. Ind. Corp.; Onda Cryl (OC), Clássico Artigos Odontológicos] were used to make the bases. Adaptation was assessed by measuring the weight of an intervening layer of silicone impression material between the base and the master die. Data was submitted to ANOVA and Tukey's test (0.05). The following means were found: (BC) CL=0.72 +/- 0.03 a; AC=0.70 +/- 0.03 b; OC=0.76 +/- 0.04 c//(RW) CL= 1.00 +/- 0.11 a; AC=1.00 +/- 0.12 a; OC=0.95 +/- 0.10 a. Different labels join groups that are not statistically different (P > 0.05). Comparisons are made among groups submitted to the same cooling procedure (BC or RW). The conclusions are: interaction of type of material and cooling procedure had a statistically significant effect on the final adaptation of the denture bases (P < 0.05); water storage was not detected as a source of variance (P > 0.05) on the final adaptation. PMID:12220348
A hybrid method for optimization of the adaptive Goldstein filter
NASA Astrophysics Data System (ADS)
Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue
2014-12-01
The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.
Binary adaptive semi-global matching based on image edges
NASA Astrophysics Data System (ADS)
Hu, Han; Rzhanov, Yuri; Hatcher, Philip J.; Bergeron, R. D.
2015-07-01
Image-based modeling and rendering is currently one of the most challenging topics in Computer Vision and Photogrammetry. The key issue here is building a set of dense correspondence points between two images, namely dense matching or stereo matching. Among all dense matching algorithms, Semi-Global Matching (SGM) is arguably one of the most promising algorithms for real-time stereo vision. Compared with global matching algorithms, SGM aggregates matching cost from several (eight or sixteen) directions rather than only the epipolar line using Dynamic Programming (DP). Thus, SGM eliminates the classical "streaking problem" and greatly improves its accuracy and efficiency. In this paper, we aim at further improvement of SGM accuracy without increasing the computational cost. We propose setting the penalty parameters adaptively according to image edges extracted by edge detectors. We have carried out experiments on the standard Middlebury stereo dataset and evaluated the performance of our modified method with the ground truth. The results have shown a noticeable accuracy improvement compared with the results using fixed penalty parameters while the runtime computational cost was not increased.
Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai
2015-01-01
The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120
Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai
2015-01-01
The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120
LDRD Final Report: Adaptive Methods for Laser Plasma Simulation
Dorr, M R; Garaizar, F X; Hittinger, J A
2003-01-29
The goal of this project was to investigate the utility of parallel adaptive mesh refinement (AMR) in the simulation of laser plasma interaction (LPI). The scope of work included the development of new numerical methods and parallel implementation strategies. The primary deliverables were (1) parallel adaptive algorithms to solve a system of equations combining plasma fluid and light propagation models, (2) a research code implementing these algorithms, and (3) an analysis of the performance of parallel AMR on LPI problems. The project accomplished these objectives. New algorithms were developed for the solution of a system of equations describing LPI. These algorithms were implemented in a new research code named ALPS (Adaptive Laser Plasma Simulator) that was used to test the effectiveness of the AMR algorithms on the Laboratory's large-scale computer platforms. The details of the algorithm and the results of the numerical tests were documented in an article published in the Journal of Computational Physics [2]. A principal conclusion of this investigation is that AMR is most effective for LPI systems that are ''hydrodynamically large'', i.e., problems requiring the simulation of a large plasma volume relative to the volume occupied by the laser light. Since the plasma-only regions require less resolution than the laser light, AMR enables the use of efficient meshes for such problems. In contrast, AMR is less effective for, say, a single highly filamented beam propagating through a phase plate, since the resulting speckle pattern may be too dense to adequately separate scales with a locally refined mesh. Ultimately, the gain to be expected from the use of AMR is highly problem-dependent. One class of problems investigated in this project involved a pair of laser beams crossing in a plasma flow. Under certain conditions, energy can be transferred from one beam to the other via a resonant interaction with an ion acoustic wave in the crossing region. AMR provides an
Adapting Western Research Methods to Indigenous Ways of Knowing
Christopher, Suzanne
2013-01-01
Indigenous communities have long experienced exploitation by researchers and increasingly require participatory and decolonizing research processes. We present a case study of an intervention research project to exemplify a clash between Western research methodologies and Indigenous methodologies and how we attempted reconciliation. We then provide implications for future research based on lessons learned from Native American community partners who voiced concern over methods of Western deductive qualitative analysis. Decolonizing research requires constant reflective attention and action, and there is an absence of published guidance for this process. Continued exploration is needed for implementing Indigenous methods alone or in conjunction with appropriate Western methods when conducting research in Indigenous communities. Currently, examples of Indigenous methods and theories are not widely available in academic texts or published articles, and are often not perceived as valid. PMID:23678897
Camera calibration approach based on adaptive active target
NASA Astrophysics Data System (ADS)
Zhang, Yalin; Zhou, Fuqiang; Deng, Peng
2011-12-01
Aiming at calibrating camera on site, where the lighting condition is hardly controlled and the quality of target images would be declined when the angle between camera and target changes, an adaptive active target is designed and the camera calibration approach based on the target is proposed. The active adaptive target in which LEDs are embedded is flat, providing active feature point. Therefore the brightness of the feature point can be modified via adjusting the electricity, judging from the threshold of image feature criteria. In order to extract features of the image accurately, the concept of subpixel-precise thresholding is also proposed. It converts the discrete representation of the digital image to continuous function by bilinear interpolation, and the sub-pixel contours are acquired by the intersection of the continuous function and the appropriate selection of threshold. According to analysis of the relationship between the features of the image and the brightness of the target, the area ratio of convex hulls and the grey value variance are adopted as the criteria. Result of experiments revealed that the adaptive active target accommodates well to the changing of the illumination in the environment, the camera calibration approach based on adaptive active target can obtain high level of accuracy and fit perfectly for image targeting in various industrial sites.
NASA Astrophysics Data System (ADS)
Gotovac, Hrvoje; Srzic, Veljko
2014-05-01
Contaminant transport in natural aquifers is a complex, multiscale process that is frequently studied using different Eulerian, Lagrangian and hybrid numerical methods. Conservative solute transport is typically modeled using the advection-dispersion equation (ADE). Despite the large number of available numerical methods that have been developed to solve it, the accurate numerical solution of the ADE still presents formidable challenges. In particular, current numerical solutions of multidimensional advection-dominated transport in non-uniform velocity fields are affected by one or all of the following problems: numerical dispersion that introduces artificial mixing and dilution, grid orientation effects, unresolved spatial and temporal scales and unphysical numerical oscillations (e.g., Herrera et al, 2009; Bosso et al., 2012). In this work we will present Eulerian Lagrangian Adaptive Fup Collocation Method (ELAFCM) based on Fup basis functions and collocation approach for spatial approximation and explicit stabilized Runge-Kutta-Chebyshev temporal integration (public domain routine SERK2) which is especially well suited for stiff parabolic problems. Spatial adaptive strategy is based on Fup basis functions which are closely related to the wavelets and splines so that they are also compactly supported basis functions; they exactly describe algebraic polynomials and enable a multiresolution adaptive analysis (MRA). MRA is here performed via Fup Collocation Transform (FCT) so that at each time step concentration solution is decomposed using only a few significant Fup basis functions on adaptive collocation grid with appropriate scales (frequencies) and locations, a desired level of accuracy and a near minimum computational cost. FCT adds more collocations points and higher resolution levels only in sensitive zones with sharp concentration gradients, fronts and/or narrow transition zones. According to the our recent achievements there is no need for solving the large
Calvo, Juan Francisco; San José, Sol; Garrido, LLuís; Puertas, Enrique; Moragues, Sandra; Pozo, Miquel; Casals, Joan
2013-10-01
To introduce an approach for online adaptive replanning (i.e., dose-guided radiosurgery) in frameless stereotactic radiosurgery, when a 6-dimensional (6D) robotic couch is not available in the linear accelerator (linac). Cranial radiosurgical treatments are planned in our department using intensity-modulated technique. Patients are immobilized using thermoplastic mask. A cone-beam computed tomography (CBCT) scan is acquired after the initial laser-based patient setup (CBCT{sub setup}). The online adaptive replanning procedure we propose consists of a 6D registration-based mapping of the reference plan onto actual CBCT{sub setup}, followed by a reoptimization of the beam fluences (“6D plan”) to achieve similar dosage as originally was intended, while the patient is lying in the linac couch and the original beam arrangement is kept. The goodness of the online adaptive method proposed was retrospectively analyzed for 16 patients with 35 targets treated with CBCT-based frameless intensity modulated technique. Simulation of reference plan onto actual CBCT{sub setup}, according to the 4 degrees of freedom, supported by linac couch was also generated for each case (4D plan). Target coverage (D99%) and conformity index values of 6D and 4D plans were compared with the corresponding values of the reference plans. Although the 4D-based approach does not always assure the target coverage (D99% between 72% and 103%), the proposed online adaptive method gave a perfect coverage in all cases analyzed as well as a similar conformity index value as was planned. Dose-guided radiosurgery approach is effective to assure the dose coverage and conformity of an intracranial target volume, avoiding resetting the patient inside the mask in a “trial and error” way so as to remove the pitch and roll errors when a robotic table is not available.
Vortical Flow Prediction using an Adaptive Unstructured Grid Method. Chapter 11
NASA Technical Reports Server (NTRS)
Pirzadeh, Shahyar Z.
2009-01-01
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving vortical flow problems. The first test case concerns vortex flow over a simple 65 delta wing with different values of leading-edge radius. Although the geometry is quite simple, it poses a challenging problem for computing vortices originating from blunt leading edges. The second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the wind-tunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
Solution of Reactive Compressible Flows Using an Adaptive Wavelet Method
NASA Astrophysics Data System (ADS)
Zikoski, Zachary; Paolucci, Samuel; Powers, Joseph
2008-11-01
This work presents numerical simulations of reactive compressible flow, including detailed multicomponent transport, using an adaptive wavelet algorithm. The algorithm allows for dynamic grid adaptation which enhances our ability to fully resolve all physically relevant scales. The thermodynamic properties, equation of state, and multicomponent transport properties are provided by CHEMKIN and TRANSPORT libraries. Results for viscous detonation in a H2:O2:Ar mixture, and other problems in multiple dimensions, are included.
An adaptive finite element method for convective heat transfer with variable fluid properties
NASA Astrophysics Data System (ADS)
Pelletier, Dominique; Ilinca, Florin; Hetu, Jean-Francois
1993-07-01
This paper presents an adaptive finite element method based on remeshing to solve incompressible viscous flow problems for which fluid properties present a strong temperature dependence. Solutions are obtained in primitive variables using a highly accurate finite element approximation on unstructured grids. Two general purpose error estimators, that take into account fluid properties variations, are presented. The methodology is applied to a problem of practical interest: the thermal convection of corn syrup in an enclosure with localized heating. Predictions are in good agreement with experimental measurements. The method leads to improved accuracy and reliability of finite element predictions.
ERIC Educational Resources Information Center
Richards, Zoe; Kostadinov, Iordan; Jones, Michelle; Richard, Lucie; Cargo, Margaret
2014-01-01
Little research has assessed the fidelity, adaptation or integrity of activities implemented within community-based obesity prevention initiatives. To address this gap, a mixed-method process evaluation was undertaken in the context of the South Australian Obesity Prevention and Lifestyle (OPAL) initiative. An ecological coding procedure assessed…
The Adapted Fresno Test of Competence in Evidence-Based Practice
ERIC Educational Resources Information Center
McCluskey, Annie; Bishop, Bianca
2009-01-01
Introduction: Health educators who teach professionals about evidence-based practice (EBP) need instruments to measure change in skills and knowledge. This study aimed to develop and evaluate the interrater reliability, internal consistency, and responsiveness of the Adapted Fresno Test (AFT) of competence in EBP. Methods: Reliability testing…
Adaptive skin segmentation via feature-based face detection
NASA Astrophysics Data System (ADS)
Taylor, Michael J.; Morris, Tim
2014-05-01
Variations in illumination can have significant effects on the apparent colour of skin, which can be damaging to the efficacy of any colour-based segmentation approach. We attempt to overcome this issue by presenting a new adaptive approach, capable of generating skin colour models at run-time. Our approach adopts a Viola-Jones feature-based face detector, in a moderate-recall, high-precision configuration, to sample faces within an image, with an emphasis on avoiding potentially detrimental false positives. From these samples, we extract a set of pixels that are likely to be from skin regions, filter them according to their relative luma values in an attempt to eliminate typical non-skin facial features (eyes, mouths, nostrils, etc.), and hence establish a set of pixels that we can be confident represent skin. Using this representative set, we train a unimodal Gaussian function to model the skin colour in the given image in the normalised rg colour space - a combination of modelling approach and colour space that benefits us in a number of ways. A generated function can subsequently be applied to every pixel in the given image, and, hence, the probability that any given pixel represents skin can be determined. Segmentation of the skin, therefore, can be as simple as applying a binary threshold to the calculated probabilities. In this paper, we touch upon a number of existing approaches, describe the methods behind our new system, present the results of its application to arbitrary images of people with detectable faces, which we have found to be extremely encouraging, and investigate its potential to be used as part of real-time systems.
Patch-based Adaptive Mesh Refinement for Multimaterial Hydrodynamics
Lomov, I; Pember, R; Greenough, J; Liu, B
2005-10-18
We present a patch-based direct Eulerian adaptive mesh refinement (AMR) algorithm for modeling real equation-of-state, multimaterial compressible flow with strength. Our approach to AMR uses a hierarchical, structured grid approach first developed by (Berger and Oliger 1984), (Berger and Oliger 1984). The grid structure is dynamic in time and is composed of nested uniform rectangular grids of varying resolution. The integration scheme on the grid hierarchy is a recursive procedure in which the coarse grids are advanced, then the fine grids are advanced multiple steps to reach the same time, and finally the coarse and fine grids are synchronized to remove conservation errors during the separate advances. The methodology presented here is based on a single grid algorithm developed for multimaterial gas dynamics by (Colella et al. 1993), refined by(Greenough et al. 1995), and extended to the solution of solid mechanics problems with significant strength by (Lomov and Rubin 2003). The single grid algorithm uses a second-order Godunov scheme with an approximate single fluid Riemann solver and a volume-of-fluid treatment of material interfaces. The method also uses a non-conservative treatment of the deformation tensor and an acoustic approximation for shear waves in the Riemann solver. This departure from a strict application of the higher-order Godunov methodology to the equation of solid mechanics is justified due to the fact that highly nonlinear behavior of shear stresses is rare. This algorithm is implemented in two codes, Geodyn and Raptor, the latter of which is a coupled rad-hydro code. The present discussion will be solely concerned with hydrodynamics modeling. Results from a number of simulations for flows with and without strength will be presented.
Anisotropic optical flow algorithm based on self-adaptive cellular neural network
NASA Astrophysics Data System (ADS)
Zhang, Congxuan; Chen, Zhen; Li, Ming; Sun, Kaiqiong
2013-01-01
An anisotropic optical flow estimation method based on self-adaptive cellular neural networks (CNN) is proposed. First, a novel optical flow energy function which contains a robust data term and an anisotropic smoothing term is projected. Next, the CNN model which has the self-adaptive feedback operator and threshold is presented according to the Euler-Lagrange partial differential equations of the proposed optical flow energy function. Finally, the elaborate evaluation experiments indicate the significant effects of the various proposed strategies for optical flow estimation, and the comparison results with the other methods show that the proposed algorithm has better performance in computing accuracy and efficiency.
NASA Technical Reports Server (NTRS)
Wang, Ray (Inventor)
2009-01-01
A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.
NASA Astrophysics Data System (ADS)
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Creating evidence-based research in adapted physical activity.
Reid, Greg; Bouffard, Marcel; MacDonald, Catherine
2012-04-01
Professional practice guided by the best research evidence is a usually referred to as evidence-based practice. The aim of the present paper is to describe five fundamental beliefs of adapted physical activity practices that should be considered in an 8-step research model to create evidence-based research in adapted physical activity. The five beliefs are individualization, critical thinking, self-determination, program effectiveness, and multifactor complexity. The research model includes conceptualize the problem, conduct research on the process of the problem, conceptualize and specify the intervention, evaluate intervention outcomes, evaluate intervention processes, determine person-by-treatment interactions, determine context-dependent limitations, and investigate factors related to intervention adoption maintenance. The eight steps are explained with reference to two research programs that used a randomized control group design. PMID:22467832
Adaptive norm-based coding of facial identity.
Rhodes, Gillian; Jeffery, Linda
2006-09-01
Identification of a face is facilitated by adapting to its computationally opposite identity, suggesting that the average face functions as a norm for coding identity [Leopold, D. A., O'Toole, A. J., Vetter, T., & Blanz, V. (2001). Prototype-referenced shape encoding revealed by high-level aftereffects. Nature Neuroscience, 4, 89-94; Leopold, D. A., Rhodes, G., Müller, K. -M., & Jeffery, L. (2005). The dynamics of visual adaptation to faces. Proceedings of the Royal Society of London, Series B, 272, 897-904]. Crucially, this interpretation requires that the aftereffect is selective for the opposite identity, but this has not been convincingly demonstrated. We demonstrate such selectivity, observing a larger aftereffect for opposite than non-opposite adapt-test pairs that are matched on perceptual contrast (dissimilarity). Component identities were also harder to detect in morphs of opposite than non-opposite face pairs. We propose an adaptive norm-based coding model of face identity. PMID:16647736
An Adaptive Watershed Management Assessment Based on Watershed Investigation Data
NASA Astrophysics Data System (ADS)
Kang, Min Goo; Park, Seung Woo
2015-05-01
The aim of this study was to assess the states of watersheds in South Korea and to formulate new measures to improve identified inadequacies. The study focused on the watersheds of the Han River basin and adopted an adaptive watershed management framework. Using data collected during watershed investigation projects, we analyzed the management context of the study basin and identified weaknesses in water use management, flood management, and environmental and ecosystems management in the watersheds. In addition, we conducted an interview survey to obtain experts' opinions on the possible management of watersheds in the future. The results of the assessment show that effective management of the Han River basin requires adaptive watershed management, which includes stakeholders' participation and social learning. Urbanization was the key variable in watershed management of the study basin. The results provide strong guidance for future watershed management and suggest that nonstructural measures are preferred to improve the states of the watersheds and that consistent implementation of the measures can lead to successful watershed management. The results also reveal that governance is essential for adaptive watershed management in the study basin. A special ordinance is necessary to establish governance and aid social learning. Based on the findings, a management process is proposed to support new watershed management practices. The results will be of use to policy makers and practitioners who can implement the measures recommended here in the early stages of adaptive watershed management in the Han River basin. The measures can also be applied to other river basins.
