Method of dimensionality reduction in contact mechanics and friction
Popov, Valentin L
2015-01-01
This book describes for the first time a simulation method for the fast calculation of contact properties and friction between rough surfaces in a complete form. In contrast to existing simulation methods, the method of dimensionality reduction (MDR) is based on the exact mapping of various types of three-dimensional contact problems onto contacts of one-dimensional foundations. Within the confines of MDR, not only are three dimensional systems reduced to one-dimensional, but also the resulting degrees of freedom are independent from another. Therefore, MDR results in an enormous reduction of the development time for the numerical implementation of contact problems as well as the direct computation time and can ultimately assume a similar role in tribology as FEM has in structure mechanics or CFD methods, in hydrodynamics. Furthermore, it substantially simplifies analytical calculation and presents a sort of “pocket book edition” of the entirety contact mechanics. Measurements of the rheology of bodies in...
Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization.
Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil
2017-01-19
Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases' quality, and make biobricks selection.
A sparse grid based method for generative dimensionality reduction of high-dimensional data
Bohn, Bastian; Garcke, Jochen; Griebel, Michael
2016-03-01
Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.
Dimensionality Reduction Methods: Comparative Analysis of methods PCA, PPCA and KPCA
Directory of Open Access Journals (Sweden)
Jorge Arroyo-Hernández
2016-01-01
Full Text Available The dimensionality reduction methods are algorithms mapping the set of data in subspaces derived from the original space, of fewer dimensions, that allow a description of the data at a lower cost. Due to their importance, they are widely used in processes associated with learning machine. This article presents a comparative analysis of PCA, PPCA and KPCA dimensionality reduction methods. A reconstruction experiment of worm-shape data was performed through structures of landmarks located in the body contour, with methods having different number of main components. The results showed that all methods can be seen as alternative processes. Nevertheless, thanks to the potential for analysis in the features space and the method for calculation of its preimage presented, KPCA offers a better method for recognition process and pattern extraction
A finite-dimensional reduction method for slightly supercritical elliptic problems
Directory of Open Access Journals (Sweden)
Riccardo Molle
2004-01-01
Full Text Available We describe a finite-dimensional reduction method to find solutions for a class of slightly supercritical elliptic problems. A suitable truncation argument allows us to work in the usual Sobolev space even in the presence of supercritical nonlinearities: we modify the supercritical term in such a way to have subcritical approximating problems; for these problems, the finite-dimensional reduction can be obtained applying the methods already developed in the subcritical case; finally, we show that, if the truncation is realized at a sufficiently large level, then the solutions of the approximating problems, given by these methods, also solve the supercritical problems when the parameter is small enough.
ANALYSIS OF IMPACT ON COMPOSITE STRUCTURES WITH THE METHOD OF DIMENSIONALITY REDUCTION
Directory of Open Access Journals (Sweden)
Valentin L. Popov
2015-04-01
Full Text Available In the present paper, we discuss the impact of rigid profiles on continua with non-local criteria for plastic yield. For the important case of media whose hardness is inversely proportional to the indentation radius, we suggest a rigorous treatment based on the method of dimensionality reduction (MDR and study the example of indentation by a conical profile.
Directory of Open Access Journals (Sweden)
Ross S Williamson
2015-04-01
Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.
Directory of Open Access Journals (Sweden)
Zhang Jing
2016-01-01
Full Text Available To assist physicians to quickly find the required 3D model from the mass medical model, we propose a novel retrieval method, called DRFVT, which combines the characteristics of dimensionality reduction (DR and feature vector transformation (FVT method. The DR method reduces the dimensionality of feature vector; only the top M low frequency Discrete Fourier Transform coefficients are retained. The FVT method does the transformation of the original feature vector and generates a new feature vector to solve the problem of noise sensitivity. The experiment results demonstrate that the DRFVT method achieves more effective and efficient retrieval results than other proposed methods.
A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis
Directory of Open Access Journals (Sweden)
Huanhuan Li
2017-08-01
Full Text Available The Shipboard Automatic Identification System (AIS is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW, a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our
A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis.
Li, Huanhuan; Liu, Jingxian; Liu, Ryan Wen; Xiong, Naixue; Wu, Kefeng; Kim, Tai-Hoon
2017-08-04
The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with
Zhang, Lianbin; Chen, Guoying; Hedhili, Mohamed N.; Zhang, Hongnan; Wang, Peng
2012-01-01
In this study, three-dimensional (3D) graphene assemblies are prepared from graphene oxide (GO) by a facile in situ reduction-assembly method, using a novel, low-cost, and environment-friendly reducing medium which is a combination of oxalic acid
International Nuclear Information System (INIS)
Kaczmarek, J.
2002-01-01
Elementary processes responsible for phenomena in material are frequently related to scale close to atomic one. Therefore atomistic simulations are important for material sciences. On the other hand continuum mechanics is widely applied in mechanics of materials. It seems inevitable that both methods will gradually integrate. A multiscale method of integration of these approaches called collection of dynamical systems with dimensional reduction is introduced in this work. The dimensional reduction procedure realizes transition between various scale models from an elementary dynamical system (EDS) to a reduced dynamical system (RDS). Mappings which transform variables and forces, skeletal dynamical system (SDS) and a set of approximation and identification methods are main components of this procedure. The skeletal dynamical system is a set of dynamical systems parameterized by some constants and has variables related to the dimensionally reduced model. These constants are identified with the aid of solutions of the elementary dynamical system. As a result we obtain a dimensionally reduced dynamical system which describes phenomena in an averaged way in comparison with the EDS. Concept of integration of atomistic simulations with continuum mechanics consists in using a dynamical system describing evolution of atoms as an elementary dynamical system. Then, we introduce a continuum skeletal dynamical system within the dimensional reduction procedure. In order to construct such a system we have to modify a continuum mechanics formulation to some degree. Namely, we formalize scale of averaging for continuum theory and as a result we consider continuum with finite-dimensional fields only. Then, realization of dimensional reduction is possible. A numerical example of realization of the dimensional reduction procedure is shown. We consider a one dimensional chain of atoms interacting by Lennard-Jones potential. Evolution of this system is described by an elementary
Directory of Open Access Journals (Sweden)
Valentin L. Popov
2014-04-01
Full Text Available The Method of Dimensionality Reduction (MDR is a method of calculation and simulation of contacts of elastic and viscoelastic bodies. It consists essentially of two simple steps: (a substitution of the three-dimensional continuum by a uniquely defined one-dimensional linearly elastic or viscoelastic foundation (Winkler foundation and (b transformation of the three-dimensional profile of the contacting bodies by means of the MDR-transformation. As soon as these two steps are completed, the contact problem can be considered to be solved. For axial symmetric contacts, only a small calculation by hand is required which does not exceed elementary calculus and will not be a barrier for any practically-oriented engineer. Alternatively, the MDR can be implemented numerically, which is almost trivial due to the independence of the foundation elements. In spite of their simplicity, all the results are exact. The present paper is a short practical guide to the MDR.
An alternative dimensional reduction prescription
International Nuclear Information System (INIS)
Edelstein, J.D.; Giambiagi, J.J.; Nunez, C.; Schaposnik, F.A.
1995-08-01
We propose an alternative dimensional reduction prescription which in respect with Green functions corresponds to drop the extra spatial coordinate. From this, we construct the dimensionally reduced Lagrangians both for scalars and fermions, discussing bosonization and supersymmetry in the particular 2-dimensional case. We argue that our proposal is in some situations more physical in the sense that it maintains the form of the interactions between particles thus preserving the dynamics corresponding to the higher dimensional space. (author). 12 refs
International Nuclear Information System (INIS)
Langner, Ulrich W.; Keall, Paul J.
2010-01-01
Purpose: To quantify the magnitude and frequency of artifacts in simulated four-dimensional computed tomography (4D CT) images using three real-time acquisition methods- direction-dependent displacement acquisition, simultaneous displacement and phase acquisition, and simultaneous displacement and velocity acquisition- and to compare these methods with commonly used retrospective phase sorting. Methods and Materials: Image acquisition for the four 4D CT methods was simulated with different displacement and velocity tolerances for spheres with radii of 0.5 cm, 1.5 cm, and 2.5 cm, using 58 patient-measured tumors and respiratory motion traces. The magnitude and frequency of artifacts, CT doses, and acquisition times were computed for each method. Results: The mean artifact magnitude was 50% smaller for the three real-time methods than for retrospective phase sorting. The dose was ∼50% lower, but the acquisition time was 20% to 100% longer for the real-time methods than for retrospective phase sorting. Conclusions: Real-time acquisition methods can reduce the frequency and magnitude of artifacts in 4D CT images, as well as the imaging dose, but they increase the image acquisition time. The results suggest that direction-dependent displacement acquisition is the preferred real-time 4D CT acquisition method, because on average, the lowest dose is delivered to the patient and the acquisition time is the shortest for the resulting number and magnitude of artifacts.
Fermion masses from dimensional reduction
International Nuclear Information System (INIS)
Kapetanakis, D.; Zoupanos, G.
1990-01-01
We consider the fermion masses in gauge theories obtained from ten dimensions through dimensional reduction on coset spaces. We calculate the general fermion mass matrix and we apply the mass formula in illustrative examples. (orig.)
Fermion masses from dimensional reduction
Energy Technology Data Exchange (ETDEWEB)
Kapetanakis, D. (National Research Centre for the Physical Sciences Democritos, Athens (Greece)); Zoupanos, G. (European Organization for Nuclear Research, Geneva (Switzerland))
1990-10-11
We consider the fermion masses in gauge theories obtained from ten dimensions through dimensional reduction on coset spaces. We calculate the general fermion mass matrix and we apply the mass formula in illustrative examples. (orig.).
Dimensional Reduction and Hadronic Processes
International Nuclear Information System (INIS)
Signer, Adrian; Stoeckinger, Dominik
2008-01-01
We consider the application of regularization by dimensional reduction to NLO corrections of hadronic processes. The general collinear singularity structure is discussed, the origin of the regularization-scheme dependence is identified and transition rules to other regularization schemes are derived.
Central subspace dimensionality reduction using covariance operators.
Kim, Minyoung; Pavlovic, Vladimir
2011-04-01
We consider the task of dimensionality reduction informed by real-valued multivariate labels. The problem is often treated as Dimensionality Reduction for Regression (DRR), whose goal is to find a low-dimensional representation, the central subspace, of the input data that preserves the statistical correlation with the targets. A class of DRR methods exploits the notion of inverse regression (IR) to discover central subspaces. Whereas most existing IR techniques rely on explicit output space slicing, we propose a novel method called the Covariance Operator Inverse Regression (COIR) that generalizes IR to nonlinear input/output spaces without explicit target slicing. COIR's unique properties make DRR applicable to problem domains with high-dimensional output data corrupted by potentially significant amounts of noise. Unlike recent kernel dimensionality reduction methods that employ iterative nonconvex optimization, COIR yields a closed-form solution. We also establish the link between COIR, other DRR techniques, and popular supervised dimensionality reduction methods, including canonical correlation analysis and linear discriminant analysis. We then extend COIR to semi-supervised settings where many of the input points lack their labels. We demonstrate the benefits of COIR on several important regression problems in both fully supervised and semi-supervised settings.
Dimensional reduction in quantum gravity
Energy Technology Data Exchange (ETDEWEB)
Hooft, G [Rijksuniversiteit Utrecht (Netherlands). Inst. voor Theoretische Fysica
1994-12-31
The requirement that physical phenomena associated with gravitational collapse should be duly reconciled with the postulates of quantum mechanics implies that at a Planckian scale our world is not 3+1 dimensional. Rather, the observable degrees of freedom can best be described as if they were Boolean variables defined on a two- dimensional lattice, evolving with time. This observation, deduced from not much more than unitarity, entropy and counting arguments, implies severe restrictions on possible models of quantum gravity. Using cellular automata as an example it is argued that this dimensional reduction implies more constraints than the freedom we have in constructing models. This is the main reason why so-far no completely consistent mathematical models of quantum black holes have been found. (author). 13 refs, 2 figs.
Dimensional reduction in anomaly mediation
International Nuclear Information System (INIS)
Boyda, Ed; Murayama, Hitoshi; Pierce, Aaron
2002-01-01
We offer a guide to dimensional reduction in theories with anomaly-mediated supersymmetry breaking. Evanescent operators proportional to ε arise in the bare Lagrangian when it is reduced from d=4 to d=4-2ε dimensions. In the course of a detailed diagrammatic calculation, we show that inclusion of these operators is crucial. The evanescent operators conspire to drive the supersymmetry-breaking parameters along anomaly-mediation trajectories across heavy particle thresholds, guaranteeing the ultraviolet insensitivity
Zhang, Lianbin
2012-01-01
In this study, three-dimensional (3D) graphene assemblies are prepared from graphene oxide (GO) by a facile in situ reduction-assembly method, using a novel, low-cost, and environment-friendly reducing medium which is a combination of oxalic acid (OA) and sodium iodide (NaI). It is demonstrated that the combination of a reducing acid, OA, and NaI is indispensable for effective reduction of GO in the current study and this unique combination (1) allows for tunable control over the volume of the thus-prepared graphene assemblies and (2) enables 3D graphene assemblies to be prepared from the GO suspension with a wide range of concentrations (0.1 to 4.5 mg mL-1). To the best of our knowledge, the GO concentration of 0.1 mg mL-1 is the lowest GO concentration ever reported for preparation of 3D graphene assemblies. The thus-prepared 3D graphene assemblies exhibit low density, highly porous structures, and electrically conducting properties. As a proof of concept, we show that by infiltrating a responsive polymer of polydimethylsiloxane (PDMS) into the as-resulted 3D conducting network of graphene, a conducting composite is obtained, which can be used as a sensing device for differentiating organic solvents with different polarity. © 2012 The Royal Society of Chemistry.
Multichannel transfer function with dimensionality reduction
Kim, Han Suk
2010-01-17
The design of transfer functions for volume rendering is a difficult task. This is particularly true for multi-channel data sets, where multiple data values exist for each voxel. In this paper, we propose a new method for transfer function design. Our new method provides a framework to combine multiple approaches and pushes the boundary of gradient-based transfer functions to multiple channels, while still keeping the dimensionality of transfer functions to a manageable level, i.e., a maximum of three dimensions, which can be displayed visually in a straightforward way. Our approach utilizes channel intensity, gradient, curvature and texture properties of each voxel. The high-dimensional data of the domain is reduced by applying recently developed nonlinear dimensionality reduction algorithms. In this paper, we used Isomap as well as a traditional algorithm, Principle Component Analysis (PCA). Our results show that these dimensionality reduction algorithms significantly improve the transfer function design process without compromising visualization accuracy. In this publication we report on the impact of the dimensionality reduction algorithms on transfer function design for confocal microscopy data.
Robust methods for data reduction
Farcomeni, Alessio
2015-01-01
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy
Dimensionality reduction with unsupervised nearest neighbors
Kramer, Oliver
2013-01-01
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustr...
Andersson, Pher G
2008-01-01
With its comprehensive overview of modern reduction methods, this book features high quality contributions allowing readers to find reliable solutions quickly and easily. The monograph treats the reduction of carbonyles, alkenes, imines and alkynes, as well as reductive aminations and cross and heck couplings, before finishing off with sections on kinetic resolutions and hydrogenolysis. An indispensable lab companion for every chemist.
Reduction of infinite dimensional equations
Directory of Open Access Journals (Sweden)
Zhongding Li
2006-02-01
Full Text Available In this paper, we use the general Legendre transformation to show the infinite dimensional integrable equations can be reduced to a finite dimensional integrable Hamiltonian system on an invariant set under the flow of the integrable equations. Then we obtain the periodic or quasi-periodic solution of the equation. This generalizes the results of Lax and Novikov regarding the periodic or quasi-periodic solution of the KdV equation to the general case of isospectral Hamiltonian integrable equation. And finally, we discuss the AKNS hierarchy as a special example.
Dimensionality reduction of collective motion by principal manifolds
Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.
2015-01-01
While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.
The dimensional reduction in a multi-dimensional cosmology
International Nuclear Information System (INIS)
Demianski, M.; Golda, Z.A.; Heller, M.; Szydlowski, M.
1986-01-01
Einstein's field equations are solved for the case of the eleven-dimensional vacuum spacetime which is the product R x Bianchi V x T 7 , where T 7 is a seven-dimensional torus. Among all possible solutions, the authors identify those in which the macroscopic space expands and the microscopic space contracts to a finite size. The solutions with this property are 'typical' within the considered class. They implement the idea of a purely dynamical dimensional reduction. (author)
Coset space dimensional reduction of gauge theories
Energy Technology Data Exchange (ETDEWEB)
Kapetanakis, D. (Physik Dept., Technische Univ. Muenchen, Garching (Germany)); Zoupanos, G. (CERN, Geneva (Switzerland))
1992-10-01
We review the attempts to construct unified theories defined in higher dimensions which are dimensionally reduced over coset spaces. We employ the coset space dimensional reduction scheme, which permits the detailed study of the resulting four-dimensional gauge theories. In the context of this scheme we present the difficulties and the suggested ways out in the attempts to describe the observed interactions in a realistic way. (orig.).
Coset space dimensional reduction of gauge theories
International Nuclear Information System (INIS)
Kapetanakis, D.; Zoupanos, G.
1992-01-01
We review the attempts to construct unified theories defined in higher dimensions which are dimensionally reduced over coset spaces. We employ the coset space dimensional reduction scheme, which permits the detailed study of the resulting four-dimensional gauge theories. In the context of this scheme we present the difficulties and the suggested ways out in the attempts to describe the observed interactions in a realistic way. (orig.)
Parallel Framework for Dimensionality Reduction of Large-Scale Datasets
Directory of Open Access Journals (Sweden)
Sai Kiranmayee Samudrala
2015-01-01
Full Text Available Dimensionality reduction refers to a set of mathematical techniques used to reduce complexity of the original high-dimensional data, while preserving its selected properties. Improvements in simulation strategies and experimental data collection methods are resulting in a deluge of heterogeneous and high-dimensional data, which often makes dimensionality reduction the only viable way to gain qualitative and quantitative understanding of the data. However, existing dimensionality reduction software often does not scale to datasets arising in real-life applications, which may consist of thousands of points with millions of dimensions. In this paper, we propose a parallel framework for dimensionality reduction of large-scale data. We identify key components underlying the spectral dimensionality reduction techniques, and propose their efficient parallel implementation. We show that the resulting framework can be used to process datasets consisting of millions of points when executed on a 16,000-core cluster, which is beyond the reach of currently available methods. To further demonstrate applicability of our framework we perform dimensionality reduction of 75,000 images representing morphology evolution during manufacturing of organic solar cells in order to identify how processing parameters affect morphology evolution.
Dimensional reduction of a generalized flux problem
International Nuclear Information System (INIS)
Moroz, A.
1992-01-01
In this paper, a generalized flux problem with Abelian and non-Abelian fluxes is considered. In the Abelian case we shall show that the generalized flux problem for tight-binding models of noninteracting electrons on either 2n- or (2n + 1)-dimensional lattice can always be reduced to an n-dimensional hopping problem. A residual freedom in this reduction enables one to identify equivalence classes of hopping Hamiltonians which have the same spectrum. In the non-Abelian case, the reduction is not possible in general unless the flux tensor factorizes into an Abelian one times are element of the corresponding algebra
Pole masses of quarks in dimensional reduction
International Nuclear Information System (INIS)
Avdeev, L.V.; Kalmykov, M.Yu.
1997-01-01
Pole masses of quarks in quantum chromodynamics are calculated to the two-loop order in the framework of the regularization by dimensional reduction. For the diagram with a light quark loop, the non-Euclidean asymptotic expansion is constructed with the external momentum on the mass shell of a heavy quark
General dimensional reduction of ten-dimensional supergravity and superstring
International Nuclear Information System (INIS)
Ferrara, S.; Porrati, M.
1986-01-01
Dimensional reductions of supergravity theories are shown to yield to specific glasses of four-dimensional no-scale models with N=4, 2 or 1 residual supersymmetry. N=1 ''maximal'' supergravity lagrangian, corresponding to the ''untwisted'' sector of orbifold compactification of superstrings, contains nine families and has a no-scale structure based on the Kaehler manifold [SU(3, 3+3n)/SU(3)xSU(3+3n)]x[SU(1, 1)/U(1)]. The quantum consistency of the resulting theories give information on the non Kaluza-Klein (string) ''twisted'' sector. (orig.)
Adaptive Sampling for Nonlinear Dimensionality Reduction Based on Manifold Learning
DEFF Research Database (Denmark)
Franz, Thomas; Zimmermann, Ralf; Goertz, Stefan
2017-01-01
We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space that is approxi...... to detect and fill up gaps in the sampling in the embedding space. The performance of the proposed manifold filling method will be illustrated by numerical experiments, where we consider nonlinear parameter-dependent steady-state Navier-Stokes flows in the transonic regime.......We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space...
Multichannel transfer function with dimensionality reduction
Kim, Han Suk; Schulze, Jü rgen P.; Cone, Angela C.; Sosinsky, Gina E.; Martone, Maryann E.
2010-01-01
. Our new method provides a framework to combine multiple approaches and pushes the boundary of gradient-based transfer functions to multiple channels, while still keeping the dimensionality of transfer functions to a manageable level, i.e., a maximum
Dimensional reduction from entanglement in Minkowski space
International Nuclear Information System (INIS)
Brustein, Ram; Yarom, Amos
2005-01-01
Using a quantum field theoretic setting, we present evidence for dimensional reduction of any sub-volume of Minkowksi space. First, we show that correlation functions of a class of operators restricted to a sub-volume of D-dimensional Minkowski space scale as its surface area. A simple example of such area scaling is provided by the energy fluctuations of a free massless quantum field in its vacuum state. This is reminiscent of area scaling of entanglement entropy but applies to quantum expectation values in a pure state, rather than to statistical averages over a mixed state. We then show, in a specific case, that fluctuations in the bulk have a lower-dimensional representation in terms of a boundary theory at high temperature. (author)
A Tannakian approach to dimensional reduction of principal bundles
Álvarez-Cónsul, Luis; Biswas, Indranil; García-Prada, Oscar
2017-08-01
Let P be a parabolic subgroup of a connected simply connected complex semisimple Lie group G. Given a compact Kähler manifold X, the dimensional reduction of G-equivariant holomorphic vector bundles over X × G / P was carried out in Álvarez-Cónsul and García-Prada (2003). This raises the question of dimensional reduction of holomorphic principal bundles over X × G / P. The method of Álvarez-Cónsul and García-Prada (2003) is special to vector bundles; it does not generalize to principal bundles. In this paper, we adapt to equivariant principal bundles the Tannakian approach of Nori, to describe the dimensional reduction of G-equivariant principal bundles over X × G / P, and to establish a Hitchin-Kobayashi type correspondence. In order to be able to apply the Tannakian theory, we need to assume that X is a complex projective manifold.
Dimensional reduction for D3-brane moduli
International Nuclear Information System (INIS)
Cownden, Brad; Frey, Andrew R.; Marsh, M.C. David; Underwood, Bret
2016-01-01
Warped string compactifications are central to many attempts to stabilize moduli and connect string theory with cosmology and particle phenomenology. We present a first-principles derivation of the low-energy 4D effective theory from dimensional reduction of a D3-brane in a warped Calabi-Yau compactification of type IIB string theory with imaginary self-dual 3-form flux, including effects of D3-brane motion beyond the probe approximation, and find the metric on the moduli space of brane positions, the universal volume modulus, and axions descending from the 4-form potential. As D3-branes may be considered as carrying either electric or magnetic charges for the self-dual 5-form field strength, we present calculations in both duality frames. Our results are consistent with, but extend significantly, earlier results on the low-energy effective theory arising from D3-branes in string compactifications.
Dimensionality reduction of quality of life indicators
Directory of Open Access Journals (Sweden)
Andrea Jindrová
2012-01-01
Full Text Available Selecting indicators for assessing the quality of life at the regional level is not unambigous. Currently, there are no precisely defined indicators that would give comprehensive information about the quality of life on a local level. In this paper we focus on the determination (selection of groups of indicators that can be interpreted, on the basis of studied literature, as factors characterizing the quality of life. Furthermore, on the application of methods to reduce the dimensionality of these indicators, from the source of the database CULS KROK, which provides statistics on the regional and districts level. To reduce the number of indicators and the subsequent creation of derived variables that capture the relationships between selected indicators multivariate statistical analysis methods, especially method of principal components and factor analysis were used. This paper also indicates the methodology grant project “Methodological Approaches to assess Subjective Aspects of the life quality in regions of the Czech Republic”.
Denoising and dimensionality reduction of genomic data
Capobianco, Enrico
2005-05-01
Genomics represents a challenging research field for many quantitative scientists, and recently a vast variety of statistical techniques and machine learning algorithms have been proposed and inspired by cross-disciplinary work with computational and systems biologists. In genomic applications, the researcher deals with noisy and complex high-dimensional feature spaces; a wealth of genes whose expression levels are experimentally measured, can often be observed for just a few time points, thus limiting the available samples. This unbalanced combination suggests that it might be hard for standard statistical inference techniques to come up with good general solutions, likewise for machine learning algorithms to avoid heavy computational work. Thus, one naturally turns to two major aspects of the problem: sparsity and intrinsic dimensionality. These two aspects are studied in this paper, where for both denoising and dimensionality reduction, a very efficient technique, i.e., Independent Component Analysis, is used. The numerical results are very promising, and lead to a very good quality of gene feature selection, due to the signal separation power enabled by the decomposition technique. We investigate how the use of replicates can improve these results, and deal with noise through a stabilization strategy which combines the estimated components and extracts the most informative biological information from them. Exploiting the inherent level of sparsity is a key issue in genetic regulatory networks, where the connectivity matrix needs to account for the real links among genes and discard many redundancies. Most experimental evidence suggests that real gene-gene connections represent indeed a subset of what is usually mapped onto either a huge gene vector or a typically dense and highly structured network. Inferring gene network connectivity from the expression levels represents a challenging inverse problem that is at present stimulating key research in biomedical
Cosmological string solutions by dimensional reduction
International Nuclear Information System (INIS)
Behrndt, K.; Foerste, S.
1993-12-01
We obtain cosmological four dimensional solutions of the low energy effective string theory by reducing a five dimensional black hole, and black hole-de Sitter solution of the Einstein gravity down to four dimensions. The appearance of a cosmological constant in the five dimensional Einstein-Hilbert produces a special dilaton potential in the four dimensional effective string action. Cosmological scenarios implement by our solutions are discussed
Discrete symmetries and coset space dimensional reduction
International Nuclear Information System (INIS)
Kapetanakis, D.; Zoupanos, G.
1989-01-01
We consider the discrete symmetries of all the six-dimensional coset spaces and we apply them in gauge theories defined in ten dimensions which are dimensionally reduced over these homogeneous spaces. Particular emphasis is given in the consequences of the discrete symmetries on the particle content as well as on the symmetry breaking a la Hosotani of the resulting four-dimensional theory. (orig.)
On dimensional reduction over coset spaces
International Nuclear Information System (INIS)
Kapetanakis, D.; Zoupanos, G.
1990-01-01
Gauge theories defined in higher dimensions can be dimensionally reduced over coset spaces giving definite predictions for the resulting four-dimensional theory. We present the most interesting features of these theories as well as an attempt to construct a model with realistic low energy behaviour within this framework. (author)
Dimensional reduction and BRST approach to the description of a Regge trajectory
International Nuclear Information System (INIS)
Pashnev, A.I.; Tsulaya, M.M.
1997-01-01
The local free field theory for Regge trajectory is described in the framework of the BRST-quantization method. The corresponding BRST-charge is constructed with the help of the method of dimensional reduction
Stochastic confinement and dimensional reduction. 1
International Nuclear Information System (INIS)
Ambjoern, J.; Olesen, P.; Peterson, C.
1984-03-01
By Monte Carlo calculations on a 16 4 lattice the authors investigate four dimensional SU(2) lattice guage theory with respect to the conjecture that at large distances this theory reduces approximately to two dimensional SU(2) lattice gauge theory. Good numerical evidence is found for this conjecture. As a by-product the SU(2) string tension is also measured and good agreement is found with scaling. The 'adjoint string tension' is also found to have a reasonable scaling behaviour. (Auth.)
Stochastic confinement and dimensional reduction. Pt. 1
International Nuclear Information System (INIS)
Ambjoern, J.; Olesen, P.; Peterson, C.
1984-01-01
By Monte Carlo calculations on a 12 4 lattice we investigate four-dimensional SU(2) lattice gauge theory with respect to the conjecture that at large distances this theory reduces approximately to two-dimensional SU(2) lattice gauge theory. We find good numerical evidence for this conjecture. As a by-product we also measure the SU(2) string tension and find reasonable agreement with scaling. The 'adjoint string tension' is also found to have a reasonable scaling behaviour. (orig.)
Supervised linear dimensionality reduction with robust margins for object recognition
Dornaika, F.; Assoum, A.
2013-01-01
Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.
Dimensional Reduction for the General Markov Model on Phylogenetic Trees.
Sumner, Jeremy G
2017-03-01
We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.
Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray
Directory of Open Access Journals (Sweden)
Lan Shu
2008-07-01
Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLEÃ¢Â€Â™s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.
Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery
Ochilov, S.; Alam, M. S.; Bal, A.
2006-05-01
Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.
Dimensional reduction near the deconfinement transition
International Nuclear Information System (INIS)
Kurkela, A.
2009-01-01
It is expected that incorporating the center symmetry in the conventional dimensionally reduced effective theory for high-temperature SU(N) Yang-Mills theory, EQCD, will considerably extend its applicability towards the deconfinement transition. In this talk, I will discuss the construction of such center-symmetric effective theories and present results from their lattice simulations in the case of two colors. The simulations demonstrate that unlike EQCD, the new center symmetric theory undergoes a second order confining phase transition in complete analogy with the full theory. I will also describe the perturbative and non-perturbative matching of the parameters of the effective theory, and outline ways to further improve its description of the physics near the deconfinement transition. (author)
Perturbative QCD Lagrangian at large distances and stochastic dimensionality reduction. Pt. 2
International Nuclear Information System (INIS)
Shintani, M.
1986-11-01
Using the method of stochastic dimensional reduction, we derive a four-dimensional quantum effective Lagrangian for the classical Yang-Mills system coupled to the Gaussian white noise. It is found that the Lagrangian coincides with the perturbative QCD at large distances constructed in our previous paper. That formalism is based on the local covariant operator formalism which maintains the unitarity of the S-matrix. Furthermore, we show the non-perturbative equivalence between super-Lorentz invariant sectors of the effective Lagrangian and two dimensional QCD coupled to the adjoint pseudo-scalars. This implies that stochastic dimensionality reduction by two is approximately operative in QCD at large distances. (orig.)
Metric dimensional reduction at singularities with implications to Quantum Gravity
International Nuclear Information System (INIS)
Stoica, Ovidiu Cristinel
2014-01-01
A series of old and recent theoretical observations suggests that the quantization of gravity would be feasible, and some problems of Quantum Field Theory would go away if, somehow, the spacetime would undergo a dimensional reduction at high energy scales. But an identification of the deep mechanism causing this dimensional reduction would still be desirable. The main contribution of this article is to show that dimensional reduction effects are due to General Relativity at singularities, and do not need to be postulated ad-hoc. Recent advances in understanding the geometry of singularities do not require modification of General Relativity, being just non-singular extensions of its mathematics to the limit cases. They turn out to work fine for some known types of cosmological singularities (black holes and FLRW Big-Bang), allowing a choice of the fundamental geometric invariants and physical quantities which remain regular. The resulting equations are equivalent to the standard ones outside the singularities. One consequence of this mathematical approach to the singularities in General Relativity is a special, (geo)metric type of dimensional reduction: at singularities, the metric tensor becomes degenerate in certain spacetime directions, and some properties of the fields become independent of those directions. Effectively, it is like one or more dimensions of spacetime just vanish at singularities. This suggests that it is worth exploring the possibility that the geometry of singularities leads naturally to the spontaneous dimensional reduction needed by Quantum Gravity. - Highlights: • The singularities we introduce are described by finite geometric/physical objects. • Our singularities are accompanied by dimensional reduction effects. • They affect the metric, the measure, the topology, the gravitational DOF (Weyl = 0). • Effects proposed in other approaches to Quantum Gravity are obtained naturally. • The geometric dimensional reduction obtained
Effective Image Database Search via Dimensionality Reduction
DEFF Research Database (Denmark)
Dahl, Anders Bjorholm; Aanæs, Henrik
2008-01-01
Image search using the bag-of-words image representation is investigated further in this paper. This approach has shown promising results for large scale image collections making it relevant for Internet applications. The steps involved in the bag-of-words approach are feature extraction, vocabul......Image search using the bag-of-words image representation is investigated further in this paper. This approach has shown promising results for large scale image collections making it relevant for Internet applications. The steps involved in the bag-of-words approach are feature extraction......, vocabulary building, and searching with a query image. It is important to keep the computational cost low through all steps. In this paper we focus on the efficiency of the technique. To do that we substantially reduce the dimensionality of the features by the use of PCA and addition of color. Building...... of the visual vocabulary is typically done using k-means. We investigate a clustering algorithm based on the leader follower principle (LF-clustering), in which the number of clusters is not fixed. The adaptive nature of LF-clustering is shown to improve the quality of the visual vocabulary using this...