Adaptation of a-Stratified Method in Variable Length Computerized Adaptive Testing.
ERIC Educational Resources Information Center
Wen, Jian-Bing; Chang, Hua-Hua; Hau, Kit-Tai
Test security has often been a problem in computerized adaptive testing (CAT) because the traditional wisdom of item selection overly exposes high discrimination items. The a-stratified (STR) design advocated by H. Chang and his collaborators, which uses items of less discrimination in earlier stages of testing, has been shown to be very…
NASA Technical Reports Server (NTRS)
Olynick, David P.; Hassan, H. A.; Moss, James N.
1988-01-01
A grid generation and adaptation procedure based on the method of transfinite interpolation is incorporated into the Direct Simulation Monte Carlo Method of Bird. In addition, time is advanced based on a local criterion. The resulting procedure is used to calculate steady flows past wedges and cones. Five chemical species are considered. In general, the modifications result in a reduced computational effort. Moreover, preliminary results suggest that the simulation method is time step dependent if requirements on cell sizes are not met.
Study of adaptive methods for data compression of scanner data
NASA Technical Reports Server (NTRS)
1977-01-01
The performance of adaptive image compression techniques and the applicability of a variety of techniques to the various steps in the data dissemination process are examined in depth. It is concluded that the bandwidth of imagery generated by scanners can be reduced without introducing significant degradation such that the data can be transmitted over an S-band channel. This corresponds to a compression ratio equivalent to 1.84 bits per pixel. It is also shown that this can be achieved using at least two fairly simple techniques with weight-power requirements well within the constraints of the LANDSAT-D satellite. These are the adaptive 2D DPCM and adaptive hybrid techniques.
Systems and Methods for Derivative-Free Adaptive Control
NASA Technical Reports Server (NTRS)
Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)
2015-01-01
An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.
ERIC Educational Resources Information Center
Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen
2012-01-01
This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…
NASA Astrophysics Data System (ADS)
Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda
2014-05-01
Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.
NASA Astrophysics Data System (ADS)
Schneider, Kai; Roussel, Olivier; Farge, Marie
2007-11-01
Coherent Vortex Simulation is based on the wavelet decomposition of the flow into coherent and incoherent components. An adaptive multiresolution method using second order finite volumes with explicit time discretization, a 2-4 Mac Cormack scheme, allows an efficient computation of the coherent flow on a dynamically adapted grid. Neglecting the influence of the incoherent background models turbulent dissipation. We present CVS computation of three dimensional compressible time developing mixing layer. We show the speed up in CPU time with respect to DNS and the obtained memory reduction thanks to dynamical octree data structures. The impact of different filtering strategies is discussed and it is found that isotropic wavelet thresholding of the Favre averaged gradient of the momentum yields the most effective results.
Adaptive particle refinement and derefinement applied to the smoothed particle hydrodynamics method
NASA Astrophysics Data System (ADS)
Barcarolo, D. A.; Le Touzé, D.; Oger, G.; de Vuyst, F.
2014-09-01
SPH simulations are usually performed with a uniform particle distribution. New techniques have been recently proposed to enable the use of spatially varying particle distributions, which encouraged the development of automatic adaptivity and particle refinement/derefinement algorithms. All these efforts resulted in very interesting and promising procedures leading to more efficient and faster SPH simulations. In this article, a family of particle refinement techniques is reviewed and a new derefinement technique is proposed and validated through several test cases involving both free-surface and viscous flows. Besides, this new procedure allows higher resolutions in the regions requiring increased accuracy. Moreover, several levels of refinement can be used with this new technique, as often encountered in adaptive mesh refinement techniques in mesh-based methods.
Individual-based models for adaptive diversification in high-dimensional phenotype spaces.
Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael
2016-02-01
Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. PMID:26598329
Adaptive sensing based on profiles for sensor systems.
Ishida, Yoshiteru; Tokumitsu, Masahiro
2009-01-01
This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission. PMID:22291516
NASA Astrophysics Data System (ADS)
Ghamisi, Pedram; Kumar, Lalit
2012-01-01
Hyperspectral sensors generate useful information about climate and the earth surface in numerous contiguous narrow spectral bands, and are widely used in resource management, agriculture, environmental monitoring, etc. Compression of the hyperspectral data helps in long-term storage and transmission systems. Lossless compression is preferred for high-detail data, such as hyperspectral data. Due to high redundancy in neighboring spectral bands and the tendency to achieve a higher compression ratio, using adaptive coding methods for hyperspectral data seems suitable for this purpose. This paper introduces two new compression methods. One of these methods is adaptive and powerful for the compression of hyperspectral data, which is based on separating the bands with different specifications by the histogram and Binary Particle Swarm Optimization (BPSO) and compressing each one a different manner. The new proposed methods improve the compression ratio of the JPEG standards and save storage space the transmission. The proposed methods are applied on different test cases, and the results are evaluated and compared with some other compression methods, such as lossless JPEG and JPEG2000.
Stille, Christopher J.; Lockhart, Steven A.; Maertens, Julie A.; Madden, Christi A.; Darden, Paul M.
2015-01-01
Background and Purpose: Primary care practice-based research has become more complex with increased use of electronic health records (EHRs). Little has been reported about changes in study planning and execution that are required as practices change from paper-based to electronic-based environments. We describe the evolution of a pediatric practice-based intervention study as it was adapted for use in the electronic environment, to enable other practice-based researchers to plan efficient, effective studies. Methods: We adapted a paper-based pediatric office-level intervention to enhance parent-provider communication about subspecialty referrals for use in two practice-based research networks (PBRNs) with partially and fully electronic environments. We documented the process of adaptation and its effect on study feasibility and efficiency, resource use, and administrative and regulatory complexities, as the study was implemented in the two networks. Results: Considerable time and money was required to adapt the paper-based study to the electronic environment, requiring extra meetings with institutional EHR-, regulatory-, and administrative teams, and increased practice training. Institutional unfamiliarity with using EHRs in practice-based research, and the consequent need to develop new policies, were major contributors to delays. Adapting intervention tools to the EHR and minimizing practice disruptions was challenging, but resulted in several efficiencies as compared with a paper-based project. In particular, recruitment and tracking of subjects and data collection were easier and more efficient. Conclusions: Practice-based intervention research in an electronic environment adds considerable cost and time at the outset of a study, especially for centers unfamiliar with such research. Efficiencies generated have the potential of easing the work of study enrollment, subject tracking, and data collection. PMID:25848633
Fast complex memory polynomial-based adaptive digital predistorter
NASA Astrophysics Data System (ADS)
Singh Sappal, Amandeep; Singh Patterh, Manjeet; Sharma, Sanjay
2011-07-01
Today's 3G wireless systems require both high linearity and high power amplifier (PA) efficiency. The high peak-to-average ratios of the digital modulation schemes used in 3G wireless systems require that the RF PA maintain high linearity over a large range while maintaining this high efficiency; these two requirements are often at odds with each other with many of the traditional amplifier architectures. In this article, a fast and easy-to-implement adaptive digital predistorter has been presented for Wideband Code Division Multiplexed signals using complex memory polynomial work function. The proposed algorithm has been implemented to test a Motorola LDMOSFET PA. The proposed technique also takes care of the memory effects of the PA, which have been ignored in many proposed techniques in the literature. The results show that the new complex memory polynomial-based adaptive digital predistorter has better linearisation performance than conventional predistortion techniques.
MEMS-based extreme adaptive optics for planet detection
NASA Astrophysics Data System (ADS)
Macintosh, Bruce; Graham, James; Oppenheimer, Ben; Poyneer, Lisa; Sivaramakrishnan, Anand; Veran, Jean-Pierre
2006-01-01
The next major step in the study of extrasolar planets will be the direct detection, resolved from their parent star, of a significant sample of Jupiter-like extrasolar giant planets. Such detection will open up new parts of the extrasolar planet distribution and allow spectroscopic characterization of the planets themselves. Detecting Jovian planets at 5-50 AU scale orbiting nearby stars requires adaptive optics systems and coronagraphs an order of magnitude more powerful than those available today - the realm of "Extreme" adaptive optics. We present the basic requirements and design for such a system, the Gemini Planet Imager (GPI.) GPI will require a MEMS-based deformable mirror with good surface quality, 2-4 micron stroke (operated in tandem with a conventional low-order "woofer" mirror), and a fully-functional 48-actuator-diameter aperture.
MEMS-based extreme adaptive optics for planet detection
Macintosh, B A; Graham, J R; Oppenheimer, B; Poyneer, L; Sivaramakrishnan, A; Veran, J
2005-11-18
The next major step in the study of extrasolar planets will be the direct detection, resolved from their parent star, of a significant sample of Jupiter-like extrasolar giant planets. Such detection will open up new parts of the extrasolar planet distribution and allow spectroscopic characterization of the planets themselves. Detecting Jovian planets at 5-50 AU scale orbiting nearby stars requires adaptive optics systems and coronagraphs an order of magnitude more powerful than those available today--the realm of ''Extreme'' adaptive optics. We present the basic requirements and design for such a system, the Gemini Planet Imager (GPI.) GPI will require a MEMS-based deformable mirror with good surface quality, 2-4 micron stroke (operated in tandem with a conventional low-order ''woofer'' mirror), and a fully-functional 48-actuator-diameter aperture.
Adaptive virulence evolution: the good old fitness-based approach.
Alizon, Samuel; Michalakis, Yannis
2015-05-01
Infectious diseases could be expected to evolve towards complete avirulence to their hosts if given enough time. However, this is not the case. Often, virulence is maintained because it is linked to adaptive advantages to the parasite, a situation that is often associated with the hypothesis known as the transmission-virulence trade-off hypothesis. Here, we argue that this hypothesis has three limitations, which are related to how virulence is defined, the possibility of multiple trade-offs, and the difficulty of testing the hypothesis empirically. By adopting a fitness-based approach, where the relation between virulence and the fitness of the parasite throughout its life cycle is directly assessed, it is possible to address these limitations and to determine directly whether virulence is adaptive. PMID:25837917
A New Method to Cancel RFI---The Adaptive Filter
NASA Astrophysics Data System (ADS)
Bradley, R.; Barnbaum, C.
1996-12-01
An increasing amount of precious radio frequency spectrum in the VHF, UHF, and microwave bands is being utilized each year to support new commercial and military ventures, and all have the potential to interfere with radio astronomy observations. Some radio spectral lines of astronomical interest occur outside the protected radio astronomy bands and are unobservable due to heavy interference. Conventional approaches to deal with RFI include legislation, notch filters, RF shielding, and post-processing techniques. Although these techniques are somewhat successful, each suffers from insufficient interference cancellation. One concept of interference excision that has not been used before in radio astronomy is adaptive interference cancellation. The concept of adaptive interference canceling was first introduced in the mid-1970s as a way to reduce unwanted noise in low frequency (audio) systems. Examples of such systems include the canceling of maternal ECG in fetal electrocardiography and the reduction of engine noise in the passenger compartment of automobiles. Only recently have high-speed digital filter chips made adaptive filtering possible in a bandwidth as large a few megahertz, finally opening the door to astronomical uses. The system consists of two receivers: the main beam of the radio telescope receives the desired signal corrupted by RFI coming in the sidelobes, and the reference antenna receives only the RFI. The reference antenna is processed using a digital adaptive filter and then subtracted from the signal in the main beam, thus producing the system output. The weights of the digital filter are adjusted by way of an algorithm that minimizes, in a least-squares sense, the power output of the system. Through an adaptive-iterative process, the interference canceler will lock onto the RFI and the filter will adjust itself to minimize the effect of the RFI at the system output. We are building a prototype 100 MHz receiver and will measure the cancellation
Vivid Motor Imagery as an Adaptation Method for Head Turns on a Short-Arm Centrifuge
NASA Technical Reports Server (NTRS)
Newby, N. J.; Mast, F. W.; Natapoff, A.; Paloski, W. H.
2006-01-01
from one another. For the perceived duration of sensations, the CG group again exhibited the least amount of adaptation. However, the rates of adaptation of the PA and the MA groups were indistinguishable, suggesting that the imagined pseudostimulus appeared to be just as effective a means of adaptation as the actual stimulus. The MA group's rate of adaptation to motion sickness symptoms was also comparable to the PA group. The use of vivid motor imagery may be an effective method for adapting to the illusory sensations and motion sickness symptoms produced by cross-coupled stimuli. For space-based AG applications, this technique may prove quite useful in retaining astronauts considered highly susceptible to motion sickness as it reduces the number of actual CCS required to attain adaptation.
Experiments on Adaptive Techniques for Host-Based Intrusion Detection
DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.; THOMAS, EDWARD V.; WUNSCH, DONALD
2001-09-01
This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerable preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.
Identification-free adaptive optimal control based on switching predictive models
NASA Astrophysics Data System (ADS)
Luo, Wenguang; Pan, Shenghui; Ma, Zhaomin; Lan, Hongli
2008-10-01
An identification-free adaptive optimal control based on switching predictive models is proposed for the systems with big inertia, long time delay and multi models. Multi predictive models are set in the identification-free adaptive predictive control, and switched according to the optimal switching instants in control of the switching law along with the system running situations in real time. The switching law is designed based on the most important character parameter of the systems, and the optimal switching instants are computed out with the optimal theory for switched systems. The simulation test results show the proposed method is suitable to the systems, such as superheated steam temperature systems of electric power plants, can provide excellent control performance, improve rejecting disturbance ability and self-adaptability, and has lower demand on the predictive model precision.
The use of the spectral method within the fast adaptive composite grid method
McKay, S.M.
1994-12-31
The use of efficient algorithms for the solution of partial differential equations has been sought for many years. The fast adaptive composite grid (FAC) method combines an efficient algorithm with high accuracy to obtain low cost solutions to partial differential equations. The FAC method achieves fast solution by combining solutions on different grids with varying discretizations and using multigrid like techniques to find fast solution. Recently, the continuous FAC (CFAC) method has been developed which utilizes an analytic solution within a subdomain to iterate to a solution of the problem. This has been shown to achieve excellent results when the analytic solution can be found. The CFAC method will be extended to allow solvers which construct a function for the solution, e.g., spectral and finite element methods. In this discussion, the spectral methods will be used to provide a fast, accurate solution to the partial differential equation. As spectral methods are more accurate than finite difference methods, the ensuing accuracy from this hybrid method outside of the subdomain will be investigated.
Zhou, Hui; Kunz, Thomas; Schwartz, Howard
2011-01-01
Traditional oscillators used in timing modules of CDMA and WiMAX base stations are large and expensive. Applying cheaper and smaller, albeit more inaccurate, oscillators in timing modules is an interesting research challenge. An adaptive control algorithm is presented to enhance the oscillators to meet the requirements of base stations during holdover mode. An oscillator frequency stability model is developed for the adaptive control algorithm. This model takes into account the control loop which creates the correction signal when the timing module is in locked mode. A recursive prediction error method is used to identify the system model parameters. Simulation results show that an oscillator enhanced by our adaptive control algorithm improves the oscillator performance significantly, compared with uncorrected oscillators. Our results also show the benefit of explicitly modeling the control loop. Finally, the cumulative time error upper bound of such enhanced oscillators is investigated analytically and comparison results between the analytical and simulated upper bound are provided. The results show that the analytical upper bound can serve as a practical guide for system designers. PMID:21244973
The Pilates method and cardiorespiratory adaptation to training.
Tinoco-Fernández, Maria; Jiménez-Martín, Miguel; Sánchez-Caravaca, M Angeles; Fernández-Pérez, Antonio M; Ramírez-Rodrigo, Jesús; Villaverde-Gutiérrez, Carmen
2016-01-01
Although all authors report beneficial health changes following training based on the Pilates method, no explicit analysis has been performed of its cardiorespiratory effects. The objective of this study was to evaluate possible changes in cardiorespiratory parameters with the Pilates method. A total of 45 university students aged 18-35 years (77.8% female and 22.2% male), who did not routinely practice physical exercise or sports, volunteered for the study and signed informed consent. The Pilates training was conducted over 10 weeks, with three 1-hour sessions per week. Physiological cardiorespiratory responses were assessed using a MasterScreen CPX apparatus. After the 10-week training, statistically significant improvements were observed in mean heart rate (135.4-124.2 beats/min), respiratory exchange ratio (1.1-0.9) and oxygen equivalent (30.7-27.6) values, among other spirometric parameters, in submaximal aerobic testing. These findings indicate that practice of the Pilates method has a positive influence on cardiorespiratory parameters in healthy adults who do not routinely practice physical exercise activities. PMID:27357919
The morphing method as a flexible tool for adaptive local/non-local simulation of static fracture
NASA Astrophysics Data System (ADS)
Azdoud, Yan; Han, Fei; Lubineau, Gilles
2014-09-01
We introduce a framework that adapts local and non-local continuum models to simulate static fracture problems. Non-local models based on the peridynamic theory are promising for the simulation of fracture, as they allow discontinuities in the displacement field. However, they remain computationally expensive. As an alternative, we develop an adaptive coupling technique based on the morphing method to restrict the non-local model adaptively during the evolution of the fracture. The rest of the structure is described by local continuum mechanics. We conduct all simulations in three dimensions, using the relevant discretization scheme in each domain, i.e., the discontinuous Galerkin finite element method in the peridynamic domain and the continuous finite element method in the local continuum mechanics domain.
Adaptive finite element methods for two-dimensional problems in computational fracture mechanics
NASA Technical Reports Server (NTRS)
Min, J. B.; Bass, J. M.; Spradley, L. W.
1994-01-01
Some recent results obtained using solution-adaptive finite element methods in two-dimensional problems in linear elastic fracture mechanics are presented. The focus is on the basic issue of adaptive finite element methods for validating the new methodology by computing demonstration problems and comparing the stress intensity factors to analytical results.