Hasei, Tomohiro; Nakanishi, Haruka; Toda, Yumiko; Watanabe, Tetsushi
2012-08-31
3-Nitrobenzanthrone (3-NBA) is an extremely strong mutagen and carcinogen in rats inducing squamous cell carcinoma and adenocarcinoma. We developed a new sensitive analytical method, a two-dimensional HPLC system coupled with on-line reduction, to quantify non-fluorescent 3-NBA as fluorescent 3-aminobenzanthrone (3-ABA). The two-dimensional HPLC system consisted of reversed-phase HPLC and normal-phase HPLC, which were connected with a switch valve. 3-NBA was purified by reversed-phase HPLC and reduced to 3-ABA with a catalyst column, packed with alumina coated with platinum, in ethanol. An alcoholic solvent is necessary for reduction of 3-NBA, but 3-ABA is not fluorescent in the alcoholic solvent. Therefore, 3-ABA was separated from alcohol and impurities by normal-phase HPLC and detected with a fluorescence detector. Extracts from surface soil, airborne particles, classified airborne particles, and incinerator dust were applied to the two-dimensional HPLC system after clean-up with a silica gel column. 3-NBA, detected as 3-ABA, in the extracts was found as a single peak on the chromatograms without any interfering peaks. 3-NBA was detected in 4 incinerator dust samples (n=5). When classified airborne particles, that is, those 7.0 μm in size, were applied to the two-dimensional HPLC system after purified using a silica gel column, 3-NBA was detected in those particles with particle sizes NBA in airborne particles and the detection of 3-NBA in incinerator dust. Copyright © 2012 Elsevier B.V. All rights reserved.
Applications of the reduction method
International Nuclear Information System (INIS)
Zimmermann, W.
1987-01-01
A renoramalizable model of quantum field theory involving several independent coupling parameters, λ 0 , ..., λ n and a normalization mass K is considered. If the model involves massive particles a formulation of the renormalization group should be used in which the β-functions are independent of the masses. The aim of the reduction method is to reduce the model to a description in terms of a single coupling parameter. Although the reduction method does not work for the gauge couplings it leads to reasonable mass constraints if applied to the Yukawa and the Higgs couplings. The underlying idea is that - whatever the fundamental interaction if going to be - eventually there is only one coupling which determines all parameters of the standard model. However, one should be skeptical about numerical results in the standard model. For the standard model is only an effective theory, its β-functions are only approximate and change on their lowest order coefficients may have large effects on the reduction solutions
Construction of N=8 supergravity theories by dimensional reduction
International Nuclear Information System (INIS)
Boucher, W.
1985-01-01
In this paper I ask which N=8 supergravity theories in four dimensions can be obtained by dimensional reduction of the N=1 supergravity theory in eleven dimensions. Several years ago Scherk and Schwarz produced a particular class of N = 8 theories by giving a dimensional reduction scheme on the restricted class of coset spaces, G/H, with dim H=0 (and therefore dim G=7). I generalize their considerations by looking at arbitrary (seven-dimensional) coset spaces. Also, instead of giving a particular ansatz which happens to work, I set about the distinctly more difficult task of determining all ansatzes which produce N=8 theories. The basic ingredient of my dimensional reduction scheme is the demand that certain symmetries, including supersymmetry, be truncated consistently. I find the surprising result that the only N=8 theories obtainable within the contexts of my scheme are those theories already written down by Scherk and Schwarz. In particular dim H=0 and dim G=7. Independently of these considerations, I prove that any dimensional reduction scheme which consistently truncates supersymmetry must also be consistent with the equations of motion. I discuss Lorentz-invariant solutions of the theories of Scherk and Schwarz, pointing out that since the ansatz of Scherk and Schwarz consistently truncates supersymmetry, any solution of these theories is also a solution of the N=1 supergravity theory in eleven dimensions and, hence, in particular that there is a Freund-Rubin-type ansatz for these theories. However I demonstrate that for most gauge groups the ansatz must be trivial which implies that for these theories the cosmological constant of any Lorentz-invariant solution must be zero (classically). Finally, I make some comparisons with work by Manton on dimensional reduction. (orig.)
Perturbative QCD lagrangian at large distances and stochastic dimensionality reduction
International Nuclear Information System (INIS)
Shintani, M.
1986-10-01
We construct a Lagrangian for perturbative QCD at large distances within the covariant operator formalism which explains the color confinement of quarks and gluons while maintaining unitarity of the S-matrix. It is also shown that when interactions are switched off, the mechanism of stochastic dimensionality reduction is operative in the system due to exact super-Lorentz symmetries. (orig.)
TPSLVM: a dimensionality reduction algorithm based on thin plate splines.
Jiang, Xinwei; Gao, Junbin; Wang, Tianjiang; Shi, Daming
2014-10-01
Dimensionality reduction (DR) has been considered as one of the most significant tools for data analysis. One type of DR algorithms is based on latent variable models (LVM). LVM-based models can handle the preimage problem easily. In this paper we propose a new LVM-based DR model, named thin plate spline latent variable model (TPSLVM). Compared to the well-known Gaussian process latent variable model (GPLVM), our proposed TPSLVM is more powerful especially when the dimensionality of the latent space is low. Also, TPSLVM is robust to shift and rotation. This paper investigates two extensions of TPSLVM, i.e., the back-constrained TPSLVM (BC-TPSLVM) and TPSLVM with dynamics (TPSLVM-DM) as well as their combination BC-TPSLVM-DM. Experimental results show that TPSLVM and its extensions provide better data visualization and more efficient dimensionality reduction compared to PCA, GPLVM, ISOMAP, etc.
N-Dimensional LLL Reduction Algorithm with Pivoted Reflection
Directory of Open Access Journals (Sweden)
Zhongliang Deng
2018-01-01
Full Text Available The Lenstra-Lenstra-Lovász (LLL lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO communication systems and carrier phase positioning in global navigation satellite system (GNSS to solve the integer least squares (ILS problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL, expanding the Lovász condition in LLL algorithm to n-dimensional space in order to obtain a further reduced basis. We also introduce pivoted Householder reflection into the algorithm to optimize the reduction time. For an m-order positive definite matrix, analysis shows that the n-LLL reduction algorithm will converge within finite steps and always produce better results than the original LLL reduction algorithm with n > 2. The simulations clearly prove that n-LLL is better than the original LLL in reducing the condition number of an ill-conditioned input matrix with 39% improvement on average for typical cases, which can significantly reduce the searching space for solving ILS problem. The simulation results also show that the pivoted reflection has significantly declined the number of swaps in the algorithm by 57%, making n-LLL a more practical reduction algorithm.
Superfluid hydrodynamics of polytropic gases: dimensional reduction and sound velocity
International Nuclear Information System (INIS)
Bellomo, N; Mazzarella, G; Salasnich, L
2014-01-01
Motivated by the fact that two-component confined fermionic gases in Bardeen–Cooper–Schrieffer–Bose–Einstein condensate (BCS–BEC) crossover can be described through an hydrodynamical approach, we study these systems—both in the cigar-shaped configuration and in the disc-shaped one—by using a polytropic Lagrangian density. We start from the Popov Lagrangian density and obtain, after a dimensional reduction process, the equations that control the dynamics of such systems. By solving these equations we study the sound velocity as a function of the density by analyzing how the dimensionality affects this velocity. (paper)
International Nuclear Information System (INIS)
Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial
2016-01-01
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial
2016-09-01
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Energy Technology Data Exchange (ETDEWEB)
Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu
2016-09-15
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Gönen, Mehmet
2014-03-01
Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F 1 , and micro F 1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks.
Kantowski-Sachs multidimensional cosmological models and dynamical dimensional reduction
International Nuclear Information System (INIS)
Demianski, M.; Rome Univ.; Golda, Z.A.; Heller, M.; Szydlowski, M.
1988-01-01
Einstein's field equations are solved for a multidimensional spacetime (KS) x Tsup(m), where (KS) is a four-dimensional Kantowski-Sachs spacetime and Tsup(m) is an m-dimensional torus. Among all possible vacuum solutions there is a large class of spacetimes in which the macroscopic space expands and the microscopic space contracts to a finite volume. We also consider a non-vacuum case and we explicitly solve the field equations for the matter satisfying the Zel'dovich equation of state. In non-vacuum models, with matter satisfying an equation of state p = γρ, O ≤ γ < 1, at a sufficiently late stage of evolution the microspace always expands and the dynamical dimensional reduction does not occur. (author)
One-loop dimensional reduction of the linear σ model
International Nuclear Information System (INIS)
Malbouisson, A.P.C.; Silva-Neto, M.B.; Svaiter, N.F.
1997-05-01
We perform the dimensional reduction of the linear σ model at one-loop level. The effective of the reduced theory obtained from the integration over the nonzero Matsubara frequencies is exhibited. Thermal mass and coupling constant renormalization constants are given, as well as the thermal renormalization group which controls the dependence of the counterterms on the temperature. We also recover, for the reduced theory, the vacuum instability of the model for large N. (author)
Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models.
Directory of Open Access Journals (Sweden)
Ryan C Williamson
2016-12-01
Full Text Available Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction-shared dimensionality and percent shared variance-with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure.
Directory of Open Access Journals (Sweden)
S. Szopa
2005-01-01
Full Text Available The objective of this work was to develop and assess an automatic procedure to generate reduced chemical schemes for the atmospheric photooxidation of volatile organic carbon (VOC compounds. The procedure is based on (i the development of a tool for writing the fully explicit schemes for VOC oxidation (see companion paper Aumont et al., 2005, (ii the application of several commonly used reduction methods to the fully explicit scheme, and (iii the assessment of resulting errors based on direct comparison between the reduced and full schemes. The reference scheme included seventy emitted VOCs chosen to be representative of both anthropogenic and biogenic emissions, and their atmospheric degradation chemistry required more than two million reactions among 350000 species. Three methods were applied to reduce the size of the reference chemical scheme: (i use of operators, based on the redundancy of the reaction sequences involved in the VOC oxidation, (ii grouping of primary species having similar reactivities into surrogate species and (iii grouping of some secondary products into surrogate species. The number of species in the final reduced scheme is 147, this being small enough for practical inclusion in current three-dimensional models. Comparisons between the fully explicit and reduced schemes, carried out with a box model for several typical tropospheric conditions, showed that the reduced chemical scheme accurately predicts ozone concentrations and some other aspects of oxidant chemistry for both polluted and clean tropospheric conditions.
Some remarks on dimensional reduction of Gauge theories and model building
International Nuclear Information System (INIS)
Rudolph, G.; Karl-Marx-Universitaet, Leipzig; Volobujev, I.P.
1989-01-01
We study the group-theoretical aspect of dimensional reduction of pure gauge theories and propose a method of solving the constraint equations for scalar fields. We show that there are possibilities of model building which differ from those commonly used. In particular, we give examples in which the resulting potential is not of Higgs type. (orig.)
Object-based Dimensionality Reduction in Land Surface Phenology Classification
Directory of Open Access Journals (Sweden)
Brian E. Bunker
2016-11-01
Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.
Generalized Time-Limited Balanced Reduction Method
DEFF Research Database (Denmark)
Shaker, Hamid Reza; Shaker, Fatemeh
2013-01-01
In this paper, a new method for model reduction of bilinear systems is presented. The proposed technique is from the family of gramian-based model reduction methods. The method uses time-interval generalized gramians in the reduction procedure rather than the ordinary generalized gramians...... and in such a way it improves the accuracy of the approximation within the time-interval which the method is applied. The time-interval generalized gramians are the solutions to the generalized time-interval Lyapunov equations. The conditions for these equations to be solvable are derived and an algorithm...
A trace ratio maximization approach to multiple kernel-based dimensionality reduction.
Jiang, Wenhao; Chung, Fu-lai
2014-01-01
Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.
Applicabilities of ship emission reduction methods
Energy Technology Data Exchange (ETDEWEB)
Guleryuz, Adem [ARGEMAN Research Group, Marine Division (Turkey)], email: ademg@argeman.org; Kilic, Alper [Istanbul Technical University, Maritime Faculty, Marine Engineering Department (Turkey)], email: enviromarineacademic@yahoo.com
2011-07-01
Ships, with their high consumption of fossil fuels to power their engines, are significant air polluters. Emission reduction methods therefore need to be implemented and the aim of this paper is to assess the advantages and disadvantages of each emissions reduction method. Benefits of the different methods are compared, with their disadvantages and requirements, to determine the applicability of such solutions. The methods studied herein are direct water injection, humid air motor, sea water scrubbing, diesel particulate filter, selected catalytic reduction, design of engine components, exhaust gas recirculation and engine replacement. Results of the study showed that the usefulness of each emissions reduction method depends on the particular case and that an evaluation should be carried out for each ship. This study pointed out that methods to reduce ship emissions are available but that their applicability depends on each case.
Reduced order methods for modeling and computational reduction
Rozza, Gianluigi
2014-01-01
This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics. Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...
Water-Induced Dimensionality Reduction in Metal-Halide Perovskites
Turedi, Bekir
2018-03-30
Metal-halide perovskite materials are highly attractive materials for optoelectronic applications. However, the instability of perovskite materials caused by moisture and heat-induced degradation impairs future prospects of using these materials. Here we employ water to directly transform films of the three-dimensional (3D) perovskite CsPbBr3 to stable two-dimensional (2D) perovskite-related CsPb2Br5. A sequential dissolution-recrystallization process governs this water induced transformation under PbBr2 rich condition. We find that these post-synthesized 2D perovskite-related material films exhibit excellent stability against humidity and high photoluminescence quantum yield. We believe that our results provide a new synthetic method to generate stable 2D perovskite-related materials that could be applicable for light emitting device applications.
Congruent reduction and mode conversion in 4-dimensional plasmas
International Nuclear Information System (INIS)
Friedland, L.; Kaufman, A.N.
1987-04-01
Standard eikonal theory reduces, to N=1, the order of the system of equations underlying wave propagation in inhomogeneous plasmas. The condition for this remarkable reducibility is that only one eigenvalue of the unreduced NxN dispersion matrix D(k,x) vanishes at a time. If, however, two or more eigenvalues of D become simultaneously small, the geometric optics reduction scheme becomes singular. These regions are associated with linear mode conversion, and are described by higher order systems. A new reduction scheme based on congruent transformations of D is developed, and it is shown that, in ''degenerate'' plasma regions, a partial reduction of order is possible. The method comprises a constructive step-by-step procedure, which, in the most frequent (doubly) degenerate case, yields a second order system, describing the pairwise mode conversion problems, the solution of which in general geometry has been found recently
Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio
2015-12-01
This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.
Directory of Open Access Journals (Sweden)
Fubiao Feng
2017-03-01
Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.
Kusratmoko, Eko; Wibowo, Adi; Cholid, Sofyan; Pin, Tjiong Giok
2017-07-01
This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng' village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.
A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem
Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša
2014-01-01
Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...
Reactor power reduction system and method
International Nuclear Information System (INIS)
Bruno, S.J.; Dunn, S.A.; Raber, M.
1978-01-01
A method of operating a nuclear power reactor is disclosed which enables an accelerated power reduction of the reactor without completely shutting the reactor down. The method includes monitoring the incidents which, upon their occurrence, would require an accelerated power reduction in order to maintain the reactor in a safe operation mode; calculating the power reduction required on the occurrence of such an incident; determining a control rod insertion sequence for the normal operation of the reactor, said sequence being chosen to optimize reactor power capability; selecting the number of control rods necessary to respond to the accelerated power reduction demand, said selection being made according to a priority determined by said control rod insertion sequence; and inserting said selected control rods into the reactor core. 11 claims, 13 figures
Ray, S. Saha
2018-04-01
In this paper, the symmetry analysis and similarity reduction of the (2+1)-dimensional Bogoyavlensky-Konopelchenko (B-K) equation are investigated by means of the geometric approach of an invariance group, which is equivalent to the classical Lie symmetry method. Using the extended Harrison and Estabrook’s differential forms approach, the infinitesimal generators for (2+1)-dimensional B-K equation are obtained. Firstly, the vector field associated with the Lie group of transformation is derived. Then the symmetry reduction and the corresponding explicit exact solution of (2+1)-dimensional B-K equation is obtained.
Reduction formalism for dimensionally regulated one-loop N-point integrals
International Nuclear Information System (INIS)
Binoth, T.; Guillet, J.Ph.; Heinrich, G.
2000-01-01
We consider one-loop scalar and tensor integrals with an arbitrary number of external legs relevant for multi-parton processes in massless theories. We present a procedure to reduce N-point scalar functions with generic 4-dimensional external momenta to box integrals in (4-2ε) dimensions. We derive a formula valid for arbitrary N and give an explicit expression for N=6. Further a tensor reduction method for N-point tensor integrals is presented. We prove that generically higher dimensional integrals contribute only to order ε for N≥5. The tensor reduction can be solved iteratively such that any tensor integral is expressible in terms of scalar integrals. Explicit formulas are given up to N=6
Ficuciello, Fanny; Siciliano, Bruno
2016-07-01
A question that often arises, among researchers working on artificial hands and robotic manipulation, concerns the real meaning of synergies. Namely, are they a realistic representation of the central nervous system control of manipulation activities at different levels and of the sensory-motor manipulation apparatus of the human being, or do they constitute just a theoretical framework exploiting analytical methods to simplify the representation of grasping and manipulation activities? Apparently, this is not a simple question to answer and, in this regard, many minds from the field of neuroscience and robotics are addressing the issue [1]. The interest of robotics is definitely oriented towards the adoption of synergies to tackle the control problem of devices with high number of degrees of freedom (DoFs) which are required to achieve motor and learning skills comparable to those of humans. The synergy concept is useful for innovative underactuated design of anthropomorphic hands [2], while the resulting dimensionality reduction simplifies the control of biomedical devices such as myoelectric hand prostheses [3]. Synergies might also be useful in conjunction with the learning process [4]. This aspect is less explored since few works on synergy-based learning have been realized in robotics. In learning new tasks through trial-and-error, physical interaction is important. On the other hand, advanced mechanical designs such as tendon-driven actuation, underactuated compliant mechanisms and hyper-redundant/continuum robots might exhibit enhanced capabilities of adapting to changing environments and learning from exploration. In particular, high DoFs and compliance increase the complexity of modelling and control of these devices. An analytical approach to manipulation planning requires a precise model of the object, an accurate description of the task, and an evaluation of the object affordance, which all make the process rather time consuming. The integration of
Directory of Open Access Journals (Sweden)
Sathya Kumar Devireddy
2014-01-01
Full Text Available Objective: The aim was to assess the accuracy of three-dimensional anatomical reductions achieved by open method of treatment in cases of displaced unilateral mandibular subcondylar fractures using preoperative (pre op and postoperative (post op computed tomography (CT scans. Materials and Methods: In this prospective study, 10 patients with unilateral sub condylar fractures confirmed by an orthopantomogram were included. A pre op and post op CT after 1 week of surgical procedure was taken in axial, coronal and sagittal plane along with three-dimensional reconstruction. Standard anatomical parameters, which undergo changes due to fractures of the mandibular condyle were measured in pre and post op CT scans in three planes and statistically analysed for the accuracy of the reduction comparing the following variables: (a Pre op fractured and nonfractured side (b post op fractured and nonfractured side (c pre op fractured and post op fractured side. P < 0.05 was considered as significant. Results: Three-dimensional anatomical reduction was possible in 9 out of 10 cases (90%. The statistical analysis of each parameter in three variables revealed (P < 0.05 that there was a gross change in the dimensions of the parameters obtained in pre op fractured and nonfractured side. When these parameters were assessed in post op CT for the three variables there was no statistical difference between the post op fractured side and non fractured side. The same parameters were analysed for the three variables in pre op fractured and post op fractured side and found significant statistical difference suggesting a considerable change in the dimensions of the fractured side post operatively. Conclusion: The statistical and clinical results in our study emphasised that it is possible to fix the condyle in three-dimensional anatomical positions with open method of treatment and avoid post op degenerative joint changes. CT is the ideal imaging tool and should be used on
Dimension reduction methods for microarray data: a review
Directory of Open Access Journals (Sweden)
Rabia Aziz
2017-03-01
Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.
One-dimensional reduction of viscous jets. I. Theory
Pitrou, Cyril
2018-04-01
We build a general formalism to describe thin viscous jets as one-dimensional objects with an internal structure. We present in full generality the steps needed to describe the viscous jets around their central line, and we argue that the Taylor expansion of all fields around that line is conveniently expressed in terms of symmetric trace-free tensors living in the two dimensions of the fiber sections. We recover the standard results of axisymmetric jets and we report the first and second corrections to the lowest order description, also allowing for a rotational component around the axis of symmetry. When applied to generally curved fibers, the lowest order description corresponds to a viscous string model whose sections are circular. However, when including the first corrections, we find that curved jets generically develop elliptic sections. Several subtle effects imply that the first corrections cannot be described by a rod model since it amounts to selectively discard some corrections. However, in a fast rotating frame, we find that the dominant effects induced by inertial and Coriolis forces should be correctly described by rod models. For completeness, we also recover the constitutive relations for forces and torques in rod models and exhibit a missing term in the lowest order expression of viscous torque. Given that our method is based on tensors, the complexity of all computations has been beaten down by using an appropriate tensor algebra package such as xAct, allowing us to obtain a one-dimensional description of curved viscous jets with all the first order corrections consistently included. Finally, we find a description for straight fibers with elliptic sections as a special case of these results, and recover that ellipticity is dynamically damped by surface tension. An application to toroidal viscous fibers is presented in the companion paper [Pitrou, Phys. Rev. E 97, 043116 (2018), 10.1103/PhysRevE.97.043116].
Active sound reduction system and method
2016-01-01
The present invention refers to an active sound reduction system and method for attenuation of sound emitted by a primary sound source, especially for attenuation of snoring sounds emitted by a human being. This system comprises a primary sound source, at least one speaker as a secondary sound
Variance Reduction Techniques in Monte Carlo Methods
Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.
2010-01-01
Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the
Dimensional reduction in field theory and hidden symmetries in extended supergravity
International Nuclear Information System (INIS)
Kremmer, E.
1985-01-01
Dimensional reduction in field theories is discussed both in theories which do not include gravity and in gravity theories. In particular, 11-dimensional supergravity and its reduction to 4 dimensions is considered. Hidden symmetries of supergravity with N=8 in 4 dimensions, global E 7 and local SU(8)-invariances in particular are detected. The hidden symmmetries permit to interpret geometrically the scalar fields
Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K
2015-01-01
This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.
Reductive methods for isotopic labeling of antibiotics
International Nuclear Information System (INIS)
Champney, W.S.
1989-01-01
Methods for the reductive methylation of the amino groups of eight different antibiotics using 3 HCOH or H 14 COH are presented. The reductive labeling of an additional seven antibiotics by NaB 3 H 4 is also described. The specific activity of the methyl-labeled drugs was determined by a phosphocellulose paper binding assay. Two quantitative assays for these compounds based on the reactivity of the antibiotic amino groups with fluorescamine and of the aldehyde and ketone groups with 2,4-dinitrophenylhydrazine are also presented. Data on the cellular uptake and ribosome binding of these labeled compounds are also presented
Water-Induced Dimensionality Reduction in Metal-Halide Perovskites
Turedi, Bekir; Lee, Kwangjae; Dursun, Ibrahim; Alamer, Badriah Jaber; Wu, Zhennan; Alarousu, Erkki; Mohammed, Omar F.; Cho, Namchul; Bakr, Osman
2018-01-01
. Here we employ water to directly transform films of the three-dimensional (3D) perovskite CsPbBr3 to stable two-dimensional (2D) perovskite-related CsPb2Br5. A sequential dissolution-recrystallization process governs this water induced transformation
Iterative methods for dose reduction and image enhancement in tomography
Miao, Jianwei; Fahimian, Benjamin Pooya
2012-09-18
A system and method for creating a three dimensional cross sectional image of an object by the reconstruction of its projections that have been iteratively refined through modification in object space and Fourier space is disclosed. The invention provides systems and methods for use with any tomographic imaging system that reconstructs an object from its projections. In one embodiment, the invention presents a method to eliminate interpolations present in conventional tomography. The method has been experimentally shown to provide higher resolution and improved image quality parameters over existing approaches. A primary benefit of the method is radiation dose reduction since the invention can produce an image of a desired quality with a fewer number projections than seen with conventional methods.
TSOM Method for Nanoelectronics Dimensional Metrology
International Nuclear Information System (INIS)
Attota, Ravikiran
2011-01-01
Through-focus scanning optical microscopy (TSOM) is a relatively new method that transforms conventional optical microscopes into truly three-dimensional metrology tools for nanoscale to microscale dimensional analysis. TSOM achieves this by acquiring and analyzing a set of optical images collected at various focus positions going through focus (from above-focus to under-focus). The measurement resolution is comparable to what is possible with typical light scatterometry, scanning electron microscopy (SEM) and atomic force microscopy (AFM). TSOM method is able to identify nanometer scale difference, type of the difference and magnitude of the difference between two nano/micro scale targets using a conventional optical microscope with visible wavelength illumination. Numerous industries could benefit from the TSOM method--such as the semiconductor industry, MEMS, NEMS, biotechnology, nanomanufacturing, data storage, and photonics. The method is relatively simple and inexpensive, has a high throughput, provides nanoscale sensitivity for 3D measurements and could enable significant savings and yield improvements in nanometrology and nanomanufacturing. Potential applications are demonstrated using experiments and simulations.
Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs
Energy Technology Data Exchange (ETDEWEB)
Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)
2016-07-15
In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.
Three-dimensional image signals: processing methods
Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru
2010-11-01
Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.
Directory of Open Access Journals (Sweden)
Dai Hongying
2013-01-01
Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.
Gao, Yang; Wang, Xuesong; Cheng, Yuhu; Wang, Z Jane
2015-08-01
To take full advantage of hyperspectral information, to avoid data redundancy and to address the curse of dimensionality concern, dimensionality reduction (DR) becomes particularly important to analyze hyperspectral data. Exploring the tensor characteristic of hyperspectral data, a DR algorithm based on class-aware tensor neighborhood graph and patch alignment is proposed here. First, hyperspectral data are represented in the tensor form through a window field to keep the spatial information of each pixel. Second, using a tensor distance criterion, a class-aware tensor neighborhood graph containing discriminating information is obtained. In the third step, employing the patch alignment framework extended to the tensor space, we can obtain global optimal spectral-spatial information. Finally, the solution of the tensor subspace is calculated using an iterative method and low-dimensional projection matrixes for hyperspectral data are obtained accordingly. The proposed method effectively explores the spectral and spatial information in hyperspectral data simultaneously. Experimental results on 3 real hyperspectral datasets show that, compared with some popular vector- and tensor-based DR algorithms, the proposed method can yield better performance with less tensor training samples required.
A Novel Four-Dimensional Energy-Saving and Emission-Reduction System and Its Linear Feedback Control
Directory of Open Access Journals (Sweden)
Minggang Wang
2012-01-01
Full Text Available This paper reports a new four-dimensional energy-saving and emission-reduction chaotic system. The system is obtained in accordance with the complicated relationship between energy saving and emission reduction, carbon emission, economic growth, and new energy development. The dynamics behavior of the system will be analyzed by means of Lyapunov exponents and equilibrium points. Linear feedback control methods are used to suppress chaos to unstable equilibrium. Numerical simulations are presented to show these results.
QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION.
Fan, Jianqing; Ke, Zheng Tracy; Liu, Han; Xia, Lucy
We propose a novel Rayleigh quotient based sparse quadratic dimension reduction method-named QUADRO (Quadratic Dimension Reduction via Rayleigh Optimization)-for analyzing high-dimensional data. Unlike in the linear setting where Rayleigh quotient optimization coincides with classification, these two problems are very different under nonlinear settings. In this paper, we clarify this difference and show that Rayleigh quotient optimization may be of independent scientific interests. One major challenge of Rayleigh quotient optimization is that the variance of quadratic statistics involves all fourth cross-moments of predictors, which are infeasible to compute for high-dimensional applications and may accumulate too many stochastic errors. This issue is resolved by considering a family of elliptical models. Moreover, for heavy-tail distributions, robust estimates of mean vectors and covariance matrices are employed to guarantee uniform convergence in estimating non-polynomially many parameters, even though only the fourth moments are assumed. Methodologically, QUADRO is based on elliptical models which allow us to formulate the Rayleigh quotient maximization as a convex optimization problem. Computationally, we propose an efficient linearized augmented Lagrangian method to solve the constrained optimization problem. Theoretically, we provide explicit rates of convergence in terms of Rayleigh quotient under both Gaussian and general elliptical models. Thorough numerical results on both synthetic and real datasets are also provided to back up our theoretical results.
On symmetry reduction and exact solutions of the linear one-dimensional Schroedinger equation
International Nuclear Information System (INIS)
Barannik, L.L.
1996-01-01
Symmetry reduction of the Schroedinger equation with potential is carried out on subalgebras of the Lie algebra which is the direct sum of the special Galilei algebra and one-dimensional algebra. Some new exact solutions are obtained
Symmetries, integrals, and three-dimensional reductions of Plebanski's second heavenly equation
International Nuclear Information System (INIS)
Neyzi, F.; Sheftel, M. B.; Yazici, D.
2007-01-01
We study symmetries and conservation laws for Plebanski's second heavenly equation written as a first-order nonlinear evolutionary system which admits a multi-Hamiltonian structure. We construct an optimal system of one-dimensional subalgebras and all inequivalent three-dimensional symmetry reductions of the original four-dimensional system. We consider these two-component evolutionary systems in three dimensions as natural candidates for integrable systems
Coset Space Dimensional Reduction approach to the Standard Model
International Nuclear Information System (INIS)
Farakos, K.; Kapetanakis, D.; Koutsoumbas, G.; Zoupanos, G.
1988-01-01
We present a unified theory in ten dimensions based on the gauge group E 8 , which is dimensionally reduced to the Standard Mode SU 3c xSU 2 -LxU 1 , which breaks further spontaneously to SU 3L xU 1em . The model gives similar predictions for sin 2 θ w and proton decay as the minimal SU 5 G.U.T., while a natural choice of the coset space radii predicts light Higgs masses a la Coleman-Weinberg
Rhythmic dynamics and synchronization via dimensionality reduction: application to human gait.
Directory of Open Access Journals (Sweden)
Jie Zhang
Full Text Available Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system.
One-dimensional reduction of viscous jets. II. Applications
Pitrou, Cyril
2018-04-01
In a companion paper [Phys. Rev. E 97, 043115 (2018), 10.1103/PhysRevE.97.043115], a formalism allowing to describe viscous fibers as one-dimensional objects was developed. We apply it to the special case of a viscous fluid torus. This allows to highlight the differences with the basic viscous string model and with its viscous rod model extension. In particular, an elliptic deformation of the torus section appears because of surface tension effects, and this cannot be described by viscous string nor viscous rod models. Furthermore, we study the Rayleigh-Plateau instability for periodic deformations around the perfect torus, and we show that the instability is not sufficient to lead to the torus breakup in several droplets before it collapses to a single spherical drop. Conversely, a rotating torus is dynamically attracted toward a stationary solution, around which the instability can develop freely and split the torus in multiple droplets.
Center-vortex dominance after dimensional reduction of SU(2) lattice gauge theory
Gattnar, J.; Langfeld, K.; Schafke, A.; Reinhardt, H.
2000-01-01
The high-temperature phase of SU(2) Yang-Mills theory is addressed by means of dimensional reduction with a special emphasis on the properties of center vortices. For this purpose, the vortex vacuum which arises from center projection is studied in pure 3-dimensional Yang-Mills theory as well as in the 3-dimensional adjoint Higgs model which describes the high temperature phase of the 4-dimensional SU(2) gauge theory. We find center-dominance within the numerical accuracy of 10%.
Energy Technology Data Exchange (ETDEWEB)
Marquard, P.; Mihaila, L.; Steinhauser, M. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Theoretische Teilchenphysik; Piclum, J.H. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Theoretische Teilchenphysik]|[Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik
2007-02-15
We compute the relation between the pole quark mass and the minimally subtracted quark mass in the framework of QCD applying dimensional reduction as a regularization scheme. Special emphasis is put on the evanescent couplings and the renormalization of the {epsilon}-scalar mass. As a by-product we obtain the three-loop on-shell renormalization constants Z{sub m}{sup OS} and Z{sub 2}{sup OS} in dimensional regularization and thus provide the first independent check of the analytical results computed several years ago. (orig.)
Sharpening the weak gravity conjecture with dimensional reduction
International Nuclear Information System (INIS)
Heidenreich, Ben; Reece, Matthew; Rudelius, Tom
2016-01-01
We investigate the behavior of the Weak Gravity Conjecture (WGC) under toroidal compactification and RG flows, finding evidence that WGC bounds for single photons become weaker in the infrared. By contrast, we find that a photon satisfying the WGC will not necessarily satisfy it after toroidal compactification when black holes charged under the Kaluza-Klein photons are considered. Doing so either requires an infinite number of states of different charges to satisfy the WGC in the original theory or a restriction on allowed compactification radii. These subtleties suggest that if the Weak Gravity Conjecture is true, we must seek a stronger form of the conjecture that is robust under compactification. We propose a “Lattice Weak Gravity Conjecture” that meets this requirement: a superextremal particle should exist for every charge in the charge lattice. The perturbative heterotic string satisfies this conjecture. We also use compactification to explore the extent to which the WGC applies to axions. We argue that gravitational instanton solutions in theories of axions coupled to dilaton-like fields are analogous to extremal black holes, motivating a WGC for axions. This is further supported by a match between the instanton action and that of wrapped black branes in a higher-dimensional UV completion.
Dimensionality Reduction in Big Data with Nonnegative Matrix Factorization
2017-06-20
Multiplicative Update Rule(MUR), Projected Gradient Meth- ods (PrG), Block Principal Pivoting method(BlP), Fast Active-set-like method(AcS), Fast...16], one of the robust ensemble meth- ods , to classify the testing datasets. The proposed algorithm outperforms the other algorithms and PCA over all
Yuan, Fang; Wang, Guangyi; Wang, Xiaowei
2017-03-01
In this paper, smooth curve models of meminductor and memcapacitor are designed, which are generalized from a memristor. Based on these models, a new five-dimensional chaotic oscillator that contains a meminductor and memcapacitor is proposed. By dimensionality reducing, this five-dimensional system can be transformed into a three-dimensional system. The main work of this paper is to give the comparisons between the five-dimensional system and its dimensionality reduction model. To investigate dynamics behaviors of the two systems, equilibrium points and stabilities are analyzed. And the bifurcation diagrams and Lyapunov exponent spectrums are used to explore their properties. In addition, digital signal processing technologies are used to realize this chaotic oscillator, and chaotic sequences are generated by the experimental device, which can be used in encryption applications.
Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A
2007-01-01
The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.
Joint statistics of strongly correlated neurons via dimensionality reduction
International Nuclear Information System (INIS)
Deniz, Taşkın; Rotter, Stefan
2017-01-01
The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input. (paper)
Assessment of metal artifact reduction methods in pelvic CT
Energy Technology Data Exchange (ETDEWEB)
Abdoli, Mehrsima [Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX (Netherlands); Mehranian, Abolfazl [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Ailianou, Angeliki; Becker, Minerva [Division of Radiology, Geneva University Hospital, Geneva CH-1211 (Switzerland); Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Geneva Neuroscience Center, Geneva University, Geneva CH-1205 (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen 9700 RB (Netherlands)
2016-04-15
Purpose: Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses. Methods: Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence). Results: Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality. Conclusions: Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.
Preliminary comparison of different reduction methods of graphene
Indian Academy of Sciences (India)
The reduction of graphene oxide (GO) is a promising route to bulk produce graphene-based sheets. Different reduction processes result in reduced graphene oxide (RGO) with different properties. In this paper three reduction methods, chemical, thermal and electrochemical reduction, were compared on three aspects ...
Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane
2013-01-01
We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR's constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to ide...
Anisotropic inflation in a 5D standing wave braneworld and effective dimensional reduction
Energy Technology Data Exchange (ETDEWEB)
Gogberashvili, Merab, E-mail: gogber@gmail.com [Andronikashvili Institute of Physics, 6 Tamarashvili St., Tbilisi 0177, Georgia (United States); Javakhishvili State University, 3 Chavchavadze Ave., Tbilisi 0128, Georgia (United States); Herrera-Aguilar, Alfredo, E-mail: aha@fis.unam.mx [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Apdo. Postal 48-3, 62251 Cuernavaca, Morelos (Mexico); Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Edificio C-3, Ciudad Universitaria, CP 58040, Morelia, Michoacán (Mexico); Malagón-Morejón, Dagoberto, E-mail: malagon@fis.unam.mx [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Apdo. Postal 48-3, 62251 Cuernavaca, Morelos (Mexico); Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Edificio C-3, Ciudad Universitaria, CP 58040, Morelia, Michoacán (Mexico); Mora-Luna, Refugio Rigel, E-mail: rigel@ifm.umich.mx [Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Edificio C-3, Ciudad Universitaria, CP 58040, Morelia, Michoacán (Mexico)
2013-10-01
We investigate a cosmological solution within the framework of a 5D standing wave braneworld model generated by gravity coupled to a massless scalar phantom-like field. By obtaining a full exact solution of the model we found a novel dynamical mechanism in which the anisotropic nature of the primordial metric gives rise to (i) inflation along certain spatial dimensions, and (ii) deflation and a shrinking reduction of the number of spatial dimensions along other directions. This dynamical mechanism can be relevant for dimensional reduction in string and other higher-dimensional theories in the attempt of getting a 4D isotropic expanding space–time.
Anisotropic inflation in a 5D standing wave braneworld and effective dimensional reduction
International Nuclear Information System (INIS)
Gogberashvili, Merab; Herrera-Aguilar, Alfredo; Malagón-Morejón, Dagoberto; Mora-Luna, Refugio Rigel
2013-01-01
We investigate a cosmological solution within the framework of a 5D standing wave braneworld model generated by gravity coupled to a massless scalar phantom-like field. By obtaining a full exact solution of the model we found a novel dynamical mechanism in which the anisotropic nature of the primordial metric gives rise to (i) inflation along certain spatial dimensions, and (ii) deflation and a shrinking reduction of the number of spatial dimensions along other directions. This dynamical mechanism can be relevant for dimensional reduction in string and other higher-dimensional theories in the attempt of getting a 4D isotropic expanding space–time
International Nuclear Information System (INIS)
Del Frate, F.; Iapaolo, M.; Casadio, S.; Godin-Beekmann, S.; Petitdidier, M.
2005-01-01
Dimensionality reduction can be of crucial importance in the application of inversion schemes to atmospheric remote sensing data. In this study the problem of dimensionality reduction in the retrieval of ozone concentration profiles from the radiance measurements provided by the instrument Global Ozone Monitoring Experiment (GOME) on board of ESA satellite ERS-2 is considered. By means of radiative transfer modelling, neural networks and pruning algorithms, a complete procedure has been designed to extract the GOME spectral ranges most crucial for the inversion. The quality of the resulting retrieval algorithm has been evaluated by comparing its performance to that yielded by other schemes and co-located profiles obtained with lidar measurements
Supersymmetry and the Parisi-Sourlas dimensional reduction: A rigorous proof
International Nuclear Information System (INIS)
Klein, A.; Landau, L.J.; Perez, J.F.
1984-01-01
Functional integrals that are formally related to the average correlation functions of a classical field theory in the presence of random external sources are given a rigorous meaning. Their dimensional reduction to the Schwinger functions of the corresponding quantum field theory in two fewer dimensions is proven. This is done by reexpressing those functional integrals as expectations of a supersymmetric field theory. The Parisi-Sourlas dimensional reduction of a supersymmetric field theory to a usual quantum field theory in two fewer dimensions is proven. (orig.)
Three-dimensional display techniques: description and critique of methods
International Nuclear Information System (INIS)
Budinger, T.F.
1982-01-01
The recent advances in non invasive medical imaging of 3 dimensional spatial distribution of radionuclides, X-ray attenuation coefficients, and nuclear magnetic resonance parameters necessitate development of a general method for displaying these data. The objective of this paper is to give a systematic description and comparison of known methods for displaying three dimensional data. The discussion of display methods is divided into two major categories: 1) computer-graphics methods which use a two dimensional display screen; and 2) optical methods (such as holography, stereopsis and vari-focal systems)
Utility of three-dimensional method for diagnosing meniscal lesions
International Nuclear Information System (INIS)
Ohshima, Suguru; Nomura, Kazutoshi; Hirano, Mako; Hashimoto, Noburo; Fukumoto, Tetsuya; Katahira, Kazuhiro
1998-01-01
MRI of the knee is a useful method for diagnosing meniscal tears. Although the spin echo method is usually used for diagnosing meniscal tears, we examined the utility of thin slice scan with the three-dimensional method. We reviewed 70 menisci in which arthroscopic findings were confirmed. In this series, sensitivity was 90.9% for medial meniscal injuries and 68.8% for lateral meniscal injuries. There were 3 meniscal tears in which we could not detect tears on preoperative MRI. We could find tears in two of these cases when re-evaluated using the same MRI. In conclusion, we can get the same diagnostic rate with the three-dimensional method compared with the spin echo method. Scan time of the three-dimensional method is 3 minutes, on the other hand that of spin echo method in 17 minutes. This slice scan with three-dimensional method is useful for screening meniscal injuries before arthroscopy. (author)
The N=4 supersymmetric E8 gauge theory and coset space dimensional reduction
International Nuclear Information System (INIS)
Olive, D.; West, P.
1983-01-01
Reasons are given to suggest that the N=4 supersymmetric E 8 gauge theory be considered as a serious candidate for a physical theory. The symmetries of this theory are broken by a scheme based on coset space dimensional reduction. The resulting theory possesses four conventional generations of low-mass fermions together with their mirror particles. (orig.)
Ultraviolet finiteness of N = 8 supergravity, spontaneously broken by dimensional reduction
International Nuclear Information System (INIS)
Sezgin, E.; Nieuwenhuizen, P. van
1982-06-01
The one-loop corrections to scalar-scalar scattering in N = 8 supergravity with 4 masses from dimensional reduction, are finite. We discuss various mechanisms that cancel the cosmological constant and infra-red divergences due to finite but non-vanishing tadpoles. (author)
Dimensional reduction of 10d heterotic string effective lagrangian with higher derivative terms
International Nuclear Information System (INIS)
Lalak, Z.; Pawelczyk, J.
1989-11-01
Dimensional reduction of the 10d Supergravity-Yang-Mills theories containing up to four derivatives is described. Unexpected nondiagonal corrections to 4d gauge kinetic function and negative contributions to scalar potential are found. We analyzed the general structure of the resulting lagrangian and discuss the possible phenomenological consequences. (author)
Dimensional reduction in Bose-Einstein-condensed alkali-metal vapors
International Nuclear Information System (INIS)
Salasnich, L.; Reatto, L.; Parola, A.
2004-01-01
We investigate the effects of dimensional reduction in atomic Bose-Einstein condensates (BECs) induced by a strong harmonic confinement in the cylindric radial direction or in the cylindric axial direction. The former case corresponds to a transition from three dimensions (3D) to 1D in cigar-shaped BECs, while the latter case corresponds to a transition from 3D to 2D in disk-shaped BECs. We analyze the first sound velocity in axially homogeneous cigar-shaped BECs and in radially homogeneous disk-shaped BECs. We consider also the dimensional reduction in a BEC confined by a harmonic potential both in the radial direction and in the axial direction. By using a variational approach, we calculate monopole and quadrupole collective oscillations of the BEC. We find that the frequencies of these collective oscillations are related to the dimensionality and to the repulsive or attractive interatomic interaction
van Manen's method and reduction in a phenomenological hermeneutic study.
Heinonen, Kristiina
2015-03-01
To describe van Manen's method and concept of reduction in a study that used a phenomenological hermeneutic approach. Nurse researchers have used van Manen's method in different ways. Participants' lifeworlds are described in depth, but descriptions of reduction have been brief. The literature and knowledge review and manual search of research articles. Databases Web Science, PubMed, CINAHL and PsycINFO, without applying a time period, to identify uses of van Manen's method. This paper shows how van Manen's method has been used in nursing research and gives some examples of van Manen's reduction. Reduction enables us to conduct in-depth phenomenological hermeneutic research and understand people's lifeworlds. As there are many variations in adapting reduction, it is complex and confusing. This paper contributes to the discussion of phenomenology, hermeneutic study and reduction. It opens up reduction as a method for researchers to exploit.
Taghanaki, Saeid Asgari; Kawahara, Jeremy; Miles, Brandon; Hamarneh, Ghassan
2017-07-01
Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. Optimizing traditional auto-encoders works well only if the initial weights are close to a proper solution. They are also trained to only reduce the mean squared reconstruction error (MRE) between the encoder inputs and the decoder outputs, but do not address the classification error. The goal of the current work is to test the hypothesis that extending traditional auto-encoders (which only minimize reconstruction error) to multi-objective optimization for finding Pareto-optimal solutions provides more discriminative features that will improve classification performance when compared to single-objective and other multi-objective approaches (i.e. scalarized and sequential). In this paper, we introduce a novel multi-objective optimization of deep auto-encoder networks, in which the auto-encoder optimizes two objectives: MRE and mean classification error (MCE) for Pareto-optimal solutions, rather than just MRE. These two objectives are optimized simultaneously by a non-dominated sorting genetic algorithm. We tested our method on 949 X-ray mammograms categorized into 12 classes. The results show that the features identified by the proposed algorithm allow a classification accuracy of up to 98.45%, demonstrating favourable accuracy over the results of state-of-the-art methods reported in the literature. We conclude that adding the classification objective to the traditional auto-encoder objective and optimizing for finding Pareto-optimal solutions, using evolutionary multi-objective optimization, results in producing more discriminative features. Copyright © 2017 Elsevier B.V. All rights reserved.
Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation
Energy Technology Data Exchange (ETDEWEB)
Akhbardeh, Alireza; Jacobs, Michael A. [Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States) and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States)
2012-04-15
Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), and diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment
Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation
International Nuclear Information System (INIS)
Akhbardeh, Alireza; Jacobs, Michael A.
2012-01-01
Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), and diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B 1 inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both
New method for solving three-dimensional Schroedinger equation
International Nuclear Information System (INIS)
Melezhik, V.S.
1990-01-01
The method derived recently for solving a multidimensional scattering problem is applied to a three-dimensional Schroedinger equation. As compared with direct three-dimensional calculations of finite elements and finite differences, this approach gives sufficiently accurate upper and lower approximations to the helium-atom binding energy, which demonstrates its efficiency. 15 refs.; 1 fig.; 2 tabs
M-Isomap: Orthogonal Constrained Marginal Isomap for Nonlinear Dimensionality Reduction.
Zhang, Zhao; Chow, Tommy W S; Zhao, Mingbo
2013-02-01
Isomap is a well-known nonlinear dimensionality reduction (DR) method, aiming at preserving geodesic distances of all similarity pairs for delivering highly nonlinear manifolds. Isomap is efficient in visualizing synthetic data sets, but it usually delivers unsatisfactory results in benchmark cases. This paper incorporates the pairwise constraints into Isomap and proposes a marginal Isomap (M-Isomap) for manifold learning. The pairwise Cannot-Link and Must-Link constraints are used to specify the types of neighborhoods. M-Isomap computes the shortest path distances over constrained neighborhood graphs and guides the nonlinear DR through separating the interclass neighbors. As a result, large margins between both interand intraclass clusters are delivered and enhanced compactness of intracluster points is achieved at the same time. The validity of M-Isomap is examined by extensive simulations over synthetic, University of California, Irvine, and benchmark real Olivetti Research Library, YALE, and CMU Pose, Illumination, and Expression databases. The data visualization and clustering power of M-Isomap are compared with those of six related DR methods. The visualization results show that M-Isomap is able to deliver more separate clusters. Clustering evaluations also demonstrate that M-Isomap delivers comparable or even better results than some state-of-the-art DR algorithms.
Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang
2017-12-01
Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.
Uranium manufacturing process employing the electrolytic reduction method
International Nuclear Information System (INIS)
Oda, Yoshio; Kazuhare, Manabu; Morimoto, Takeshi.
1986-01-01
The present invention related to a uranium manufacturing process that employs the electrolytic reduction method, but particularly to a uranium manufacturing process that employs an electrolytic reduction method requiring low voltage. The process, in which uranium is obtained by means of the electrolytic method and with uranyl acid as the raw material, is prior art
Nicolini, Paolo; Frezzato, Diego
2013-06-21
Simplification of chemical kinetics description through dimensional reduction is particularly important to achieve an accurate numerical treatment of complex reacting systems, especially when stiff kinetics are considered and a comprehensive picture of the evolving system is required. To this aim several tools have been proposed in the past decades, such as sensitivity analysis, lumping approaches, and exploitation of time scales separation. In addition, there are methods based on the existence of the so-called slow manifolds, which are hyper-surfaces of lower dimension than the one of the whole phase-space and in whose neighborhood the slow evolution occurs after an initial fast transient. On the other hand, all tools contain to some extent a degree of subjectivity which seems to be irremovable. With reference to macroscopic and spatially homogeneous reacting systems under isothermal conditions, in this work we shall adopt a phenomenological approach to let self-emerge the dimensional reduction from the mathematical structure of the evolution law. By transforming the original system of polynomial differential equations, which describes the chemical evolution, into a universal quadratic format, and making a direct inspection of the high-order time-derivatives of the new dynamic variables, we then formulate a conjecture which leads to the concept of an "attractiveness" region in the phase-space where a well-defined state-dependent rate function ω has the simple evolution ω[over dot]=-ω(2) along any trajectory up to the stationary state. This constitutes, by itself, a drastic dimensional reduction from a system of N-dimensional equations (being N the number of chemical species) to a one-dimensional and universal evolution law for such a characteristic rate. Step-by-step numerical inspections on model kinetic schemes are presented. In the companion paper [P. Nicolini and D. Frezzato, J. Chem. Phys. 138, 234102 (2013)] this outcome will be naturally related to the
Restoration of dimensional reduction in the random-field Ising model at five dimensions
Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas
2017-04-01
The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D equality at all studied dimensions.
Similarity measurement method of high-dimensional data based on normalized net lattice subspace
Institute of Scientific and Technical Information of China (English)
Li Wenfa; Wang Gongming; Li Ke; Huang Su
2017-01-01
The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.
Direct Linear Transformation Method for Three-Dimensional Cinematography
Shapiro, Robert
1978-01-01
The ability of Direct Linear Transformation Method for three-dimensional cinematography to locate points in space was shown to meet the accuracy requirements associated with research on human movement. (JD)
Iterative Two- and One-Dimensional Methods for Three-Dimensional Neutron Diffusion Calculations
International Nuclear Information System (INIS)
Lee, Hyun Chul; Lee, Deokjung; Downar, Thomas J.
2005-01-01
Two methods are proposed for solving the three-dimensional neutron diffusion equation by iterating between solutions of the two-dimensional (2-D) radial and one-dimensional (1-D) axial solutions. In the first method, the 2-D/1-D equations are coupled using a current correction factor (CCF) with the average fluxes of the lower and upper planes and the axial net currents at the plane interfaces. In the second method, an analytic expression for the axial net currents at the interface of the planes is used for planar coupling. A comparison of the new methods is made with two previously proposed methods, which use interface net currents and partial currents for planar coupling. A Fourier convergence analysis of the four methods was performed, and results indicate that the two new methods have at least three advantages over the previous methods. First, the new methods are unconditionally stable, whereas the net current method diverges for small axial mesh size. Second, the new methods provide better convergence performance than the other methods in the range of practical mesh sizes. Third, the spectral radii of the new methods asymptotically approach zero as the mesh size increases, while the spectral radius of the partial current method approaches a nonzero value as the mesh size increases. Of the two new methods proposed here, the analytic method provides a smaller spectral radius than the CCF method, but the CCF method has several advantages over the analytic method in practical applications
A reduction method for phase equilibrium calculations with cubic equations of state
Directory of Open Access Journals (Sweden)
D. V. Nichita
2006-09-01
Full Text Available In this work we propose a new reduction method for phase equilibrium calculations using a general form of cubic equations of state (CEOS. The energy term in the CEOS is a quadratic form, which is diagonalized by applying a linear transformation. The number of the reduction parameters is related to the rank of the matrix C with elements (1-Cij, where Cij denotes the binary interaction parameters (BIPs. The dimensionality of the problem depends only on the number of reduction parameters, and is independent of the number of components in the mixture.
A Fast and High-precision Orientation Algorithm for BeiDou Based on Dimensionality Reduction
Directory of Open Access Journals (Sweden)
ZHAO Jiaojiao
2015-05-01
Full Text Available A fast and high-precision orientation algorithm for BeiDou is proposed by deeply analyzing the constellation characteristics of BeiDou and GEO satellites features.With the advantage of good east-west geometry, the baseline vector candidate values were solved by the GEO satellites observations combined with the dimensionality reduction theory at first.Then, we use the ambiguity function to judge the values in order to obtain the optical baseline vector and get the wide lane integer ambiguities. On this basis, the B1 ambiguities were solved. Finally, the high-precision orientation was estimated by the determinating B1 ambiguities. This new algorithm not only can improve the ill-condition of traditional algorithm, but also can reduce the ambiguity search region to a great extent, thus calculating the integer ambiguities in a single-epoch.The algorithm is simulated by the actual BeiDou ephemeris and the result shows that the method is efficient and fast for orientation. It is capable of very high single-epoch success rate(99.31% and accurate attitude angle (the standard deviation of pitch and heading is respectively 0.07°and 0.13°in a real time and dynamic environment.
Three-dimensional space charge calculation method
International Nuclear Information System (INIS)
Lysenko, W.P.; Wadlinger, E.A.
1981-01-01
A method is presented for calculating space-charge forces suitable for use in a particle tracing code. Poisson's equation is solved in three dimensions with boundary conditions specified on an arbitrary surface by using a weighted residual method. Using a discrete particle distribution as our source input, examples are shown of off-axis, bunched beams of noncircular crosssection in radio-frequency quadrupole (RFQ) and drift-tube linac geometries
Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform
Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah
2017-02-01
Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.
Reduction Method for Active Distribution Networks
DEFF Research Database (Denmark)
Raboni, Pietro; Chen, Zhe
2013-01-01
On-line security assessment is traditionally performed by Transmission System Operators at the transmission level, ignoring the effective response of distributed generators and small loads. On the other hand the required computation time and amount of real time data for including Distribution...... Networks also would be too large. In this paper an adaptive aggregation method for subsystems with power electronic interfaced generators and voltage dependant loads is proposed. With this tool may be relatively easier including distribution networks into security assessment. The method is validated...... by comparing the results obtained in PSCAD® with the detailed network model and with the reduced one. Moreover the control schemes of a wind turbine and a photovoltaic plant included in the detailed network model are described....
Variational iteration method for one dimensional nonlinear thermoelasticity
International Nuclear Information System (INIS)
Sweilam, N.H.; Khader, M.M.
2007-01-01
This paper applies the variational iteration method to solve the Cauchy problem arising in one dimensional nonlinear thermoelasticity. The advantage of this method is to overcome the difficulty of calculation of Adomian's polynomials in the Adomian's decomposition method. The numerical results of this method are compared with the exact solution of an artificial model to show the efficiency of the method. The approximate solutions show that the variational iteration method is a powerful mathematical tool for solving nonlinear problems
N=2-Maxwell-Chern-Simons model with anomalous magnetic moment coupling via dimensional reduction
International Nuclear Information System (INIS)
Christiansen, H.R.; Cunha, M.S.; Helayel Neto, Jose A.; Manssur, L.R.U; Nogueira, A.L.M.A.
1998-02-01
An N=1-supersymmetric version of the Cremmer-Scherk-Kalb-Ramond model with non-minimal coupling to matter is built up both in terms of superfields and in a component field formalism. By adopting a dimensional reduction procedure, the N=2-D=3 counterpart of the model comes out, with two main features: a genuine (diagonal) Chern-Simons term and an anomalous magnetic moment coupling between matter and the gauge potential. (author)
Use of dimensionality reduction for structural mapping of hip joint osteoarthritis data
International Nuclear Information System (INIS)
Theoharatos, C; Fotopoulos, S; Boniatis, I; Panayiotakis, G; Panagiotopoulos, E
2009-01-01
A visualization-based, computer-oriented, classification scheme is proposed for assessing the severity of hip osteoarthritis (OA) using dimensionality reduction techniques. The introduced methodology tries to cope with the confined ability of physicians to structurally organize the entire available set of medical data into semantically similar categories and provide the capability to make visual observations among the ensemble of data using low-dimensional biplots. In this work, 18 pelvic radiographs of patients with verified unilateral hip OA are evaluated by experienced physicians and assessed into Normal, Mild and Severe following the Kellgren and Lawrence scale. Two regions of interest corresponding to radiographic hip joint spaces are determined and representative features are extracted using a typical texture analysis technique. The structural organization of all hip OA data is accomplished using distance and topology preservation-based dimensionality reduction techniques. The resulting map is a low-dimensional biplot that reflects the intrinsic organization of the ensemble of available data and which can be directly accessed by the physician. The conceivable visualization scheme can potentially reveal critical data similarities and help the operator to visually estimate their initial diagnosis. In addition, it can be used to detect putative clustering tendencies, examine the presence of data similarities and indicate the existence of possible false alarms in the initial perceptual evaluation
Reduction method of exhaust gas quantity
Energy Technology Data Exchange (ETDEWEB)
Ono, Y.; Morishita, K.
1975-02-08
A cleaning method for automobile exhaust through contact with sintered oxide semiconductors consisting of tin, antimony, manganese, and palladium oxides is discussed. This device has a much higher efficiency and lasts longer than any similar device developed previously consisting of oxides of iron, manganese cobalt, nickel, aluminum, and other rare earth metals. This sintered oxide semiconductor device is composed of: tin oxide: 30 wt ratio, tin hydrogen oxide: 30 wt ratio, antimony oxide: 2 wt ratio, manganese chloride: 2 wt ratio, palladium chloride: 1 wt ratio, carbon powder: 4 wt ratio, and ammonium carbonate: 10 wt ratio, for example. This device converts 100 percent of carbon monoxide into carbon dioxide at 350 C. This compound provides oxygen to CO at higher temperatures and absorbs oxygen from air at normal temperatures. There is no effect on efficiency.
A multi-dimensional sampling method for locating small scatterers
International Nuclear Information System (INIS)
Song, Rencheng; Zhong, Yu; Chen, Xudong
2012-01-01
A multiple signal classification (MUSIC)-like multi-dimensional sampling method (MDSM) is introduced to locate small three-dimensional scatterers using electromagnetic waves. The indicator is built with the most stable part of signal subspace of the multi-static response matrix on a set of combinatorial sampling nodes inside the domain of interest. It has two main advantages compared to the conventional MUSIC methods. First, the MDSM is more robust against noise. Second, it can work with a single incidence even for multi-scatterers. Numerical simulations are presented to show the good performance of the proposed method. (paper)
Rydzewski, J; Nowak, W
2016-04-12
In this work we propose an application of a nonlinear dimensionality reduction method to represent the high-dimensional configuration space of the ligand-protein dissociation process in a manner facilitating interpretation. Rugged ligand expulsion paths are mapped into 2-dimensional space. The mapping retains the main structural changes occurring during the dissociation. The topological similarity of the reduced paths may be easily studied using the Fréchet distances, and we show that this measure facilitates machine learning classification of the diffusion pathways. Further, low-dimensional configuration space allows for identification of residues active in transport during the ligand diffusion from a protein. The utility of this approach is illustrated by examination of the configuration space of cytochrome P450cam involved in expulsing camphor by means of enhanced all-atom molecular dynamics simulations. The expulsion trajectories are sampled and constructed on-the-fly during molecular dynamics simulations using the recently developed memetic algorithms [ Rydzewski, J.; Nowak, W. J. Chem. Phys. 2015 , 143 ( 12 ), 124101 ]. We show that the memetic algorithms are effective for enforcing the ligand diffusion and cavity exploration in the P450cam-camphor complex. Furthermore, we demonstrate that machine learning techniques are helpful in inspecting ligand diffusion landscapes and provide useful tools to examine structural changes accompanying rare events.
Irregular grid methods for pricing high-dimensional American options
Berridge, S.J.
2004-01-01
This thesis proposes and studies numerical methods for pricing high-dimensional American options; important examples being basket options, Bermudan swaptions and real options. Four new methods are presented and analysed, both in terms of their application to various test problems, and in terms of
International Nuclear Information System (INIS)
Fang, Guochang; Tian, Lixin; Sun, Mei; Fu, Min
2012-01-01
A novel three-dimensional energy-saving and emission-reduction chaotic system is proposed, which has not yet been reported in present literature. The system is established in accordance with the complicated relationship between energy-saving and emission-reduction, carbon emissions and economic growth. The dynamic behavior of the system is analyzed by means of Lyapunov exponents and bifurcation diagrams. With undetermined coefficient method, expressions of homoclinic orbits of the system are obtained. The Šilnikov theorem guarantees that the system has Smale horseshoes and the horseshoes chaos. Artificial neural network (ANN) is used to identify the quantitative coefficients in the simulation models according to the statistical data of China, and an empirical study of the real system is carried out with the results in perfect agreement with actual situation. It is found that the sooner and more perfect energy-saving and emission-reduction is started, the easier and sooner the maximum of the carbon emissions will be achieved so as to reduce carbon emissions and energy intensity. Numerical simulations are presented to demonstrate the results. -- Highlights: ► Use non-linear dynamical method to model the energy-saving and emission-reduction system. ► The energy-saving and emission-reduction attractor is obtained. ► Identify the unknown parameters of the energy-saving and emission-reduction system based on the statistical data. ► Evaluating the achievements of energy-saving and emission-reduction by the time-varying energy intensity calculation formula. ► Some statistical results based on the statistical data in China are presented, which are vivid and adherent to the reality.
A DETERMINISTIC METHOD FOR TRANSIENT, THREE-DIMENSIONAL NUETRON TRANSPORT
International Nuclear Information System (INIS)
S. GOLUOGLU, C. BENTLEY, R. DEMEGLIO, M. DUNN, K. NORTON, R. PEVEY I.SUSLOV AND H.L. DODDS
1998-01-01
A deterministic method for solving the time-dependent, three-dimensional Boltzmam transport equation with explicit representation of delayed neutrons has been developed and evaluated. The methodology used in this study for the time variable of the neutron flux is known as the improved quasi-static (IQS) method. The position, energy, and angle-dependent neutron flux is computed deterministically by using the three-dimensional discrete ordinates code TORT. This paper briefly describes the methodology and selected results. The code developed at the University of Tennessee based on this methodology is called TDTORT. TDTORT can be used to model transients involving voided and/or strongly absorbing regions that require transport theory for accuracy. This code can also be used to model either small high-leakage systems, such as space reactors, or asymmetric control rod movements. TDTORT can model step, ramp, step followed by another step, and step followed by ramp type perturbations. It can also model columnwise rod movement can also be modeled. A special case of columnwise rod movement in a three-dimensional model of a boiling water reactor (BWR) with simple adiabatic feedback is also included. TDTORT is verified through several transient one-dimensional, two-dimensional, and three-dimensional benchmark problems. The results show that the transport methodology and corresponding code developed in this work have sufficient accuracy and speed for computing the dynamic behavior of complex multidimensional neutronic systems
DEFF Research Database (Denmark)
Eckardt, Henrik; Lind, Marianne
2015-01-01
BACKGROUND: Operative treatment of displaced calcaneal fractures should restore joint congruence, but conventional fluoroscopy is unable to fully visualize the subtalar joint. We questioned whether intraoperative 3-dimensional (3D) imaging would aid in the reduction of calcaneal fractures......, resulting in improved articular congruence and implant positioning. METHOD: Sixty-two displaced calcaneal fractures were operated on using standard fluoroscopic views. When the surgeon had achieved a satisfactory reduction, an intraoperative 3D scan was conducted, malreductions or implant imperfections were...
Chavez Chavez, Gustavo Ivan; Turkiyyah, George; Zampini, Stefano; Keyes, David E.