Quality evaluation of adaptive optical image based on DCT and Rényi entropy
NASA Astrophysics Data System (ADS)
Xu, Yuannan; Li, Junwei; Wang, Jing; Deng, Rong; Dong, Yanbing
2015-04-01
The adaptive optical telescopes play a more and more important role in the detection system on the ground, and the adaptive optical images are so many that we need find a suitable method of quality evaluation to choose good quality images automatically in order to save human power. It is well known that the adaptive optical images are no-reference images. In this paper, a new logarithmic evaluation method based on the use of the discrete cosine transform(DCT) and Rényi entropy for the adaptive optical images is proposed. Through the DCT using one or two dimension window, the statistical property of Rényi entropy for images is studied. The different directional Rényi entropy maps of an input image containing different information content are obtained. The mean values of different directional Rényi entropy maps are calculated. For image quality evaluation, the different directional Rényi entropy and its standard deviation corresponding to region of interest is selected as an indicator for the anisotropy of the images. The standard deviation of different directional Rényi entropy is obtained as the quality evaluation value for adaptive optical image. Experimental results show the proposed method that the sorting quality matches well with the visual inspection.
Adaptive finite volume methods for time-dependent P.D.E.S.
Ware, J.; Berzins, M.
1995-12-31
The aim of adaptive methods for time-dependent p.d.e.s is to control the numerical error so that it is less than a user-specified tolerance. This error depends on the spatial discretization method, the spatial mesh, the method of time integration and the timestep. The spatial discretization method and positioning of the spatial mesh points should attempt to ensure that the spatial error is controlled to meet the user`s requirements. It is then desirable to integrate the o.d.e. system in time with sufficient accuracy so that the temporal error does not corrupt the spatial accuracy or the reliability of the spatial error estimates. This paper is concerned with the development of a prototype algorithm of this type, based on a cell-centered triangular finite volume scheme, for two space dimensional convection-dominated problems.
A Cartesian Adaptive Level Set Method for Two-Phase Flows
NASA Technical Reports Server (NTRS)
Ham, F.; Young, Y.-N.
2003-01-01
In the present contribution we develop a level set method based on local anisotropic Cartesian adaptation as described in Ham et al. (2002). Such an approach should allow for the smallest possible Cartesian grid capable of resolving a given flow. The remainder of the paper is organized as follows. In section 2 the level set formulation for free surface calculations is presented and its strengths and weaknesses relative to the other free surface methods reviewed. In section 3 the collocated numerical method is described. In section 4 the method is validated by solving the 2D and 3D drop oscilation problem. In section 5 we present some results from more complex cases including the 3D drop breakup in an impulsively accelerated free stream, and the 3D immiscible Rayleigh-Taylor instability. Conclusions are given in section 6.
Adaptive Projection Subspace Dimension for the Thick-Restart Lanczos Method
Yamazaki, Ichitaro; Bai, Zhaojun; Simon, Horst; Wang, Lin-Wang; Wu, K.
2008-10-01
The Thick-Restart Lanczos (TRLan) method is an effective method for solving large-scale Hermitian eigenvalue problems. However, its performance strongly depends on the dimension of the projection subspace. In this paper, we propose an objective function to quantify the effectiveness of a chosen subspace dimension, and then introduce an adaptive scheme to dynamically adjust the dimension at each restart. An open-source software package, nu-TRLan, which implements the TRLan method with this adaptive projection subspace dimension is available in the public domain. The numerical results of synthetic eigenvalue problems are presented to demonstrate that nu-TRLan achieves speedups of between 0.9 and 5.1 over the static method using a default subspace dimension. To demonstrate the effectiveness of nu-TRLan in a real application, we apply it to the electronic structure calculations of quantum dots. We show that nu-TRLan can achieve speedups of greater than 1.69 over the state-of-the-art eigensolver for this application, which is based on the Conjugate Gradient method with a powerful preconditioner.
Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.
Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong
2016-01-01
Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm. PMID:27092505
Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update
Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong
2016-01-01
Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm. PMID:27092505
Adaptive image contrast enhancement algorithm for point-based rendering
NASA Astrophysics Data System (ADS)
Xu, Shaoping; Liu, Xiaoping P.
2015-03-01
Surgical simulation is a major application in computer graphics and virtual reality, and most of the existing work indicates that interactive real-time cutting simulation of soft tissue is a fundamental but challenging research problem in virtual surgery simulation systems. More specifically, it is difficult to achieve a fast enough graphic update rate (at least 30 Hz) on commodity PC hardware by utilizing traditional triangle-based rendering algorithms. In recent years, point-based rendering (PBR) has been shown to offer the potential to outperform the traditional triangle-based rendering in speed when it is applied to highly complex soft tissue cutting models. Nevertheless, the PBR algorithms are still limited in visual quality due to inherent contrast distortion. We propose an adaptive image contrast enhancement algorithm as a postprocessing module for PBR, providing high visual rendering quality as well as acceptable rendering efficiency. Our approach is based on a perceptible image quality technique with automatic parameter selection, resulting in a visual quality comparable to existing conventional PBR algorithms. Experimental results show that our adaptive image contrast enhancement algorithm produces encouraging results both visually and numerically compared to representative algorithms, and experiments conducted on the latest hardware demonstrate that the proposed PBR framework with the postprocessing module is superior to the conventional PBR algorithm and that the proposed contrast enhancement algorithm can be utilized in (or compatible with) various variants of the conventional PBR algorithm.
Advances in Patch-Based Adaptive Mesh Refinement Scalability
Gunney, Brian T.N.; Anderson, Robert W.
2015-12-18
Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extension of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.
Advances in Patch-Based Adaptive Mesh Refinement Scalability
Gunney, Brian T.N.; Anderson, Robert W.
2015-12-18
Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extensionmore » of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.« less
Rule-based mechanisms of learning for intelligent adaptive flight control
NASA Technical Reports Server (NTRS)
Handelman, David A.; Stengel, Robert F.
1990-01-01
How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.
Method and apparatus for adaptive force and position control of manipulators
NASA Technical Reports Server (NTRS)
Seraji, Homayoun (Inventor)
1989-01-01
The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.
A Massively Parallel Adaptive Fast Multipole Method on Heterogeneous Architectures
Lashuk, Ilya; Chandramowlishwaran, Aparna; Langston, Harper; Nguyen, Tuan-Anh; Sampath, Rahul S; Shringarpure, Aashay; Vuduc, Richard; Ying, Lexing; Zorin, Denis; Biros, George
2012-01-01
We describe a parallel fast multipole method (FMM) for highly nonuniform distributions of particles. We employ both distributed memory parallelism (via MPI) and shared memory parallelism (via OpenMP and GPU acceleration) to rapidly evaluate two-body nonoscillatory potentials in three dimensions on heterogeneous high performance computing architectures. We have performed scalability tests with up to 30 billion particles on 196,608 cores on the AMD/CRAY-based Jaguar system at ORNL. On a GPU-enabled system (NSF's Keeneland at Georgia Tech/ORNL), we observed 30x speedup over a single core CPU and 7x speedup over a multicore CPU implementation. By combining GPUs with MPI, we achieve less than 10 ns/particle and six digits of accuracy for a run with 48 million nonuniformly distributed particles on 192 GPUs.
FPGA-based RF spectrum merging and adaptive hopset selection
NASA Astrophysics Data System (ADS)
McLean, R. K.; Flatley, B. N.; Silvius, M. D.; Hopkinson, K. M.
The radio frequency (RF) spectrum is a limited resource. Spectrum allotment disputes stem from this scarcity as many radio devices are confined to a fixed frequency or frequency sequence. One alternative is to incorporate cognition within a reconfigurable radio platform, therefore enabling the radio to adapt to dynamic RF spectrum environments. In this way, the radio is able to actively sense the RF spectrum, decide, and act accordingly, thereby sharing the spectrum and operating in more flexible manner. In this paper, we present a novel solution for merging many distributed RF spectrum maps into one map and for subsequently creating an adaptive hopset. We also provide an example of our system in operation, the result of which is a pseudorandom adaptive hopset. The paper then presents a novel hardware design for the frequency merger and adaptive hopset selector, both of which are written in VHDL and implemented as a custom IP core on an FPGA-based embedded system using the Xilinx Embedded Development Kit (EDK) software tool. The design of the custom IP core is optimized for area, and it can process a high-volume digital input via a low-latency circuit architecture. The complete embedded system includes the Xilinx PowerPC microprocessor, UART serial connection, and compact flash memory card IP cores, and our custom map merging/hopset selection IP core, all of which are targeted to the Virtex IV FPGA. This system is then incorporated into a cognitive radio prototype on a Rice University Wireless Open Access Research Platform (WARP) reconfigurable radio.
Wagner, Roland; Helin, Tapio; Obereder, Andreas; Ramlau, Ronny
2016-02-20
The imaging quality of modern ground-based telescopes such as the planned European Extremely Large Telescope is affected by atmospheric turbulence. In consequence, they heavily depend on stable and high-performance adaptive optics (AO) systems. Using measurements of incoming light from guide stars, an AO system compensates for the effects of turbulence by adjusting so-called deformable mirror(s) (DMs) in real time. In this paper, we introduce a novel reconstruction method for ground layer adaptive optics. In the literature, a common approach to this problem is to use Bayesian inference in order to model the specific noise structure appearing due to spot elongation. This approach leads to large coupled systems with high computational effort. Recently, fast solvers of linear order, i.e., with computational complexity O(n), where n is the number of DM actuators, have emerged. However, the quality of such methods typically degrades in low flux conditions. Our key contribution is to achieve the high quality of the standard Bayesian approach while at the same time maintaining the linear order speed of the recent solvers. Our method is based on performing a separate preprocessing step before applying the cumulative reconstructor (CuReD). The efficiency and performance of the new reconstructor are demonstrated using the OCTOPUS, the official end-to-end simulation environment of the ESO for extremely large telescopes. For more specific simulations we also use the MOST toolbox. PMID:26906596
NASA Astrophysics Data System (ADS)
Coleman, S.; Hurley, S.; Koliba, C.; Zia, A.; Exler, S.
2014-12-01
Eutrophication and nutrient pollution of surface waters occur within complex governance, social, hydrologic and biophysical basin contexts. The pervasive and perennial nutrient pollution in Lake Champlain Basin, despite decades of efforts, exemplifies problems found across the world's surface waters. Stakeholders with diverse values, interests, and forms of explicit and tacit knowledge determine water quality impacts through land use, agricultural and water resource decisions. Uncertainty, ambiguity and dynamic feedback further complicate the ability to promote the continual provision of water quality and ecosystem services. Adaptive management of water resources and land use requires mechanisms to allow for learning and integration of new information over time. The transdisciplinary Research on Adaptation to Climate Change (RACC) team is working to build regional adaptive capacity in Lake Champlain Basin while studying and integrating governance, land use, hydrological, and biophysical systems to evaluate implications for adaptive management. The RACC team has engaged stakeholders through mediated modeling workshops, online forums, surveys, focus groups and interviews. In March 2014, CSS2CC.org, an interactive online forum to source and identify adaptive interventions from a group of stakeholders across sectors was launched. The forum, based on the Delphi Method, brings forward the collective wisdom of stakeholders and experts to identify potential interventions and governance designs in response to scientific uncertainty and ambiguity surrounding the effectiveness of any strategy, climate change impacts, and the social and natural systems governing water quality and eutrophication. A Mediated Modeling Workshop followed the forum in May 2014, where participants refined and identified plausible interventions under different governance, policy and resource scenarios. Results from the online forum and workshop can identify emerging consensus across scales and sectors
Learners' Perceptions and Illusions of Adaptivity in Computer-Based Learning Environments
ERIC Educational Resources Information Center
Vandewaetere, Mieke; Vandercruysse, Sylke; Clarebout, Geraldine
2012-01-01
Research on computer-based adaptive learning environments has shown exemplary growth. Although the mechanisms of effective adaptive instruction are unraveled systematically, little is known about the relative effect of learners' perceptions of adaptivity in adaptive learning environments. As previous research has demonstrated that the learners'…
PID Controller Tuning Based on the Covariance Matrix Adaptation Evolution Strategy
NASA Astrophysics Data System (ADS)
Wakasa, Yuji; Kanagawa, Shinji; Tanaka, Kanya; Nishimura, Yuki
The covariance matrix adaptation evolution strategy (CMA-ES) is a kind of stochastic optimization such as particle swarm optimization (PSO), and has been shown to have a good performance. However, there are few control applications of the CMA-ES except for only one paper. This paper deals with a PID control problem with constraints on sensitivity and complementary sensitivity functions, and proposes a PID controller tuning method based on the CMA-ES. Numerical examples are given to show the effectiveness of the proposed method in comparison with the recently proposed PSO-based method.
Infrared gas detection based on an adaptive Savitzky-Golay algorithm
NASA Astrophysics Data System (ADS)
Deng, Hao; Li, Jingsong; Li, Pengfei; Liu, Yu; Yu, Benli
2015-08-01
We have developed a simple but robust method based on the Savitzky-Golay filter for real-time processing tunable diode laser absorption spectroscopy (TDLAS) signal. Our method was developed to resolve the blindness of selecting the input filter parameters and potential signal distortion induced in digital signal processing. By applying the developed adaptive Savitzky-Golay filter algorithm to the simulated and experimentally observed signal and comparing with the wavelet-based de-noising technique, the results indicate that the new developed method is effective in obtaining high-quality TDLAS data for a wide variety of applications including atmospheric environmental monitoring and industrial processing control.
A Machine Learning Based Framework for Adaptive Mobile Learning
NASA Astrophysics Data System (ADS)
Al-Hmouz, Ahmed; Shen, Jun; Yan, Jun
Advances in wireless technology and handheld devices have created significant interest in mobile learning (m-learning) in recent years. Students nowadays are able to learn anywhere and at any time. Mobile learning environments must also cater for different user preferences and various devices with limited capability, where not all of the information is relevant and critical to each learning environment. To address this issue, this paper presents a framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.
Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms
NASA Astrophysics Data System (ADS)
Nazimov, Alexey I.; Pavlov, Alexey N.; Hramov, Alexander E.; Grubov, Vadim V.; Koronovskii, Alexey A.; Sitnikova, Evgenija Y.
2013-02-01
The problem of automatic recognition of specific oscillatory patterns on electroencephalograms (EEG) is addressed using the continuous wavelet-transform (CWT). A possibility of improving the quality of recognition by optimizing the choice of CWT parameters is discussed. An adaptive approach is proposed to identify sleep spindles (SS) and spike wave discharges (SWD) that assumes automatic selection of CWT-parameters reflecting the most informative features of the analyzed time-frequency structures. Advantages of the proposed technique over the standard wavelet-based approaches are considered.
Image super-resolution based on image adaptive decomposition
NASA Astrophysics Data System (ADS)
Xie, Qiwei; Wang, Haiyan; Shen, Lijun; Chen, Xi; Han, Hua
2011-11-01
In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.
Robust observer-based adaptive fuzzy sliding mode controller
NASA Astrophysics Data System (ADS)
Oveisi, Atta; Nestorović, Tamara
2016-08-01
In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.
Context-Aware Adaptation in Web-Based Groupware Systems
NASA Astrophysics Data System (ADS)
Pinheiro, Manuele Kirsch; Carrillo-Ramos, Angela; Villanova-Oliver, Marlène; Gensel, Jérôme; Berbers, Yolande
In this chapter, we propose a context-aware filtering process for adapting content delivered to mobile users by Web-based Groupware Systems. This process is based on context-aware profiles, expressing mobile users preferences for particular situations they encounter when using these systems. These profiles, which are shared between members of a given community, are exploited by the adaptation process in order to select and organize the delivered information into several levels of detail, based on a progressive access model. By defining these profiles, we propose a filtering process that considers both the user's current context and the user's preferences for this context. The context notion of context is represented by an object-oriented model we propose and which takes into account consideration both the user's physical and collaborative context, including elements related to collaborative activities performed inside the groupware system. The filtering process selects, in a first step, the context-aware profiles that match the user's current context, and then it filters the available content according to the selected profiles and uses the progressive access model to organize the selected information.
Colby, Margaret; Hecht, Michael L.; Miller-Day, Michelle; Krieger, Janice L.; Syvertsen, Amy K.; Graham, John W.; Pettigrew, Jonathan
2014-01-01
A central challenge facing twenty-first century community-based researchers and prevention scientists is curriculum adaptation processes. While early prevention efforts sought to develop effective programs, taking programs to scale implies that they will be adapted, especially as programs are implemented with populations other than those with whom they were developed or tested. The principle of cultural grounding, which argues that health message adaptation should be informed by knowledge of the target population and by cultural insiders, provides a theoretical rational for cultural regrounding and presents an illustrative case of methods used to reground the keepin’ it REAL substance use prevention curriculum for a rural adolescent population. We argue that adaptation processes like those presented should be incorporated into the design and dissemination of prevention interventions. PMID:22961604
UAV multiple image dense matching based on self-adaptive patch
NASA Astrophysics Data System (ADS)
Zhu, Jin; Ding, Yazhou; Xiao, Xiongwu; Guo, Bingxuan; Li, Deren; Yang, Nan; Zhang, Weilong; Huang, Xiangxiang; Li, Linhui; Peng, Zhe; Pan, Fei
2015-12-01
This article using some state-of-art multi-view dense matching methods for reference, proposes an UAV multiple image dense matching algorithm base on Self-Adaptive patch (UAV-AP) in view of the specialty of UAV images. The main idea of matching propagating based on Self-Adaptive patch is to build patches centered by seed points which are already matched. The extent and figure of the patches can adapt to the terrain relief automatically: when the surface is smooth, the extent of the patch would become bigger to cover the whole smooth terrain; while the terrain is very rough, the extent of the patch would become smaller to describe the details of the surface. With this approach, the UAV image sequences and the given or previously triangulated orientation elements are taken as inputs. The main processing procedures are as follows: (1) multi-view initial feature matching, (2) matching propagating based on Self-Adaptive patch, (3) filtering the erroneous matching points. Finally, the algorithm outputs a dense colored point cloud. Experiments indicate that this method surpassed the existing related algorithm in efficiency and the matching precision is also quite ideal.
An HP Adaptive Discontinuous Galerkin Method for Hyperbolic Conservation Laws. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Bey, Kim S.