2017-01-01
and the cyclic reduction method. The setup and application phases of the preconditioner achieve log-linear complexity in memory footprint and number of operations, and numerical experiments exhibit good weak and strong scalability at large processor counts in a
2013-01-01
Background The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. Results In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Conclusions Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship. PMID:23845024
Lifetime of rho meson in correlation with magnetic-dimensional reduction
Energy Technology Data Exchange (ETDEWEB)
Kawaguchi, Mamiya [Nagoya University, Department of Physics, Nagoya (Japan); Matsuzaki, Shinya [Nagoya University, Department of Physics, Nagoya (Japan); Nagoya University, Institute for Advanced Research, Nagoya (Japan)
2017-04-15
It is naively expected that in a strong magnetic configuration, the Landau quantization ceases the neutral rho meson to decay to the charged pion pair, so the neutral rho meson will be long-lived. To closely access this naive observation, we explicitly compute the charged pion loop in the magnetic field at the one-loop level, to evaluate the magnetic dependence of the lifetime for the neutral rho meson as well as its mass. Due to the dimensional reduction induced by the magnetic field (violation of the Lorentz invariance), the polarization (spin s{sub z} = 0, ±1) modes of the rho meson, as well as the corresponding pole mass and width, are decomposed in a nontrivial manner compared to the vacuum case. To see the significance of the reduction effect, we simply take the lowest Landau level approximation to analyze the spin-dependent rho masses and widths. We find that the ''fate'' of the rho meson may be more complicated because of the magnetic-dimensional reduction: as the magnetic field increases, the rho width for the spin s{sub z} = 0 starts to develop, reaches a peak, then vanishes at the critical magnetic field to which the folklore refers. On the other side, the decay rates of the other rhos for s{sub z} = ±1 monotonically increase as the magnetic field develops. The correlation between the polarization dependence and the Landau level truncation is also addressed. (orig.)
Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.
Glaser, Joshua I; Zamft, Bradley M; Church, George M; Kording, Konrad P
2015-01-01
Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.
Sponberg, Simon; Daniel, Thomas L; Fairhall, Adrienne L
2015-04-01
What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity) consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in high dimensional
Directory of Open Access Journals (Sweden)
Simon Sponberg
2015-04-01
Full Text Available What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in
Sponberg, Simon; Daniel, Thomas L.; Fairhall, Adrienne L.
2015-01-01
What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity) consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in high dimensional
Preliminary comparison of different reduction methods of graphene ...
Indian Academy of Sciences (India)
diverse applications and developing a simple, green, and efficient method for the mass production of ... properties of graphene have driven the search to find methods ... Chemical reduction of GO sheets has been performed with ... efficient method for the mass production of graphene. 2. ... temperature was raised to 35.
International Nuclear Information System (INIS)
Chen Yong; Yan Zhenya
2005-01-01
In this paper (2 + 1)-dimensional Gardner equation is investigated using a sine-Gordon equation expansion method, which was presented via a generalized sine-Gordon reduction equation and a new transformation. As a consequence, it is shown that the method is more powerful to obtain many types of new doubly periodic solutions of (2 + 1)-dimensional Gardner equation. In particular, solitary wave solutions are also given as simple limits of doubly periodic solutions
A method of image improvement in three-dimensional imaging
International Nuclear Information System (INIS)
Suto, Yasuzo; Huang, Tewen; Furuhata, Kentaro; Uchino, Masafumi.
1988-01-01
In general, image interpolation is required when the surface configurations of such structures as bones and organs are three-dimensionally constructed from the multi-sliced images obtained by CT. Image interpolation is a processing method whereby an artificial image is inserted between two adjacent slices to make spatial resolution equal to slice resolution in appearance. Such image interpolation makes it possible to increase the image quality of the constructed three-dimensional image. In our newly-developed algorithm, we have converted the presently and subsequently sliced images to distance images, and generated the interpolation images from these two distance images. As a result, compared with the previous method, three-dimensional images with better image quality have been constructed. (author)
Computational methods for three-dimensional microscopy reconstruction
Frank, Joachim
2014-01-01
Approaches to the recovery of three-dimensional information on a biological object, which are often formulated or implemented initially in an intuitive way, are concisely described here based on physical models of the object and the image-formation process. Both three-dimensional electron microscopy and X-ray tomography can be captured in the same mathematical framework, leading to closely-related computational approaches, but the methodologies differ in detail and hence pose different challenges. The editors of this volume, Gabor T. Herman and Joachim Frank, are experts in the respective methodologies and present research at the forefront of biological imaging and structural biology. Computational Methods for Three-Dimensional Microscopy Reconstruction will serve as a useful resource for scholars interested in the development of computational methods for structural biology and cell biology, particularly in the area of 3D imaging and modeling.
International Nuclear Information System (INIS)
Fiziev, P P; Shirkov, D V
2012-01-01
The paper presents a generalization and further development of our recent publications, where solutions of the Klein–Fock–Gordon equation defined on a few particular D = (2 + 1)-dimensional static spacetime manifolds were considered. The latter involve toy models of two-dimensional spaces with axial symmetry, including dimensional reduction to the one-dimensional space as a singular limiting case. Here, the non-static models of space geometry with axial symmetry are under consideration. To make these models closer to physical reality, we define a set of ‘admissible’ shape functions ρ(t, z) as the (2 + 1)-dimensional Einstein equation solutions in the vacuum spacetime, in the presence of the Λ-term and for the spacetime filled with the standard ‘dust’. It is curious that in the last case the Einstein equations reduce to the well-known Monge–Ampère equation, thus enabling one to obtain the general solution of the Cauchy problem, as well as a set of other specific solutions involving one arbitrary function. A few explicit solutions of the Klein–Fock–Gordon equation in this set are given. An interesting qualitative feature of these solutions relates to the dimensional reduction points, their classification and time behavior. In particular, these new entities could provide us with novel insight into the nature of P- and T-violations and of the Big Bang. A short comparison with other attempts to utilize the dimensional reduction of the spacetime is given. (paper)
Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces
Energy Technology Data Exchange (ETDEWEB)
Li, Yongfeng; Qu, Shaobo; Wang, Jiafu; Chen, Hongya [College of Science, Air Force Engineering University, Xi' an, Shaanxi 710051 (China); Zhang, Jieqiu [College of Science, Air Force Engineering University, Xi' an, Shaanxi 710051 (China); Electronic Materials Research Laboratory, Key Laboratory of Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Xu, Zhuo [Electronic Materials Research Laboratory, Key Laboratory of Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Zhang, Anxue [School of Electronics and Information Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)
2014-06-02
Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.
Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces
International Nuclear Information System (INIS)
Li, Yongfeng; Qu, Shaobo; Wang, Jiafu; Chen, Hongya; Zhang, Jieqiu; Xu, Zhuo; Zhang, Anxue
2014-01-01
Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.
Directory of Open Access Journals (Sweden)
N.R. Sakthivel
2014-03-01
Full Text Available Bearing fault, Impeller fault, seal fault and cavitation are the main causes of breakdown in a mono block centrifugal pump and hence, the detection and diagnosis of these mechanical faults in a mono block centrifugal pump is very crucial for its reliable operation. Based on a continuous acquisition of signals with a data acquisition system, it is possible to classify the faults. This is achieved by the extraction of features from the measured data and employing data mining approaches to explore the structural information hidden in the signals acquired. In the present study, statistical features derived from the vibration data are used as the features. In order to increase the robustness of the classifier and to reduce the data processing load, dimensionality reduction is necessary. In this paper dimensionality reduction is performed using traditional dimensionality reduction techniques and nonlinear dimensionality reduction techniques. The effectiveness of each dimensionality reduction technique is also verified using visual analysis. The reduced feature set is then classified using a decision tree. The results obtained are compared with those generated by classifiers such as Naïve Bayes, Bayes Net and kNN. The effort is to bring out the better dimensionality reduction technique–classifier combination.
The stress analysis method for three-dimensional composite materials
Nagai, Kanehiro; Yokoyama, Atsushi; Maekawa, Zen'ichiro; Hamada, Hiroyuki
1994-05-01
This study proposes a stress analysis method for three-dimensionally fiber reinforced composite materials. In this method, the rule-of mixture for composites is successfully applied to 3-D space in which material properties would change 3-dimensionally. The fundamental formulas for Young's modulus, shear modulus, and Poisson's ratio are derived. Also, we discuss a strength estimation and an optimum material design technique for 3-D composite materials. The analysis is executed for a triaxial orthogonally woven fabric, and their results are compared to the experimental data in order to verify the accuracy of this method. The present methodology can be easily understood with basic material mechanics and elementary mathematics, so it enables us to write a computer program of this theory without difficulty. Furthermore, this method can be applied to various types of 3-D composites because of its general-purpose characteristics.
Analysis of Drag Reduction Methods and Mechanisms of Turbulent
Directory of Open Access Journals (Sweden)
Gu Yunqing
2017-01-01
Full Text Available Turbulent flow is a difficult issue in fluid dynamics, the rules of which have not been totally revealed up to now. Fluid in turbulent state will result in a greater frictional force, which must consume great energy. Therefore, it is not only an important influence in saving energy and improving energy utilization rate but also an extensive application prospect in many fields, such as ship domain and aerospace. Firstly, bionic drag reduction technology is reviewed and is a hot research issue now, the drag reduction mechanism of body surface structure is analyzed, such as sharks, earthworms, and dolphins. Besides, we make a thorough study of drag reduction characteristics and mechanisms of microgrooved surface and compliant wall. Then, the relevant drag reduction technologies and mechanisms are discussed, focusing on the microbubbles, the vibrant flexible wall, the coating, the polymer drag reduction additives, superhydrophobic surface, jet surface, traveling wave surface drag reduction, and the composite drag reduction methods. Finally, applications and advancements of the drag reduction technology in turbulence are prospected.
The Validity of Dimensional Regularization Method on Fractal Spacetime
Directory of Open Access Journals (Sweden)
Yong Tao
2013-01-01
Full Text Available Svozil developed a regularization method for quantum field theory on fractal spacetime (1987. Such a method can be applied to the low-order perturbative renormalization of quantum electrodynamics but will depend on a conjectural integral formula on non-integer-dimensional topological spaces. The main purpose of this paper is to construct a fractal measure so as to guarantee the validity of the conjectural integral formula.
A simple three dimensional wide-angle beam propagation method
Ma, Changbao; van Keuren, Edward
2006-05-01
The development of three dimensional (3-D) waveguide structures for chip scale planar lightwave circuits (PLCs) is hampered by the lack of effective 3-D wide-angle (WA) beam propagation methods (BPMs). We present a simple 3-D wide-angle beam propagation method (WA-BPM) using Hoekstra’s scheme along with a new 3-D wave equation splitting method. The applicability, accuracy and effectiveness of our method are demonstrated by applying it to simulations of wide-angle beam propagation and comparing them with analytical solutions.
METHODS OF REDUCTION OF FREE PHENOL CONTENT IN PHENOLIC FOAM
Directory of Open Access Journals (Sweden)
Bruyako Mikhail Gerasimovich
2012-12-01
method aimed at reduction of toxicity of phenolic foams consists in the introduction of a composite mixture of chelate compounds. Raw materials applied in the production of phenolic foams include polymers FRB-1A and VAG-3. The aforementioned materials are used to produce foams FRP-1. Introduction of 1% aluminum fluoride leads to the 40% reduction of the free phenol content in the foam. Introduction of crystalline zinc chloride accelerates the foaming and curing of phenolic foams. The technology that contemplates the introduction of zeolites into the mixture includes pre-mixing with FRB -1A and subsequent mixing with VAG-3; thereafter, the composition is poured into the form, in which the process of foaming is initiated. The content of free phenol was identified using the method of UV spectroscopy. The objective of the research was to develop methods of reduction of the free phenol content in the phenolic foam.
Krivov, Sergei V
2011-07-01
Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.
A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem
Directory of Open Access Journals (Sweden)
Zekić-Sušac Marijana
2014-09-01
Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.
Energy Technology Data Exchange (ETDEWEB)
Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca [Department of Radiology, Stanford University, Stanford, California 94305 (United States); Department of Radiology, Stanford University, Stanford, California 94305 (United States) and Center for Medical Image Science and Visualization, Linkoeping University, Linkoeping (Sweden); Pattern Recognition Laboratory, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, 91054, Erlangen (Germany); Nuclear and Radiological Engineering and Medical Physics Programs, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Siemens AG Healthcare, Forchheim 91301 (Germany); Department of Radiology, Stanford University, Stanford, California 94305 (United States)
2011-11-15
Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8
International Nuclear Information System (INIS)
Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca
2011-01-01
Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold
Vibration of carbon nanotubes with defects: order reduction methods
Hudson, Robert B.; Sinha, Alok
2018-03-01
Order reduction methods are widely used to reduce computational effort when calculating the impact of defects on the vibrational properties of nearly periodic structures in engineering applications, such as a gas-turbine bladed disc. However, despite obvious similarities these techniques have not yet been adapted for use in analysing atomic structures with inevitable defects. Two order reduction techniques, modal domain analysis and modified modal domain analysis, are successfully used in this paper to examine the changes in vibrational frequencies, mode shapes and mode localization caused by defects in carbon nanotubes. The defects considered are isotope defects and Stone-Wales defects, though the methods described can be extended to other defects.
Wave field restoration using three-dimensional Fourier filtering method.
Kawasaki, T; Takai, Y; Ikuta, T; Shimizu, R
2001-11-01
A wave field restoration method in transmission electron microscopy (TEM) was mathematically derived based on a three-dimensional (3D) image formation theory. Wave field restoration using this method together with spherical aberration correction was experimentally confirmed in through-focus images of amorphous tungsten thin film, and the resolution of the reconstructed phase image was successfully improved from the Scherzer resolution limit to the information limit. In an application of this method to a crystalline sample, the surface structure of Au(110) was observed in a profile-imaging mode. The processed phase image showed quantitatively the atomic relaxation of the topmost layer.
Directory of Open Access Journals (Sweden)
Tom Cattaert
Full Text Available We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR with Model-Based MDR (MB-MDR. We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR, which is a generalization of Multifactor Dimensionality Reduction (MDR to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC, an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS. This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.
New method for solving three-dimensional Schroedinger equation
International Nuclear Information System (INIS)
Melezhik, V.S.
1992-01-01
A new method is developed for solving the multidimensional Schroedinger equation without the variable separation. To solve the Schroedinger equation in a multidimensional coordinate space X, a difference grid Ω i (i=1,2,...,N) for some of variables, Ω, from X={R,Ω} is introduced and the initial partial-differential equation is reduced to a system of N differential-difference equations in terms of one of the variables R. The arising multi-channel scattering (or eigenvalue) problem is solved by the algorithm based on a continuous analog of the Newton method. The approach has been successfully tested for several two-dimensional problems (scattering on a nonspherical potential well and 'dipole' scatterer, a hydrogen atom in a homogenous magnetic field) and for a three-dimensional problem of the helium-atom bound states. (author)
A comparative study of two stochastic mode reduction methods
Energy Technology Data Exchange (ETDEWEB)
Stinis, Panagiotis
2005-09-01
We present a comparative study of two methods for thereduction of the dimensionality of a system of ordinary differentialequations that exhibits time-scale separation. Both methods lead to areduced system of stochastic differential equations. The novel feature ofthese methods is that they allow the use, in the reduced system, ofhigher order terms in the resolved variables. The first method, proposedby Majda, Timofeyev and Vanden-Eijnden, is based on an asymptoticstrategy developed by Kurtz. The second method is a short-memoryapproximation of the Mori-Zwanzig projection formalism of irreversiblestatistical mechanics, as proposed by Chorin, Hald and Kupferman. Wepresent conditions under which the reduced models arising from the twomethods should have similar predictive ability. We apply the two methodsto test cases that satisfy these conditions. The form of the reducedmodels and the numerical simulations show that the two methods havesimilar predictive ability as expected.
On two flexible methods of 2-dimensional regression analysis
Czech Academy of Sciences Publication Activity Database
Volf, Petr
2012-01-01
Roč. 18, č. 4 (2012), s. 154-164 ISSN 1803-9782 Grant - others:GA ČR(CZ) GAP209/10/2045 Institutional support: RVO:67985556 Keywords : regression analysis * Gordon surface * prediction error * projection pursuit Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/SI/volf-on two flexible methods of 2-dimensional regression analysis.pdf
Continuum methods of physical modeling continuum mechanics, dimensional analysis, turbulence
Hutter, Kolumban
2004-01-01
The book unifies classical continuum mechanics and turbulence modeling, i.e. the same fundamental concepts are used to derive model equations for material behaviour and turbulence closure and complements these with methods of dimensional analysis. The intention is to equip the reader with the ability to understand the complex nonlinear modeling in material behaviour and turbulence closure as well as to derive or invent his own models. Examples are mostly taken from environmental physics and geophysics.
High dimensional model representation method for fuzzy structural dynamics
Adhikari, S.; Chowdhury, R.; Friswell, M. I.
2011-03-01
Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.
The supersymmetric Adler-Bardeen theorem and regularization by dimensional reduction
International Nuclear Information System (INIS)
Ensign, P.; Mahanthappa, K.T.
1987-01-01
We examine the subtraction scheme dependence of the anomaly of the supersymmetric, gauge singlet axial current in pure and coupled supersymmetric Yang-Mills theories. Preserving supersymmetry and gauge invariance explicitly by using supersymmetric background field theory and dimensional reduction, we show that only the one-loop value of the axial anomaly is subtraction scheme independent, and that one can always define a subtraction scheme in which the Adler-Bardeen theorem is satisfied to all orders in perturbation theory. In general this subtraction scheme may be non-minimal, but in both the pure and the coupled theories, the Adler-Bardeen theorem is satisfied to two loops in minimal subtraction. (orig.)
Three-dimensional protein structure prediction: Methods and computational strategies.
Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C
2014-10-12
A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.
Two-Dimensional Impact Reconstruction Method for Rail Defect Inspection
Directory of Open Access Journals (Sweden)
Jie Zhao
2014-01-01
Full Text Available The safety of train operating is seriously menaced by the rail defects, so it is of great significance to inspect rail defects dynamically while the train is operating. This paper presents a two-dimensional impact reconstruction method to realize the on-line inspection of rail defects. The proposed method utilizes preprocessing technology to convert time domain vertical vibration signals acquired by wireless sensor network to space signals. The modern time-frequency analysis method is improved to reconstruct the obtained multisensor information. Then, the image fusion processing technology based on spectrum threshold processing and node color labeling is proposed to reduce the noise, and blank the periodic impact signal caused by rail joints and locomotive running gear. This method can convert the aperiodic impact signals caused by rail defects to partial periodic impact signals, and locate the rail defects. An application indicates that the two-dimensional impact reconstruction method could display the impact caused by rail defects obviously, and is an effective on-line rail defects inspection method.
Development of two dimensional electrophoresis method using single chain DNA
International Nuclear Information System (INIS)
Ikeda, Junichi; Hidaka, So
1998-01-01
By combining a separation method due to molecular weight and a method to distinguish difference of mono-bases, it was aimed to develop a two dimensional single chain DNA labeled with Radioisotope (RI). From electrophoretic pattern difference of parent and variant strands, it was investigated to isolate the root module implantation control gene. At first, a Single Strand Conformation Polymorphism (SSCP) method using concentration gradient gel was investigated. As a result, it was formed that intervals between double chain and single chain DNAs expanded, but intervals of both single chain DNAs did not expand. On next, combination of non-modified acrylic amide electrophoresis method and Denaturing Gradient-Gel Electrophoresis (DGGE) method was examined. As a result, hybrid DNA developed by two dimensional electrophoresis arranged on two lines. But, among them a band of DNA modified by high concentration of urea could not be found. Therefore, in this fiscal year's experiments, no preferable result could be obtained. By the used method, it was thought to be impossible to detect the differences. (G.K.)
One New Method to Generate 3-Dimensional Virtual Mannequin
Xiu-jin, Shi; Zhi-jun, Wang; Jia-jin, Le
The personal virtual mannequin is very important in electronic made to measure (eMTM) system. There is one new easy method to generate personal virtual mannequin. First, the characteristic information of customer's body is got from two photos. Secondly, some human body part templates corresponding with the customer are selected from the templates library. Thirdly, these templates are modified and assembled according to certain rules to generate a personalized 3-dimensional human, and then the virtual mannequin is realized. Experimental result shows that the method is easy and feasible.
The transmission probability method in one-dimensional cylindrical geometry
International Nuclear Information System (INIS)
Rubin, I.E.
1983-01-01
The collision probability method widely used in solving the problems of neutron transpopt in a reactor cell is reliable for simple cells with small number of zones. The increase of the number of zones and also taking into account the anisotropy of scattering greatly increase the scope of calculations. In order to reduce the time of calculation the transmission probability method is suggested to be used for flux calculation in one-dimensional cylindrical geometry taking into account the scattering anisotropy. The efficiency of the suggested method is verified using the one-group calculations for cylindrical cells. The use of the transmission probability method allows to present completely angular and spatial dependences is neutrons distributions without the increase in the scope of calculations. The method is especially effective in solving the multi-group problems
Fast Reduction Method in Dominance-Based Information Systems
Li, Yan; Zhou, Qinghua; Wen, Yongchuan
2018-01-01
In real world applications, there are often some data with continuous values or preference-ordered values. Rough sets based on dominance relations can effectively deal with these kinds of data. Attribute reduction can be done in the framework of dominance-relation based approach to better extract decision rules. However, the computational cost of the dominance classes greatly affects the efficiency of attribute reduction and rule extraction. This paper presents an efficient method of computing dominance classes, and further compares it with traditional method with increasing attributes and samples. Experiments on UCI data sets show that the proposed algorithm obviously improves the efficiency of the traditional method, especially for large-scale data.
Variance reduction methods applied to deep-penetration problems
International Nuclear Information System (INIS)
Cramer, S.N.
1984-01-01
All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course
Metal artifact reduction method using metal streaks image subtraction
International Nuclear Information System (INIS)
Pua, Rizza D.; Cho, Seung Ryong
2014-01-01
Many studies have been dedicated for metal artifact reduction (MAR); however, the methods are successful to varying degrees depending on situations. Sinogram in-painting, filtering, iterative method are some of the major categories of MAR. Each has its own merits and weaknesses. A combination of these methods or hybrid methods have also been developed to make use of the different benefits of two techniques and minimize the unfavorable results. Our method focuses on the in-paitning approach and a hybrid MAR described by Xia et al. Although in-painting scheme is an effective technique in reducing the primary metal artifacts, a major drawback is the reintroduction of new artifacts that can be caused by an inaccurate interpolation process. Furthermore, combining the segmented metal image to the corrected nonmetal image in the final step of a conventional inpainting approach causes an issue of incorrect metal pixel values. Our proposed method begins with a sinogram in-painting approach and ends with an image-based metal artifact reduction scheme. This work provides a simple, yet effective solution for reducing metal artifacts and acquiring the original metal pixel information. The proposed method demonstrated its effectiveness in a simulation setting. The proposed method showed image quality that is comparable to the standard MAR; however, quantitatively more accurate than the standard MAR
Review of noise reduction methods for centrifugal fans
Neise, W.
1981-11-01
Several methods for the reduction of centrifugal fan noise are presented, the most of which are aimed at a lower blade passage frequency level. The methods are grouped into five categories: casing modifications to increase the distance between impeller and cutoff, the introduction of a phase shift of the source pressure fluctuations, impeller modifications, radial clearance between impeller eye and inlet nozzle, and acoustical measures. Resonators mounted at the cutoff of centrifugal fans appear to be a highly efficient and simple means of reducing the blade passage tone, and the method can be used for new fan construction and existing installations without affecting the aerodynamic performance of the fan.
Speckle reduction methods in laser-based picture projectors
Akram, M. Nadeem; Chen, Xuyuan
2016-02-01
Laser sources have been promised for many years to be better light sources as compared to traditional lamps or light-emitting diodes (LEDs) for projectors, which enable projectors having wide colour gamut for vivid image, super brightness and high contrast for the best picture quality, long lifetime for maintain free operation, mercury free, and low power consumption for green environment. A major technology obstacle in using lasers for projection has been the speckle noise caused by to the coherent nature of the lasers. For speckle reduction, current state of the art solutions apply moving parts with large physical space demand. Solutions beyond the state of the art need to be developed such as integrated optical components, hybrid MOEMS devices, and active phase modulators for compact speckle reduction. In this article, major methods reported in the literature for the speckle reduction in laser projectors are presented and explained. With the advancement in semiconductor lasers with largely reduced cost for the red, green and the blue primary colours, and the developed methods for their speckle reduction, it is hoped that the lasers will be widely utilized in different projector applications in the near future.
Aytaç Korkmaz, Sevcan; Binol, Hamidullah
2018-03-01
Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.
Ye, Fei; Marchetti, P. A.; Su, Z. B.; Yu, L.
2017-09-01
The relation between braid and exclusion statistics is examined in one-dimensional systems, within the framework of Chern-Simons statistical transmutation in gauge invariant form with an appropriate dimensional reduction. If the matter action is anomalous, as for chiral fermions, a relation between braid and exclusion statistics can be established explicitly for both mutual and nonmutual cases. However, if it is not anomalous, the exclusion statistics of emergent low energy excitations is not necessarily connected to the braid statistics of the physical charged fields of the system. Finally, we also discuss the bosonization of one-dimensional anyonic systems through T-duality. Dedicated to the memory of Mario Tonin.
International Nuclear Information System (INIS)
Ye, Fei; Marchetti, P A; Su, Z B; Yu, L
2017-01-01
The relation between braid and exclusion statistics is examined in one-dimensional systems, within the framework of Chern–Simons statistical transmutation in gauge invariant form with an appropriate dimensional reduction. If the matter action is anomalous, as for chiral fermions, a relation between braid and exclusion statistics can be established explicitly for both mutual and nonmutual cases. However, if it is not anomalous, the exclusion statistics of emergent low energy excitations is not necessarily connected to the braid statistics of the physical charged fields of the system. Finally, we also discuss the bosonization of one-dimensional anyonic systems through T-duality. (paper)
Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh
2017-06-01
Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.
Dimensional analysis and qualitative methods in problem solving: II
International Nuclear Information System (INIS)
Pescetti, D
2009-01-01
We show that the underlying mathematical structure of dimensional analysis (DA), in the qualitative methods in problem-solving context, is the algebra of the affine spaces. In particular, we show that the qualitative problem-solving procedure based on the parallel decomposition of a problem into simple special cases yields the new original mathematical concepts of special points and special representations of affine spaces. A qualitative problem-solving algorithm piloted by the mathematics of DA is illustrated by a set of examples.
Four-Dimensional Data Assimilation Using the Adjoint Method
Bao, Jian-Wen
The calculus of variations is used to confirm that variational four-dimensional data assimilation (FDDA) using the adjoint method can be implemented when the numerical model equations have a finite number of first-order discontinuous points. These points represent the on/off switches associated with physical processes, for which the Jacobian matrix of the model equation does not exist. Numerical evidence suggests that, in some situations when the adjoint method is used for FDDA, the temperature field retrieved using horizontal wind data is numerically not unique. A physical interpretation of this type of non-uniqueness of the retrieval is proposed in terms of energetics. The adjoint equations of a numerical model can also be used for model-parameter estimation. A general computational procedure is developed to determine the size and distribution of any internal model parameter. The procedure is then applied to a one-dimensional shallow -fluid model in the context of analysis-nudging FDDA: the weighting coefficients used by the Newtonian nudging technique are determined. The sensitivity of these nudging coefficients to the optimal objectives and constraints is investigated. Experiments of FDDA using the adjoint method are conducted using the dry version of the hydrostatic Penn State/NCAR mesoscale model (MM4) and its adjoint. The minimization procedure converges and the initialization experiment is successful. Temperature-retrieval experiments involving an assimilation of the horizontal wind are also carried out using the adjoint of MM4.
An MPCA/LDA Based Dimensionality Reduction Algorithm for Face Recognition
Directory of Open Access Journals (Sweden)
Jun Huang
2014-01-01
Full Text Available We proposed a face recognition algorithm based on both the multilinear principal component analysis (MPCA and linear discriminant analysis (LDA. Compared with current traditional existing face recognition methods, our approach treats face images as multidimensional tensor in order to find the optimal tensor subspace for accomplishing dimension reduction. The LDA is used to project samples to a new discriminant feature space, while the K nearest neighbor (KNN is adopted for sample set classification. The results of our study and the developed algorithm are validated with face databases ORL, FERET, and YALE and compared with PCA, MPCA, and PCA + LDA methods, which demonstrates an improvement in face recognition accuracy.
New method of 2-dimensional metrology using mask contouring
Matsuoka, Ryoichi; Yamagata, Yoshikazu; Sugiyama, Akiyuki; Toyoda, Yasutaka
2008-10-01
We have developed a new method of accurately profiling and measuring of a mask shape by utilizing a Mask CD-SEM. The method is intended to realize high accuracy, stability and reproducibility of the Mask CD-SEM adopting an edge detection algorithm as the key technology used in CD-SEM for high accuracy CD measurement. In comparison with a conventional image processing method for contour profiling, this edge detection method is possible to create the profiles with much higher accuracy which is comparable with CD-SEM for semiconductor device CD measurement. This method realizes two-dimensional metrology for refined pattern that had been difficult to measure conventionally by utilizing high precision contour profile. In this report, we will introduce the algorithm in general, the experimental results and the application in practice. As shrinkage of design rule for semiconductor device has further advanced, an aggressive OPC (Optical Proximity Correction) is indispensable in RET (Resolution Enhancement Technology). From the view point of DFM (Design for Manufacturability), a dramatic increase of data processing cost for advanced MDP (Mask Data Preparation) for instance and surge of mask making cost have become a big concern to the device manufacturers. This is to say, demands for quality is becoming strenuous because of enormous quantity of data growth with increasing of refined pattern on photo mask manufacture. In the result, massive amount of simulated error occurs on mask inspection that causes lengthening of mask production and inspection period, cost increasing, and long delivery time. In a sense, it is a trade-off between the high accuracy RET and the mask production cost, while it gives a significant impact on the semiconductor market centered around the mask business. To cope with the problem, we propose the best method of a DFM solution using two-dimensional metrology for refined pattern.
Noise reduction methods for nucleic acid and macromolecule sequencing
Schuller, Ivan K.; Di Ventra, Massimiliano; Balatsky, Alexander
2018-05-08
Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.
Li, Fengwang; Xue, Mianqi; Li, Jiezhen; Ma, Xinlei; Chen, Lu; Zhang, Xueji; MacFarlane, Douglas R; Zhang, Jie
2017-11-13
Two-dimensional (2D) materials are known to be useful in catalysis. Engineering 3D bulk materials into the 2D form can enhance the exposure of the active edge sites, which are believed to be the origin of the high catalytic activity. Reported herein is the production of 2D "few-layer" antimony (Sb) nanosheets by cathodic exfoliation. Application of this 2D engineering method turns Sb, an inactive material for CO 2 reduction in its bulk form, into an active 2D electrocatalyst for reduction of CO 2 to formate with high efficiency. The high activity is attributed to the exposure of a large number of catalytically active edge sites. Moreover, this cathodic exfoliation process can be coupled with the anodic exfoliation of graphite in a single-compartment cell for in situ production of a few-layer Sb nanosheets and graphene composite. The observed increased activity of this composite is attributed to the strong electronic interaction between graphene and Sb. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
New Cogging Torque Reduction Methods for Permanent Magnet Machine
Bahrim, F. S.; Sulaiman, E.; Kumar, R.; Jusoh, L. I.
2017-08-01
Permanent magnet type motors (PMs) especially permanent magnet synchronous motor (PMSM) are expanding its limbs in industrial application system and widely used in various applications. The key features of this machine include high power and torque density, extending speed range, high efficiency, better dynamic performance and good flux-weakening capability. Nevertheless, high in cogging torque, which may cause noise and vibration, is one of the threat of the machine performance. Therefore, with the aid of 3-D finite element analysis (FEA) and simulation using JMAG Designer, this paper proposed new method for cogging torque reduction. Based on the simulation, methods of combining the skewing with radial pole pairing method and skewing with axial pole pairing method reduces the cogging torque effect up to 71.86% and 65.69% simultaneously.
Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo
2018-03-01
In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.
Slot technique - an alternative method of scatter reduction in radiography
International Nuclear Information System (INIS)
Panzer, W.; Widenmann, L.
1983-01-01
The most common method of scatter reduction in radiography is the use of an antiscatter grid. Its disadvantage is the absorption of a certain percentage of primary radiation in the lead strips of the grid and the fact that due to the limited thickness of the lead strips their scatter absorption is also limited. A possibility for avoiding this disadvantage is offered by the so-called slot technique, ie, the successive exposure of the subject with a narrow fan beam provided by slots in rather thick lead plates. The results of a comparison between grid and slot technique regarding dose to the patient, scatter reduction, image quality and the effect of automatic exposure control are reported. (author)
METHODS OF NOISE LEVEL REDUCTION OF DRIVE IN LATHES
Directory of Open Access Journals (Sweden)
Janusz ROGULA
2014-06-01
Full Text Available The aim of this work is method presentation to noise level reduction of fixed headstock of the lathe. It is connected with the causes finding of non-uniform work of lathe headstock, description of recent design and its analysis. Problem of the excessive noise level concern to near 35% of the lathes have been produced. In spite of lack of noise reduction possibility there were no system solution of problem. Design optimisation weren’t done after application the electric motor with inverter. New solution of electric motor control let to reduce number of gear wheels in lathe drive system. For this drive solution there weren’t made the analysis of drive particular parts influence on the noise generation.
Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods
Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.
2011-12-01
Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion
Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test.
Palmerini, Luca; Mellone, Sabato; Rocchi, Laura; Chiari, Lorenzo
2011-01-01
The Timed Up and Go is a clinical test to assess mobility in the elderly and in Parkinson's disease. Lately instrumented versions of the test are being considered, where inertial sensors assess motion. To improve the pervasiveness, ease of use, and cost, we consider a smartphone's accelerometer as the measurement system. Several parameters (usually highly correlated) can be computed from the signals recorded during the test. To avoid redundancy and obtain the features that are most sensitive to the locomotor performance, a dimensionality reduction was performed through principal component analysis (PCA). Forty-nine healthy subjects of different ages were tested. PCA was performed to extract new features (principal components) which are not redundant combinations of the original parameters and account for most of the data variability. They can be useful for exploratory analysis and outlier detection. Then, a reduced set of the original parameters was selected through correlation analysis with the principal components. This set could be recommended for studies based on healthy adults. The proposed procedure could be used as a first-level feature selection in classification studies (i.e. healthy-Parkinson's disease, fallers-non fallers) and could allow, in the future, a complete system for movement analysis to be incorporated in a smartphone.
Faust, Kevin; Xie, Quin; Han, Dominick; Goyle, Kartikay; Volynskaya, Zoya; Djuric, Ugljesa; Diamandis, Phedias
2018-05-16
There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce. Here, we leverage t-distributed Stochastic Neighbor Embedding (t-SNE) to reduce dimensionality and depict how CNNs organize histomorphologic information. Unique to our workflow, we develop a quantitative and transparent approach to visualizing classification decisions prior to softmax compression. By discretizing the relationships between classes on the t-SNE plot, we show we can super-impose randomly sampled regions of test images and use their distribution to render statistically-driven classifications. Therefore, in addition to providing intuitive outputs for human review, this visual approach can carry out automated and objective multi-class classifications similar to more traditional and less-transparent categorical probability distribution scores. Importantly, this novel classification approach is driven by a priori statistically defined cutoffs. It therefore serves as a generalizable classification and anomaly detection tool less reliant on post-hoc tuning. Routine incorporation of this convenient approach for quantitative visualization and error reduction in histopathology aims to accelerate early adoption of CNNs into generalized real-world applications where unanticipated and previously untrained classes are often encountered.
Kas, Recep; Hummadi, Khalid Khazzal; Kortlever, Ruud; de Wit, Patrick; Milbrat, Alexander; Luiten-Olieman, Maria W.J.; Benes, Nieck Edwin; Koper, Marc T.M.; Mul, Guido
2016-01-01
Aqueous-phase electrochemical reduction of carbon dioxide requires an active, earth-abundant electrocatalyst, as well as highly efficient mass transport. Here we report the design of a porous hollow fibre copper electrode with a compact three-dimensional geometry, which provides a large area,
On a novel matrix method for three-dimensional photoelasticity
International Nuclear Information System (INIS)
Theocaris, P.S.; Gdoutos, E.E.
1978-01-01
A non-destructive method for the photoelastic determination of three-dimensional stress distributions, based on the Mueller and Jones calculi, is developed. The differential equations satisfied by the Stokes and Jones vectors, when a polarized light beam passes through a photoelastic model, presenting rotation of the secondary principal stress directions, are established in matrix form. The Peano-Baker method is used for the solution of these differential equations in a matrix series form, establishing the elements of the Mueller and Jones matrices of the photoelastic model. These matrices are experimentally determined by using different wavelengths in conjunction with Jones' 'equivalence theorem'. The Neumann equations are immediately deduced from the above-mentioned differential equations. (orig.) [de
Dimensionality Reduction and Information-Theoretic Divergence Between Sets of Ladar Images
National Research Council Canada - National Science Library
Gray, David M; Principe, Jose C
2008-01-01
... can be exploited while circumventing many of the problems associated with the so-called "curse of dimensionality." In this study, PCA techniques are used to find a low-dimensional sub-space representation of LADAR image sets...
Dimensional reduction of exceptional E6,E8 gauge groups and flavour chirality
International Nuclear Information System (INIS)
Koca, M.
1984-01-01
Ten-dimensional Yang - Mills gauge theories based on the exceptional groups E 6 and E 8 are reduced to four-dimensional flavour-chiral Yang - Mills - Higgs theories where the extra six dimensions are identified with the compact G 2 /SU(3) and SO(7)/SO(6) coset spaces. A ten-dimensional E 8 theory leads to three families of SU(5), one of which lies in the 144-dimensional representation of SO(10)
New method of three-dimensional reconstruction from two-dimensional MR data sets
International Nuclear Information System (INIS)
Wrazidlo, W.; Schneider, S.; Brambs, H.J.; Richter, G.M.; Kauffmann, G.W.; Geiger, B.; Fischer, C.
1989-01-01
In medical diagnosis and therapy, cross-sectional images are obtained by means of US, CT, or MR imaging. The authors propose a new solution to the problem of constructing a shape over a set of cross-sectional contours from two-dimensional (2D) MR data sets. The authors' method reduces the problem of constructing a shape over the cross sections to one of constructing a sequence of partial shapes, each of them connecting two cross sections lying on adjacent planes. The solution makes use of the Delaunay triangulation, which is isomorphic in that specific situation. The authors compute this Delaunay triangulation. Shape reconstruction is then achieved section by pruning Delaunay triangulations
Modeling of three-dimensional diffusible resistors with the one-dimensional tube multiplexing method
International Nuclear Information System (INIS)
Gillet, Jean-Numa; Degorce, Jean-Yves; Meunier, Michel
2009-01-01
Electronic-behavior modeling of three-dimensional (3D) p + -π-p + and n + -ν-n + semiconducting diffusible devices with highly accurate resistances for the design of analog resistors, which are compatible with the CMOS (complementary-metal-oxide-semiconductor) technologies, is performed in three dimensions with the fast tube multiplexing method (TMM). The current–voltage (I–V) curve of a silicon device is usually computed with traditional device simulators of technology computer-aided design (TCAD) based on the finite-element method (FEM). However, for the design of 3D p + -π-p + and n + -ν-n + diffusible resistors, they show a high computational cost and convergence that may fail with fully non-separable 3D dopant concentration profiles as observed in many diffusible resistors resulting from laser trimming. These problems are avoided with the proposed TMM, which divides the 3D resistor into one-dimensional (1D) thin tubes with longitudinal axes following the main orientation of the average electrical field in the tubes. The I–V curve is rapidly obtained for a device with a realistic 3D dopant profile, since a system of three first-order ordinary differential equations has to be solved for each 1D multiplexed tube with the TMM instead of three second-order partial differential equations in the traditional TCADs. Simulations with the TMM are successfully compared to experimental results from silicon-based 3D resistors fabricated by laser-induced dopant diffusion in the gaps of MOSFETs (metal-oxide-semiconductor field-effect transistors) without initial gate. Using thin tubes with other shapes than parallelepipeds as ring segments with toroidal lateral surfaces, the TMM can be generalized to electronic devices with other types of 3D diffusible microstructures
Reduction of the dimensionality and comparative analysis of multivariate radiological data
International Nuclear Information System (INIS)
Seddeek, M.K.; Kozae, A.M.; Sharshar, T.; Badran, H.M.
2009-01-01
Computational methods were used to reduce the dimensionality and to find clusters of multivariate data. The variables were the natural radioactivity contents and the texture characteristics of sand samples. The application of discriminate analysis revealed that samples with high negative values of the former score have the highest contamination with black sand. Principal component analysis (PCA) revealed that radioactivity concentrations alone are sufficient for the classification. Rough set analysis (RSA) showed that the concentration of 238 U, 226 Ra or 232 Th, combined with the concentration of 40 K, can specify the clusters and characteristics of the sand. Both PCA and RSA show that 238 U, 226 Ra and 232 Th behave similarly. RSA revealed that one or two of them can be omitted without degrading predictions.
Exact rebinning methods for three-dimensional PET.
Liu, X; Defrise, M; Michel, C; Sibomana, M; Comtat, C; Kinahan, P; Townsend, D
1999-08-01
The high computational cost of data processing in volume PET imaging is still hindering the routine application of this successful technique, especially in the case of dynamic studies. This paper describes two new algorithms based on an exact rebinning equation, which can be applied to accelerate the processing of three-dimensional (3-D) PET data. The first algorithm, FOREPROJ, is a fast-forward projection algorithm that allows calculation of the 3-D attenuation correction factors (ACF's) directly from a two-dimensional (2-D) transmission scan, without first reconstructing the attenuation map and then performing a 3-D forward projection. The use of FOREPROJ speeds up the estimation of the 3-D ACF's by more than a factor five. The second algorithm, FOREX, is a rebinning algorithm that is also more than five times faster, compared to the standard reprojection algorithm (3DRP) and does not suffer from the image distortions generated by the even faster approximate Fourier rebinning (FORE) method at large axial apertures. However, FOREX is probably not required by most existing scanners, as the axial apertures are not large enough to show improvements over FORE with clinical data. Both algorithms have been implemented and applied to data simulated for a scanner with a large axial aperture (30 degrees), and also to data acquired with the ECAT HR and the ECAT HR+ scanners. Results demonstrate the excellent accuracy achieved by these algorithms and the important speedup when the sinogram sizes are powers of two.
Greenhouse effect gases: reduction challenges and accounting methods
International Nuclear Information System (INIS)
Dumergues, Laurent
2012-01-01
In this article, the author first proposes an overview of strategic challenges related to the reduction of greenhouse gas emissions. He indicates and discusses the various economic consequences of climate change. These consequences can be environmental (issues ranging from a loss of biodiversity to agriculture), social (from climate refugees to tourism), and economic (from climate disasters to insurance). He focuses on the issue of energy (oil at the base of our economy, carbon contents) and discusses competition issues (an always more demanding regulation, and unavoidable practices). In the second part, he proposes an overview of methods of accounting of greenhouse effect gases, and discusses how to perform an emission inventory
Jin, Yulin; Lu, Kuan; Hou, Lei; Chen, Yushu
2017-12-01
The proper orthogonal decomposition (POD) method is a main and efficient tool for order reduction of high-dimensional complex systems in many research fields. However, the robustness problem of this method is always unsolved, although there are some modified POD methods which were proposed to solve this problem. In this paper, a new adaptive POD method called the interpolation Grassmann manifold (IGM) method is proposed to address the weakness of local property of the interpolation tangent-space of Grassmann manifold (ITGM) method in a wider parametric region. This method is demonstrated here by a nonlinear rotor system of 33-degrees of freedom (DOFs) with a pair of liquid-film bearings and a pedestal looseness fault. The motion region of the rotor system is divided into two parts: simple motion region and complex motion region. The adaptive POD method is compared with the ITGM method for the large and small spans of parameter in the two parametric regions to present the advantage of this method and disadvantage of the ITGM method. The comparisons of the responses are applied to verify the accuracy and robustness of the adaptive POD method, as well as the computational efficiency is also analyzed. As a result, the new adaptive POD method has a strong robustness and high computational efficiency and accuracy in a wide scope of parameter.
DEFF Research Database (Denmark)
Eckardt, Henrik; Lind, Dennis; Toendevold, Erik
2015-01-01
was evaluated on reconstructed coronal and sagittal images of the acetabulum. Results - The fracture severity and patient characteristics were similar in the 2 groups. In the 3D group, 46 of 72 patients (0.6) had a perfect result after open reduction and internal fixation, and in the control group, 17 of 42 (0...
Directory of Open Access Journals (Sweden)
Arehart Eric
2009-03-01
Full Text Available Abstract Background The fidelity of DNA replication serves as the nidus for both genetic evolution and genomic instability fostering disease. Single nucleotide polymorphisms (SNPs constitute greater than 80% of the genetic variation between individuals. A new theory regarding DNA replication fidelity has emerged in which selectivity is governed by base-pair geometry through interactions between the selected nucleotide, the complementary strand, and the polymerase active site. We hypothesize that specific nucleotide combinations in the flanking regions of SNP fragments are associated with mutation. Results We modeled the relationship between DNA sequence and observed polymorphisms using the novel multifactor dimensionality reduction (MDR approach. MDR was originally developed to detect synergistic interactions between multiple SNPs that are predictive of disease susceptibility. We initially assembled data from the Broad Institute as a pilot test for the hypothesis that flanking region patterns associate with mutagenesis (n = 2194. We then confirmed and expanded our inquiry with human SNPs within coding regions and their flanking sequences collected from the National Center for Biotechnology Information (NCBI database (n = 29967 and a control set of sequences (coding region not associated with SNP sites randomly selected from the NCBI database (n = 29967. We discovered seven flanking region pattern associations in the Broad dataset which reached a minimum significance level of p ≤ 0.05. Significant models (p Conclusion The present study represents the first use of this computational methodology for modeling nonlinear patterns in molecular genetics. MDR was able to identify distinct nucleotide patterning around sites of mutations dependent upon the observed nucleotide change. We discovered one flanking region set that included five nucleotides clustered around a specific type of SNP site. Based on the strongly associated patterns identified in
Directory of Open Access Journals (Sweden)
Enrico eChiovetto
2013-02-01
Full Text Available A long standing hypothesis in the neuroscience community is that the CNS generates the muscle activities to accomplish movements by combining a relatively small number of stereotyped patterns of muscle activations, often referred to as muscle synergies. Different definitions of synergies have been given in the literature. The most well-known are those of synchronous, time-varying and temporal muscle synergies. Each one of them is based on a different mathematical model used to factor some EMG array recordings collected during the execution of variety of motor tasks into a well-determined spatial, temporal or spatio-temporal organization. This plurality of definitions and their separate application to complex tasks have so far complicated the comparison and interpretation of the results obtained across studies, and it has always remained unclear why and when one synergistic decomposition should be preferred to another one. By using well-understood motor tasks such as elbow flexions and extensions, we aimed in this study to clarify better what are the motor features characterized by each kind of decomposition and to assess whether, when and why one of them should be preferred to the others. We found that three temporal synergies, each one of them accounting for specific temporal phases of the movements could account for the majority of the data variation. Similar performances could be achieved by two synchronous synergies, encoding the agonist-antagonist nature of the two muscles considered, and by two time-varying muscle synergies, encoding each one a task-related feature of the elbow movements, specifically their direction. Our findings support the notion that each EMG decomposition provides a set of well-interpretable muscle synergies, identifying reduction of dimensionality in different aspects of the movements. Taken together, our findings suggest that all decompositions are not equivalent and may imply different neurophysiological substrates
International Nuclear Information System (INIS)
Shao, Zhen; Yang, Shan-Lin; Gao, Fei
2014-01-01
Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and
Method of simulating dose reduction for digital radiographic systems
International Nuclear Information System (INIS)
Baath, M.; Haakansson, M.; Tingberg, A.; Maansson, L. G.
2005-01-01
The optimisation of image quality vs. radiation dose is an important task in medical imaging. To obtain maximum validity of the optimisation, it must be based on clinical images. Images at different dose levels can then either be obtained by collecting patient images at the different dose levels sought to investigate - including additional exposures and permission from an ethical committee - or by manipulating images to simulate different dose levels. The aim of the present work was to develop a method of simulating dose reduction for digital radiographic systems. The method uses information about the detective quantum efficiency and noise power spectrum at the original and simulated dose levels to create an image containing filtered noise. When added to the original image this results in an image with noise which, in terms of frequency content, agrees with the noise present in an image collected at the simulated dose level. To increase the validity, the method takes local dose variations in the original image into account. The method was tested on a computed radiography system and was shown to produce images with noise behaviour similar to that of images actually collected at the simulated dose levels. The method can, therefore, be used to modify an image collected at one dose level so that it simulates an image of the same object collected at any lower dose level. (authors)
International Nuclear Information System (INIS)
Tonogi, Morio; Yamane, Genyuki; Aoyagi, Yutaka; Hasegawa, Azusa; Mizoe, Junetsu; Tsujii, Hirohiko
2004-01-01
Reduction methods for irradiation on oral mucosa examined concerning in acute phase of the carbon ion radiotherapy for head and neck malignancies. We enforced a mechanical teeth and gingival cleaning as an Oral hearth care and gargled a polaprezinc with sodium alginate, and azulene- lidocaine with glycerin sodium as a oral linces before radiation. The response of the mucosal failure was reduced compare with no care group. In this Result, we considered that oral hearth care for prevention of infection, and mucosa protection by the drug was important factor. (author)
One-dimensional transient radiative transfer by lattice Boltzmann method.
Zhang, Yong; Yi, Hongliang; Tan, Heping
2013-10-21
The lattice Boltzmann method (LBM) is extended to solve transient radiative transfer in one-dimensional slab containing scattering media subjected to a collimated short laser irradiation. By using a fully implicit backward differencing scheme to discretize the transient term in the radiative transfer equation, a new type of lattice structure is devised. The accuracy and computational efficiency of this algorithm are examined firstly. Afterwards, effects of the medium properties such as the extinction coefficient, the scattering albedo and the anisotropy factor, and the shapes of laser pulse on time-resolved signals of transmittance and reflectance are investigated. Results of the present method are found to compare very well with the data from the literature. For an oblique incidence, the LBM results in this paper are compared with those by Monte Carlo method generated by ourselves. In addition, transient radiative transfer in a two-Layer inhomogeneous media subjected to a short square pulse irradiation is investigated. At last, the LBM is further extended to study the transient radiative transfer in homogeneous medium with a refractive index discontinuity irradiated by the short pulse laser. Several trends on the time-resolved signals different from those for refractive index of 1 (i.e. refractive-index-matched boundary) are observed and analysed.
Simulation of Thermal Stratification in BWR Suppression Pools with One Dimensional Modeling Method
Energy Technology Data Exchange (ETDEWEB)
Haihua Zhao; Ling Zou; Hongbin Zhang
2014-01-01
The suppression pool in a boiling water reactor (BWR) plant not only is the major heat sink within the containment system, but also provides the major emergency cooling water for the reactor core. In several accident scenarios, such as a loss-of-coolant accident and extended station blackout, thermal stratification tends to form in the pool after the initial rapid venting stage. Accurately predicting the pool stratification phenomenon is important because it affects the peak containment pressure; the pool temperature distribution also affects the NPSHa (available net positive suction head) and therefore the performance of the Emergency Core Cooling System and Reactor Core Isolation Cooling System pumps that draw cooling water back to the core. Current safety analysis codes use zero dimensional (0-D) lumped parameter models to calculate the energy and mass balance in the pool; therefore, they have large uncertainties in the prediction of scenarios in which stratification and mixing are important. While three-dimensional (3-D) computational fluid dynamics (CFD) methods can be used to analyze realistic 3-D configurations, these methods normally require very fine grid resolution to resolve thin substructures such as jets and wall boundaries, resulting in a long simulation time. For mixing in stably stratified large enclosures, the BMIX++ code (Berkeley mechanistic MIXing code in C++) has been developed to implement a highly efficient analysis method for stratification where the ambient fluid volume is represented by one-dimensional (1-D) transient partial differential equations and substructures (such as free or wall jets) are modeled with 1-D integral models. This allows very large reductions in computational effort compared to multi-dimensional CFD modeling. One heat-up experiment performed at the Finland POOLEX facility, which was designed to study phenomena relevant to Nordic design BWR suppression pool including thermal stratification and mixing, is used for
Reduction of aflatoxin in rice by different cooking methods.
Sani, Ali Mohamadi; Azizi, Eisa Gholampour; Salehi, Esmaeel Ataye; Rahimi, Khadije
2014-07-01
Rice (Oryza sativa Linn) is one of the basic diets in the north of Iran. The aim of present study was to detect total aflatoxin (AFT) in domestic and imported rice in Amol (in the north of Iran) and to evaluate the effect of different cooking methods on the levels of the toxin. For this purpose, 42 rice samples were collected from retail stores. The raw samples were analysed by enzyme-linked immunosorbent assay (ELISA) technique for toxin assessment and then submitted to two different cooking methods including traditional local method and in rice cooker. After treatment, AFT was determined. Results show that the average concentration of AFT in domestic and imported samples was 1.08 ± 0.02 and 1.89 ± 0.87 ppb, respectively, which is lower than national and European Union standards. The highest AFT reduction (24.8%) was observed when rice samples were cooked by rice cooker but the difference with local method was not statistically significant (p > 0.05). © The Author(s) 2012.
Wispy Prosthesis: A Novel Method in Denture Weight Reduction.
Anne, Gopinadh; Budeti, Sreedevi; Anche, Sampath Kumar; Zakkula, Srujana; Atla, Jyothi; Jyothula, Ravi Rakesh Dev; Appana, Krishna Chaitanya; Peddinti, Vijaya Kumar
2016-04-01
Stability and retention of the denture becomes at stake with the increase in weight of the denture prosthesis. As a consequence, different materials and methods have been introduced to overcome these issues but denture weight reduction still remains to be a cumbersome and strenuous procedure. To introduce a novel technique for the fabrication of denture prosthesis where in the weight of the denture will not affect the retention and stability of the denture. Four groups with a sample size of 10 each, were included where in one group was control and other three were study groups. The control group samples were made completely solid and the study group samples were packed with materials like bean balls, cellulose balls and polyacrylic fibers. The weight of all the samples of each study group was measured and compared with the control group. The observations were analyzed statistically by paired t-test. It was observed that the bean balls group produced a weight reduction of 31.3%, cellulose balls group 27.4% and polyacrylic fibers group 24.5% when compared to that of the control group. This novel technique will eliminate the problems that were associated in creating hollowness and at the same time will reduce the weight of the prosthesis and among all the study groups, bean balls group were found to reduce maximum weight of the prosthesis.
On the dimensional reduction of a gravitational theory containing higher-derivative terms
International Nuclear Information System (INIS)
Pollock, M.D.
1990-02-01
From the higher-dimensional gravitational theory L-circumflex=R-circumflex-2Λ-circumflex-α-circumflex 1 R-circumflex 2 =α-circumflex 2 R-circumflex AB R-circumflex AB -α-circumflex 3 R-circumflex ABCD R-circumflex ABCD , we derive the effective four-dimensional Lagrangian L. (author). 12 refs
Matrix method for two-dimensional waveguide mode solution
Sun, Baoguang; Cai, Congzhong; Venkatesh, Balajee Seshasayee
2018-05-01
In this paper, we show that the transfer matrix theory of multilayer optics can be used to solve the modes of any two-dimensional (2D) waveguide for their effective indices and field distributions. A 2D waveguide, even composed of numerous layers, is essentially a multilayer stack and the transmission through the stack can be analysed using the transfer matrix theory. The result is a transfer matrix with four complex value elements, namely A, B, C and D. The effective index of a guided mode satisfies two conditions: (1) evanescent waves exist simultaneously in the first (cladding) layer and last (substrate) layer, and (2) the complex element D vanishes. For a given mode, the field distribution in the waveguide is the result of a 'folded' plane wave. In each layer, there is only propagation and absorption; at each boundary, only reflection and refraction occur, which can be calculated according to the Fresnel equations. As examples, we show that this method can be used to solve modes supported by the multilayer step-index dielectric waveguide, slot waveguide, gradient-index waveguide and various plasmonic waveguides. The results indicate the transfer matrix method is effective for 2D waveguide mode solution in general.
Chavez Chavez, Gustavo Ivan
2017-12-07
We present a robust and scalable preconditioner for the solution of large-scale linear systems that arise from the discretization of elliptic PDEs amenable to rank compression. The preconditioner is based on hierarchical low-rank approximations and the cyclic reduction method. The setup and application phases of the preconditioner achieve log-linear complexity in memory footprint and number of operations, and numerical experiments exhibit good weak and strong scalability at large processor counts in a distributed memory environment. Numerical experiments with linear systems that feature symmetry and nonsymmetry, definiteness and indefiniteness, constant and variable coefficients demonstrate the preconditioner applicability and robustness. Furthermore, it is possible to control the number of iterations via the accuracy threshold of the hierarchical matrix approximations and their arithmetic operations, and the tuning of the admissibility condition parameter. Together, these parameters allow for optimization of the memory requirements and performance of the preconditioner.
Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua
2014-01-01
The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.
Method of local pointed function reduction of original shape in Fourier transformation
International Nuclear Information System (INIS)
Dosch, H.; Slavyanov, S.Yu.
2002-01-01
The method for analytical reduction of the original shape in the one-dimensional Fourier transformation by the fourier image modulus is proposed. The basic concept of the method consists in the presentation of the model shape in the form of the local peak functions sum. The eigenfunctions, generated by the linear differential equations with the polynomial coefficients, are selected as the latter ones. This provides for the possibility of managing the Fourier transformation without numerical integration. This reduces the reverse task to the nonlinear regression with a small number of the evaluated parameters and to the numerical or asymptotic study on the model peak functions - the eigenfunctions of the differential tasks and their fourier images [ru
PWR core safety analysis with 3-dimensional methods
International Nuclear Information System (INIS)
Gensler, A.; Kühnel, K.; Kuch, S.
2015-01-01
Highlights: • An overview of AREVA’s safety analysis codes their coupling is provided. • The validation base and licensing applications of these codes are summarized. • Coupled codes and methods provide improved margins and non-conservative results. • Examples for REA and inadvertent opening of the pressurizer safety valve are given. - Abstract: The main focus of safety analysis is to demonstrate the required safety level of the reactor core. Because of the demanding requirements, the quality of the safety analysis strongly affects the confidence in the operational safety of a reactor. To ensure the highest quality, it is essential that the methodology consists of appropriate analysis tools, an extensive validation base, and last but not least highly educated engineers applying the methodology. The sophisticated 3-dimensional core models applied by AREVA ensure that all physical effects relevant for safety are treated and the results are reliable and conservative. Presently AREVA employs SCIENCE, CASMO/NEMO and CASCADE-3D for pressurized water reactors. These codes are currently being consolidated into the next generation 3D code system ARCADIA®. AREVA continuously extends the validation base, including measurement campaigns in test facilities and comparisons of the predictions of steady state and transient measured data gathered from plants during many years of operation. Thus, the core models provide reliable and comprehensive results for a wide range of applications. For the application of these powerful tools, AREVA is taking benefit of its interdisciplinary know-how and international teamwork. Experienced engineers of different technical backgrounds are working together to ensure an appropriate interpretation of the calculation results, uncertainty analysis, along with continuously maintaining and enhancing the quality of the analysis methodologies. In this paper, an overview of AREVA’s broad application experience as well as the broad validation
International Nuclear Information System (INIS)
Itsubo, Mariko; Kameda, Haruo; Suzuki, Naoki; Okamura, Tetsuo
1989-01-01
The method of three-dimensional display of hepatocellular carcinoma using conventional hepatic arteriogram by computer graphics method was newly exploited and applied in clinical use. Three-dimensional models were reconstructed from contour lines of tumors demonstrated as hypervascular lesions by hepatic arteriography. Although objects were limited by angiographic images in which tumors need to be demonstrated as nodules with hypervascularity, this method of three-dimensional display was not worse on accuracy than that using computed tomographic images. According to this method property of the tumor expressed by vascularity was demonstrated clear and in addition volume of the tumor was calculated easily. When the tumor arose in necrotic changes in which demonstrated as a vascular lesion by hepatic arteriography with reduction of size in usual by conservative treatment such as transcathter arterial embolization therapy, this three-dimensional display was able to demonstrate such changes clear. This preliminary study demonstrates the feasibility and clinical usefulness of three-dimensional display of hepatocellular carcinoma using hepatic arteriogram by computer graphics method. (author)
Aviles, Angelica I.; Alsaleh, Samar; Sobrevilla, Pilar; Casals, Alicia
2016-03-01
Robotic-Assisted Surgery approach overcomes the limitations of the traditional laparoscopic and open surgeries. However, one of its major limitations is the lack of force feedback. Since there is no direct interaction between the surgeon and the tissue, there is no way of knowing how much force the surgeon is applying which can result in irreversible injuries. The use of force sensors is not practical since they impose different constraints. Thus, we make use of a neuro-visual approach to estimate the applied forces, in which the 3D shape recovery together with the geometry of motion are used as input to a deep network based on LSTM-RNN architecture. When deep networks are used in real time, pre-processing of data is a key factor to reduce complexity and improve the network performance. A common pre-processing step is dimensionality reduction which attempts to eliminate redundant and insignificant information by selecting a subset of relevant features to use in model construction. In this work, we show the effects of dimensionality reduction in a real-time application: estimating the applied force in Robotic-Assisted Surgeries. According to the results, we demonstrated positive effects of doing dimensionality reduction on deep networks including: faster training, improved network performance, and overfitting prevention. We also show a significant accuracy improvement, ranging from about 33% to 86%, over existing approaches related to force estimation.
Three-dimensional discrete element method simulation of core disking
Wu, Shunchuan; Wu, Haoyan; Kemeny, John
2018-04-01
The phenomenon of core disking is commonly seen in deep drilling of highly stressed regions in the Earth's crust. Given its close relationship with the in situ stress state, the presence and features of core disking can be used to interpret the stresses when traditional in situ stress measuring techniques are not available. The core disking process was simulated in this paper using the three-dimensional discrete element method software PFC3D (particle flow code). In particular, PFC3D is used to examine the evolution of fracture initiation, propagation and coalescence associated with core disking under various stress states. In this paper, four unresolved problems concerning core disking are investigated with a series of numerical simulations. These simulations also provide some verification of existing results by other researchers: (1) Core disking occurs when the maximum principal stress is about 6.5 times the tensile strength. (2) For most stress situations, core disking occurs from the outer surface, except for the thrust faulting stress regime, where the fractures were found to initiate from the inner part. (3) The anisotropy of the two horizontal principal stresses has an effect on the core disking morphology. (4) The thickness of core disk has a positive relationship with radial stress and a negative relationship with axial stresses.
Dimensional reduction of a general advection–diffusion equation in 2D channels
Kalinay, Pavol; Slanina, František
2018-06-01
Diffusion of point-like particles in a two-dimensional channel of varying width is studied. The particles are driven by an arbitrary space dependent force. We construct a general recurrence procedure mapping the corresponding two-dimensional advection-diffusion equation onto the longitudinal coordinate x. Unlike the previous specific cases, the presented procedure enables us to find the one-dimensional description of the confined diffusion even for non-conservative (vortex) forces, e.g. caused by flowing solvent dragging the particles. We show that the result is again the generalized Fick–Jacobs equation. Despite of non existing scalar potential in the case of vortex forces, the effective one-dimensional scalar potential, as well as the corresponding quasi-equilibrium and the effective diffusion coefficient can be always found.
Dose rate reduction method for NMCA applied BWR plants
International Nuclear Information System (INIS)
Nagase, Makoto; Aizawa, Motohiro; Ito, Tsuyoshi; Hosokawa, Hideyuki; Varela, Juan; Caine, Thomas
2012-09-01
BRAC (BWR Radiation Assessment and Control) dose rate is used as an indicator of the incorporation of activated corrosion by products into BWR recirculation piping, which is known to be a significant contributor to dose rate received by workers during refueling outages. In order to reduce radiation exposure of the workers during the outage, it is desirable to keep BRAC dose rates as low as possible. After HWC was adopted to reduce IGSCC, a BRAC dose rate increase was observed in many plants. As a countermeasure to these rapid dose rate increases under HWC conditions, Zn injection was widely adopted in United States and Europe resulting in a reduction of BRAC dose rates. However, BRAC dose rates in several plants remain high, prompting the industry to continue to investigate methods to achieve further reductions. In recent years a large portion of the BWR fleet has adopted NMCA (NobleChem TM ) to enhance the hydrogen injection effect to suppress SCC. After NMCA, especially OLNC (On-Line NobleChem TM ), BRAC dose rates were observed to decrease. In some OLNC applied BWR plants this reduction was observed year after year to reach a new reduced equilibrium level. This dose rate reduction trends suggest the potential dose reduction might be obtained by the combination of Pt and Zn injection. So, laboratory experiments and in-plant tests were carried out to evaluate the effect of Pt and Zn on Co-60 deposition behaviour. Firstly, laboratory experiments were conducted to study the effect of noble metal deposition on Co deposition on stainless steel surfaces. Polished type 316 stainless steel coupons were prepared and some of them were OLNC treated in the test loop before the Co deposition test. Water chemistry conditions to simulate HWC were as follows: Dissolved oxygen, hydrogen and hydrogen peroxide were below 5 ppb, 100 ppb and 0 ppb (no addition), respectively. Zn was injected to target a concentration of 5 ppb. The test was conducted up to 1500 hours at 553 K. Test
Bedani, F.; Schoenmakers, P.J.; Janssen, H.-G.