1994-01-01
This dissertation addresses various issues for model classes of hyperbolic conservation laws. The basic approach developed in this work employs a new family of adaptive, hp-version, finite element methods based on a special discontinuous Galerkin formulation for hyperbolic problems. The discontinuous Galerkin formulation admits high-order local approximations on domains of quite general geometry, while providing a natural framework for finite element approximations and for theoretical developments. The use of hp-versions of the finite element method makes possible exponentially convergent schemes with very high accuracies in certain cases; the use of adaptive hp-schemes allows h-refinement in regions of low regularity and p-enrichment to deliver high accuracy, while keeping problem sizes manageable and dramatically smaller than many conventional approaches. The use of discontinuous Galerkin methods is uncommon in applications, but the methods rest on a reasonable mathematical basis for low-order cases and has local approximation features that can be exploited to produce very efficient schemes, especially in a parallel, multiprocessor environment. The place of this work is to first and primarily focus on a model class of linear hyperbolic conservation laws for which concrete mathematical results, methodologies, error estimates, convergence criteria, and parallel adaptive strategies can be developed, and to then briefly explore some extensions to more general cases. Next, we provide preliminaries to the study and a review of some aspects of the theory of hyperbolic conservation laws. We also provide a review of relevant literature on this subject and on the numerical analysis of these types of problems.
Radiation hydrodynamics including irradiation and adaptive mesh refinement with AZEuS. I. Methods
NASA Astrophysics Data System (ADS)
Ramsey, J. P.; Dullemond, C. P.
2015-02-01
Aims: The importance of radiation to the physical structure of protoplanetary disks cannot be understated. However, protoplanetary disks evolve with time, and so to understand disk evolution and by association, disk structure, one should solve the combined and time-dependent equations of radiation hydrodynamics. Methods: We implement a new implicit radiation solver in the AZEuS adaptive mesh refinement magnetohydrodynamics fluid code. Based on a hybrid approach that combines frequency-dependent ray-tracing for stellar irradiation with non-equilibrium flux limited diffusion, we solve the equations of radiation hydrodynamics while preserving the directionality of the stellar irradiation. The implementation permits simulations in Cartesian, cylindrical, and spherical coordinates, on both uniform and adaptive grids. Results: We present several hydrostatic and hydrodynamic radiation tests which validate our implementation on uniform and adaptive grids as appropriate, including benchmarks specifically designed for protoplanetary disks. Our results demonstrate that the combination of a hybrid radiation algorithm with AZEuS is an effective tool for radiation hydrodynamics studies, and produces results which are competitive with other astrophysical radiation hydrodynamics codes.
ERIC Educational Resources Information Center
Kluge, Annette; Sauer, Juergen; Burkolter, Dina; Ritzmann, Sandrina
2010-01-01
Training in process control environments requires operators to be prepared for temporal and adaptive transfer of skill. Three training methods were compared with regard to their effectiveness in supporting transfer: Drill & Practice (D&P), Error Training (ET), and procedure-based and error heuristics training (PHT). Communication electronics…
Robustness of an adaptive beamforming method for hearing aids.
Peterson, P M; Wei, S M; Rabinowitz, W M; Zurek, P M
1990-01-01
We describe the results of computer simulations of a multimicrophone adaptive-beamforming system as a noise reduction device for hearing aids. Of particular concern was the system's sensitivity to violations of the underlying assumption that the target signal is identical at the microphones. Two- and four-microphone versions of the system were tested in simulated anechoic and modestly-reverberant environments with one and two jammers, and with deviations from the assumed straight-ahead target direction. Also examined were the effects of input target-to-jammer ratio and adaptive-filter length. Generally, although the noise-reduction performance of the system is degraded by target misalignment and modest reverberation, the system still provides positive advantage at input target-to-jammer ratios up to about 0 dB. This is in contrast to the degrading target-cancellation effect that the system can have when the equal-target assumption is violated and the input target-to-jammer ratio is greater than zero. PMID:2356741
Co-production of knowledge: recipe for success in land-based climate change adaptation?
NASA Astrophysics Data System (ADS)
Coninx, Ingrid; Swart, Rob
2015-04-01
After multiple failures of scientists to trigger policymakers and other relevant actors to take action when communicating research findings, the request for co-production (or co-creation) of knowledge and stakeholder involvement in climate change adaptation efforts has rapidly increased over the past few years. In particular for land-based adaptation, on-the-ground action is often met by societal resistance towards solutions proposed by scientists, by a misfit of potential solutions with the local context, leading to misunderstanding and even rejection of scientific recommendations. A fully integrative co-creation process in which both scientists and practitioners discuss climate vulnerability and possible responses, exploring perspectives and designing adaptation measures based on their own knowledge, is expected to prevent the adaptation deadlock. The apparent conviction that co-creation processes result in successful adaptation, has not yet been unambiguously empirically demonstrated, but has resulted in co-creation being one of basic principles in many new research and policy programmes. But is co-creation that brings knowledge of scientists and practitioners together always the best recipe for success in climate change adaptation? Assessing a number of actual cases, the authors have serious doubts. The paper proposes additional considerations for adaptively managing the environment that should be taken into account in the design of participatory knowledge development in which climate scientists play a role. These include the nature of the problem at stake; the values, interests and perceptions of the actors involved; the methods used to build trust, strengthen alignment and develop reciprocal relationships among scientists and practitioners; and the concreteness of the co-creation output.
Using Mixed-Methods Research to Adapt and Evaluate a Family Strengthening Intervention in Rwanda
Betancourt, Theresa S.; Meyers-Ohki, Sarah E.; Stevenson, Anne; Ingabire, Charles; Kanyanganzi, Fredrick; Munyana, Morris; Mushashi, Christina; Teta, Sharon; Fayida, Ildephonse; Cyamatare, Felix Rwabukwisi; Stulac, Sara; Beardslee, William R.
2013-01-01
Introduction Research in several international settings indicates that children and adolescents affected by HIV and other compounded adversities are at increased risk for a range of mental health problems including depression, anxiety, and social withdrawal. More intervention research is needed to develop valid measurement and intervention tools to address child mental health in such settings. Objective This article presents a collaborative mixed-methods approach to designing and evaluating a mental health intervention to assist families facing multiple adversities in Rwanda. Methods Qualitative methods were used to gain knowledge of culturally-relevant mental health problems in children and adolescents, individual, family and community resources, and contextual dynamics among HIV-affected families. This data was used to guide the selection and adaptation of mental health measures to assess intervention outcomes. Measures were subjected to a quantitative validation exercise. Qualitative data and community advisory board input also informed the selection and adaptation of a family-based preventive intervention to reduce the risk for mental health problems among children in families affected by HIV.. Community-based participatory methods were used to ensure that the intervention targeted relevant problems manifest in Rwandan children and families and built on local strengths. Results Qualitative data on culturally-appropriate practices for building resilience in vulnerable families has enriched the development of a Family-Strengthening Intervention (FSI). Input from community partners has also contributed to creating a feasible and culturally-relevant intervention. Mental health measures demonstrate strong performance in this population. Conclusion The mixed-methods model discussed represents a refined, multi-phase protocol for incorporating qualitative data and community input in the development and evaluation of feasible, culturally-sound quantitative assessments
Stable indirect adaptive switching control for fuzzy dynamical systems based on T-S multiple models
NASA Astrophysics Data System (ADS)
Sofianos, Nikolaos A.; Boutalis, Yiannis S.
2013-08-01
A new indirect adaptive switching fuzzy control method for fuzzy dynamical systems, based on Takagi-Sugeno (T-S) multiple models is proposed in this article. Motivated by the fact that indirect adaptive control techniques suffer from poor transient response, especially when the initialisation of the estimation model is highly inaccurate and the region of uncertainty for the plant parameters is very large, we present a fuzzy control method that utilises the advantages of multiple models strategy. The dynamical system is expressed using the T-S method in order to cope with the nonlinearities. T-S adaptive multiple models of the system to be controlled are constructed using different initial estimations for the parameters while one feedback linearisation controller corresponds to each model according to a specified reference model. The controller to be applied is determined at every time instant by the model which best approximates the plant using a switching rule with a suitable performance index. Lyapunov stability theory is used in order to obtain the adaptive law for the multiple models parameters, ensuring the asymptotic stability of the system while a modification in this law keeps the control input away from singularities. Also, by introducing the next best controller logic, we avoid possible infeasibilities in the control signal. Simulation results are presented, indicating the effectiveness and the advantages of the proposed method.
Investigating Item Exposure Control Methods in Computerized Adaptive Testing
ERIC Educational Resources Information Center
Ozturk, Nagihan Boztunc; Dogan, Nuri
2015-01-01
This study aims to investigate the effects of item exposure control methods on measurement precision and on test security under various item selection methods and item pool characteristics. In this study, the Randomesque (with item group sizes of 5 and 10), Sympson-Hetter, and Fade-Away methods were used as item exposure control methods. Moreover,…
Site-adaptation of satellite-based DNI and GHI time series: Overview and SolarGIS approach
NASA Astrophysics Data System (ADS)
Cebecauer, Tomas; Suri, Marcel
2016-05-01
Site adaptation is an approach of reducing uncertainty in the satellite-based longterm estimates of solar radiation by combining them with short-term high-accuracy measurements at a project site. We inventory the existing approaches and introduce the SolarGIS method that is optimized for providing bankable data for energy simulation in Concentrating Solar Power. We also indicate the achievable uncertainty of SolarGIS model outputs based on site-adaptation of projects executed in various geographical conditions.
Adaptive Thresholding Technique for Retinal Vessel Segmentation Based on GLCM-Energy Information
Mapayi, Temitope; Viriri, Serestina; Tapamo, Jules-Raymond
2015-01-01
Although retinal vessel segmentation has been extensively researched, a robust and time efficient segmentation method is highly needed. This paper presents a local adaptive thresholding technique based on gray level cooccurrence matrix- (GLCM-) energy information for retinal vessel segmentation. Different thresholds were computed using GLCM-energy information. An experimental evaluation on DRIVE database using the grayscale intensity and Green Channel of the retinal image demonstrates the high performance of the proposed local adaptive thresholding technique. The maximum average accuracy rates of 0.9511 and 0.9510 with maximum average sensitivity rates of 0.7650 and 0.7641 were achieved on DRIVE and STARE databases, respectively. When compared to the widely previously used techniques on the databases, the proposed adaptive thresholding technique is time efficient with a higher average sensitivity and average accuracy rates in the same range of very good specificity. PMID:25802550
Nonlinear adaptive control systems design of BTT missile based on fully tuned RBF neural networks
NASA Astrophysics Data System (ADS)
Hu, Yunan; Jin, Yuqiang; Li, Jing
2003-09-01
Based on fully tuned RBF neural networks and backstepping control techniques, a novel nonlinear adaptive control scheme is proposed for missile control systems with a general set of uncertainties. The effect of the uncertainties is synthesized one term in the design procedure. Then RBF neural networks are used to eliminate its effect. The nonlinear adaptive controller is designed using backstepping control techniques. The control problem is resolved while the control coefficient matrix is unknown. The adaptive tuning rules for updating all of the parameters of the fully tuned RBF neural networks are firstly derived by the Lyapunov stability theorem. Finally, nonlinear 6-DOF numerical simulation results for a BTT missile model are presented to demonstrate the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada
We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.
Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System
2016-01-01
This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165
Data-adapted moving least squares method for 3-D image interpolation
NASA Astrophysics Data System (ADS)
Jang, Sumi; Nam, Haewon; Lee, Yeon Ju; Jeong, Byeongseon; Lee, Rena; Yoon, Jungho
2013-12-01
In this paper, we present a nonlinear three-dimensional interpolation scheme for gray-level medical images. The scheme is based on the moving least squares method but introduces a fundamental modification. For a given evaluation point, the proposed method finds the local best approximation by reproducing polynomials of a certain degree. In particular, in order to obtain a better match to the local structures of the given image, we employ locally data-adapted least squares methods that can improve the classical one. Some numerical experiments are presented to demonstrate the performance of the proposed method. Five types of data sets are used: MR brain, MR foot, MR abdomen, CT head, and CT foot. From each of the five types, we choose five volumes. The scheme is compared with some well-known linear methods and other recently developed nonlinear methods. For quantitative comparison, we follow the paradigm proposed by Grevera and Udupa (1998). (Each slice is first assumed to be unknown then interpolated by each method. The performance of each interpolation method is assessed statistically.) The PSNR results for the estimated volumes are also provided. We observe that the new method generates better results in both quantitative and visual quality comparisons.
Goffin, Mark A.; Baker, Christopher M.J.; Buchan, Andrew G.; Pain, Christopher C.; Eaton, Matthew D.; Smith, Paul N.
2013-06-01
This article presents a method for goal-based anisotropic adaptive methods for the finite element method applied to the Boltzmann transport equation. The neutron multiplication factor, k{sub eff}, is used as the goal of the adaptive procedure. The anisotropic adaptive algorithm requires error measures for k{sub eff} with directional dependence. General error estimators are derived for any given functional of the flux and applied to k{sub eff} to acquire the driving force for the adaptive procedure. The error estimators require the solution of an appropriately formed dual equation. Forward and dual error indicators are calculated by weighting the Hessian of each solution with the dual and forward residual respectively. The Hessian is used as an approximation of the interpolation error in the solution which gives rise to the directional dependence. The two indicators are combined to form a single error metric that is used to adapt the finite element mesh. The residual is approximated using a novel technique arising from the sub-grid scale finite element discretisation. Two adaptive routes are demonstrated: (i) a single mesh is used to solve all energy groups, and (ii) a different mesh is used to solve each energy group. The second method aims to capture the benefit from representing the flux from each energy group on a specifically optimised mesh. The k{sub eff} goal-based adaptive method was applied to three examples which illustrate the superior accuracy in criticality problems that can be obtained.
Binary hologram generation based on shape adaptive sampling
NASA Astrophysics Data System (ADS)
Tsang, P. W. M.; Pan, Y.; Poon, T.-C.
2014-05-01
Past research has revealed that by down-sampling the projected intensity profile of a source object scene with a regular sampling lattice, a binary Fresnel hologram can be generated swiftly to preserve favorable quality on its reconstructed image. However, this method also results in a prominent textural pattern which is conflicting to the geometrical profile of the object scene, leading to an unnatural visual perception. In this paper, we shall overcome this problem with a down-sampling process that is adaptive to the geometry of the object. Experimental results demonstrate that by applying our proposed method to generate a binary hologram, the reconstructed image is rendered with a texture which abides with the shape of the three-dimensional object(s).
An adaptive fusion approach for infrared and visible images based on NSCT and compressed sensing
NASA Astrophysics Data System (ADS)
Zhang, Qiong; Maldague, Xavier
2016-01-01
A novel nonsubsampled contourlet transform (NSCT) based image fusion approach, implementing an adaptive-Gaussian (AG) fuzzy membership method, compressed sensing (CS) technique, total variation (TV) based gradient descent reconstruction algorithm, is proposed for the fusion computation of infrared and visible images. Compared with wavelet, contourlet, or any other multi-resolution analysis method, NSCT has many evident advantages, such as multi-scale, multi-direction, and translation invariance. As is known, a fuzzy set is characterized by its membership function (MF), while the commonly known Gaussian fuzzy membership degree can be introduced to establish an adaptive control of the fusion processing. The compressed sensing technique can sparsely sample the image information in a certain sampling rate, and the sparse signal can be recovered by solving a convex problem employing gradient descent based iterative algorithm(s). In the proposed fusion process, the pre-enhanced infrared image and the visible image are decomposed into low-frequency subbands and high-frequency subbands, respectively, via the NSCT method as a first step. The low-frequency coefficients are fused using the adaptive regional average energy rule; the highest-frequency coefficients are fused using the maximum absolute selection rule; the other high-frequency coefficients are sparsely sampled, fused using the adaptive-Gaussian regional standard deviation rule, and then recovered by employing the total variation based gradient descent recovery algorithm. Experimental results and human visual perception illustrate the effectiveness and advantages of the proposed fusion approach. The efficiency and robustness are also analyzed and discussed through different evaluation methods, such as the standard deviation, Shannon entropy, root-mean-square error, mutual information and edge-based similarity index.
An examination of an adapter method for measuring the vibration transmitted to the human arms
Xu, Xueyan S.; Dong, Ren G.; Welcome, Daniel E.; Warren, Christopher; McDowell, Thomas W.
2016-01-01
The objective of this study is to evaluate an adapter method for measuring the vibration on the human arms. Four instrumented adapters with different weights were used to measure the vibration transmitted to the wrist, forearm, and upper arm of each subject. Each adapter was attached at each location on the subjects using an elastic cloth wrap. Two laser vibrometers were also used to measure the transmitted vibration at each location to evaluate the validity of the adapter method. The apparent mass at the palm of the hand along the forearm direction was also measured to enhance the evaluation. This study found that the adapter and laser-measured transmissibility spectra were comparable with some systematic differences. While increasing the adapter mass reduced the resonant frequency at the measurement location, increasing the tightness of the adapter attachment increased the resonant frequency. However, the use of lightweight (≤15 g) adapters under medium attachment tightness did not change the basic trends of the transmissibility spectrum. The resonant features observed in the transmissibility spectra were also correlated with those observed in the apparent mass spectra. Because the local coordinate systems of the adapters may be significantly misaligned relative to the global coordinates of the vibration test systems, large errors were observed for the adapter-measured transmissibility in some individual orthogonal directions. This study, however, also demonstrated that the misalignment issue can be resolved by either using the total vibration transmissibility or by measuring the misalignment angles to correct the errors. Therefore, the adapter method is acceptable for understanding the basic characteristics of the vibration transmission in the human arms, and the adapter-measured data are acceptable for approximately modeling the system. PMID:26834309
Domain Adaptation for Pedestrian Detection Based on Prediction Consistency
Huan-ling, Tang; Zhi-yong, An
2014-01-01
Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene. PMID:25013850
Optimization-based wavefront sensorless adaptive optics for multiphoton microscopy.