2012-01-01
On-line comprehensive two-dimensional liquid chromatography techniques promise to resolve samples that current one-dimensional liquid chromatography methods cannot adequately deal with. To make full use of the potential of two-dimensional liquid chromatography, optimization is required. Optimization
Method and system for manipulating a digital representation of a three-dimensional object
DEFF Research Database (Denmark)
2010-01-01
A method of manipulating a three-dimensional virtual building block model by means of two-dimensional cursor movements, the virtual building block model including a plurality of virtual building blocks each including a number of connection elements for connecting the virtual building block...... with another virtual building block according to a set of connection rules, the method comprising positioning by means of cursor movements in a computer display area representing a two-dimensional projection of said model, a two-dimensional projection of a first virtual building block to be connected...... to the structure, resulting in a two-dimensional position; determining, from the two-dimensional position, a number of three-dimensional candidate positions of the first virtual building block in the three-dimensional coordinate system; selecting one of said candidate positions based on the connection rules...
The Use of Statistical Methods in Dimensional Process Control
National Research Council Canada - National Science Library
Krajcsik, Stephen
1985-01-01
... erection. To achieve this high degree of unit accuracy, we have begun a pilot dimensional control program that has set the guidelines for systematically monitoring each stage of the production process prior to erection...
Generalized similarity method in unsteady two-dimensional MHD ...
African Journals Online (AJOL)
user
International Journal of Engineering, Science and Technology. Vol. 1, No. 1, 2009 ... temperature two-dimensional MHD laminar boundary layer of incompressible fluid. ...... Φ η is Blasius solution for stationary boundary layer on the plate,. ( ). 0.
International Nuclear Information System (INIS)
Yoo, Sung Min; Kim, Yoon Young
2007-01-01
This work is concerned with the topology optimization of three-dimensional cooling fins or heat sinks. Motivated by earlier success of the Internal Element Connectivity Method (I-ECP) method in two dimensional problems, the extension of I-ECP to three-dimensional problems is carried out. The main efforts were made to maintain the numerical trouble-free characteristics of I-ECP for full three-dimensional problems; a serious numerical problem appearing in thermal topology optimization is erroneous temperature undershooting. The effectiveness of the present implementation was checked through the design optimization of three-dimensional fins
Boundary element methods applied to two-dimensional neutron diffusion problems
International Nuclear Information System (INIS)
Itagaki, Masafumi
1985-01-01
The Boundary element method (BEM) has been applied to two-dimensional neutron diffusion problems. The boundary integral equation and its discretized form have been derived. Some numerical techniques have been developed, which can be applied to critical and fixed-source problems including multi-region ones. Two types of test programs have been developed according to whether the 'zero-determinant search' or the 'source iteration' technique is adopted for criticality search. Both programs require only the fluxes and currents on boundaries as the unknown variables. The former allows a reduction in computing time and memory in comparison with the finite element method (FEM). The latter is not always efficient in terms of computing time due to the domain integral related to the inhomogeneous source term; however, this domain integral can be replaced by the equivalent boundary integral for a region with a non-multiplying medium or with a uniform source, resulting in a significant reduction in computing time. The BEM, as well as the FEM, is well suited for solving irregular geometrical problems for which the finite difference method (FDM) is unsuited. The BEM also solves problems with infinite domains, which cannot be solved by the ordinary FEM and FDM. Some simple test calculations are made to compare the BEM with the FEM and FDM, and discussions are made concerning the relative merits of the BEM and problems requiring future solution. (author)
The JCMT Transient Survey: Data Reduction and Calibration Methods
Energy Technology Data Exchange (ETDEWEB)
Mairs, Steve; Lane, James [Department of Physics and Astronomy, University of Victoria, Victoria, BC, V8P 1A1 (Canada); Johnstone, Doug; Kirk, Helen [NRC Herzberg Astronomy and Astrophysics, 5071 West Saanich Road, Victoria, BC, V9E 2E7 (Canada); Lacaille, Kevin; Chapman, Scott [Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, B3H 4R2 (Canada); Bower, Geoffrey C. [Academia Sinica Institute of Astronomy and Astrophysics, 645 N. A‘ohōkū Place, Hilo, HI 96720 (United States); Bell, Graham S.; Graves, Sarah, E-mail: smairs@uvic.ca [East Asian Observatory, 660 North A‘ohōkū Place, University Park, Hilo, Hawaii 96720 (United States); Collaboration: JCMT Transient Team
2017-07-01
Though there has been a significant amount of work investigating the early stages of low-mass star formation in recent years, the evolution of the mass assembly rate onto the central protostar remains largely unconstrained. Examining in depth the variation in this rate is critical to understanding the physics of star formation. Instabilities in the outer and inner circumstellar disk can lead to episodic outbursts. Observing these brightness variations at infrared or submillimeter wavelengths constrains the current accretion models. The JCMT Transient Survey is a three-year project dedicated to studying the continuum variability of deeply embedded protostars in eight nearby star-forming regions at a one-month cadence. We use the SCUBA-2 instrument to simultaneously observe these regions at wavelengths of 450 and 850 μ m. In this paper, we present the data reduction techniques, image alignment procedures, and relative flux calibration methods for 850 μ m data. We compare the properties and locations of bright, compact emission sources fitted with Gaussians over time. Doing so, we achieve a spatial alignment of better than 1″ between the repeated observations and an uncertainty of 2%–3% in the relative peak brightness of significant, localized emission. This combination of imaging performance is unprecedented in ground-based, single-dish submillimeter observations. Finally, we identify a few sources that show possible and confirmed brightness variations. These sources will be closely monitored and presented in further detail in additional studies throughout the duration of the survey.
Hybrid CMS methods with model reduction for assembly of structures
Farhat, Charbel
1991-01-01
Future on-orbit structures will be designed and built in several stages, each with specific control requirements. Therefore there must be a methodology which can predict the dynamic characteristics of the assembled structure, based on the dynamic characteristics of the subassemblies and their interfaces. The methodology developed by CSC to address this issue is Hybrid Component Mode Synthesis (HCMS). HCMS distinguishes itself from standard component mode synthesis algorithms in the following features: (1) it does not require the subcomponents to have displacement compatible models, which makes it ideal for analyzing the deployment of heterogeneous flexible multibody systems, (2) it incorporates a second-level model reduction scheme at the interface, which makes it much faster than other algorithms and therefore suitable for control purposes, and (3) it does answer specific questions such as 'how does the global fundamental frequency vary if I change the physical parameters of substructure k by a specified amount?'. Because it is based on an energy principle rather than displacement compatibility, this methodology can also help the designer to define an assembly process. Current and future efforts are devoted to applying the HCMS method to design and analyze docking and berthing procedures in orbital construction.
The JCMT Transient Survey: Data Reduction and Calibration Methods
International Nuclear Information System (INIS)
Mairs, Steve; Lane, James; Johnstone, Doug; Kirk, Helen; Lacaille, Kevin; Chapman, Scott; Bower, Geoffrey C.; Bell, Graham S.; Graves, Sarah
2017-01-01
Though there has been a significant amount of work investigating the early stages of low-mass star formation in recent years, the evolution of the mass assembly rate onto the central protostar remains largely unconstrained. Examining in depth the variation in this rate is critical to understanding the physics of star formation. Instabilities in the outer and inner circumstellar disk can lead to episodic outbursts. Observing these brightness variations at infrared or submillimeter wavelengths constrains the current accretion models. The JCMT Transient Survey is a three-year project dedicated to studying the continuum variability of deeply embedded protostars in eight nearby star-forming regions at a one-month cadence. We use the SCUBA-2 instrument to simultaneously observe these regions at wavelengths of 450 and 850 μ m. In this paper, we present the data reduction techniques, image alignment procedures, and relative flux calibration methods for 850 μ m data. We compare the properties and locations of bright, compact emission sources fitted with Gaussians over time. Doing so, we achieve a spatial alignment of better than 1″ between the repeated observations and an uncertainty of 2%–3% in the relative peak brightness of significant, localized emission. This combination of imaging performance is unprecedented in ground-based, single-dish submillimeter observations. Finally, we identify a few sources that show possible and confirmed brightness variations. These sources will be closely monitored and presented in further detail in additional studies throughout the duration of the survey.
Method for coupling two-dimensional to three-dimensional discrete ordinates calculations
International Nuclear Information System (INIS)
Thompson, J.L.; Emmett, M.B.; Rhoades, W.A.; Dodds, H.L. Jr.
1985-01-01
A three-dimensional (3-D) discrete ordinates transport code, TORT, has been developed at the Oak Ridge National Laboratory for radiation penetration studies. It is not feasible to solve some 3-D penetration problems with TORT, such as a building located a large distance from a point source, because (a) the discretized 3-D problem is simply too big to fit on the computer or (b) the computing time (and corresponding cost) is prohibitive. Fortunately, such problems can be solved with a hybrid approach by coupling a two-dimensional (2-D) description of the point source, which is assumed to be azimuthally symmetric, to a 3-D description of the building, the region of interest. The purpose of this paper is to describe this hybrid methodology along with its implementation and evaluation in the DOTTOR (Discrete Ordinates to Three-dimensional Oak Ridge Transport) code
The Analysis of Dimensionality Reduction Techniques in Cryptographic Object Code Classification
Energy Technology Data Exchange (ETDEWEB)
Jason L. Wright; Milos Manic
2010-05-01
This paper compares the application of three different dimension reduction techniques to the problem of locating cryptography in compiled object code. A simple classi?er is used to compare dimension reduction via sorted covariance, principal component analysis, and correlation-based feature subset selection. The analysis concentrates on the classi?cation accuracy as the number of dimensions is increased.
New method for reduction of burning sulfur of coal
International Nuclear Information System (INIS)
Lyutskanov, L.; Dushanov, D.
1998-01-01
The coal pyrolysis is key phase in the the pyrolysis-combustion cycle as it provides char for combustor. The behaviour of sulfur compounds during coal pyrolysis depends on factors as rank of coal, quantity of sulfur and sulfur forms distribution in the coal, quantity and kind of mineral matter and the process conditions. The mineral content of coal may inhibit or catalyze the formation of volatile sulfur compounds. The pyrolysis itself is a mean of removing inorganic and organic sulfur but anyway a portion of it remains in the char while the other moves into the tar and gas. The aim of this study was to determine an optimal reduction of burning sulfur at the coal pyrolysis by varying parametric conditions. The pyrolysis of different kinds of coal has been studied. The samples with size particles o C at atmospheric pressure and with a heating rate of 6-50 o C min -1 . They were treated with exhaust gas and nitrogen at an addition of steam and air. The char obtained remains up to 10 min at the final temperature. The char samples cool without a contact with air. Two methods of desulfurization-pyrolysis were studied - using 9-vertical tubular reactor and 9-horizontal turning reactor. The results obtained show that at all samples there is a decrease of burning sulfur with maximal removal efficiency 83%. For example at a pyrolysis of Maritsa Iztok lignite coal the burning sulfur is only 16% in comparison with the control sample. The remained is 90% sulfate, 10% organic and pyrite traces when a mixture 'exhaust gas-water stream-air' was used. The method of desulfurization by pyrolysis could be applied at different kinds of coal and different conditions. Char obtained as a clean product can be used for generating electric power. This innovation is in a stage of patenting
An algebraic method for system reduction of stationary Gaussian systems
D. Jibetean; J.H. van Schuppen (Jan)
2003-01-01
textabstractSystem identification for a particular approach reduces to system reduction, determining for a system with a high state-space dimension a system of low state-space dimension. For Gaussian systems the problem of system reduction is considered with the divergence rate criterion. The
arXiv Supersymmetric gauged matrix models from dimensional reduction on a sphere
Closset, Cyril; Seong, Rak-Kyeong
2018-05-04
It was recently proposed that $ \\mathcal{N} $ = 1 supersymmetric gauged matrix models have a duality of order four — that is, a quadrality — reminiscent of infrared dualities of SQCD theories in higher dimensions. In this note, we show that the zero-dimensional quadrality proposal can be inferred from the two-dimensional Gadde-Gukov-Putrov triality. We consider two-dimensional $ \\mathcal{N} $ = (0, 2) SQCD compactified on a sphere with the half-topological twist. For a convenient choice of R-charge, the zero-mode sector on the sphere gives rise to a simple $ \\mathcal{N} $ = 1 gauged matrix model. Triality on the sphere then implies a triality relation for the supersymmetric matrix model, which can be completed to the full quadrality.
National Research Council Canada - National Science Library
Ingel, R
1999-01-01
.... Projection operators are employed for the model reduction or condensation process. Interpolation is then introduced over a user defined frequency window, which can have real and imaginary boundaries and be quite large. Hermitian...
Two-dimensional dynamics of elasto-inertial turbulence and its role in polymer drag reduction
Sid, S.; Terrapon, V. E.; Dubief, Y.
2018-02-01
The goal of the present study is threefold: (i) to demonstrate the two-dimensional nature of the elasto-inertial instability in elasto-inertial turbulence (EIT), (ii) to identify the role of the bidimensional instability in three-dimensional EIT flows, and (iii) to establish the role of the small elastic scales in the mechanism of self-sustained EIT. Direct numerical simulations of viscoelastic fluid flows are performed in both two- and three-dimensional straight periodic channels using the Peterlin finitely extensible nonlinear elastic model (FENE-P). The Reynolds number is set to Reτ=85 , which is subcritical for two-dimensional flows but beyond the transition for three-dimensional ones. The polymer properties selected correspond to those of typical dilute polymer solutions, and two moderate Weissenberg numbers, Wiτ=40 ,100 , are considered. The simulation results show that sustained turbulence can be observed in two-dimensional subcritical flows, confirming the existence of a bidimensional elasto-inertial instability. The same type of instability is also observed in three-dimensional simulations where both Newtonian and elasto-inertial turbulent structures coexist. Depending on the Wi number, one type of structure can dominate and drive the flow. For large Wi values, the elasto-inertial instability tends to prevail over the Newtonian turbulence. This statement is supported by (i) the absence of typical Newtonian near-wall vortices and (ii) strong similarities between two- and three-dimensional flows when considering larger Wi numbers. The role of small elastic scales is investigated by introducing global artificial diffusion (GAD) in the hyperbolic transport equation for polymers. The aim is to measure how the flow reacts when the smallest elastic scales are progressively filtered out. The study results show that the introduction of large polymer diffusion in the system strongly damps a significant part of the elastic scales that are necessary to feed
Ico, G; Myung, A; Kim, B S; Myung, N V; Nam, J
2018-02-08
Despite the significant potential of organic piezoelectric materials in the electro-mechanical or mechano-electrical applications that require light and flexible material properties, the intrinsically low piezoelectric performance as compared to traditional inorganic materials has limited their full utilization. In this study, we demonstrate that dimensional reduction of poly(vinylidene fluoride trifluoroethylene) (P(VDF-TrFE)) at the nanoscale by electrospinning, combined with an appropriate thermal treatment, induces a transformative enhancement in piezoelectric performance. Specifically, the piezoelectric coefficient (d 33 ) reached up to -108 pm V -1 , approaching that of inorganic counterparts. Electrospun mats composed of thermo-treated 30 nm nanofibers with a thickness of 15 μm produced a consistent peak-to-peak voltage of 38.5 V and a power output of 74.1 μW at a strain of 0.26% while sustaining energy production over 10k repeated actuations. The exceptional piezoelectric performance was realized by the enhancement of piezoelectric dipole alignment and the materialization of flexoelectricity, both from the synergistic effects of dimensional reduction and thermal treatment. Our findings suggest that dimensionally controlled and thermally treated electrospun P(VDF-TrFE) nanofibers provide an opportunity to exploit their flexibility and durability for mechanically challenging applications while matching the piezoelectric performance of brittle, inorganic piezoelectric materials.
Transport Methods Conquering the Seven-Dimensional Mountain
International Nuclear Information System (INIS)
Graziani, F; Olson, G
2003-01-01
In a wide variety of applications, a significant fraction of the momentum and energy present in a physical problem is carried by the transport of particles. Depending on the circumstances, the types of particles might involve some or all of photons, neutrinos, charged particles, or neutrons. In application areas that use transport, the computational time is usually dominated by the transport calculation. Therefore, there is a potential for great synergy; progress in transport algorithms could help quicken the time to solution for many applications. The complexity, and hence expense, involved in solving the transport problem can be understood by realizing that the general solution to the Boltzmann transport equation is seven dimensional: 3 spatial coordinates, 2 angles, 1 time, and 1 for speed or energy. Low-order approximations to the transport equation are frequently used due in part to physical justification but many times simply because a solution to the full transport problem is too computationally expensive. An example is the diffusion equation, which effectively drops the two angles in phase space by assuming that a linear representation in angle is adequate. Another approximation is the grey approximation, which drops the energy variable by averaging over it. If the grey approximation is applied to the diffusion equation, the expense of solving what amounts to the simplest possible description of transport is roughly equal to the cost of implicit computational fluid dynamics. It is clear therefore, that for those application areas needing some form of transport, fast, accurate and robust transport algorithms can lead to an increase in overall code performance and a decrease in time to solution. The seven-dimensional nature of transport means that factors of 100 or 1000 improvement in computer speed or memory are quickly absorbed in slightly higher resolution in space, angle, and energy. Therefore, the biggest advances in the last few years and in the next
Shi, Chengdi; Cai, Leyi; Hu, Wei; Sun, Junying
2017-09-19
ABSTRACTS Objective: To study the method of X-ray diagnosis of unstable pelvic fractures displaced in three-dimensional (3D) space and its clinical application in closed reduction. Five models of hemipelvic displacement were made in an adult pelvic specimen. Anteroposterior radiographs of the pelvis were analyzed in PACS. The method of X-ray diagnosis was applied in closed reductions. From February 2012 to June 2016, 23 patients (15 men, 8 women; mean age, 43.4 years) with unstable pelvic fractures were included. All patients were treated by closed reduction and percutaneous cannulate screw fixation of the pelvic ring. According to Tile's classification, the patients were classified into type B1 in 7 cases, B2 in 3, B3 in 3, C1 in 5, C2 in 3, and C3 in 2. The operation time and intraoperative blood loss were recorded. Postoperative images were evaluated by Matta radiographic standards. Five models of displacement were made successfully. The X-ray features of the models were analyzed. For clinical patients, the average operation time was 44.8 min (range, 20-90 min) and the average intraoperative blood loss was 35.7 (range, 20-100) mL. According to the Matta standards, 7 cases were excellent, 12 cases were good, and 4 were fair. The displacements in 3D space of unstable pelvic fractures can be diagnosed rapidly by X-ray analysis to guide closed reduction, with a satisfactory clinical outcome.
A new method for the chemoselective reduction of aldehydes and ...
Indian Academy of Sciences (India)
Department of Chemistry, Akdeniz University, 07058, Antalya, Turkey e-mail: ... Kinetics of reduction of aldehydes and ketones to corresponding alcohols were also examined and .... hol and unreducted ketone remain in organic phase. The.
Dimension Reduction and Discretization in Stochastic Problems by Regression Method
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
1996-01-01
The chapter mainly deals with dimension reduction and field discretizations based directly on the concept of linear regression. Several examples of interesting applications in stochastic mechanics are also given.Keywords: Random fields discretization, Linear regression, Stochastic interpolation, ...
Green functions and dimensional reduction of quantum fields on product manifolds
International Nuclear Information System (INIS)
Haba, Z
2008-01-01
We discuss Euclidean Green functions on product manifolds P=N x M. We show that if M is compact and N is not compact then the Euclidean field on P can be approximated by its zero mode which is a Euclidean field on N. We estimate the remainder of this approximation. We show that for large distances on N the remainder is small. If P=R D-1 x S β , where S β is a circle of radius β, then the result reduces to the well-known approximation of the D-dimensional finite temperature quantum field theory by (D - 1)-dimensional one in the high-temperature limit. Analytic continuation of Euclidean fields is discussed briefly
Mittal, Yogesh; Varghese, K George; Mohan, S; Jayakumar, N; Chhag, Somil
2016-03-01
Three dimensional titanium plating system was developed by Farmand in 1995 to meet the requirements of semi rigid fixation with lesser complication. The purpose of this in vivo prospective study was to evaluate and compare the clinical effectiveness of three dimensional and two dimensional Titanium miniplates for open reduction and fixation of mandibular parasymphysis fracture. Thirty patients with non-comminuted mandibular parasymphysis fractures were divided randomly into two equal groups and were treated with 2 mm 3D and 2D miniplate system respectively. All patients were systematically monitored at 1st, 2nd, 3rd, 6th week, 3rd and 6th month postoperatively. The outcome parameters recorded were severity of pain, infection, mobility, occlusion derangement, paresthesia and implant failure. The data so collected was analyzed using independent t test and Chi square test (α = .05). The results showed that one patient in each group had post-operative infection, occlusion derangement and mobility (p > .05). In Group A, one patient had paresthesia while in Group B, two patients had paresthesia (p > .05). None of the patients in both the groups had implant failure. There was no statistically significant difference between 3D and 2D miniplate system in all the recorded parameters at all the follow-ups (p > .05). 3D miniplates were found to be better than 2D miniplates in terms of cost, ease of surgery and operative time. However, 3D miniplates were unfavorable for cases where fracture line was oblique and in close proximity to mental foramen, where they were difficult to adapt and more chances for tooth-root damage and inadvertent injury to the mental nerve due to traction.
Comparative study of synthesis and reduction methods for graphene oxide
Alazmi, Amira; Rasul, Shahid; Patole, Shashikant P.; Da Costa, Pedro M. F. J.
2016-01-01
Graphene oxide (GO) and reduced graphene oxide (rGO) have congregated much interest as promising active materials for a variety of applications such as electrodes for supercapacitors. Yet, partially given the absence of comparative studies in synthesis methodologies, a lack of understanding persists on how to best tailor these materials. In this work, the effect of using different graphene oxidation-reduction strategies in the structure and chemistry of rGOs is systematically discussed. Two of the most popular oxidation routes in the literature were used to obtain GO. Subsequently, two sets of rGO powders were synthesised employing three different reduction routes, totalling six separate products. It is shown that the extension of the structural rearrangement in rGOs is not just dependent on the reduction step but also on the approach followed for the initial graphite oxidation.
Some variance reduction methods for numerical stochastic homogenization.
Blanc, X; Le Bris, C; Legoll, F
2016-04-28
We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).
Comparative study of synthesis and reduction methods for graphene oxide
Alazmi, Amira
2016-05-14
Graphene oxide (GO) and reduced graphene oxide (rGO) have congregated much interest as promising active materials for a variety of applications such as electrodes for supercapacitors. Yet, partially given the absence of comparative studies in synthesis methodologies, a lack of understanding persists on how to best tailor these materials. In this work, the effect of using different graphene oxidation-reduction strategies in the structure and chemistry of rGOs is systematically discussed. Two of the most popular oxidation routes in the literature were used to obtain GO. Subsequently, two sets of rGO powders were synthesised employing three different reduction routes, totalling six separate products. It is shown that the extension of the structural rearrangement in rGOs is not just dependent on the reduction step but also on the approach followed for the initial graphite oxidation.
Wu, Xian-Qian; Wang, Xi; Wei, Yan-Peng; Song, Hong-Wei; Huang, Chen-Guang
2012-06-01
Shot peening is a widely used surface treatment method by generating compressive residual stress near the surface of metallic materials to increase fatigue life and resistance to corrosion fatigue, cracking, etc. Compressive residual stress and dent profile are important factors to evaluate the effectiveness of shot peening process. In this paper, the influence of dimensionless parameters on maximum compressive residual stress and maximum depth of the dent were investigated. Firstly, dimensionless relations of processing parameters that affect the maximum compressive residual stress and the maximum depth of the dent were deduced by dimensional analysis method. Secondly, the influence of each dimensionless parameter on dimensionless variables was investigated by the finite element method. Furthermore, related empirical formulas were given for each dimensionless parameter based on the simulation results. Finally, comparison was made and good agreement was found between the simulation results and the empirical formula, which shows that a useful approach is provided in this paper for analyzing the influence of each individual parameter.
Tsukagoshi, Yuta; Kamada, Hiroshi; Kamegaya, Makoto; Takeuchi, Ryoko; Nakagawa, Shogo; Tomaru, Yohei; Tanaka, Kenta; Onishi, Mio; Nishino, Tomofumi; Yamazaki, Masashi
2018-05-02
Previous reports on patients with developmental dysplasia of the hip (DDH) showed that the prereduced femoral head was notably smaller and more nonspherical than the intact head, with growth failure observed at the proximal posteromedial area. We evaluated the shape of the femoral head cartilage in patients with DDH before and after reduction, with size and sphericity assessed using 3-dimensional (3D) magnetic resonance imaging (MRI). We studied 10 patients with unilateral DDH (all female) who underwent closed reduction. Patients with avascular necrosis of the femoral head on the plain radiograph 1 year after reduction were excluded. 3D MRI was performed before reduction and after reduction, at 2 years of age. 3D-image analysis software was used to reconstruct the multiplanes. After setting the axial, coronal, and sagittal planes in the software (based on the femoral shaft and neck axes), the smallest sphere that included the femoral head cartilage was drawn, the diameter was measured, and the center of the sphere was defined as the femoral head center. We measured the distance between the center and cartilage surface every 30 degrees on the 3 reconstructed planes. Sphericity of the femoral head was calculated using a ratio (the distance divided by each radius) and compared between prereduction and postreduction. The mean patient age was 7±3 and 26±3 months at the first and second MRI, respectively. The mean duration between the reduction and second MRI was 18±3 months. The femoral head diameter was 26.7±1.5 and 26.0±1.6 mm on the diseased and intact sides, respectively (P=0.069). The ratios of the posteromedial area on the axial plane and the proximoposterior area on the sagittal plane after reduction were significantly larger than before reduction (P<0.01). We demonstrated that the size of the reduced femoral head was nearly equal to that of the intact femoral head and that the growth failure area of the head before reduction, in the proximal posteromedial
International Nuclear Information System (INIS)
Ma Songhua; Fang Jianping; Zheng Chunlong
2009-01-01
By means of an extended mapping method and a variable separation method, a series of solitary wave solutions, periodic wave solutions and variable separation solutions to the (2 + 1)-dimensional breaking soliton system is derived.
Rubin's CMS reduction method for general state-space models
Kraker, de A.; Campen, van D.H.
1996-01-01
In this paper the Rubin CMS procedure for the reduction and successive coupling of undamped structural subsystems with symmetric system matrices will be modified for the case of general damping. The final coordinate transformation is based on the use of complex (residual) flexibility modes,
Application of Exp-function method for (2 + 1)-dimensional nonlinear evolution equations
International Nuclear Information System (INIS)
Bekir, Ahmet; Boz, Ahmet
2009-01-01
In this paper, the Exp-function method is used to construct solitary and soliton solutions of (2 + 1)-dimensional nonlinear evolution equations. (2 + 1)-dimensional breaking soliton (Calogero) equation, modified Zakharov-Kuznetsov and Konopelchenko-Dubrovsky equations are chosen to illustrate the effectiveness of the method. The method is straightforward and concise, and its applications are promising. The Exp-function method presents a wider applicability for handling nonlinear wave equations.
On reduction and exact solutions of nonlinear many-dimensional Schroedinger equations
International Nuclear Information System (INIS)
Barannik, A.F.; Marchenko, V.A.; Fushchich, V.I.
1991-01-01
With the help of the canonical decomposition of an arbitrary subalgebra of the orthogonal algebra AO(n) the rank n and n-1 maximal subalgebras of the extended isochronous Galileo algebra, the rank n maximal subalgebras of the generalized extended classical Galileo algebra AG(a,n) the extended special Galileo algebra AG(2,n) and the extended whole Galileo algebra AG(3,n) are described. By using the rank n subalgebras, ansatze reducing the many dimensional Schroedinger equations to ordinary differential equations is found. With the help of the reduced equation solutions exact solutions of the Schroedinger equation are considered
Dimensional reduction of the Standard Model coupled to a new singlet scalar field
Energy Technology Data Exchange (ETDEWEB)
Brauner, Tomáš [Faculty of Science and Technology, University of Stavanger,N-4036 Stavanger (Norway); Tenkanen, Tuomas V.I. [Department of Physics and Helsinki Institute of Physics,P.O. Box 64, FI-00014 University of Helsinki (Finland); Tranberg, Anders [Faculty of Science and Technology, University of Stavanger,N-4036 Stavanger (Norway); Vuorinen, Aleksi [Department of Physics and Helsinki Institute of Physics,P.O. Box 64, FI-00014 University of Helsinki (Finland); Weir, David J. [Faculty of Science and Technology, University of Stavanger,N-4036 Stavanger (Norway); Department of Physics and Helsinki Institute of Physics,P.O. Box 64, FI-00014 University of Helsinki (Finland)
2017-03-01
We derive an effective dimensionally reduced theory for the Standard Model augmented by a real singlet scalar. We treat the singlet as a superheavy field and integrate it out, leaving an effective theory involving only the Higgs and SU(2){sub L}×U(1){sub Y} gauge fields, identical to the one studied previously for the Standard Model. This opens up the possibility of efficiently computing the order and strength of the electroweak phase transition, numerically and nonperturbatively, in this extension of the Standard Model. Understanding the phase diagram is crucial for models of electroweak baryogenesis and for studying the production of gravitational waves at thermal phase transitions.
Algorithm for statistical noise reduction in three-dimensional ion implant simulations
International Nuclear Information System (INIS)
Hernandez-Mangas, J.M.; Arias, J.; Jaraiz, M.; Bailon, L.; Barbolla, J.
2001-01-01
As integrated circuit devices scale into the deep sub-micron regime, ion implantation will continue to be the primary means of introducing dopant atoms into silicon. Different types of impurity profiles such as ultra-shallow profiles and retrograde profiles are necessary for deep submicron devices in order to realize the desired device performance. A new algorithm to reduce the statistical noise in three-dimensional ion implant simulations both in the lateral and shallow/deep regions of the profile is presented. The computational effort in BCA Monte Carlo ion implant simulation is also reduced
International Nuclear Information System (INIS)
Chen, G.S.; Christenson, J.M.
1985-01-01
In this paper, the authors present some initial results from an investigation of the application of a locally one-dimensional (LOD) finite difference method to the solution of the two-dimensional, two-group reactor kinetics equations. Although the LOD method is relatively well known, it apparently has not been previously applied to the space-time kinetics equations. In this investigation, the LOD results were benchmarked against similar computational results (using the same computing environment, the same programming structure, and the same sample problems) obtained by the TWIGL program. For all of the problems considered, the LOD method provided accurate results in one-half to one-eight of the time required by the TWIGL program
Directory of Open Access Journals (Sweden)
Ernestina Martel
2018-06-01
Full Text Available Dimensionality reduction represents a critical preprocessing step in order to increase the efficiency and the performance of many hyperspectral imaging algorithms. However, dimensionality reduction algorithms, such as the Principal Component Analysis (PCA, suffer from their computationally demanding nature, becoming advisable for their implementation onto high-performance computer architectures for applications under strict latency constraints. This work presents the implementation of the PCA algorithm onto two different high-performance devices, namely, an NVIDIA Graphics Processing Unit (GPU and a Kalray manycore, uncovering a highly valuable set of tips and tricks in order to take full advantage of the inherent parallelism of these high-performance computing platforms, and hence, reducing the time that is required to process a given hyperspectral image. Moreover, the achieved results obtained with different hyperspectral images have been compared with the ones that were obtained with a field programmable gate array (FPGA-based implementation of the PCA algorithm that has been recently published, providing, for the first time in the literature, a comprehensive analysis in order to highlight the pros and cons of each option.
Ly, Cheng
2013-10-01
The population density approach to neural network modeling has been utilized in a variety of contexts. The idea is to group many similar noisy neurons into populations and track the probability density function for each population that encompasses the proportion of neurons with a particular state rather than simulating individual neurons (i.e., Monte Carlo). It is commonly used for both analytic insight and as a time-saving computational tool. The main shortcoming of this method is that when realistic attributes are incorporated in the underlying neuron model, the dimension of the probability density function increases, leading to intractable equations or, at best, computationally intensive simulations. Thus, developing principled dimension-reduction methods is essential for the robustness of these powerful methods. As a more pragmatic tool, it would be of great value for the larger theoretical neuroscience community. For exposition of this method, we consider a single uncoupled population of leaky integrate-and-fire neurons receiving external excitatory synaptic input only. We present a dimension-reduction method that reduces a two-dimensional partial differential-integral equation to a computationally efficient one-dimensional system and gives qualitatively accurate results in both the steady-state and nonequilibrium regimes. The method, termed modified mean-field method, is based entirely on the governing equations and not on any auxiliary variables or parameters, and it does not require fine-tuning. The principles of the modified mean-field method have potential applicability to more realistic (i.e., higher-dimensional) neural networks.