Antonello, Jacopo; van Werkhoven, Tim; Verhaegen, Michel; Truong, Hoa H; Keller, Christoph U; Gerritsen, Hans C
2014-06-01
Optical aberrations have detrimental effects in multiphoton microscopy. These effects can be curtailed by implementing model-based wavefront sensorless adaptive optics, which only requires the addition of a wavefront shaping device, such as a deformable mirror (DM) to an existing microscope. The aberration correction is achieved by maximizing a suitable image quality metric. We implement a model-based aberration correction algorithm in a second-harmonic microscope. The tip, tilt, and defocus aberrations are removed from the basis functions used for the control of the DM, as these aberrations induce distortions in the acquired images. We compute the parameters of a quadratic polynomial that is used to model the image quality metric directly from experimental input-output measurements. Finally, we apply the aberration correction by maximizing the image quality metric using the least-squares estimate of the unknown aberration. PMID:24977374
NASA Astrophysics Data System (ADS)
Danaila, Ionut; Moglan, Raluca; Hecht, Frédéric; Le Masson, Stéphane
2014-10-01
We present a new numerical system using finite elements with mesh adaptivity for the simulation of solid-liquid phase change systems. In the liquid phase, the natural convection flow is simulated by solving the incompressible Navier-Stokes equations with Boussinesq approximation. A variable viscosity model allows the velocity to progressively vanish in the solid phase, through an intermediate mushy region. The phase change is modeled by introducing an implicit enthalpy source term in the heat equation. The final system of equations describing the liquid-solid system by a single domain approach is solved using a Newton iterative algorithm. The space discretization is based on a P2-P1 Taylor-Hood finite elements and mesh adaptivity by metric control is used to accurately track the solid-liquid interface or the density inversion interface for water flows. The numerical method is validated against classical benchmarks that progressively add strong non-linearities in the system of equations: natural convection of air, natural convection of water, melting of a phase-change material and water freezing. Very good agreement with experimental data is obtained for each test case, proving the capability of the method to deal with both melting and solidification problems with convection. The presented numerical method is easy to implement using FreeFem++ software using a syntax close to the mathematical formulation.
The older person has a stroke: Learning to adapt using the Feldenkrais® Method.
Jackson-Wyatt, O
1995-01-01
The older person with a stroke requires adapted therapeutic interventions to take into account normal age-related changes. The Feldenkrais® Method presents a model for learning to promote adaptability that addresses key functional changes seen with normal aging. Clinical examples related to specific functional tasks are discussed to highlight major treatment modifications and neuromuscular, psychological, emotional, and sensory considerations. PMID:27619899
Automated Tract Extraction via Atlas Based Adaptive Clustering
Tunç, Birkan; Parker, William A.; Ingalhalikar, Madhura; Verma, Ragini
2014-01-01
Advancements in imaging protocols such as the high angular resolution diffusion-weighted imaging (HARDI) and in tractography techniques are expected to cause an increase in the tract-based analyses. Statistical analyses over white matter tracts can contribute greatly towards understanding structural mechanisms of the brain since tracts are representative of the connectivity pathways. The main challenge with tract-based studies is the extraction of the tracts of interest in a consistent and comparable manner over a large group of individuals without drawing the inclusion and exclusion regions of interest. In this work, we design a framework for automated extraction of white matter tracts. The framework introduces three main components, namely a connectivity based fiber representation, a fiber clustering atlas, and a clustering approach called Adaptive Clustering. The fiber representation relies on the connectivity signatures of fibers to establish an easy correspondence between different subjects. A group-wise clustering of these fibers that are represented by the connectivity signatures is then used to generate a fiber bundle atlas. Finally, Adaptive Clustering incorporates the previously generated clustering atlas as a prior, to cluster the fibers of a new subject automatically. Experiments on the HARDI scans of healthy individuals acquired repeatedly, demonstrate the applicability, the reliability and the repeatability of our approach in extracting white matter tracts. By alleviating the seed region selection or the inclusion/exclusion ROI drawing requirements that are usually handled by trained radiologists, the proposed framework expands the range of possible clinical applications and establishes the ability to perform tract-based analyses with large samples. PMID:25134977
An adaptive filter method for spacecraft using gravity assist
NASA Astrophysics Data System (ADS)
Ning, Xiaolin; Huang, Panpan; Fang, Jiancheng; Liu, Gang; Ge, Shuzhi Sam
2015-04-01
Celestial navigation (CeleNav) has been successfully used during gravity assist (GA) flyby for orbit determination in many deep space missions. Due to spacecraft attitude errors, ephemeris errors, the camera center-finding bias, and the frequency of the images before and after the GA flyby, the statistics of measurement noise cannot be accurately determined, and yet have time-varying characteristics, which may introduce large estimation error and even cause filter divergence. In this paper, an unscented Kalman filter (UKF) with adaptive measurement noise covariance, called ARUKF, is proposed to deal with this problem. ARUKF scales the measurement noise covariance according to the changes in innovation and residual sequences. Simulations demonstrate that ARUKF is robust to the inaccurate initial measurement noise covariance matrix and time-varying measurement noise. The impact factors in the ARUKF are also investigated.
Adaptive inferential sensors based on evolving fuzzy models.
Angelov, Plamen; Kordon, Arthur
2010-04-01
A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can address the
Adaptive nonlocal means filtering based on local noise level for CT denoising
Li, Zhoubo; Trzasko, Joshua D.; Lake, David S.; Blezek, Daniel J.; Manduca, Armando; Yu, Lifeng; Fletcher, Joel G.; McCollough, Cynthia H.
2014-01-15
Purpose: To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. Methods: A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analytical noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. Results: The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the
NASA Technical Reports Server (NTRS)
Rost, Martin C.; Sayood, Khalid
1991-01-01
A method for efficiently coding natural images using a vector-quantized variable-blocksized transform source coder is presented. The method, mixture block coding (MBC), incorporates variable-rate coding by using a mixture of discrete cosine transform (DCT) source coders. Which coders are selected to code any given image region is made through a threshold driven distortion criterion. In this paper, MBC is used in two different applications. The base method is concerned with single-pass low-rate image data compression. The second is a natural extension of the base method which allows for low-rate progressive transmission (PT). Since the base method adapts easily to progressive coding, it offers the aesthetic advantage of progressive coding without incorporating extensive channel overhead. Image compression rates of approximately 0.5 bit/pel are demonstrated for both monochrome and color images.
NASA Astrophysics Data System (ADS)
Beritelli, Francesco; Capizzi, Giacomo; Lo Sciuto, Grazia; Napoli, Christian; Tramontana, Emiliano; Woźniak, Marcin
2015-09-01
Solving channel equalization problem in communication systems is based on adaptive filtering algorithms. Today, Mobile Agents (MAs) with Recurrent Neural Networks (RNNs) can be also adopted for effective interference reduction in modern wireless communication systems (WCSs). In this paper MAs with RNNs are proposed as novel computing algorithms for reducing interferences in WCSs performing an adaptive channel equalization. The method to provide it is so called MAs-RNNs. We perform the implementation of this new paradigm for interferences reduction. Simulations results and evaluations demonstrates the effectiveness of this approach and as better transmission performance in wireless communication network can be achieved by using the MAs-RNNs based adaptive filtering algorithm.
Wavelet-based adaptive numerical simulation of unsteady 3D flow around a bluff body
NASA Astrophysics Data System (ADS)
de Stefano, Giuliano; Vasilyev, Oleg
2012-11-01
The unsteady three-dimensional flow past a two-dimensional bluff body is numerically simulated using a wavelet-based method. The body is modeled by exploiting the Brinkman volume-penalization method, which results in modifying the governing equations with the addition of an appropriate forcing term inside the spatial region occupied by the obstacle. The volume-penalized incompressible Navier-Stokes equations are numerically solved by means of the adaptive wavelet collocation method, where the non-uniform spatial grid is dynamically adapted to the flow evolution. The combined approach is successfully applied to the simulation of vortex shedding flow behind a stationary prism with square cross-section. The computation is conducted at transitional Reynolds numbers, where fundamental unstable three-dimensional vortical structures exist, by well-predicting the unsteady forces arising from fluid-structure interaction.
Particle filter based visual tracking with multi-cue adaptive fusion
NASA Astrophysics Data System (ADS)
Li, Anping; Jing, Zhongliang; Hu, Shiqiang
2005-06-01
To improve the robustness of visual tracking in complex environments such as: cluttered backgrounds, partial occlusions, similar distraction and pose variations, a novel tracking method based on adaptive fusion and particle filter is proposed in this paper. In this method, the image color and shape cues are adaptively fused to represent the target observation; fuzzy logic is applied to dynamically adjust each cue weight according to its associated reliability in the past frame; particle filter is adopted to deal with non-linear and non-Gaussian problems in visual tracking. The method is demonstrated to be robust to illumination changes, pose variations, partial occlusions, cluttered backgrounds and camera motion for a test image sequence.
Adaptive Timer-Based Countermeasures against TCP SYN Flood Attacks
NASA Astrophysics Data System (ADS)
Tanabe, Masao; Akaike, Hirofumi; Aida, Masaki; Murata, Masayuki; Imase, Makoto
As a result of the rapid development of the Internet in recent years, network security has become an urgent issue. Distributed denial of service (DDoS) attacks are one of the most serious security issues. In particular, 60 percent of the DDoS attacks found on the Internet are TCP attacks, including SYN flood attacks. In this paper, we propose adaptive timer-based countermeasures against SYN flood attacks. Our proposal utilizes the concept of soft-state protocols that are widely used for resource management on the Internet. In order to avoid deadlock, a server releases resources using a time-out mechanism without any explicit requests from its clients. If we change the value of the timer in accordance with the network conditions, we can add more flexibility to the soft-state protocols. The timer is used to manage the resources assigned to half-open connections in a TCP 3-way handshake mechanism, and its value is determined adaptively according to the network conditions. In addition, we report our simulation results to show the effectiveness of our approach.
Adaptive multiwavelet-based watermarking through JPW masking.
Cui, Lihong; Li, Wenguo
2011-04-01
In this paper, a multibit, multiplicative, spread spectrum watermarking using the discrete multiwavelet (including unbalanced and balanced multiwavelet) transform is presented. Performance improvement with respect to existing algorithm is obtained by means of a new just perceptual weighting (JPW) model. The new model incorporates various masking effects of human visual perception by taking into account the eye's sensitivity to noise changes depending on spatial frequency, luminance and texture of all the image subbands. In contrast to conventional JND threshold model, JPW describing minimum perceptual sensitivity weighting to noise changes, is fitter for nonadditive watermarking. Specifically, watermarking strength is adaptively adjusted to obtain minimum perceptual distortion by employing the JPW model. Correspondingly, an adaptive optimum decoding is derived using a statistic model based on generalized-Gaussian distribution (GGD) for multiwavelet coefficients of the cover-image. Furthermore, the impact of multiwavelet characteristics on proposed watermarking scheme is also analyzed. Finally, the experimental results show that proposed JPW model can improve the quality of the watermarked image and give more robustness of the watermark as compared with a variety of state-of-the-art algorithms. PMID:20876023
Space-based RF signal classification using adaptive wavelet features
Caffrey, M.; Briles, S.
1995-04-01
RF signals are dispersed in frequency as they propagate through the ionosphere. For wide-band signals, this results in nonlinearly- chirped-frequency, transient signals in the VHF portion of the spectrum. This ionospheric dispersion provide a means of discriminating wide-band transients from other signals (e.g., continuous-wave carriers, burst communications, chirped-radar signals, etc.). The transient nature of these dispersed signals makes them candidates for wavelet feature selection. Rather than choosing a wavelet ad hoc, we adaptively compute an optimal mother wavelet via a neural network. Gaussian weighted, linear frequency modulate (GLFM) wavelets are linearly combined by the network to generate our application specific mother wavelet, which is optimized for its capacity to select features that discriminate between the dispersed signals and clutter (e.g., multiple continuous-wave carriers), not for its ability to represent the dispersed signal. The resulting mother wavelet is then used to extract features for a neutral network classifier. The performance of the adaptive wavelet classifier is the compared to an FFT based neural network classifier.
Hybrid regularizers-based adaptive anisotropic diffusion for image denoising.
Liu, Kui; Tan, Jieqing; Ai, Liefu
2016-01-01
To eliminate the staircasing effect for total variation filter and synchronously avoid the edges blurring for fourth-order PDE filter, a hybrid regularizers-based adaptive anisotropic diffusion is proposed for image denoising. In the proposed model, the [Formula: see text]-norm is considered as the fidelity term and the regularization term is composed of a total variation regularization and a fourth-order filter. The two filters can be adaptively selected according to the diffusion function. When the pixels locate at the edges, the total variation filter is selected to filter the image, which can preserve the edges. When the pixels belong to the flat regions, the fourth-order filter is adopted to smooth the image, which can eliminate the staircase artifacts. In addition, the split Bregman and relaxation approach are employed in our numerical algorithm to speed up the computation. Experimental results demonstrate that our proposed model outperforms the state-of-the-art models cited in the paper in both the qualitative and quantitative evaluations. PMID:27047730
Lens-based wavefront sensorless adaptive optics swept source OCT
NASA Astrophysics Data System (ADS)
Jian, Yifan; Lee, Sujin; Ju, Myeong Jin; Heisler, Morgan; Ding, Weiguang; Zawadzki, Robert J.; Bonora, Stefano; Sarunic, Marinko V.
2016-06-01
Optical coherence tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. Although the axial resolution of OCT system, which is a function of the light source bandwidth, is sufficient to resolve retinal features at a micrometer scale, the lateral resolution is dependent on the delivery optics and is limited by ocular aberrations. Through the combination of wavefront sensorless adaptive optics and the use of dual deformable transmissive optical elements, we present a compact lens-based OCT system at an imaging wavelength of 1060 nm for high resolution retinal imaging. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient’s eyes, and a novel multi-actuator adaptive lens for aberration correction to achieve near diffraction limited imaging performance at the retina. With a parallel processing computational platform, high resolution cross-sectional and en face retinal image acquisition and display was performed in real time. In order to demonstrate the system functionality and clinical utility, we present images of the photoreceptor cone mosaic and other retinal layers acquired in vivo from research subjects.
Lens-based wavefront sensorless adaptive optics swept source OCT
Jian, Yifan; Lee, Sujin; Ju, Myeong Jin; Heisler, Morgan; Ding, Weiguang; Zawadzki, Robert J.; Bonora, Stefano; Sarunic, Marinko V.
2016-01-01
Optical coherence tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. Although the axial resolution of OCT system, which is a function of the light source bandwidth, is sufficient to resolve retinal features at a micrometer scale, the lateral resolution is dependent on the delivery optics and is limited by ocular aberrations. Through the combination of wavefront sensorless adaptive optics and the use of dual deformable transmissive optical elements, we present a compact lens-based OCT system at an imaging wavelength of 1060 nm for high resolution retinal imaging. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient’s eyes, and a novel multi-actuator adaptive lens for aberration correction to achieve near diffraction limited imaging performance at the retina. With a parallel processing computational platform, high resolution cross-sectional and en face retinal image acquisition and display was performed in real time. In order to demonstrate the system functionality and clinical utility, we present images of the photoreceptor cone mosaic and other retinal layers acquired in vivo from research subjects. PMID:27278853
Lens-based wavefront sensorless adaptive optics swept source OCT.
Jian, Yifan; Lee, Sujin; Ju, Myeong Jin; Heisler, Morgan; Ding, Weiguang; Zawadzki, Robert J; Bonora, Stefano; Sarunic, Marinko V
2016-01-01
Optical coherence tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. Although the axial resolution of OCT system, which is a function of the light source bandwidth, is sufficient to resolve retinal features at a micrometer scale, the lateral resolution is dependent on the delivery optics and is limited by ocular aberrations. Through the combination of wavefront sensorless adaptive optics and the use of dual deformable transmissive optical elements, we present a compact lens-based OCT system at an imaging wavelength of 1060 nm for high resolution retinal imaging. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient's eyes, and a novel multi-actuator adaptive lens for aberration correction to achieve near diffraction limited imaging performance at the retina. With a parallel processing computational platform, high resolution cross-sectional and en face retinal image acquisition and display was performed in real time. In order to demonstrate the system functionality and clinical utility, we present images of the photoreceptor cone mosaic and other retinal layers acquired in vivo from research subjects. PMID:27278853
Knowledge-based control of an adaptive interface
NASA Technical Reports Server (NTRS)
Lachman, Roy
1989-01-01
The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.
An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy
NASA Astrophysics Data System (ADS)
Zhong, Hualiang; Wen, Ning; Gordon, James J.; Elshaikh, Mohamed A.; Movsas, Benjamin; Chetty, Indrin J.
2015-04-01
Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm-3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume
Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids
NASA Technical Reports Server (NTRS)
Nielsen, Eric J.
2006-01-01
Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.
New methods and astrophysical applications of adaptive mesh fluid simulations
NASA Astrophysics Data System (ADS)
Wang, Peng
The formation of stars, galaxies and supermassive black holes are among the most interesting unsolved problems in astrophysics. Those problems are highly nonlinear and involve enormous dynamical ranges. Thus numerical simulations with spatial adaptivity are crucial in understanding those processes. In this thesis, we discuss the development and application of adaptive mesh refinement (AMR) multi-physics fluid codes to simulate those nonlinear structure formation problems. To simulate the formation of star clusters, we have developed an AMR magnetohydrodynamics (MHD) code, coupled with radiative cooling. We have also developed novel algorithms for sink particle creation, accretion, merging and outflows, all of which are coupled with the fluid algorithms using operator splitting. With this code, we have been able to perform the first AMR-MHD simulation of star cluster formation for several dynamical times, including sink particle and protostellar outflow feedbacks. The results demonstrated that protostellar outflows can drive supersonic turbulence in dense clumps and explain the observed slow and inefficient star formation. We also suggest that global collapse rate is the most important factor in controlling massive star accretion rate. In the topics of galaxy formation, we discuss the results of three projects. In the first project, using cosmological AMR hydrodynamics simulations, we found that isolated massive star still forms in cosmic string wakes even though the mega-parsec scale structure has been perturbed significantly by the cosmic strings. In the second project, we calculated the dynamical heating rate in galaxy formation. We found that by balancing our heating rate with the atomic cooling rate, it gives a critical halo mass which agrees with the result of numerical simulations. This demonstrates that the effect of dynamical heating should be put into semi-analytical works in the future. In the third project, using our AMR-MHD code coupled with radiative
Grid coupling mechanism in the semi-implicit adaptive Multi-Level Multi-Domain method
NASA Astrophysics Data System (ADS)
Innocenti, M. E.; Tronci, C.; Markidis, S.; Lapenta, G.