Classification Methods for High-Dimensional Genetic Data
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2014-01-01
Roč. 34, č. 1 (2014), s. 10-18 ISSN 0208-5216 Institutional support: RVO:67985807 Keywords : multivariate statistics * classification analysis * shrinkage estimation * dimension reduction * data mining Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.646, year: 2014
Practical methods of dose reduction to the bladder wall
International Nuclear Information System (INIS)
Smith, E.M.; Warner, G.G.
1976-01-01
The radiation dose to the bladder wall following the administration of radionuclides to patients can be reduced by a factor between 25 percent and 75 percent when the effective half-life for the radioactivity entering the urine is two hours or less. A significant but smaller reduction in dose to the gonads may also be achieved in situations where the major fraction of the administered activity is rapidly excreted in the urine. This reduction in dose is achieved by ensuring that the patient has between 50 and 150 ml of urine in his bladder when the radioactivity is injected, and is encouraged to void between one and two hours after the activity has been administered. The interrelationship of voiding schedule, effective half-life, initial urine volume, and demand urination has been analyzed in these studies. In addition, the significance of the rate of urine production and volume of urine in the bladder on the radiation dose to the bladder is demonstrated
Methods for preparation of three-dimensional bodies
Mulligan, Anthony C.; Rigali, Mark J.; Sutaria, Manish P.; Artz, Gregory J.; Gafner, Felix H.; Vaidyanathan, K. Ranji
2004-09-28
Processes for mechanically fabricating two and three-dimensional fibrous monolith composites include preparing a fibrous monolith filament from a core composition of a first powder material and a boundary material of a second powder material. The filament includes a first portion of the core composition surrounded by a second portion of the boundary composition. One or more filaments are extruded through a mechanically-controlled deposition nozzle onto a working surface to create a fibrous monolith composite object. The objects may be formed directly from computer models and have complex geometries.
Energy Technology Data Exchange (ETDEWEB)
Prell, Daniel; Kyriakou, Yiannis; Beister, Marcel; Kalender, Willi A [Institute of Medical Physics, University of Erlangen-Nuernberg, Henkestrasse 91, 91052 Erlangen (Germany)], E-mail: daniel.prell@imp.uni-erlangen.de
2009-11-07
Metallic implants generate streak-like artifacts in flat-detector computed tomography (FD-CT) reconstructed volumetric images. This study presents a novel method for reducing these disturbing artifacts by inserting discarded information into the original rawdata using a three-step correction procedure and working directly with each detector element. Computation times are minimized by completely implementing the correction process on graphics processing units (GPUs). First, the original volume is corrected using a three-dimensional interpolation scheme in the rawdata domain, followed by a second reconstruction. This metal artifact-reduced volume is then segmented into three materials, i.e. air, soft-tissue and bone, using a threshold-based algorithm. Subsequently, a forward projection of the obtained tissue-class model substitutes the missing or corrupted attenuation values directly for each flat detector element that contains attenuation values corresponding to metal parts, followed by a final reconstruction. Experiments using tissue-equivalent phantoms showed a significant reduction of metal artifacts (deviations of CT values after correction compared to measurements without metallic inserts reduced typically to below 20 HU, differences in image noise to below 5 HU) caused by the implants and no significant resolution losses even in areas close to the inserts. To cover a variety of different cases, cadaver measurements and clinical images in the knee, head and spine region were used to investigate the effectiveness and applicability of our method. A comparison to a three-dimensional interpolation correction showed that the new approach outperformed interpolation schemes. Correction times are minimized, and initial and corrected images are made available at almost the same time (12.7 s for the initial reconstruction, 46.2 s for the final corrected image compared to 114.1 s and 355.1 s on central processing units (CPUs))
International Nuclear Information System (INIS)
Prell, Daniel; Kyriakou, Yiannis; Beister, Marcel; Kalender, Willi A
2009-01-01
Metallic implants generate streak-like artifacts in flat-detector computed tomography (FD-CT) reconstructed volumetric images. This study presents a novel method for reducing these disturbing artifacts by inserting discarded information into the original rawdata using a three-step correction procedure and working directly with each detector element. Computation times are minimized by completely implementing the correction process on graphics processing units (GPUs). First, the original volume is corrected using a three-dimensional interpolation scheme in the rawdata domain, followed by a second reconstruction. This metal artifact-reduced volume is then segmented into three materials, i.e. air, soft-tissue and bone, using a threshold-based algorithm. Subsequently, a forward projection of the obtained tissue-class model substitutes the missing or corrupted attenuation values directly for each flat detector element that contains attenuation values corresponding to metal parts, followed by a final reconstruction. Experiments using tissue-equivalent phantoms showed a significant reduction of metal artifacts (deviations of CT values after correction compared to measurements without metallic inserts reduced typically to below 20 HU, differences in image noise to below 5 HU) caused by the implants and no significant resolution losses even in areas close to the inserts. To cover a variety of different cases, cadaver measurements and clinical images in the knee, head and spine region were used to investigate the effectiveness and applicability of our method. A comparison to a three-dimensional interpolation correction showed that the new approach outperformed interpolation schemes. Correction times are minimized, and initial and corrected images are made available at almost the same time (12.7 s for the initial reconstruction, 46.2 s for the final corrected image compared to 114.1 s and 355.1 s on central processing units (CPUs)).
International Nuclear Information System (INIS)
Ma, Yanjiao; Wang, Hui; Feng, Hanqing; Ji, Shan; Mao, Xuefeng; Wang, Rongfang
2014-01-01
Graphical abstract: Three-dimentional Fe, N-doped carbon foams prepared by two steps exhibited comparable catalytic activity for oxygen reduction reaction to commercial Pt/C due to the unique structure and the synergistic effect of Fe and N atoms. - Highlights: • Three-dimensional Fe, N-doped carbon foam (3D-CF) were prepared. • 3D-CF exhibits comparable catalytic activity to Pt/C for oxygen reduction reaction. • The enhanced activity of 3D-CF results of its unique structure. - Abstract: Three-dimensional (3D) Fe, N-doped carbon foams (3D-CF) as efficient cathode catalysts for the oxygen reduction reaction (ORR) in alkaline solution are reported. The 3D-CF exhibit interconnected hierarchical pore structure. In addition, Fe, N-doped carbon without porous strucuture (Fe-N-C) and 3D N-doped carbon without Fe (3D-CF’) are prepared to verify the electrocatalytic activity of 3D-CF. The electrocatalytic performance of as-prepared 3D-CF for ORR shows that the onset potential on 3D-CF electrode positively shifts about 41 mV than those of 3D-CF’ and Fe-N-C respectively. In addition, the onset potential on 3D-CF electrode for ORR is about 27 mV more negative than that on commercial Pt/C electrode. 3D-CF also show better methanol tolerance and durability than commercial Pt/C catalyst. These results show that to synthesize 3D hierarchical pores with high specific surface area is an efficient way to improve the ORR performance
Dimensional reduction of a Lorentz and CPT-violating Maxwell-Chern-Simons model
Energy Technology Data Exchange (ETDEWEB)
Belich, H. Jr.; Helayel Neto, J.A. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil). Coordenacao de Teoria de Campos e Particulas; Grupo de Fisica Teorica Jose Leite Lopes, Petropolis, RJ (Brazil); E-mails: belich@cbpf.br; helayel@cbpf.br; Ferreira, M.M. Jr. [Grupo de Fisica Teorica Jose Leite Lopes, Petropolis, RJ (Brazil); Maranhao Univ., Sao Luiz, MA (Brazil). Dept. de Fisica]. E-mail: manojr@cbpf.br; Orlando, M.T.D. [Grupo de Fisica Teorica Jose Leite Lopes, Petropolis, RJ (Brazil); Espirito Santo Univ., Vitoria, ES (Brazil). Dept. de Fisica e Quimica; E-mail: orlando@cce.ufes.br
2003-01-01
Taking as starting point a Lorentz and CPT non-invariant Chern-Simons-like model defined in 1+3 dimensions, we proceed realizing its dimensional to D = 1+2. One then obtains a new planar model, composed by the Maxwell-Chern-Simons (MCS) sector, a Klein-Gordon massless scalar field, and a coupling term that mixes the gauge field to the external vector, {nu}{sup {mu}}. In spite of breaking Lorentz invariance in the particle frame, this model may preserve the CPT symmetry for a single particular choice of {nu}{sup {mu}} . Analyzing the dispersion relations, one verifies that the reduced model exhibits stability, but the causality can be jeopardized by some modes. The unitary of the gauge sector is assured without any restriction , while the scalar sector is unitary only in the space-like case. (author)
Feature Space Dimensionality Reduction for Real-Time Vision-Based Food Inspection
Directory of Open Access Journals (Sweden)
Mai Moussa CHETIMA
2009-03-01
Full Text Available Machine vision solutions are becoming a standard for quality inspection in several manufacturing industries. In the processed-food industry where the appearance attributes of the product are essential to customer’s satisfaction, visual inspection can be reliably achieved with machine vision. But such systems often involve the extraction of a larger number of features than those actually needed to ensure proper quality control, making the process less efficient and difficult to tune. This work experiments with several feature selection techniques in order to reduce the number of attributes analyzed by a real-time vision-based food inspection system. Identifying and removing as much irrelevant and redundant information as possible reduces the dimensionality of the data and allows classification algorithms to operate faster. In some cases, accuracy on classification can even be improved. Filter-based and wrapper-based feature selectors are experimentally evaluated on different bakery products to identify the best performing approaches.
Dimensional reduction of a Lorentz and CPT-violating Maxwell-Chern-Simons model
International Nuclear Information System (INIS)
Belich, H. Jr.; Helayel Neto, J.A.; Ferreira, M.M. Jr.; Maranhao Univ., Sao Luiz, MA; Orlando, M.T.D.; Espirito Santo Univ., Vitoria, ES
2003-01-01
Taking as starting point a Lorentz and CPT non-invariant Chern-Simons-like model defined in 1+3 dimensions, we proceed realizing its dimensional to D = 1+2. One then obtains a new planar model, composed by the Maxwell-Chern-Simons (MCS) sector, a Klein-Gordon massless scalar field, and a coupling term that mixes the gauge field to the external vector, ν μ . In spite of breaking Lorentz invariance in the particle frame, this model may preserve the CPT symmetry for a single particular choice of ν μ . Analyzing the dispersion relations, one verifies that the reduced model exhibits stability, but the causality can be jeopardized by some modes. The unitary of the gauge sector is assured without any restriction , while the scalar sector is unitary only in the space-like case. (author)
One-dimensional calculation of flow branching using the method of characteristics
International Nuclear Information System (INIS)
Meier, R.W.; Gido, R.G.
1978-05-01
In one-dimensional flow systems, the flow often branches, such as at a tee or manifold. The study develops a formulation for calculating the flow through branch points with one-dimensional method of characteristics equations. The resultant equations were verified by comparison with experimental measurements
One-dimensional treatment of polyatomic crystals by the Laplace transform method
International Nuclear Information System (INIS)
Rosato, A.; Santana, P.H.A.
1976-01-01
The one dimensional periodic potential problem is solved using the Laplace transform method and a condensed expression for the relation E x k and effective mass for one electron in a polyatomic structure is determined. Applications related to the effect of the asymmetry of the potential upon the one dimensional band structure are discussed [pt
Moderator feedback effects in two-dimensional nodal methods for pressurized water reactor analysis
International Nuclear Information System (INIS)
Downar, T.J.
1987-01-01
A method was developed for incorporating moderator feedback effects in two-dimensional nodal codes used for pressurized water reactor (PWR) neutronic analysis. Equations for the assembly average quality and density are developed in terms of the assembly power calculated in two dimensions. The method is validated with a Westinghouse PWR using the Electric Power Research Institute code SIMULATE-E. Results show a several percent improvement is achieved in the two-dimensional power distribution prediction compared to methods without moderator feedback
A Golub-Kahan-type reduction method for matrix pairs
Hochstenbach, M.E.; Reichel, L.; Yu, X.
2015-01-01
We describe a novel method for reducing a pair of large matrices {A;B} to a pair of small matrices {H;K}. The method is an extension of Golub-Kahan bidiagonalization to matrix pairs, and simplifies to the latter method when B is the identity matrix. Applications to Tikhonov regularization of large
A Golub-Kahan-type reduction method for matrix pairs
Hochstenbach, M.E.; Reichel, L.; Yu, X.
2015-01-01
We describe a novel method for reducing a pair of large matrices {A,B} to a pair of small matrices {H,K}. The method is an extension of Golub–Kahan bidiagonalization to matrix pairs, and simplifies to the latter method when B is the identity matrix. Applications to Tikhonov regularization of large
The boomerang osteotomy -- a new method of reduction malarplasty.
Nakanishi, Yuji; Nagasao, Tomohisa; Shimizu, Yusuke; Miyamoto, Junpei; Kishi, Kazuo; Fukuta, Keizo
2012-05-01
To achieve optimal outcomes in reduction malarplasty, it is important to preserve the natural curvature of the cheek while reducing the zygoma prominence and the width of the midface. The present article introduces an effective technique that aims to achieve these purposes. Through an intraoral approach, boomerang-shaped bone incision lines are marked on the anterior aspect of the zygomatico-maxillary junction. The lines are placed medial to the most prominent part of the zygoma. The zygomatic arch is divided at its posterior part through a small incision made in the pre-auricular region. By performing these manoeuvres, a unit of bone-composed of a part of the zygoma body and zygomatic arch - is mobilised. The mobilised bone is shifted medially, reducing the width of the midface and making the zygoma region less prominent. After performing reduction malarplasty for 89 patients (10 males and 79 females) using this technique, clinical outcomes were evaluated. Outcomes of the treatment was optimal, with over 80% of the patients evaluating the results as excellent in terms of effectiveness in malar prominence, facial width and symmetry. Because the continuity of the main part of the zygoma body and zygomatic arch is preserved in our technique, medial transfer of the zygoma is enabled while preserving the natural curvature of the malar region and the superior-inferior position of the zygomatic arch. Because of these advantages, we recommend our technique as an effective technique of reduction malarplasty. Copyright © 2012 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
SW Kang
2015-02-01
Full Text Available This article introduces an improved non-dimensional dynamic influence function method using a sub-domain method for efficiently extracting the eigenvalues and mode shapes of concave membranes with arbitrary shapes. The non-dimensional dynamic influence function method (non-dimensional dynamic influence function method, which was developed by the authors in 1999, gives highly accurate eigenvalues for membranes, plates, and acoustic cavities, compared with the finite element method. However, it needs the inefficient procedure of calculating the singularity of a system matrix in the frequency range of interest for extracting eigenvalues and mode shapes. To overcome the inefficient procedure, this article proposes a practical approach to make the system matrix equation of the concave membrane of interest into a form of algebraic eigenvalue problem. It is shown by several case studies that the proposed method has a good convergence characteristics and yields very accurate eigenvalues, compared with an exact method and finite element method (ANSYS.
Rumpler, Romain; Deü, Jean-François; Göransson, Peter
2012-11-01
Structural-acoustic finite element models including three-dimensional (3D) modeling of porous media are generally computationally costly. While being the most commonly used predictive tool in the context of noise reduction applications, efficient solution strategies are required. In this work, an original modal reduction technique, involving real-valued modes computed from a classical eigenvalue solver is proposed to reduce the size of the problem associated with the porous media. In the form presented in this contribution, the method is suited for homogeneous porous layers. It is validated on a 1D poro-acoustic academic problem and tested for its performance on a 3D application, using a subdomain decomposition strategy. The performance of the proposed method is estimated in terms of degrees of freedom downsizing, computational time enhancement, as well as matrix sparsity of the reduced system.
International Nuclear Information System (INIS)
Ikai, T.; Yoshimura, T.; Shinohara, A.; Takayama, T.; Sekine, T.
2006-01-01
Selenide capping hexatechnetium cluster complex [Tc 6 (μ 3 -Se) 8 CN 6 ] 4- (1) was prepared by the reactions of one-dimensional polymer complex [Tc 6 (μ 3 -Se) 8 Br 4 ] 2- and cyanides at high temperature. Similar reaction of sulfide capping hexatechnetium cluster complex, [Tc 6 (μ 3 -S) 8 Br 6 ] 4- with cyanide gave the terminal substituted complex [Tc 6 (μ 3 -S) 8 CN 6 ] 4- (2). The single-crystal X-ray analysis of 1 and 2, showed that the Tc-Tc bond lengths become longer with lager ionic radius of the face capping ligands in the order S -1 , and that of 2 showed it at 2119 cm -1 . Each of cyclic voltammogram of 1 and 2 showed a reversible one electron redox wave assignable to the Tc 6 III /Tc 5 III Tc IV process. These redox potentials shift to the positive about 0.4V compared to those of the Re cluster analogs. (author)
Catalyst and method for reduction of nitrogen oxides
Ott, Kevin C [Los Alamos, NM
2008-05-27
A Selective Catalytic Reduction (SCR) catalyst was prepared by slurry coating ZSM-5 zeolite onto a cordierite monolith, then subliming an iron salt onto the zeolite, calcining the monolith, and then dipping the monolith either into an aqueous solution of manganese nitrate and cerium nitrate and then calcining, or by similar treatment with separate solutions of manganese nitrate and cerium nitrate. The supported catalyst containing iron, manganese, and cerium showed 80 percent conversion at 113 degrees Celsius of a feed gas containing nitrogen oxides having 4 parts NO to one part NO.sub.2, about one equivalent ammonia, and excess oxygen; conversion improved to 94 percent at 147 degrees Celsius. N.sub.2O was not detected (detection limit: 0.6 percent N.sub.2O).
Discussion on calculation method of overburden cover for radon reduction
International Nuclear Information System (INIS)
Liang Jianlong; Zhou Xinghuo; Zhou Ju; Liu Huijuan
2010-01-01
The article collects a large number of experimental results from domestic researchers with regard to soil overburden experimental methods. Based on analyzing experimental results, some questions in determining requirements for overburden cover thickness, data processing method and negative intercept have been dis- cussed. (authors)
Effective method for construction of low-dimensional models for heat transfer process
Energy Technology Data Exchange (ETDEWEB)
Blinov, D.G.; Prokopov, V.G.; Sherenkovskii, Y.V.; Fialko, N.M.; Yurchuk, V.L. [National Academy of Sciences of Ukraine, Kiev (Ukraine). Inst. of Engineering Thermophysics
2004-12-01
A low-dimensional model based on the method of proper orthogonal decomposition (POD) and the method of polyargumental systems (MPS) for thermal conductivity problems with strongly localized source of heat has been presented. The key aspect of these methods is that they enable to avoid weak points of other projection methods, which consists in a priori choice of basis functions. It enables us to use the MPS method and the POD method as convenient means to construct low-dimensional models of heat and mass transfer problems. (Author)
Three-dimensional compound comparison methods and their application in drug discovery.
Shin, Woong-Hee; Zhu, Xiaolei; Bures, Mark Gregory; Kihara, Daisuke
2015-07-16
Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS) methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D). Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.
Three-Dimensional Compound Comparison Methods and Their Application in Drug Discovery
Directory of Open Access Journals (Sweden)
Woong-Hee Shin
2015-07-01
Full Text Available Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D, two-dimensional (2D, and three-dimensional (3D. Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.
Dimensional reduction of U(1) x SU(2) Chern-Simons bosonization: Application to the t - J model
International Nuclear Information System (INIS)
Marchetti, P.A.
1996-09-01
We perform a dimensional reduction of the U(1) x SU(2) Chern-Simons bosonization and apply it to the t - J model, relevant for high T c superconductors. This procedure yields a decomposition of the electron field into a product of two ''semionic'' fields, i.e. fields obeying Abelian braid statistics with statistics parameter θ = 1/4, one carrying the charge and the other the spin degrees of freedom. A mean field theory is then shown to reproduce correctly the large distance behaviour of the correlation functions of the 1D t - J model at >> J. This result shows that to capture the essential physical properties of the model one needs a specific ''semionic'' form of spin-charge separation. (author). 31 refs
International Nuclear Information System (INIS)
Rogers, C; Schief, W K
2011-01-01
A 2+1-dimensional version of a non-isothermal gas dynamic system with origins in the work of Ovsiannikov and Dyson on spinning gas clouds is shown to admit a Hamiltonian reduction which is completely integrable when the adiabatic index γ = 2. This nonlinear dynamical subsystem is obtained via an elliptic vortex ansatz which is intimately related to the construction of a Lax pair in the integrable case. The general solution of the gas dynamic system is derived in terms of Weierstrass (elliptic) functions. The latter derivation makes use of a connection with a stationary nonlinear Schrödinger equation and a Steen–Ermakov–Pinney equation, the superposition principle of which is based on the classical Lamé equation
Directory of Open Access Journals (Sweden)
Xiaoni Dong
2016-01-01
Full Text Available Process models and parameters are two critical steps for fault prognosis in the operation of rotating machinery. Due to the requirement for a short and rapid response, it is important to study robust sensor data representation schemes. However, the conventional holospectrum defined by one-dimensional or two-dimensional methods does not sufficiently present this information in both the frequency and time domains. To supply a complete holospectrum model, a new three-dimensional spatial representation method is proposed. This method integrates improved three-dimensional (3D holospectra and 3D filtered orbits, leading to the integration of radial and axial vibration features in one bearing section. The results from simulation and experimental analysis on a complex compressor show that the proposed method can present the real operational status and clearly reveal early faults, thus demonstrating great potential for condition-based maintenance prediction in industrial machinery.
A simple and efficient electrochemical reductive method for ...
Indian Academy of Sciences (India)
Administrator
This approach opens up a new, practical and green reducing method to prepare large- scale graphene. ... has the following significant advantages: (1) It is simple to operate. .... The authors thank the National High Technology Research.
Computerized simulation methods for dose reduction, in radiodiagnosis
International Nuclear Information System (INIS)
Brochi, M.A.C.
1990-01-01
The present work presents computational methods that allow the simulation of any situation encountered in diagnostic radiology. Parameters of radiographic techniques that yield a standard radiographic image, previously chosen, and so could compare the dose of radiation absorbed by the patient is studied. Initially the method was tested on a simple system composed of 5.0 cm of water and 1.0 mm of aluminium and, after verifying experimentally its validity, it was applied in breast and arm fracture radiographs. It was observed that the choice of the filter material is not an important factor, because analogous behaviours were presented by aluminum, iron, copper, gadolinium, and other filters. A method of comparison of materials based on the spectral match is shown. Both the results given by this simulation method and the experimental measurements indicate an equivalence of brass and copper, both more efficient than aluminium, in terms of exposition time, but not of dose. (author)
Cost reduction by using budgeting via the Kaizen method
Dorina Budugan; Iuliana Georgescu
2009-01-01
In the current conditions, continuous improvement is one of the main issues faced by the manag-ers of organizations. The Japanese use the term kaizen to designate continuous improvement. Budgeting via the kaizen method explicitly integrates improvement throughout the period budgeted in the budget data. Budget explanation via the kaizen method refers, on the one hand, to budgeting for the purposes of continuously improving the number of work hours per product unit, and, on the other hand, to t...
A computational method for the solution of one-dimensional ...
Indian Academy of Sciences (India)
embedding parameter p ∈ [0, 1], which is considered as a 'small parameter'. Consid- erable research work has recently been conducted in applying this method to a class of linear and nonlinear equations. This method was further developed and improved by He, and applied to nonlinear oscillators with discontinuities [1], ...
Reduction of scour around bridge piers using a modified method for vortex reduction
Directory of Open Access Journals (Sweden)
Entesar A.S. EL-Ghorab
2013-09-01
Full Text Available The current study presents a modified method to reduce the scour depth in front of the bridge piers. The idea of this method is based on reducing the stagnation of the flow and vortex formation in front of the pier. Therefore, the pressure difference around the pier is used for driving the flow through an arrangement of openings in front and connected to the openings along the pier’s side. A test program was planned using an experimental flume at the Hydraulics Research Institute (HRI and three hundred thirty six runs were conducted. Three different pier shapes, circular, square, and rectangular, provided with different openings arrangement and vertical spacing are tested. This method showed that the scour depth is reduced by 45% and also the volume of the scoured material is decreased up to 64%. These results were obtained using opening diameter of 20% of the pier width (w and vertical spacing equals the pier width (w. Also, a dimensionless regression equation was developed based on the obtained results. These findings when implemented in the field can easily safeguard the bridge piers and dramatically reduce the maintenance efforts and costs as well as improve the hydraulic performance of the water structure.
Incineration method for volume reduction and disposal of transuranic waste
International Nuclear Information System (INIS)
Borham, B.M.
1985-01-01
The Process Experimental Pilot Plant (PREPP) at Idaho National Engineering Laboratory (INEL) is designed to process 7 TPD of transuranic (TRU) waste producing 8.5 TPD of cemented waste and 4100 ACFM of combustion gases with a volume reduction of up to 17:1. The waste and its container are shredded then fed to a rotary kiln heated to 1700 0 F, then cooled and classified by a trommel screen. The fine portion is mixed with a cement grout which is placed with the coarse portion in steel drums for disposal at the Waste Isolation Pilot Plant (WIPP). The kiln off-gas is reheated to 2000 0 F to destroy any remaining hydrocarbons and toxic volatiles. The gases are cooled and passed in a venturi scrubber to remove particulates and corrosive gases. The venturi off-gas is passed through a mist eliminator and is reheated to 50 0 F above the dew point prior to passing through a High Efficiency Particulate Air (HEPA) filter. The scrub solution is concentrated to 25% solids by an inertial filter. The sludge containing the combustion chemical contaminants is encapsulated with the residue of the incinerated waste
Three dimensional iterative beam propagation method for optical waveguide devices
Ma, Changbao; Van Keuren, Edward
2006-10-01
The finite difference beam propagation method (FD-BPM) is an effective model for simulating a wide range of optical waveguide structures. The classical FD-BPMs are based on the Crank-Nicholson scheme, and in tridiagonal form can be solved using the Thomas method. We present a different type of algorithm for 3-D structures. In this algorithm, the wave equation is formulated into a large sparse matrix equation which can be solved using iterative methods. The simulation window shifting scheme and threshold technique introduced in our earlier work are utilized to overcome the convergence problem of iterative methods for large sparse matrix equation and wide-angle simulations. This method enables us to develop higher-order 3-D wide-angle (WA-) BPMs based on Pade approximant operators and the multistep method, which are commonly used in WA-BPMs for 2-D structures. Simulations using the new methods will be compared to the analytical results to assure its effectiveness and applicability.
A three-dimensional correlation method for registration of medical images in radiology
International Nuclear Information System (INIS)
Georgiou, Michalakis; Sfakianakis, George N.; Nagel, Joachim H.
1998-01-01
The availability of methods to register multi-modality images in order to 'fuse' them to correlate their information is increasingly becoming an important requirement for various diagnostic and therapeutic procedures. A variety of image registration methods have been developed but they remain limited to specific clinical applications. Assuming rigid body transformation, two images can be registered if their differences are calculated in terms of translation, rotation and scaling. This paper describes the development and testing of a new correlation based approach for three-dimensional image registration. First, the scaling factors introduced by the imaging devices are calculated and compensated for. Then, the two images become translation invariant by computing their three-dimensional Fourier magnitude spectra. Subsequently, spherical coordinate transformation is performed and then the three-dimensional rotation is computed using a novice approach referred to as p olar Shells . The method of polar shells maps the three angles of rotation into one rotation and two translations of a two-dimensional function and then proceeds to calculate them using appropriate transformations based on the Fourier invariance properties. A basic assumption in the method is that the three-dimensional rotation is constrained to one large and two relatively small angles. This assumption is generally satisfied in normal clinical settings. The new three-dimensional image registration method was tested with simulations using computer generated phantom data as well as actual clinical data. Performance analysis and accuracy evaluation of the method using computer simulations yielded errors in the sub-pixel range. (authors)
Levakhina, Yulia
2014-01-01
Yulia Levakhina gives an introduction to the major challenges of image reconstruction in Digital Tomosynthesis (DT), particularly to the connection of the reconstruction problem with the incompleteness of the DT dataset. The author discusses the factors which cause the formation of limited angle artifacts and proposes how to account for them in order to improve image quality and axial resolution of modern DT. The addressed methods include a weighted non-linear back projection scheme for algebraic reconstruction and?novel dual-axis acquisition geometry. All discussed algorithms and methods are supplemented by detailed illustrations, hints for practical implementation, pseudo-code, simulation results and real patient case examples.
Reduction Methods for Real-time Simulations in Hybrid Testing
DEFF Research Database (Denmark)
Andersen, Sebastian
2016-01-01
Hybrid testing constitutes a cost-effective experimental full scale testing method. The method was introduced in the 1960's by Japanese researchers, as an alternative to conventional full scale testing and small scale material testing, such as shake table tests. The principle of the method...... is performed on a glass fibre reinforced polymer composite box girder. The test serves as a pilot test for prospective real-time tests on a wind turbine blade. The Taylor basis is implemented in the test, used to perform the numerical simulations. Despite of a number of introduced errors in the real...... is to divide a structure into a physical substructure and a numerical substructure, and couple these in a test. If the test is conducted in real-time it is referred to as real time hybrid testing. The hybrid testing concept has developed significantly since its introduction in the 1960', both with respect...
International Nuclear Information System (INIS)
Shen, Junlin; Du, Xiangying; Guo, Daode; Cao, Lizhen; Gao, Yan; Bai, Mei; Li, Pengyu; Liu, Jiabin; Li, Kuncheng
2013-01-01
Purpose: To investigate the potential of noise-based tube current reduction method with iterative reconstruction to reduce radiation exposure while achieving consistent image quality in coronary CT angiography (CCTA). Materials and methods: 294 patients underwent CCTA on a 64-detector row CT equipped with iterative reconstruction. 102 patients with fixed tube current were assigned to Group 1, which was used to establish noise-based tube current modulation formulas, where tube current was modulated by the noise of test bolus image. 192 patients with noise-based tube current were randomly assigned to Group 2 and Group 3. Filtered back projection was applied for Group 2 and iterative reconstruction for Group 3. Qualitative image quality was assessed with a 5 point score. Image noise, signal intensity, volume CT dose index, and dose-length product were measured. Results: The noise-based tube current modulation formulas were established through regression analysis using image noise measurements in Group 1. Image noise was precisely maintained at the target value of 35.00 HU with small interquartile ranges for Group 2 (34.17–35.08 HU) and Group 3 (34.34–35.03 HU), while it was from 28.41 to 36.49 HU for Group 1. All images in the three groups were acceptable for diagnosis. A relative 14% and 41% reduction in effective dose for Group 2 and Group 3 were observed compared with Group 1. Conclusion: Adequate image quality could be maintained at a desired and consistent noise level with overall 14% dose reduction using noise-based tube current reduction method. The use of iterative reconstruction further achieved approximately 40% reduction in effective dose
Xing, Yafei; Macq, Benoit
2017-11-01
With the emergence of clinical prototypes and first patient acquisitions for proton therapy, the research on prompt gamma imaging is aiming at making most use of the prompt gamma data for in vivo estimation of any shift from expected Bragg peak (BP). The simple problem of matching the measured prompt gamma profile of each pencil beam with a reference simulation from the treatment plan is actually made complex by uncertainties which can translate into distortions during treatment. We will illustrate this challenge and demonstrate the robustness of a predictive linear model we proposed for BP shift estimation based on principal component analysis (PCA) method. It considered the first clinical knife-edge slit camera design in use with anthropomorphic phantom CT data. Particularly, 4115 error scenarios were simulated for the learning model. PCA was applied to the training input randomly chosen from 500 scenarios for eliminating data collinearities. A total variance of 99.95% was used for representing the testing input from 3615 scenarios. This model improved the BP shift estimation by an average of 63+/-19% in a range between -2.5% and 86%, comparing to our previous profile shift (PS) method. The robustness of our method was demonstrated by a comparative study conducted by applying 1000 times Poisson noise to each profile. 67% cases obtained by the learning model had lower prediction errors than those obtained by PS method. The estimation accuracy ranged between 0.31 +/- 0.22 mm and 1.84 +/- 8.98 mm for the learning model, while for PS method it ranged between 0.3 +/- 0.25 mm and 20.71 +/- 8.38 mm.