2016-05-01
The Multi-Level Multi-Domain (MLMD) method is a semi-implicit adaptive method for Particle-In-Cell plasma simulations. It has been demonstrated in the past in simulations of Maxwellian plasmas, electrostatic and electromagnetic instabilities, plasma expansion in vacuum, magnetic reconnection [1, 2, 3]. In multiple occasions, it has been commented on the coupling between the coarse and the refined grid solutions. The coupling mechanism itself, however, has never been explored in depth. Here, we investigate the theoretical bases of grid coupling in the MLMD system. We obtain an evolution law for the electric field solution in the overlap area of the MLMD system which highlights a dependance on the densities and currents from both the coarse and the refined grid, rather than from the coarse grid alone: grid coupling is obtained via densities and currents.
NASA Astrophysics Data System (ADS)
Zanotti, O.; Dumbser, M.; Fambri, F.
2016-05-01
We describe a new method for the solution of the ideal MHD equations in special relativity which adopts the following strategy: (i) the main scheme is based on Discontinuous Galerkin (DG) methods, allowing for an arbitrary accuracy of order N+1, where N is the degree of the basis polynomials; (ii) in order to cope with oscillations at discontinuities, an ”a-posteriori” sub-cell limiter is activated, which scatters the DG polynomials of the previous time-step onto a set of 2N+1 sub-cells, over which the solution is recomputed by means of a robust finite volume scheme; (iii) a local spacetime Discontinuous-Galerkin predictor is applied both on the main grid of the DG scheme and on the sub-grid of the finite volume scheme; (iv) adaptive mesh refinement (AMR) with local time-stepping is used. We validate the new scheme and comment on its potential applications in high energy astrophysics.
NASA Astrophysics Data System (ADS)
Le Jeune, L.; Robert, S.; Dumas, P.; Membre, A.; Prada, C.
2015-03-01
In this paper, we propose an ultrasonic adaptive imaging method based on the phased-array technology and the synthetic focusing algorithm Total Focusing Method (TFM). The general principle is to image the surface by applying the TFM algorithm in a semi-infinite water medium. Then, the reconstructed surface is taken into account to make a second TFM image inside the component. In the surface reconstruction step, the TFM algorithm has been optimized to decrease computation time and to limit noise in water. In the second step, the ultrasonic paths through the reconstructed surface are calculated by the Fermat's principle and an iterative algorithm, and the classical TFM is applied to obtain an image inside the component. This paper presents several results of TFM imaging in components of different geometries, and a result obtained with a new technology of probes equipped with a flexible wedge filled with water (manufactured by Imasonic).
NASA Astrophysics Data System (ADS)
Kust, German; Andreeva, Olga
2015-04-01
A number of new concepts and paradigms appeared during last decades, such as sustainable land management (SLM), climate change (CC) adaptation, environmental services, ecosystem health, and others. All of these initiatives still not having the common scientific platform although some agreements in terminology were reached, schemes of links and feedback loops created, and some models developed. Nevertheless, in spite of all these scientific achievements, the land related issues are still not in the focus of CC adaptation and mitigation. The last did not grow much beyond the "greenhouse gases" (GHG) concept, which makes land degradation as the "forgotten side of climate change" The possible decision to integrate concepts of climate and desertification/land degradation could be consideration of the "GHG" approach providing global solution, and "land" approach providing local solution covering other "locally manifesting" issues of global importance (biodiversity conservation, food security, disasters and risks, etc.) to serve as a central concept among those. SLM concept is a land-based approach, which includes the concepts of both ecosystem-based approach (EbA) and community-based approach (CbA). SLM can serve as in integral CC adaptation strategy, being based on the statement "the more healthy and resilient the system is, the less vulnerable and more adaptive it will be to any external changes and forces, including climate" The biggest scientific issue is the methods to evaluate the SLM and results of the SLM investments. We suggest using the approach based on the understanding of the balance or equilibrium of the land and nature components as the major sign of the sustainable system. Prom this point of view it is easier to understand the state of the ecosystem stress, size of the "health", range of adaptive capacity, drivers of degradation and SLM nature, as well as the extended land use, and the concept of environmental land management as the improved SLM approach
Fixed-Structure H∞ Controller Synthesis Based on the Covariance Matrix Adaptation Evolution Strategy
NASA Astrophysics Data System (ADS)
Wakasa, Yuji; Kanagawa, Shinji; Tanaka, Kanya; Nishimura, Yuki
This paper provides a design method of fixed-structure controllers satisfying multiple H∞ norm specifications by using the covariance matrix adaptation evolution strategy (CMA-ES). The CMA-ES is a kind of stochastic optimization such as particle swarm optimization (PSO), and has been shown to have a good performance for nonconvex optimization problems. However, there are few control applications of the CMA-ES, and therefore, its superiority is not clear in control problems. The effectiveness of the proposed method is demonstrated through numerical examples in comparison with the PSO-based method that has recently been proposed as a good approach.
Parallel architectures for iterative methods on adaptive, block structured grids
NASA Technical Reports Server (NTRS)
Gannon, D.; Vanrosendale, J.
1983-01-01
A parallel computer architecture well suited to the solution of partial differential equations in complicated geometries is proposed. Algorithms for partial differential equations contain a great deal of parallelism. But this parallelism can be difficult to exploit, particularly on complex problems. One approach to extraction of this parallelism is the use of special purpose architectures tuned to a given problem class. The architecture proposed here is tuned to boundary value problems on complex domains. An adaptive elliptic algorithm which maps effectively onto the proposed architecture is considered in detail. Two levels of parallelism are exploited by the proposed architecture. First, by making use of the freedom one has in grid generation, one can construct grids which are locally regular, permitting a one to one mapping of grids to systolic style processor arrays, at least over small regions. All local parallelism can be extracted by this approach. Second, though there may be a regular global structure to the grids constructed, there will be parallelism at this level. One approach to finding and exploiting this parallelism is to use an architecture having a number of processor clusters connected by a switching network. The use of such a network creates a highly flexible architecture which automatically configures to the problem being solved.
An adaptive mesh refinement algorithm for the discrete ordinates method
Jessee, J.P.; Fiveland, W.A.; Howell, L.H.; Colella, P.; Pember, R.B.
1996-03-01
The discrete ordinates form of the radiative transport equation (RTE) is spatially discretized and solved using an adaptive mesh refinement (AMR) algorithm. This technique permits the local grid refinement to minimize spatial discretization error of the RTE. An error estimator is applied to define regions for local grid refinement; overlapping refined grids are recursively placed in these regions; and the RTE is then solved over the entire domain. The procedure continues until the spatial discretization error has been reduced to a sufficient level. The following aspects of the algorithm are discussed: error estimation, grid generation, communication between refined levels, and solution sequencing. This initial formulation employs the step scheme, and is valid for absorbing and isotopically scattering media in two-dimensional enclosures. The utility of the algorithm is tested by comparing the convergence characteristics and accuracy to those of the standard single-grid algorithm for several benchmark cases. The AMR algorithm provides a reduction in memory requirements and maintains the convergence characteristics of the standard single-grid algorithm; however, the cases illustrate that efficiency gains of the AMR algorithm will not be fully realized until three-dimensional geometries are considered.
Analysis of modified SMI method for adaptive array weight control
NASA Technical Reports Server (NTRS)
Dilsavor, R. L.; Moses, R. L.
1989-01-01
An adaptive array is applied to the problem of receiving a desired signal in the presence of weak interference signals which need to be suppressed. A modification, suggested by Gupta, of the sample matrix inversion (SMI) algorithm controls the array weights. In the modified SMI algorithm, interference suppression is increased by subtracting a fraction F of the noise power from the diagonal elements of the estimated covariance matrix. Given the true covariance matrix and the desired signal direction, the modified algorithm is shown to maximize a well-defined, intuitive output power ratio criterion. Expressions are derived for the expected value and variance of the array weights and output powers as a function of the fraction F and the number of snapshots used in the covariance matrix estimate. These expressions are compared with computer simulation and good agreement is found. A trade-off is found to exist between the desired level of interference suppression and the number of snapshots required in order to achieve that level with some certainty. The removal of noise eigenvectors from the covariance matrix inverse is also discussed with respect to this application. Finally, the type and severity of errors which occur in the covariance matrix estimate are characterized through simulation.
An adaptive filter bank for motor imagery based Brain Computer Interface.
Thomas, Kavitha P; Guan, Cuntai; Tong, Lau Chiew; Prasad, Vinod A
2008-01-01
Brain Computer Interface (BCI) provides an alternative communication and control method for people with severe motor disabilities. Motor imagery patterns are widely used in Electroencephalogram (EEG) based BCIs. These motor imagery activities are associated with variation in alpha and beta band power of EEG signals called Event Related Desynchronization/synchronization (ERD/ERS). The dominant frequency bands are subject-specific and therefore performance of motor imagery based BCIs are sensitive to both temporal filtering and spatial filtering. As the optimum filter is strongly subject-dependent, we propose a method that selects the subject-specific discriminative frequency components using time-frequency plots of Fisher ratio of two-class motor imagery patterns. We also propose a low complexity adaptive Finite Impulse Response (FIR) filter bank system based on coefficient decimation technique which can realize the subject-specific bandpass filters adaptively depending on the information of Fisher ratio map. Features are extracted only from the selected frequency components. The proposed adaptive filter bank based system offers average classification accuracy of about 90%, which is slightly better than the existing fixed filter bank system. PMID:19162856
Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P
2015-03-01
Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. PMID:25463325
NASA Astrophysics Data System (ADS)
Nejadmalayeri, Alireza
The current work develops a wavelet-based adaptive variable fidelity approach that integrates Wavelet-based Direct Numerical Simulation (WDNS), Coherent Vortex Simulations (CVS), and Stochastic Coherent Adaptive Large Eddy Simulations (SCALES). The proposed methodology employs the notion of spatially and temporarily varying wavelet thresholding combined with hierarchical wavelet-based turbulence modeling. The transition between WDNS, CVS, and SCALES regimes is achieved through two-way physics-based feedback between the modeled SGS dissipation (or other dynamically important physical quantity) and the spatial resolution. The feedback is based on spatio-temporal variation of the wavelet threshold, where the thresholding level is adjusted on the fly depending on the deviation of local significant SGS dissipation from the user prescribed level. This strategy overcomes a major limitation for all previously existing wavelet-based multi-resolution schemes: the global thresholding criterion, which does not fully utilize the spatial/temporal intermittency of the turbulent flow. Hence, the aforementioned concept of physics-based spatially variable thresholding in the context of wavelet-based numerical techniques for solving PDEs is established. The procedure consists of tracking the wavelet thresholding-factor within a Lagrangian frame by exploiting a Lagrangian Path-Line Diffusive Averaging approach based on either linear averaging along characteristics or direct solution of the evolution equation. This innovative technique represents a framework of continuously variable fidelity wavelet-based space/time/model-form adaptive multiscale methodology. This methodology has been tested and has provided very promising results on a benchmark with time-varying user prescribed level of SGS dissipation. In addition, a longtime effort to develop a novel parallel adaptive wavelet collocation method for numerical solution of PDEs has been completed during the course of the current work
Eulerian adaptive finite-difference method for high-velocity impact and penetration problems
Barton, Philip T.; Deiterding, Ralf; Meiron, Daniel I.; Pullin, Dale I
2013-01-01
Owing to the complex processes involved, faithful prediction of high-velocity impact events demands a simulation method delivering efficient calculations based on comprehensively formulated constitutive models. Such an approach is presented herein, employing a weighted essentially non-oscillatory (WENO) method within an adaptive mesh refinement (AMR) framework for the numerical solution of hyperbolic partial differential equations. Applied widely in computational fluid dynamics, these methods are well suited to the involved locally non-smooth finite deformations, circumventing any requirement for artificial viscosity functions for shock capturing. Application of the methods is facilitated through using a model of solid dynamics based upon hyper-elastic theory comprising kinematic evolution equations for the elastic distortion tensor. The model for finite inelastic deformations is phenomenologically equivalent to Maxwell s model of tangential stress relaxation. Closure relations tailored to the expected high-pressure states are proposed and calibrated for the materials of interest. Sharp interface resolution is achieved by employing level-set functions to track boundary motion, along with a ghost material method to capture the necessary internal boundary conditions for material interactions and stress-free surfaces. The approach is demonstrated for the simulation of high velocity impacts of steel projectiles on aluminium target plates in two and three dimensions.
2013-01-01
Background In order to benefit from the highly conformal irradiation of tumors in ion radiotherapy, sophisticated treatment planning and simulation are required. The purpose of this study was to investigate the potential of MRI for ion radiotherapy treatment plan simulation and adaptation using a classification-based approach. Methods Firstly, a voxelwise tissue classification was applied to derive pseudo CT numbers from MR images using up to 8 contrasts. Appropriate MR sequences and parameters were evaluated in cross-validation studies of three phantoms. Secondly, ion radiotherapy treatment plans were optimized using both MRI-based pseudo CT and reference CT and recalculated on reference CT. Finally, a target shift was simulated and a treatment plan adapted to the shift was optimized on a pseudo CT and compared to reference CT optimizations without plan adaptation. Results The derivation of pseudo CT values led to mean absolute errors in the range of 81 - 95 HU. Most significant deviations appeared at borders between air and different tissue classes and originated from partial volume effects. Simulations of ion radiotherapy treatment plans using pseudo CT for optimization revealed only small underdosages in distal regions of a target volume with deviations of the mean dose of PTV between 1.4 - 3.1% compared to reference CT optimizations. A plan adapted to the target volume shift and optimized on the pseudo CT exhibited a comparable target dose coverage as a non-adapted plan optimized on a reference CT. Conclusions We were able to show that a MRI-based derivation of pseudo CT values using a purely statistical classification approach is feasible although no physical relationship exists. Large errors appeared at compact bone classes and came from an imperfect distinction of bones and other tissue types in MRI. In simulations of treatment plans, it was demonstrated that these deviations are comparable to uncertainties of a target volume shift of 2 mm in two directions
Wavefront sensorless adaptive optics temporal focusing-based multiphoton microscopy
Chang, Chia-Yuan; Cheng, Li-Chung; Su, Hung-Wei; Hu, Yvonne Yuling; Cho, Keng-Chi; Yen, Wei-Chung; Xu, Chris; Dong, Chen Yuan; Chen, Shean-Jen
2014-01-01
Temporal profile distortions reduce excitation efficiency and image quality in temporal focusing-based multiphoton microscopy. In order to compensate the distortions, a wavefront sensorless adaptive optics system (AOS) was integrated into the microscope. The feedback control signal of the AOS was acquired from local image intensity maximization via a hill-climbing algorithm. The control signal was then utilized to drive a deformable mirror in such a way as to eliminate the distortions. With the AOS correction, not only is the axial excitation symmetrically refocused, but the axial resolution with full two-photon excited fluorescence (TPEF) intensity is also maintained. Hence, the contrast of the TPEF image of a R6G-doped PMMA thin film is enhanced along with a 3.7-fold increase in intensity. Furthermore, the TPEF image quality of 1μm fluorescent beads sealed in agarose gel at different depths is improved. PMID:24940539
An adaptive compromise programming method for multi-objective path optimization
NASA Astrophysics Data System (ADS)
Li, Rongrong; Leung, Yee; Lin, Hui; Huang, Bo
2013-04-01
Network routing problems generally involve multiple objectives which may conflict one another. An effective way to solve such problems is to generate a set of Pareto-optimal solutions that is small enough to be handled by a decision maker and large enough to give an overview of all possible trade-offs among the conflicting objectives. To accomplish this, the present paper proposes an adaptive method based on compromise programming to assist decision makers in identifying Pareto-optimal paths, particularly for non-convex problems. This method can provide an unbiased approximation of the Pareto-optimal alternatives by adaptively changing the origin and direction of search in the objective space via the dynamic updating of the largest unexplored region till an appropriately structured Pareto front is captured. To demonstrate the efficacy of the proposed methodology, a case study is carried out for the transportation of dangerous goods in the road network of Hong Kong with the support of geographic information system. The experimental results confirm the effectiveness of the approach.
An Adaptive Fast Multipole Boundary Element Method for Poisson-Boltzmann Electrostatics
Lu, Benzhuo; Cheng, Xiaolin; Huang, Jingfang; McCammon, Jonathan
2009-01-01
The numerical solution of the Poisson Boltzmann (PB) equation is a useful but a computationally demanding tool for studying electrostatic solvation effects in chemical and biomolecular systems. Recently, we have described a boundary integral equation-based PB solver accelerated by a new version of the fast multipole method (FMM). The overall algorithm shows an order N complexity in both the computational cost and memory usage. Here, we present an updated version of the solver by using an adaptive FMM for accelerating the convolution type matrix-vector multiplications. The adaptive algorithm, when compared to our previous nonadaptive one, not only significantly improves the performance of the overall memory usage but also remarkably speeds the calculation because of an improved load balancing between the local- and far-field calculations. We have also implemented a node-patch discretization scheme that leads to a reduction of unknowns by a factor of 2 relative to the constant element method without sacrificing accuracy. As a result of these improvements, the new solver makes the PB calculation truly feasible for large-scale biomolecular systems such as a 30S ribosome molecule even on a typical 2008 desktop computer.
NASA Technical Reports Server (NTRS)
Kopasakis, George
2004-01-01
An adaptive feedback control method was demonstrated that suppresses thermoacoustic instabilities in a liquid-fueled combustor of a type used in aircraft engines. Extensive research has been done to develop lean-burning (low fuel-to-air ratio) combustors that can reduce emissions throughout the mission cycle to reduce the environmental impact of aerospace propulsion systems. However, these lean-burning combustors are susceptible to thermoacoustic instabilities (high-frequency pressure waves), which can fatigue combustor components and even the downstream turbine blades. This can significantly decrease the safe operating lives of the combustor and turbine. Thus, suppressing the thermoacoustic combustor instabilities is an enabling technology for lean, low-emissions combustors under NASA's Propulsion and Power Program. This control methodology has been developed and tested in a partnership of the NASA Glenn Research Center, Pratt & Whitney, United Technologies Research Center, and the Georgia Institute of Technology. Initial combustor rig testing of the controls algorithm was completed during 2002. Subsequently, the test results were analyzed and improvements to the method were incorporated in 2003, which culminated in the final status of this controls algorithm. This control methodology is based on adaptive phase shifting. The combustor pressure oscillations are sensed and phase shifted, and a high-frequency fuel valve is actuated to put pressure oscillations into the combustor to cancel pressure oscillations produced by the instability.
An adaptation of Krylov subspace methods to path following
Walker, H.F.
1996-12-31
Krylov subspace methods at present constitute a very well known and highly developed class of iterative linear algebra methods. These have been effectively applied to nonlinear system solving through Newton-Krylov methods, in which Krylov subspace methods are used to solve the linear systems that characterize steps of Newton`s method (the Newton equations). Here, we will discuss the application of Krylov subspace methods to path following problems, in which the object is to track a solution curve as a parameter varies. Path following methods are typically of predictor-corrector form, in which a point near the solution curve is {open_quotes}predicted{close_quotes} by some easy but relatively inaccurate means, and then a series of Newton-like corrector iterations is used to return approximately to the curve. The analogue of the Newton equation is underdetermined, and an additional linear condition must be specified to determine corrector steps uniquely. This is typically done by requiring that the steps be orthogonal to an approximate tangent direction. Augmenting the under-determined system with this orthogonality condition in a straightforward way typically works well if direct linear algebra methods are used, but Krylov subspace methods are often ineffective with this approach. We will discuss recent work in which this orthogonality condition is imposed directly as a constraint on the corrector steps in a certain way. The means of doing this preserves problem conditioning, allows the use of preconditioners constructed for the fixed-parameter case, and has certain other advantages. Experiments on standard PDE continuation test problems indicate that this approach is effective.
Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control
NASA Technical Reports Server (NTRS)
Kim, Kilsoo (Inventor); Yucelen, Tansel (Inventor); Calise, Anthony J. (Inventor)
2015-01-01
Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.
AP-Cloud: Adaptive particle-in-cloud method for optimal solutions to Vlasov–Poisson equation
Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; Yu, Kwangmin
2016-04-19
We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less
AP-Cloud: Adaptive Particle-in-Cloud method for optimal solutions to Vlasov-Poisson equation
NASA Astrophysics Data System (ADS)
Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; Yu, Kwangmin
2016-07-01
We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov-Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes of computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.
Solving delay differential equations in S-ADAPT by method of steps.
Bauer, Robert J; Mo, Gary; Krzyzanski, Wojciech
2013-09-01
S-ADAPT is a version of the ADAPT program that contains additional simulation and optimization abilities such as parametric population analysis. S-ADAPT utilizes LSODA to solve ordinary differential equations (ODEs), an algorithm designed for large dimension non-stiff and stiff problems. However, S-ADAPT does not have a solver for delay differential equations (DDEs). Our objective was to implement in S-ADAPT a DDE solver using the methods of steps. The method of steps allows one to solve virtually any DDE system by transforming it to an ODE system. The solver was validated for scalar linear DDEs with one delay and bolus and infusion inputs for which explicit analytic solutions were derived. Solutions of nonlinear DDE problems coded in S-ADAPT were validated by comparing them with ones obtained by the MATLAB DDE solver dde23. The estimation of parameters was tested on the MATLB simulated population pharmacodynamics data. The comparison of S-ADAPT generated solutions for DDE problems with the explicit solutions as well as MATLAB produced solutions which agreed to at least 7 significant digits. The population parameter estimates from using importance sampling expectation-maximization in S-ADAPT agreed with ones used to generate the data. PMID:23810514
Automatic multirate methods for ordinary differential equations. [Adaptive time steps
Gear, C.W.
1980-01-01
A study is made of the application of integration methods in which different step sizes are used for different members of a system of equations. Such methods can result in savings if the cost of derivative evaluation is high or if a system is sparse; however, the estimation and control of errors is very difficult and can lead to high overheads. Three approaches are discussed, and it is shown that the least intuitive is the most promising. 2 figures.
Adaptive error covariances estimation methods for ensemble Kalman filters
Zhen, Yicun; Harlim, John
2015-08-01
This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.
Qin, Lei; Snoussi, Hichem; Abdallah, Fahed
2014-01-01
We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. PMID:24865883
NASA Astrophysics Data System (ADS)
Davies, D. R.; Davies, J. H.; Hassan, O.; Morgan, K.; Nithiarasu, P.
2007-05-01
An adaptive finite element procedure is presented for improving the quality of solutions to convection-dominated problems in geodynamics. The method adapts the mesh automatically around regions of high solution gradient, yielding enhanced resolution of the associated flow features. The approach requires the coupling of an automatic mesh generator, a finite element flow solver, and an error estimator. In this study, the procedure is implemented in conjunction with the well-known geodynamical finite element code ConMan. An unstructured quadrilateral mesh generator is utilized, with mesh adaptation accomplished through regeneration. This regeneration employs information provided by an interpolation-based local error estimator, obtained from the computed solution on an existing mesh. The technique is validated by solving thermal and thermochemical problems with well-established benchmark solutions. In a purely thermal context, results illustrate that the method is highly successful, improving solution accuracy while increasing computational efficiency. For thermochemical simulations the same conclusions can be drawn. However, results also demonstrate that the grid-based methods employed for simulating the compositional field are not competitive with the other methods (tracer particle and marker chain) currently employed in this field, even at the higher spatial resolutions allowed by the adaptive grid strategies.
Tsai, M.F.; Tzou, Y.Y.
1997-03-01
In this paper, the authors design and implement an adaptive speed controller that can estimate load torque for ac induction motor drives employing a transputer-based parallel processing technique. The adaptive speed controller, which precedes the field-oriented control loop, consists of a two-degree-of-freedom controller and a feedforward load-torque compensator. The two-degree-of-freedom controller is designed by a pole-placement technique with polynomial manipulations. Its parameters are adjusted adaptively in terms of estimated model parameters. Estimating the model parameters entails a second-order least-squares estimator with constant trace to avoid estimator windup. The design of the feedforward compensator is based on an estimated load-torque model. Estimating the load torque entails a first-order least-squares estimator with variable forgetting factor and covariance resetting, the purposes of which are to detect any slow or sudden changes of torque disturbance, respectively. The resulting adaptive controller is implemented in parallel by IMS T800-20 transputers. Experimental results demonstrate the robustness of the proposed control method in contending with varying load and torque disturbance.
AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.
Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang
2015-01-01
An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665
AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal
Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang
2015-01-01
An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665
Polymer-based micro deformable mirror for adaptive optics applications
NASA Astrophysics Data System (ADS)
Zamkotsian, Frederic; Conedera, Veronique; Liotard, Arnaud; Schroeder, Andreas; Fabre, Norbert; Camon, Henri; Lanzoni, Patrick
2005-01-01
Next generation giant telescopes as well as next generation instrumentation for 10m-class telescopes relies on the availability of highly performing adaptive optical systems, for studying new fields like circumstellar disks and extrasolar planets. These systems require deformable mirrors with very challenging parameters, including number of actuators up to 250 000 and inter-actuator spacing around 500μm. MOEMS-based devices are promising for future deformable mirrors. However, only limited strokes for large driving voltages have been demonstrated. In order to overcome these limitations, we are currently developing a micro-deformable mirror based on an array of electrostatic actuators with attachment posts to a continuous mirror on top. The originality of our approach lies in the elaboration of a sacrificial layer and of a structural layer made of polymer materials, using low-temperature process. This process allows the realization of high optical quality mirrors on top of an actuator array made with various techniques. We have developed the first polymer piston-motion actuator in order to reach high strokes for low driving voltages: a 10μm thick mobile plate with four springs attached to the substrate, and with an air gap of 10μm exhibits a piston motion of 2μm for 30V. Preliminary comparison with FEM models show very good agreement and design of a complete polymer-based MDM looks possible.
Efficient community-based control strategies in adaptive networks
NASA Astrophysics Data System (ADS)
Yang, Hui; Tang, Ming; Zhang, Hai-Feng
2012-12-01
Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible-infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible-infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans.
AES based secure low energy adaptive clustering hierarchy for WSNs
NASA Astrophysics Data System (ADS)
Kishore, K. R.; Sarma, N. V. S. N.
2013-01-01
Wireless sensor networks (WSNs) provide a low cost solution in diversified application areas. The wireless sensor nodes are inexpensive tiny devices with limited storage, computational capability and power. They are being deployed in large scale in both military and civilian applications. Security of the data is one of the key concerns where large numbers of nodes are deployed. Here, an energy-efficient secure routing protocol, secure-LEACH (Low Energy Adaptive Clustering Hierarchy) for WSNs based on the Advanced Encryption Standard (AES) is being proposed. This crypto system is a session based one and a new session key is assigned for each new session. The network (WSN) is divided into number of groups or clusters and a cluster head (CH) is selected among the member nodes of each cluster. The measured data from the nodes is aggregated by the respective CH's and then each CH relays this data to another CH towards the gateway node in the WSN which in turn sends the same to the Base station (BS). In order to maintain confidentiality of data while being transmitted, it is necessary to encrypt the data before sending at every hop, from a node to the CH and from the CH to another CH or to the gateway node.
Implementer-initiated adaptation of evidence-based interventions: kids remember the blue wig.
Gibbs, D A; Krieger, K E; Cutbush, S L; Clinton-Sherrod, A M; Miller, S
2016-06-01
Adaptation of evidence-based interventions by implementers is widespread. Although frequently viewed as departures from fidelity, adaptations may be positive in impact and consistent with fidelity. Research typically catalogs adaptations but rarely includes the implementers' perspectives on adaptation. We report data on individuals implementing an evidence-based teen dating violence prevention curriculum. Key informant interviews (n = 20) and an online focus group (n = 10) addressed reasons for adaptations, adaptation processes and kinds of adaptations. All implementers described making adaptations, which they considered necessary to achieving intended outcomes. Adaptations were tailored to needs of individual students or learning opportunities presented by current events, fine-tuned over repeated applications and shared with colleagues. Adaptations modified both content and delivery and included both planned and in-the-moment changes. Implementers made adaptations to increase student engagement, and to fit students' learning needs, learning style, social maturity and culture. Student engagement served as an indicator that adaptation might be needed and provided feedback about the immediate effects of the adaptation. These findings underscore the value of fidelity assessments that measure participant response, intervention-specific guidance to implementers and evaluation of the impact of adaptations on participant response and intervention outcomes. PMID:27107432
SuBSENSE: a universal change detection method with local adaptive sensitivity.
St-Charles, Pierre-Luc; Bilodeau, Guillaume-Alexandre; Bergevin, Robert
2015-01-01
Foreground/background segmentation via change detection in video sequences is often used as a stepping stone in high-level analytics and applications. Despite the wide variety of methods that have been proposed for this problem, none has been able to fully address the complex nature of dynamic scenes in real surveillance tasks. In this paper, we present a universal pixel-level segmentation method that relies on spatiotemporal binary features as well as color information to detect changes. This allows camouflaged foreground objects to be detected more easily while most illumination variations are ignored. Besides, instead of using manually set, frame-wide constants to dictate model sensitivity and adaptation speed, we use pixel-level feedback loops to dynamically adjust our method's internal parameters without user intervention. These adjustments are based on the continuous monitoring of model fidelity and local segmentation noise levels. This new approach enables us to outperform all 32 previously tested state-of-the-art methods on the 2012 and 2014 versions of the ChangeDetection.net dataset in terms of overall F-Measure. The use of local binary image descriptors for pixel-level modeling also facilitates high-speed parallel implementations: our own version, which used no low-level or architecture-specific instruction, reached real-time processing speed on a midlevel desktop CPU. A complete C++ implementation based on OpenCV is available online. PMID:25494507
NASA Astrophysics Data System (ADS)
Wu, Zhenhui; Dong, Chaoyang
2006-11-01
Because of nonlinearity and strong coupling of reaction-jet and aerodynamics compound control missile, a missile autopilot design method based on adaptive fuzzy sliding mode control (AFSMC) is proposed in this paper. The universal approximation ability of adaptive fuzzy system is used to approximate the nonlinear function in missile dynamics equation during the flight of high angle of attack. And because the sliding mode control is robustness to external disturbance strongly, the sliding mode surface of the error system is constructed to overcome the influence of approximation error and external disturbance so that the actual overload can track the maneuvering command with high precision. Simulation results show that the missile autopilot designed in this paper not only can track large overload command with higher precision than traditional method, but also is robust to model uncertainty and external disturbance strongly.
NASA Astrophysics Data System (ADS)
Li, Shigao; Su, Kehua; Jia, Liming
2016-01-01
Disparity compensation (DC) and transform coding are incorporated into a hybrid coding to reduce the code-rate of multiview images. However, occlusion and inaccurate disparity estimations (DE) impair the performance of DC, especially in spaceborne images. This paper proposes an adaptive disparity-compensation scheme for the compression of spaceborne multiview images, including stereo image pairs and three-line-scanner images. DC with adaptive loop filter is used to remove redundancy between reference images and target images and a wavelet-based coding method is used to encode reference images and residue images. In occlusion regions, the DC efficiency may be poor because no interview correlation exists. A rate-distortion optimization method is thus designed to select the best prediction mode for local regions. Experimental results show that the proposed scheme can provide significant coding gain compared with some other similar coding schemes, and the time complexity is also competitive.
Adaptive frequency-separation-based energy management system for electric vehicles
NASA Astrophysics Data System (ADS)
Florescu, Adrian; Bacha, Seddik; Munteanu, Iulian; Bratcu, Antoneta Iuliana; Rumeau, Axel
2015-04-01
This paper deals with an adaptive frequency-based power sharing method between batteries and ultracapacitors (UC) as power sources within an electric vehicle. An adaptive frequency splitter is used for routing the low-frequency content of power demand into the battery and its high-frequency content into the UC system, taking profit from the UC as a peak power unit. Autonomy may thus be increased while preserving battery state of health and ensuring that UC voltage variations remain confined within certain desired range. Results obtained by real-time experiments on a dedicated test rig validate the proposed energy management approach and recommend it to be applied as power source coordination method to microgrids in general.
A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony
Othman, Zulaiha Ali
2014-01-01
Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748
An adaptive wavelet-based deblocking algorithm for MPEG-4 codec
NASA Astrophysics Data System (ADS)
Truong, Trieu-Kien; Chen, Shi-Huang; Jhang, Rong-Yi
2005-08-01
This paper proposed an adaptive wavelet-based deblocking algorithm for MPEG-4 video coding standard. The novelty of this method is that the deblocking filter uses a wavelet-based threshold to detect and analyze artifacts on coded block boundaries. This threshold value is based on the difference between the wavelet transform coefficients of image blocks and the coefficients of the entire image. Therefore, the threshold value is made adaptive to different images and characteristics of blocking artifacts. Then one can attenuate those artifacts by applying a selected filter based on the above threshold value. It is shown in this paper that the proposed method is robust, fast, and works remarkably well for MPEG-4 codec at low bit rates. Another advantage of the new method is that it retains sharp features in the decoded frames since it only removes artifacts. Experimental results show that the proposed method can achieve a significantly improved visual quality and increase the PSNR in the decoded video frame.
Restrictive Stochastic Item Selection Methods in Cognitive Diagnostic Computerized Adaptive Testing
ERIC Educational Resources Information Center
Wang, Chun; Chang, Hua-Hua; Huebner, Alan
2011-01-01
This paper proposes two new item selection methods for cognitive diagnostic computerized adaptive testing: the restrictive progressive method and the restrictive threshold method. They are built upon the posterior weighted Kullback-Leibler (KL) information index but include additional stochastic components either in the item selection index or in…
Weighted Structural Regression: A Broad Class of Adaptive Methods for Improving Linear Prediction.
ERIC Educational Resources Information Center
Pruzek, Robert M.; Lepak, Greg M.
1992-01-01
Adaptive forms of weighted structural regression are developed and discussed. Bootstrapping studies indicate that the new methods have potential to recover known population regression weights and predict criterion score values routinely better than do ordinary least squares methods. The new methods are scale free and simple to compute. (SLD)
NASA Astrophysics Data System (ADS)
Yang, Jianhong; Yi, Cancan; Xu, Jinwu; Ma, Xianghong
2015-05-01
A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.
NASA Astrophysics Data System (ADS)
Yu, Lei; Qi, Yue; Li, Dayu; Xia, Mingliang; Xuan, Li
2013-07-01
The residual aberrations of the adaptive optics retinal imaging system will decrease the quality of the retinal images. To overcome this obstacle, we found that the optical transfer function (OTF) of the adaptive optics retinal imaging system can be described as the Levy stable distribution. Then a new method is introduced to estimate the OTF of the open-loop adaptive optics system, based on analyzing the residual aberrations of the open-loop adaptive optics system in the residual aberrations measuring mode. At last, the estimated OTF is applied to restore the retinal images of the open-loop adaptive optics retinal imaging system. The contrast and resolution of the restored image is significantly improved with the Laplacian sum (LS) from 0.0785 to 0.1480 and gray mean grads (GMG) from 0.0165 to 0.0306.
An Adaptive Kalman Filter using a Simple Residual Tuning Method
NASA Technical Reports Server (NTRS)
Harman, Richard R.
1999-01-01
One difficulty in using Kalman filters in real world situations is the selection of the correct process noise, measurement noise, and initial state estimate and covariance. These parameters are commonly referred to as tuning parameters. Multiple methods have been developed to estimate these parameters. Most of those methods such as maximum likelihood, subspace, and observer Kalman Identification require extensive offline processing and are not suitable for real time processing. One technique, which is suitable for real time processing, is the residual tuning method. Any mismodeling of the filter tuning parameters will result in a non-white sequence for the filter measurement residuals. The residual tuning technique uses this information to estimate corrections to those tuning parameters. The actual implementation results in a set of sequential equations that run in parallel with the Kalman filter. Equations for the estimation of the measurement noise have also been developed. These algorithms are used to estimate the process noise and measurement noise for the Wide Field Infrared Explorer star tracker and gyro.
An Adaptive Kalman Filter Using a Simple Residual Tuning Method
NASA Technical Reports Server (NTRS)
Harman, Richard R.
1999-01-01
One difficulty in using Kalman filters in real world situations is the selection of the correct process noise, measurement noise, and initial state estimate and covariance. These parameters are commonly referred to as tuning parameters. Multiple methods have been developed to estimate these parameters. Most of those methods such as maximum likelihood, subspace, and observer Kalman Identification require extensive offline processing and are not suitable for real time processing. One technique, which is suitable for real time processing, is the residual tuning method. Any mismodeling of the filter tuning parameters will result in a non-white sequence for the filter measurement residuals. The residual tuning technique uses this information to estimate corrections to those tuning parameters. The actual implementation results in a set of sequential equations that run in parallel with the Kalman filter. A. H. Jazwinski developed a specialized version of this technique for estimation of process noise. Equations for the estimation of the measurement noise have also been developed. These algorithms are used to estimate the process noise and measurement noise for the Wide Field Infrared Explorer star tracker and gyro.
Adapting and using quality management methods to improve health promotion.
Becker, Craig M; Glascoff, Mary A; Felts, William Michael; Kent, Christopher
2015-01-01
Although the western world is the most technologically advanced civilization to date, it is also the most addicted, obese, medicated, and in-debt adult population in history. Experts had predicted that the 21st century would be a time of better health and prosperity. Although wealth has increased, our quest to quell health problems using a pathogenic approach without understanding the interconnectedness of everyone and everything has damaged personal and planetary health. While current efforts help identify and eliminate causes of problems, they do not facilitate the creation of health and well-being as would be done with a salutogenic approach. Sociologist Aaron Antonovsky coined the term salutogenesis in 1979. It is derived from salus, which is Latin for health, and genesis, meaning to give birth. Salutogenesis, the study of the origins and creation of health, provides a method to identify an interconnected way to enhance well-being. Salutogenesis provides a framework for a method of practice to improve health promotion efforts. This article illustrates how quality management methods can be used to guide health promotion efforts focused on improving health beyond the absence of disease. PMID:25777291
MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods
Schmidt, Johannes F. M.; Santelli, Claudio; Kozerke, Sebastian
2016-01-01
An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675
Adaptive Discrete Equation Method for injection of stochastic cavitating flows
NASA Astrophysics Data System (ADS)
Geraci, Gianluca; Rodio, Maria Giovanna; Iaccarino, Gianluca; Abgrall, Remi; Congedo, Pietro
2014-11-01
This work aims at the improvement of the prediction and of the control of biofuel injection for combustion. In fact, common injector should be optimized according to the specific physical/chemical properties of biofuels. In order to attain this scope, an optimized model for reproducing the injection for several biofuel blends will be considered. The originality of this approach is twofold, i) the use of cavitating two-phase compressible models, known as Baer & Nunziato, in order to reproduce the injection, and ii) the design of a global scheme for directly taking into account experimental measurements uncertainties in the simulation. In particular, stochastic intrusive methods display a high efficiency when dealing with discontinuities in unsteady compressible flows. We have recently formulated a new scheme for simulating stochastic multiphase flows relying on the Discrete Equation Method (DEM) for describing multiphase effects. The set-up of the intrusive stochastic method for multiphase unsteady compressible flows in quasi 1D configuration will be presented. The target test-case is a multiphase unsteady nozzle for injection of biofuels, described by complex thermodynamics models, for which experimental data and associated uncertainties are available.
MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.
Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian
2016-01-01
An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675
Adaptive noise cancellation based on beehive pattern evolutionary digital filter
NASA Astrophysics Data System (ADS)
Zhou, Xiaojun; Shao, Yimin
2014-01-01
Evolutionary digital filtering (EDF) exhibits the advantage of avoiding the local optimum problem by using cloning and mating searching rules in an adaptive noise cancellation system. However, convergence performance is restricted by the large population of individuals and the low level of information communication among them. The special beehive structure enables the individuals on neighbour beehive nodes to communicate with each other and thus enhance the information spread and random search ability of the algorithm. By introducing the beehive pattern evolutionary rules into the original EDF, this paper proposes an improved beehive pattern evolutionary digital filter (BP-EDF) to overcome the defects of the original EDF. In the proposed algorithm, a new evolutionary rule which combines competing cloning, complete cloning and assistance mating methods is constructed to enable the individuals distributed on the beehive to communicate with their neighbours. Simulation results are used to demonstrate the improved performance of the proposed algorithm in terms of convergence speed to the global optimum compared with the original methods. Experimental results also verify the effectiveness of the proposed algorithm in extracting feature signals that are contaminated by significant amounts of noise during the fault diagnosis task.
Towards Motivation-Based Adaptation of Difficulty in E-Learning Programs
ERIC Educational Resources Information Center
Endler, Anke; Rey, Gunter Daniel; Butz, Martin V.
2012-01-01
The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of…
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles.
Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb
2015-01-01
Social Internet of Things (SIoT) has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV) is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems. PMID:26389905
Adapting Drug Approval Pathways for Bacteriophage-Based Therapeutics.
Cooper, Callum J; Khan Mirzaei, Mohammadali; Nilsson, Anders S
2016-01-01
The global rise of multi-drug resistant bacteria has resulted in the notion that an "antibiotic apocalypse" is fast approaching. This has led to a number of well publicized calls for global funding initiatives to develop new antibacterial agents. The long clinical history of phage therapy in Eastern Europe, combined with more recent in vitro and in vivo success, demonstrates the potential for whole phage or phage based antibacterial agents. To date, no whole phage or phage derived products are approved for human therapeutic use in the EU or USA. There are at least three reasons for this: (i) phages possess different biological, physical, and pharmacological properties compared to conventional antibiotics. Phages need to replicate in order to achieve a viable antibacterial effect, resulting in complex pharmacodynamics/pharmacokinetics. (ii) The specificity of individual phages requires multiple phages to treat single species infections, often as part of complex cocktails. (iii) The current approval process for antibacterial agents has evolved with the development of chemically based drugs at its core, and is not suitable for phages. Due to similarities with conventional antibiotics, phage derived products such as endolysins are suitable for approval under current processes as biological therapeutic proteins. These criteria render the approval of phages for clinical use theoretically possible but not economically viable. In this review, pitfalls of the current approval process will be discussed for whole phage and phage derived products, in addition to the utilization of alternative approval pathways including adaptive licensing and "Right to try" legislation. PMID:27536293
An Efficient Adaptive Binary Arithmetic Coder Based on Logarithmic Domain.
Yu, Quanhe; Yu, Wei; Yang, Ping; Zheng, Jianhua; Zheng, Xiaozhen; He, Yun
2015-11-01
This paper proposes an efficient adaptive binary arithmetic coder based on a logarithmic domain (LBAC) and a probability estimation based on the LBAC (P-LBAC). Both the LBAC and the P-LBAC achieve a high data-compression ratio with low complexity and a hardware-efficient structure. They introduce a mapping mechanism between the logarithmic domain and the original domain for both the coding process and the probability estimation. The proposed schemes have high accuracy and constitute an efficient BAC. The proposed LBAC and P-LBAC do not use either multiplication and division operations or lookup tables, and only addition and shifting operations are required. The proposed LBAC is designed to favor the coding of multiple symbols and has high throughput. The proposed P-LBAC achieves a good tradeoff between accuracy and speed in probability estimation through a single parameter. When the proposed algorithms are implemented on H.265/HEVC platforms, and they achieve a compression efficiency equivalent to that of CABAC. PMID:26241975
Workload Model Based Dynamic Adaptation of Social Internet of Vehicles
Alam, Kazi Masudul; Saini, Mukesh; El Saddik, Abdulmotaleb
2015-01-01
Social Internet of Things (SIoT) has gained much interest among different research groups in recent times. As a key member of a smart city, the vehicular domain of SIoT (SIoV) is also undergoing steep development. In the SIoV, vehicles work as sensor-hub to capture surrounding information using the in-vehicle and Smartphone sensors and later publish them for the consumers. A cloud centric cyber-physical system better describes the SIoV model where physical sensing-actuation process affects the cloud based service sharing or computation in a feedback loop or vice versa. The cyber based social relationship abstraction enables distributed, easily navigable and scalable peer-to-peer communication among the SIoV subsystems. These cyber-physical interactions involve a huge amount of data and it is difficult to form a real instance of the system to test the feasibility of SIoV applications. In this paper, we propose an analytical model to measure the workloads of various subsystems involved in the SIoV process. We present the basic model which is further extended to incorporate complex scenarios. We provide extensive simulation results for different parameter settings of the SIoV system. The findings of the analyses are further used to design example adaptation strategies for the SIoV subsystems which would foster deployment of intelligent transport systems. PMID:26389905
An adaptive lattice Boltzmann method for predicting turbulent wake fields in wind parks
NASA Astrophysics Data System (ADS)
Deiterding, Ralf; Wood, Stephen L.
2014-11-01
Wind turbines create large-scale wake structures that can affect downstream turbines considerably. Numerical simulation of the turbulent flow field is a viable approach in order to obtain a better understanding of these interactions and to optimize the turbine placement in wind parks. Yet, the development of effective computational methods for predictive wind farm simulation is challenging. As an alternative approach to presently employed vortex and actuator-based methods, we are currently developing a parallel adaptive lattice Boltzmann method for large eddy simulation of turbulent weakly compressible flows with embedded moving structures that shows good potential for effective wind turbine wake prediction. Since the method is formulated in an Eulerian frame of reference and on a dynamically changing nonuniform Cartesian grid, even moving boundaries can be considered rather easily. The presentation will describe all crucial components of the numerical method and discuss first verification computations. Among other configurations, simulations of the wake fields created by multiple Vesta V27 turbines will be shown.
The geometry of r-adaptive meshes generated using optimal transport methods
NASA Astrophysics Data System (ADS)
Budd, C. J.; Russell, R. D.; Walsh, E.
2015-02-01
The principles of mesh equidistribution and alignment play a fundamental role in the design of adaptive methods, and a metric tensor and mesh metric are useful theoretical tools for understanding a method's level of mesh alignment, or anisotropy. We consider a mesh redistribution method based on the Monge-Ampère equation which combines equidistribution of a given scalar density function with optimal transport. It does not involve explicit use of a metric tensor, although such a tensor must exist for the method, and an interesting question to ask is whether or not the alignment produced by the metric gives an anisotropic mesh. For model problems with a linear feature and with a radially symmetric feature, we derive the exact form of the metric, which involves expressions for its eigenvalues and eigenvectors. The eigenvectors are shown to be orthogonal and tangential to the feature, and the ratio of the eigenvalues (corresponding to the level of anisotropy) is shown to depend, both locally and globally, on the value of the density function and the amount of curvature. We thereby demonstrate how the optimal transport method produces an anisotropic mesh along a given feature while equidistributing a suitably chosen scalar density function. Numerical results are given to verify these results and to demonstrate how the analysis is useful for problems involving more complex features, including for a non-trivial time dependant nonlinear PDE which evolves narrow and curved reaction fronts.
The image adaptive method for solder paste 3D measurement system
NASA Astrophysics Data System (ADS)
Xiaohui, Li; Changku, Sun; Peng, Wang
2015-03-01
The extensive application of Surface Mount Technology (SMT) requires various measurement methods to evaluate the circuit board. The solder paste 3D measurement system utilizing laser light projecting on the printed circuit board (PCB) surface is one of the critical methods. The local oversaturation, arising from the non-consistent reflectivity of the PCB surface, will lead to inaccurate measurement. The paper reports a novel optical image adaptive method of remedying the local oversaturation for solder paste measurement. The liquid crystal on silicon (LCoS) and image sensor (CCD or CMOS) are combined as the high dynamic range image (HDRI) acquisition system. The significant characteristic of the new method is that the image after adjustment is captured by specially designed HDRI acquisition system programmed by the LCoS mask. The formation of the LCoS mask, depending on a HDRI combined with the image fusion algorithm, is based on separating the laser light from the local oversaturated region. Experimental results demonstrate that the method can significantly improve the accuracy for the solder paste 3D measurement system with local oversaturation.
Polymer-based micro-deformable mirror for adaptive optics
NASA Astrophysics Data System (ADS)
Liotard, Arnaud; Zamkotsian, Frederic; Conedera, Veronique; Fabre, Norbert; Lanzoni, Patrick; Camon, Henri; Chazallet, Frederic
2006-01-01
Highly performing adaptive optical (AO) systems are mandatory for next generation giant telescopes as well as next generation instrumentation for 10m-class telescopes, for studying new fields like circumstellar disks and extra-solar planets. These systems require deformable mirrors with very challenging parameters, including number of actuators up to 250 000 and inter-actuator spacing around 500μm. MOEMS-based devices are promising for future deformable mirrors. We are currently developing a micro-deformable mirror (MDM) based on an array of electrostatic actuators with attachment posts to a continuous mirror on top. In order to reach large stroke for low driving voltage, the originality of our approach lies in the elaboration of a sacrificial layer and of a structural layer made of polymer materials. We have developed the first polymer piston-motion actuator: a 10μm thick mobile plate with four springs attached to the substrate, and with an air gap of 10μm exhibits a piston motion of 2μm for 30V, and measured resonance frequency of 6.5kHz is well suited for AO systems. The electrostatic force provides a non-linear actuation, while AO systems are based on linear matrices operations. We have successfully developed a dedicated 14-bit electronics in order to "linearize" the actuation. Actual location of the actuator versus expected location of the actuator is obtained with a standard deviation of 21 nm. Comparison with FEM models shows very good agreement, and design of a complete polymer-based MDM has been done.
A Space-Time Adaptive Method for Simulating Complex Cardiac Dynamics
NASA Astrophysics Data System (ADS)
Cherry, E. M.; Greenside, H. S.; Henriquez, C. S.
2000-03-01
A new space-time adaptive mesh refinement algorithm (AMRA) is presented and analyzed which, by automatically adding and deleting local patches of higher-resolution Cartesian meshes, can simulate quantitatively accurate models of cardiac electrical dynamics efficiently in large domains. We find in two space dimensions that the AMRA is able to achieve a factor of 5 speedup and a factor of 5 reduction in memory while achieving the same accuracy compared to a code based on a uniform space-time mesh at the highest resolution of the AMRA method. We summarize applications of the code to the Luo-Rudy 1 cardiac model in large two- and three-dimensional domains and discuss the implications of our results for understanding the initiation of arrhythmias.
NASA Technical Reports Server (NTRS)
Aftosmis, M. J.; Berger, M. J.; Adomavicius, G.
2000-01-01
Preliminary verification and validation of an efficient Euler solver for adaptively refined Cartesian meshes with embedded boundaries is presented. The parallel, multilevel method makes use of a new on-the-fly parallel domain decomposition strategy based upon the use of space-filling curves, and automatically generates a sequence of coarse meshes for processing by the multigrid smoother. The coarse mesh generation algorithm produces grids which completely cover the computational domain at every level in the mesh hierarchy. A series of examples on realistically complex three-dimensional configurations demonstrate that this new coarsening algorithm reliably achieves mesh coarsening ratios in excess of 7 on adaptively refined meshes. Numerical investigations of the scheme's local truncation error demonstrate an achieved order of accuracy between 1.82 and 1.88. Convergence results for the multigrid scheme are presented for both subsonic and transonic test cases and demonstrate W-cycle multigrid convergence rates between 0.84 and 0.94. Preliminary parallel scalability tests on both simple wing and complex complete aircraft geometries shows a computational speedup of 52 on 64 processors using the run-time mesh partitioner.
NASA Astrophysics Data System (ADS)
Chassaing, J.-C.; Lucor, D.; Trégon, J.
2012-01-01
An adaptive stochastic spectral projection method is deployed for the uncertainty quantification in limit-cycle oscillations of an elastically mounted two-dimensional lifting surface in a supersonic flow field. Variabilities in the structural parameters are propagated in the aeroelastic system which accounts for nonlinear restoring force and moment by means of hardening cubic springs. The physical nonlinearities promote sharp and sudden flutter onset for small change of the reduced velocity. In a stochastic context, this behavior translates to steep solution gradients developing in the parametric space. A remedy is to expand the stochastic response of the airfoil on a piecewise generalized polynomial chaos basis. Accurate approximation andaffordable computational costs are obtained using sensitivity-based adaptivity for various types of supersonic stochastic responses depending on the selected values of the Mach number on the bifurcation map. Sensitivity analysis via Sobol' indices shows how the probability density function of the peak pitch amplitude responds to combined uncertainties: e.g. the elastic axis location, torsional stiffness and flap angle. We believe that this work demonstrates the capability and flexibility of the approach for more reliable predictions of realistic aeroelastic systems subject to a moderate number of uncertainties.
A Fast Variational Method for the Construction of Resolution Adaptive C-Smooth Molecular Surfaces.
Bajaj, Chandrajit L; Xu, Guoliang; Zhang, Qin
2009-05-01
We present a variational approach to smooth molecular (proteins, nucleic acids) surface constructions, starting from atomic coordinates, as available from the protein and nucleic-acid data banks. Molecular dynamics (MD) simulations traditionally used in understanding protein and nucleic-acid folding processes, are based on molecular force fields, and require smooth models of these molecular surfaces. To accelerate MD simulations, a popular methodology is to employ coarse grained molecular models, which represent clusters of atoms with similar physical properties by psuedo- atoms, resulting in coarser resolution molecular surfaces. We consider generation of these mixed-resolution or adaptive molecular surfaces. Our approach starts from deriving a general form second order geometric partial differential equation in the level-set formulation, by minimizing a first order energy functional which additionally includes a regularization term to minimize the occurrence of chemically infeasible molecular surface pockets or tunnel-like artifacts. To achieve even higher computational efficiency, a fast cubic B-spline C(2) interpolation algorithm is also utilized. A narrow band, tri-cubic B-spline level-set method is then used to provide C(2) smooth and resolution adaptive molecular surfaces. PMID:19802355
Error estimation and adaptive order nodal method for solving multidimensional transport problems
Zamonsky, O.M.; Gho, C.J.; Azmy, Y.Y.
1998-01-01
The authors propose a modification of the Arbitrarily High Order Transport Nodal method whereby they solve each node and each direction using different expansion order. With this feature and a previously proposed a posteriori error estimator they develop an adaptive order scheme to automatically improve the accuracy of the solution of the transport equation. They implemented the modified nodal method, the error estimator and the adaptive order scheme into a discrete-ordinates code for solving monoenergetic, fixed source, isotropic scattering problems in two-dimensional Cartesian geometry. They solve two test problems with large homogeneous regions to test the adaptive order scheme. The results show that using the adaptive process the storage requirements are reduced while preserving the accuracy of the results.