Ringing Artefact Reduction By An Efficient Likelihood Improvement Method
Fuderer, Miha
1989-10-01
In MR imaging, the extent of the acquired spatial frequencies of the object is necessarily finite. The resulting image shows artefacts caused by "truncation" of its Fourier components. These are known as Gibbs artefacts or ringing artefacts. These artefacts are particularly. visible when the time-saving reduced acquisition method is used, say, when scanning only the lowest 70% of the 256 data lines. Filtering the data results in loss of resolution. A method is described that estimates the high frequency data from the low-frequency data lines, with the likelihood of the image as criterion. It is a computationally very efficient method, since it requires practically only two extra Fourier transforms, in addition to the normal. reconstruction. The results of this method on MR images of human subjects are promising. Evaluations on a 70% acquisition image show about 20% decrease of the error energy after processing. "Error energy" is defined as the total power of the difference to a 256-data-lines reference image. The elimination of ringing artefacts then appears almost complete..
The iterative shrinkage method for impulsive noise reduction from images
International Nuclear Information System (INIS)
Beygi, Sajjad; Kafashan, Mohammadmehdi; Bahrami, Hamid Reza; Mugler, Dale H
2012-01-01
In this paper, we present a novel scheme to compensate impulsive noise from images using the sparse shrinkage method. In this scheme, we assume the remaining noise after using a simple median filtering in place of corrupted pixels, found by boundary discriminative noise detection method, to be Gaussian additive noise. This assumption will later be verified by the means of simulation. Knowing that the pure image in the discrete wavelet transform (DWT) domain is a sparse vector, we define an optimization problem to minimize the l 0 -norm of the estimated image vector from the noisy one in the DWT domain. l 0 -norm makes the optimization problem a combinatorial optimization problem which is NP-hard to solve. To come up with a solution for our optimization problem, we convert the l 0 -norm problem to a continuous optimization problem which is then solved to find the estimated image with reduced noise. In the simulation and discussion part, the performance of our proposed method in reducing impulsive noise is compared to that of existing methods in the literature. We show that our proposed algorithm generally performs better in terms of both subjective and objective evaluations and is less complex. (paper)
Liang, Hui; Li, Chenwei; Chen, Tao; Cui, Liang; Han, Jingrui; Peng, Zhi; Liu, Jingquan
2018-02-01
Because of the urgent need for renewable resources, oxygen reduction reaction (ORR) has been widely studied. Finding efficient and low cost non-precious metal catalyst is increasingly critical. In this study, melamine foam is used as template to obtain porous sulfur and nitrogen-codoped graphene/carbon foam with uniformly distributed cobalt sulfide nanoparticles (Co1-xS/SNG/CF) which is prepared by a simple infiltration-drying-sulfuration method. It is noteworthy that melamine foam not only works as a three-dimensional support skeleton, but also provides a nitrogen source without any environmental pollution. Such Co1-xS/SNG/CF catalyst shows excellent oxygen reduction catalytic performance with an onset potential of only 0.99 V, which is the same as that of Pt/C catalyst (Eonset = 0.99 V). Furthermore, the stability and methanol tolerance of Co1-xS/SNG/CF are more outstanding than those of Pt/C catalyst. Our work manifests a facile method to prepare S and N-codoped 3D graphene network decorated with Co1-xS nanoparticles, which may be utilized as potential alternative to the expensive Pt/C catalysts toward ORR.
Cai, Kai; Liu, Jiawei; Zhang, Huan; Huang, Zhao; Lu, Zhicheng; Foda, Mohamed F; Li, Tingting; Han, Heyou
2015-05-11
An intermediate-template-directed method has been developed for the synthesis of quasi-one-dimensional Au/PtAu heterojunction nanotubes by the heterogeneous nucleation and growth of Au on Te/Pt core-shell nanostructures in aqueous solution. The synthesized porous Au/PtAu bimetallic nanotubes (PABNTs) consist of porous tubular framework and attached Au nanoparticles (AuNPs). The reaction intermediates played an important role in the preparation, which fabricated the framework and provided a localized reducing agent for the reduction of the Au and Pt precursors. The Pt7 Au PABNTs showed higher electrocatalytic activity and durability in the oxygen-reduction reaction (ORR) in 0.1 M HClO4 than porous Pt nanotubes (PtNTs) and commercially available Pt/C. The mass activity of PABNTs was 218 % that of commercial Pt/C after an accelerated durability test. This study demonstrates the potential of PABNTs as highly efficient electrocatalysts. In addition, this method provides a facile strategy for the synthesis of desirable hetero-nanostructures with controlled size and shape by utilizing an intermediate template. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Qiu, J.; Khalloufi, S.; Martynenko, A.; Dalen, van G.; Schutyser, M.A.I.; Almeida-Rivera, C.
2015-01-01
Several experimental methods for measuring porosity, bulk density and volume reduction during drying of foodstuff are available. These methods include among others geometric dimension, volume displacement, mercury porosimeter, micro-CT, and NMR. However, data on their accuracy, sensitivity, and
Numerical comparison of robustness of some reduction methods in rough grids
Hou, Jiangyong; Sun, Shuyu; Chen, Zhangxin
2014-01-01
In this article, we present three nonsymmetric mixed hybrid RT 1 2 methods and compare with some recently developed reduction methods which are suitable for the single-phase Darcy flow problem with full anisotropic and highly heterogeneous
Controllable reductive method for synthesizing metal-containing particles
Moon, Ji-Won; Jung, Hyunsung; Phelps, Tommy Joe; Duty, Chad E.; Ivanov, Ilia N.; Joshi, Pooran Chandra; Jellison, Jr., Gerald Earle; Armstrong, Beth Louise; Smith, Sean Campbell; Rondinone, Adam Justin; Love, Lonnie J.
2018-03-06
The invention is directed to a method for producing metal-containing particles, the method comprising subjecting an aqueous solution comprising a metal salt, E.sub.h, lowering reducing agent, pH adjusting agent, and water to conditions that maintain the E.sub.h value of the solution within the bounds of an E.sub.h-pH stability field corresponding to the composition of the metal-containing particles to be produced, and producing said metal-containing particles in said aqueous solution at a selected E.sub.h value within the bounds of said E.sub.h-pH stability field. The invention is also directed to the resulting metal-containing particles as well as devices in which they are incorporated.
A general reduction method for one-loop N-point integrals
International Nuclear Information System (INIS)
Heinrich, G.; Binoth, T.
2000-01-01
In order to calculate cross sections with a large number of particles/jets in the final state at next-to-leading order, one has to reduce the occurring scalar and tensor one-loop integrals to a small set of known integrals. In massless theories, this reduction procedure is complicated by the presence of infrared divergences. Working in n = 4 - 2ε dimensions, it will be outlined how to achieve such a reduction for diagrams with an arbitrary number of external legs. As a result, any integral with more than four propagators and generic 4-dimensional external momenta can be reduced to box integrals
Methods and devices for fabricating three-dimensional nanoscale structures
Rogers, John A.; Jeon, Seokwoo; Park, Jangung
2010-04-27
The present invention provides methods and devices for fabricating 3D structures and patterns of 3D structures on substrate surfaces, including symmetrical and asymmetrical patterns of 3D structures. Methods of the present invention provide a means of fabricating 3D structures having accurately selected physical dimensions, including lateral and vertical dimensions ranging from 10s of nanometers to 1000s of nanometers. In one aspect, methods are provided using a mask element comprising a conformable, elastomeric phase mask capable of establishing conformal contact with a radiation sensitive material undergoing photoprocessing. In another aspect, the temporal and/or spatial coherence of electromagnetic radiation using for photoprocessing is selected to fabricate complex structures having nanoscale features that do not extend entirely through the thickness of the structure fabricated.
Linear finite element method for one-dimensional diffusion problems
Energy Technology Data Exchange (ETDEWEB)
Brandao, Michele A.; Dominguez, Dany S.; Iglesias, Susana M., E-mail: micheleabrandao@gmail.com, E-mail: dany@labbi.uesc.br, E-mail: smiglesias@uesc.br [Universidade Estadual de Santa Cruz (LCC/DCET/UESC), Ilheus, BA (Brazil). Departamento de Ciencias Exatas e Tecnologicas. Laboratorio de Computacao Cientifica
2011-07-01
We describe in this paper the fundamentals of Linear Finite Element Method (LFEM) applied to one-speed diffusion problems in slab geometry. We present the mathematical formulation to solve eigenvalue and fixed source problems. First, we discretized a calculus domain using a finite set of elements. At this point, we obtain the spatial balance equations for zero order and first order spatial moments inside each element. Then, we introduce the linear auxiliary equations to approximate neutron flux and current inside the element and architect a numerical scheme to obtain the solution. We offer numerical results for fixed source typical model problems to illustrate the method's accuracy for coarse-mesh calculations in homogeneous and heterogeneous domains. Also, we compare the accuracy and computational performance of LFEM formulation with conventional Finite Difference Method (FDM). (author)
Reduction in requirements for allogeneic blood products: nonpharmacologic methods.
Hardy, J F; Bélisle, S; Janvier, G; Samama, M
1996-12-01
Various strategies have been proposed to decrease bleeding and allogeneic transfusion requirements during and after cardiac operations. This article attempts to document the usefulness, or lack thereof, of the nonpharmacologic methods available in clinical practice. Blood conservation methods were reviewed in chronologic order, as they become available to patients during the perisurgical period. The literature in support of or against each strategy was reexamined critically. Avoidance of preoperative anemia and adherence to published guidelines for the practice of transfusion are of paramount importance. Intraoperatively, tolerance of low hemoglobin concentrations and use of autologous blood (predonated or harvested before bypass) will reduce allogeneic transfusions. The usefulness of plateletpheresis and retransfusion of shed mediastinal fluid remains controversial. Intraoperatively and postoperatively, maintenance of normothermia contributes to improved hemostasis. Several approaches have been shown to be effective. An efficient combination of methods can reduce, and sometimes abolish, the need for allogeneic blood products after cardiac operations, inasmuch as all those involved in the care of cardiac surgical patients adhere thoughtfully to existing transfusion guidelines.
General methods for alarm reduction; Larmsanering med generella metoder
Energy Technology Data Exchange (ETDEWEB)
Ahnlund, Jonas; Bergquist, Tord; Raaberg, Martin [Lund Univ. (Sweden). Dept. of Information Technology
2003-10-01
The information in the control rooms has increased due to the technological advances in process control. Large industries produce large data quantities, where some information is unnecessary or even incorrect. The operator needs support from an advanced and well-adjusted alarm system to be able to separate a real event from a minor disturbance. The alarms must be of assistance and not a nuisance. An enhanced alarm situation qualifies an increased efficiency with fewer production disturbances and an improved safety. Yet, it is still unusual that actions are taken to improve the situation. An alarm cleanup with general methods can shortly be described as taking advantage of the control systems built-in functions, the possibility to modify or create function blocks and fine-tune the settings in the alarm system. In this project, we make use of an intelligent software, Alarm Cleanup Toolbox, that simulate different signal processing methods and tries to find improved settings on all the signals in the process. This is a fast and cost-efficient way to improve the overall alarm situation, and lays a foundation for more advanced alarm systems. An alarm cleanup has been carried out at Flintraennan district heating plant in Malmoe, where various signal processing methods has been implemented in a parallel alarm system. This made it possible to compare the two systems under the same conditions. The result is very promising, and shows that a lot of improvements can be achieved with very little effort. An analysis of the alarm system at Vattenreningen (the water purification process) at Heleneholmsverket in Malmoe has been carried out. Alarm Cleanup Toolbox has, besides suggesting improved settings, also found logical errors in the alarm system. Here, no implementation was carried out and therefore the results are analytical, but they validate the efficiency of the general methods. The project has shown that an alarm cleanup with general methods is cost-efficient, and that the
The Chimera Method of Simulation for Unsteady Three-Dimensional Viscous Flow
Meakin, Robert L.
1996-01-01
The Chimera overset grid method is reviewed and discussed in the context of a method of solution and analysis of unsteady three-dimensional viscous flows. The state of maturity of the various pieces of support software required to use the approach is discussed. A variety of recent applications of the method is presented. Current limitations of the approach are defined.
International Nuclear Information System (INIS)
Shtromberger, N.L.
1989-01-01
To design a cyclotron magnetic system the legitimacy of two-dimensional approximations application is discussed. In all the calculations the finite difference method is used, and the linearization method with further use of the gradient conjugation method is used to solve the set of finite-difference equations. 3 refs.; 5 figs
The Albedo method for tri-dimensional calculations of fast reactors, with application to PEC
International Nuclear Information System (INIS)
Bianchini, G.; Loizzo, P.
1983-01-01
The Pec core simulator computer code, being now defined at Enea, is a relatively simple and inexpensive calculational model used by the reactor operator to derive the core life and the single subassemblies power and sodium flow. The diffusion module of this code will be based on the neutronic design code Citation. Here are outlined the theoretical foundations and the procedures to reduce the tri-dimensional diffusion computer time by the use of the following approximations: 1) the reactor zones far from the core are substituted by boundary conditions (albedo method); suitable flux logarithmic derivates are defined; 2) the fuel elements are represented by exagonal meshes; appropriate normalization factors are defined. With respect to the standard design procedures the computer cpu time is reduced from 90 minutes to 2 minutes (Ibm 4341/2). The errors amount to a few mk on the multiplication factor and to a few percent on the power distribution. The approximations (1) and (2) are equally important with respect to the time reduction
Three-dimensional wake field analysis by boundary element method
International Nuclear Information System (INIS)
Miyata, K.
1987-01-01
A computer code HERTPIA was developed for the calculation of electromagnetic wake fields excited by charged particles travelling through arbitrarily shaped accelerating cavities. This code solves transient wave problems for a Hertz vector. The numerical analysis is based on the boundary element method. This program is validated by comparing its results with analytical solutions in a pill-box cavity
TreePM Method for Two-Dimensional Cosmological Simulations ...
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
We discuss the integration of the equations of motion that we use in the 2d TreePM code in section 7. .... spaced values of r in order to keep interpolation errors in control. .... hence we cannot use the usual leap-frog method. We recast the ...
Evaluation of cost reduction method for manufacturing ODS ferritic claddings
International Nuclear Information System (INIS)
Fujiwara, Masayuki; Mizuta, Shunji; Ukai, Shigeharu
2000-04-01
For evaluating the fast reactor system technology, it is important to evaluate the practical feasibility of ODS ferritic claddings, which is the most promising materials to attain the goal of high coolant temperature and more than 150 GWd/t. Based on the results of their technology development, mass production process with highly economically benefit as well as manufacturing cost estimation of ODS ferritic claddings were preliminarily conducted. From the view point of future utility scale, the cost for manufacturing mother tubes has a dominant factor in the total manufacturing cost. The method to reduce the cost of mother tube manufacturing was also preliminarily investigated. (author)
Improved algorithm for three-dimensional inverse method
Qiu, Xuwen
An inverse method, which works for full 3D viscous applications in turbomachinery aerodynamic design, is developed. The method takes pressure loading and thickness distribution as inputs and computes the 3D-blade geometry. The core of the inverse method consists of two closely related steps, which are integrated into a time-marching procedure of a Navier-Stokes solver. First, the pressure loading condition is enforced while flow is allowed to cross the blade surfaces. A permeable blade boundary condition is developed here in order to be consistent with the propagation characteristics of the transient Navier-Stokes equations. In the second step, the blade geometry is adjusted so that the flow-tangency condition is satisfied for the new blade. A Non-Uniform Rational B-Spline (NURBS) model is used to represent the span-wise camber curves. The flow-tangency condition is then transformed into a general linear least squares fitting problem, which is solved by a robust Singular Value Decomposition (SVD) scheme. This blade geometry generation scheme allows the designer to have direct control over the smoothness of the calculated blade, and thus ensures the numerical stability during the iteration process. Numerical experiments show that this method is very accurate, efficient and robust. In target-shooting tests, the program was able to converge to the target blade accurately from a different initial blade. The speed of an inverse run is only about 15% slower than its analysis counterpart, which means a complete 3D viscous inverse design can be done in a matter of hours. The method is also proved to work well with the presence of clearance between the blade and the housing, a key factor to be considered in aerodynamic design. The method is first developed for blades without splitters, and is then extended to provide the capability of analyzing and designing machines with splitters. This gives designers an integrated environment where the aerodynamic design of both full
A numerical method for two-dimensional anisotropic transport problem in cylindrical geometry
International Nuclear Information System (INIS)
Du Mingsheng; Feng Tiekai; Fu Lianxiang; Cao Changshu; Liu Yulan
1988-01-01
The authors deal with the triangular mesh-discontinuous finite element method for solving the time-dependent anisotropic neutron transport problem in two-dimensional cylindrical geometry. A prior estimate of the numerical solution is given. Stability is proved. The authors have computed a two dimensional anisotropic neutron transport problem and a Tungsten-Carbide critical assembly problem by using the numerical method. In comparision with DSN method and the experimental results obtained by others both at home and abroad, the method is satisfactory
Solution of (3+1-Dimensional Nonlinear Cubic Schrodinger Equation by Differential Transform Method
Directory of Open Access Journals (Sweden)
Hassan A. Zedan
2012-01-01
Full Text Available Four-dimensional differential transform method has been introduced and fundamental theorems have been defined for the first time. Moreover, as an application of four-dimensional differential transform, exact solutions of nonlinear system of partial differential equations have been investigated. The results of the present method are compared very well with analytical solution of the system. Differential transform method can easily be applied to linear or nonlinear problems and reduces the size of computational work. With this method, exact solutions may be obtained without any need of cumbersome work, and it is a useful tool for analytical and numerical solutions.
Two-dimensional isostatic meshes in the finite element method
Martínez Marín, Rubén; Samartín, Avelino
2002-01-01
In a Finite Element (FE) analysis of elastic solids several items are usually considered, namely, type and shape of the elements, number of nodes per element, node positions, FE mesh, total number of degrees of freedom (dot) among others. In this paper a method to improve a given FE mesh used for a particular analysis is described. For the improvement criterion different objective functions have been chosen (Total potential energy and Average quadratic error) and the number of nodes and dof's...
Singular perturbations introduction to system order reduction methods with applications
Shchepakina, Elena; Mortell, Michael P
2014-01-01
These lecture notes provide a fresh approach to investigating singularly perturbed systems using asymptotic and geometrical techniques. It gives many examples and step-by-step techniques, which will help beginners move to a more advanced level. Singularly perturbed systems appear naturally in the modelling of many processes that are characterized by slow and fast motions simultaneously, for example, in fluid dynamics and nonlinear mechanics. This book’s approach consists in separating out the slow motions of the system under investigation. The result is a reduced differential system of lesser order. However, it inherits the essential elements of the qualitative behaviour of the original system. Singular Perturbations differs from other literature on the subject due to its methods and wide range of applications. It is a valuable reference for specialists in the areas of applied mathematics, engineering, physics, biology, as well as advanced undergraduates for the earlier parts of the book, and graduate stude...
Adaptive Subband Filtering Method for MEMS Accelerometer Noise Reduction
Directory of Open Access Journals (Sweden)
Piotr PIETRZAK
2008-12-01
Full Text Available Silicon microaccelerometers can be considered as an alternative to high-priced piezoelectric sensors. Unfortunately, relatively high noise floor of commercially available MEMS (Micro-Electro-Mechanical Systems sensors limits the possibility of their usage in condition monitoring systems of rotating machines. The solution of this problem is the method of signal filtering described in the paper. It is based on adaptive subband filtering employing Adaptive Line Enhancer. For filter weights adaptation, two novel algorithms have been developed. They are based on the NLMS algorithm. Both of them significantly simplify its software and hardware implementation and accelerate the adaptation process. The paper also presents the software (Matlab and hardware (FPGA implementation of the proposed noise filter. In addition, the results of the performed tests are reported. They confirm high efficiency of the solution.
A coupled Eulerian/Lagrangian method for the solution of three-dimensional vortical flows
Felici, Helene Marie
1992-01-01
A coupled Eulerian/Lagrangian method is presented for the reduction of numerical diffusion observed in solutions of three-dimensional rotational flows using standard Eulerian finite-volume time-marching procedures. A Lagrangian particle tracking method using particle markers is added to the Eulerian time-marching procedure and provides a correction of the Eulerian solution. In turn, the Eulerian solutions is used to integrate the Lagrangian state-vector along the particles trajectories. The Lagrangian correction technique does not require any a-priori information on the structure or position of the vortical regions. While the Eulerian solution ensures the conservation of mass and sets the pressure field, the particle markers, used as 'accuracy boosters,' take advantage of the accurate convection description of the Lagrangian solution and enhance the vorticity and entropy capturing capabilities of standard Eulerian finite-volume methods. The combined solution procedures is tested in several applications. The convection of a Lamb vortex in a straight channel is used as an unsteady compressible flow preservation test case. The other test cases concern steady incompressible flow calculations and include the preservation of turbulent inlet velocity profile, the swirling flow in a pipe, and the constant stagnation pressure flow and secondary flow calculations in bends. The last application deals with the external flow past a wing with emphasis on the trailing vortex solution. The improvement due to the addition of the Lagrangian correction technique is measured by comparison with analytical solutions when available or with Eulerian solutions on finer grids. The use of the combined Eulerian/Lagrangian scheme results in substantially lower grid resolution requirements than the standard Eulerian scheme for a given solution accuracy.
Dimensional analysis and self-similarity methods for engineers and scientists
Zohuri, Bahman
2015-01-01
This ground-breaking reference provides an overview of key concepts in dimensional analysis, and then pushes well beyond traditional applications in fluid mechanics to demonstrate how powerful this tool can be in solving complex problems across many diverse fields. Of particular interest is the book's coverage of dimensional analysis and self-similarity methods in nuclear and energy engineering. Numerous practical examples of dimensional problems are presented throughout, allowing readers to link the book's theoretical explanations and step-by-step mathematical solutions to practical impleme
Three-dimensional space-charge calculation method
International Nuclear Information System (INIS)
Lysenko, W.P.; Wadlinger, E.A.
1980-09-01
A method is presented for calculating space-charge forces on individual particles in a particle tracing simulation code. Poisson's equation is solved in three dimensions with boundary conditions specified on an arbitrary surface. When the boundary condition is defined by an impressed radio-frequency field, the external electric fields as well as the space-charge fields are determined. A least squares fitting procedure is used to calculate the coefficients of expansion functions, which need not be orthogonal nor individually satisfy the boundary condition
A Diminution Method of Large Multi-dimensional Data Retrievals
Directory of Open Access Journals (Sweden)
Nushwan Yousif Baithoon
2010-01-01
Full Text Available The intention of this work is to introduce a method ofcompressing data at the transmitter (source and expanding it atthe receiver (destination.The amount of data compression is directly related to datadimensionality, hence, for example an N by N RGB image file isconsidered to be an M-D, with M=3, image data file.Also, the amount of scatter in an M-D file, hence, the covariancematrix is calculated, along with the average value of eachdimension, to represent the signature or code for each individualdata set to be sent by the source.At the destination random sets can test a particular receivedsignature so that only one set is acceptable thus giving thecorresponding intended set to be received.Sound results are obtained depending on the constrains beingimplemented. These constrains are user tolerant in so far as howwell tuned or rapid the information is to be processed for dataretrieval.The proposed method is well suited in application areas whereboth source and destination are communicating using the samesets of data files at each end. Also such a technique is feasible forthe availability of fast microprocessors and frame-grabbers.
Calculation of two-dimensional thermal transients by the finite element method
International Nuclear Information System (INIS)
Fontoura Rodrigues, J.L.A. da; Barcellos, C.S. de
1981-01-01
The linear heat conduction through anisotropic and/or heterogeneous matter, in either two-dimensional fields with any kind of geometry or three-dimensional fields with axial symmetry is analysed. It only accepts time-independent boundary conditions and it is possible to have internal heat generation. The solution is obtained by modal analysis employing the finite element method under Galerkin formulation. (Author) [pt
Method and apparatus for two-dimensional spectroscopy
DeCamp, Matthew F.; Tokmakoff, Andrei
2010-10-12
Preferred embodiments of the invention provide for methods and systems of 2D spectroscopy using ultrafast, first light and second light beams and a CCD array detector. A cylindrically-focused second light beam interrogates a target that is optically interactive with a frequency-dispersed excitation (first light) pulse, whereupon the second light beam is frequency-dispersed at right angle orientation to its line of focus, so that the horizontal dimension encodes the spatial location of the second light pulse and the first light frequency, while the vertical dimension encodes the second light frequency. Differential spectra of the first and second light pulses result in a 2D frequency-frequency surface equivalent to double-resonance spectroscopy. Because the first light frequency is spatially encoded in the sample, an entire surface can be acquired in a single interaction of the first and second light pulses.
Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD
Directory of Open Access Journals (Sweden)
Gagan S Sidhu
2012-11-01
Full Text Available This article explores various preprocessing tools that select/create features to help a learner produce a classifier that can use fMRI data to effectively discriminate Attention-Deficit Hyperactivity Disorder (ADHD patients from healthy controls. We consider four different learning tasks: predicting either two (ADHD vs control or three classes (ADHD-1 vs ADHD-3 vs control, where each use either the imaging data only, or the phenotypic and imaging data. After averaging, BOLD-signal normalization, and masking of the fMRI images, we considered applying Fast Fourier Transform (FFT, possibly followed by some Principal Component Analysis (PCA variant (over time: PCA-t; over space and time: PCA-st or the kernelized variant, kPCA-st, to produce inputs to a learner, to determine which learned classifier performs the best – or at least better than the baseline of 64.2%, which is the proportion of the majority class (here, controls.In the two-class setting, PCA-t and PCA-st did not perform statistically better than baseline, whereas FFT and kPCA-st did (FFT, 68.4%; kPCA-st, 70.3%; when combined with the phenotypic data, which by itself produces 72.9% accuracy, all methods performed statistically better than the baseline, but none did better than using the phenotypic data. In the three-class setting, neither the PCA variants, or the phenotypic data classifiers, performed statistically better than the baseline.We next used the FFT output as input to the PCA variants. In the two-class setting, the PCA variants performed statistically better than the baseline using either the FFTed waveforms only (FFT+PCA-t, 69.6%,; FFT+PCA-st, 69.3% ; FFT+kPCA-st, 68.7%, or combining them with the phenotypic data (FFT+PCA-t, 70.6%; FFT+PCA-st, 70.6%; kPCA-st, 76%. In both settings, combining FFT+kPCA-st’s features with the phenotypic data was better than using only the phenotypic data, with the result in the two-class setting being statistically better.
Energy Technology Data Exchange (ETDEWEB)
Sato, T; Matsuoka, T [Japan Petroleum Exploration Corp., Tokyo (Japan); Saeki, T [Japan National Oil Corp., Tokyo (Japan). Technology Research Center
1997-05-27
Discussed in this report is a wavefield simulation in the 3-dimensional seismic survey. With the level of the object of exploration growing deeper and the object more complicated in structure, the survey method is now turning 3-dimensional. There are several modelling methods for numerical calculation of 3-dimensional wavefields, such as the difference method, pseudospectral method, and the like, all of which demand an exorbitantly large memory and long calculation time, and are costly. Such methods have of late become feasible, however, thanks to the advent of the parallel computer. As compared with the difference method, the pseudospectral method requires a smaller computer memory and shorter computation time, and is more flexible in accepting models. It outputs the result in fullwave just like the difference method, and does not cause wavefield numerical variance. As the computation platform, the parallel computer nCUBE-2S is used. The object domain is divided into the number of the processors, and each of the processors takes care only of its share so that parallel computation as a whole may realize a very high-speed computation. By the use of the pseudospectral method, a 3-dimensional simulation is completed within a tolerable computation time length. 7 refs., 3 figs., 1 tab.
Method for simulating dose reduction in digital mammography using the Anscombe transformation
Borges, Lucas R.; de Oliveira, Helder C. R.; Nunes, Polyana F.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.
2016-01-01
Purpose: This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose. Methods: The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the d...
Calculation of two-dimensional thermal transients by the method of finite elements
International Nuclear Information System (INIS)
Fontoura Rodrigues, J.L.A. da.
1980-08-01
The unsteady linear heat conduction analysis throught anisotropic and/or heterogeneous matter, in either two-dimensional fields with any kind of geometry or three-dimensional fields with axial symmetry is presented. The boundary conditions and the internal heat generation are supposed time - independent. The solution is obtained by modal analysis employing the finite element method under Galerkin formulation. Optionally, it can be used with a reduced resolution method called Stoker Economizing Method wich allows a decrease on the program processing costs. (Author) [pt
Comparing 3-dimensional virtual methods for reconstruction in craniomaxillofacial surgery.
Benazzi, Stefano; Senck, Sascha
2011-04-01
In the present project, the virtual reconstruction of digital osteomized zygomatic bones was simulated using different methods. A total of 15 skulls were scanned using computed tomography, and a virtual osteotomy of the left zygomatic bone was performed. Next, virtual reconstructions of the missing part using mirror imaging (with and without best fit registration) and thin plate spline interpolation functions were compared with the original left zygomatic bone. In general, reconstructions using thin plate spline warping showed better results than the mirroring approaches. Nevertheless, when dealing with skulls characterized by a low degree of asymmetry, mirror imaging and subsequent registration can be considered a valid and easy solution for zygomatic bone reconstruction. The mirroring tool is one of the possible alternatives in reconstruction, but it might not always be the optimal solution (ie, when the hemifaces are asymmetrical). In the present pilot study, we have verified that best fit registration of the mirrored unaffected hemiface and thin plate spline warping achieved better results in terms of fitting accuracy, overcoming the evident limits of the mirroring approach. Copyright © 2011 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.
Development of three-dimensional ENRICHED FREE MESH METHOD and its application to crack analysis
International Nuclear Information System (INIS)
Suzuki, Hayato; Matsubara, Hitoshi; Ezawa, Yoshitaka; Yagawa, Genki
2010-01-01
In this paper, we describe a method for three-dimensional high accurate analysis of a crack included in a large-scale structure. The Enriched Free Mesh Method (EFMM) is a method for improving the accuracy of the Free Mesh Method (FMM), which is a kind of meshless method. First, we developed an algorithm of the three-dimensional EFMM. The elastic problem was analyzed using the EFMM and we find that its accuracy compares advantageously with the FMM, and the number of CG iterations is smaller. Next, we developed a method for calculating the stress intensity factor by employing the EFMM. The structure with a crack was analyzed using the EFMM, and the stress intensity factor was calculated by the developed method. The analysis results were very well in agreement with reference solution. It was shown that the proposed method is very effective in the analysis of the crack included in a large-scale structure. (author)
The analysis of RPV fast neutron flux calculation for PWR with three-dimensional SN method
International Nuclear Information System (INIS)
Yang Shouhai; Chen Yixue; Wang Weijin; Shi Shengchun; Lu Daogang
2011-01-01
Discrete ordinates (S N ) method is one of the most widely used method for reactor pressure vessel (RPV) design. As the fast development of computer CPU speed and memory capacity and consummation of three-dimensional discrete-ordinates method, it is mature for 3-D S N method to be used to engineering design for nuclear facilities. This work was done specifically for PWR model, with the results of 3-D core neutron transport calculation by 3-D core calculation, 3-D RPV fast neutron flux distribution obtain by 3-D S N method were compared with gained by 1-D and 2-D S N method and the 3-D Monte Carlo (MC) method. In this paper, the application of three-dimensional S N method in calculating RPV fast neutron flux distribution for pressurized water reactor (PWR) is presented and discussed. (authors)
International Nuclear Information System (INIS)
Langrene, Nicolas
2014-01-01
This thesis deals with the numerical solution of general stochastic control problems, with notable applications for electricity markets. We first propose a structural model for the price of electricity, allowing for price spikes well above the marginal fuel price under strained market conditions. This model allows to price and partially hedge electricity derivatives, using fuel forwards as hedging instruments. Then, we propose an algorithm, which combines Monte-Carlo simulations with local basis regressions, to solve general optimal switching problems. A comprehensive rate of convergence of the method is provided. Moreover, we manage to make the algorithm parsimonious in memory (and hence suitable for high dimensional problems) by generalizing to this framework a memory reduction method that avoids the storage of the sample paths. We illustrate this on the problem of investments in new power plants (our structural power price model allowing the new plants to impact the price of electricity). Finally, we study more general stochastic control problems (the control can be continuous and impact the drift and volatility of the state process), the solutions of which belong to the class of fully nonlinear Hamilton-Jacobi-Bellman equations, and can be handled via constrained Backward Stochastic Differential Equations, for which we develop a backward algorithm based on control randomization and parametric optimizations. A rate of convergence between the constraPned BSDE and its discrete version is provided, as well as an estimate of the optimal control. This algorithm is then applied to the problem of super replication of options under uncertain volatilities (and correlations). (author)
Directory of Open Access Journals (Sweden)
Min Liu
2018-03-01
Full Text Available Sidelobe reduction is a very primary task for synthetic aperture radar (SAR images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.
The dimension split element-free Galerkin method for three-dimensional potential problems
Meng, Z. J.; Cheng, H.; Ma, L. D.; Cheng, Y. M.
2018-02-01
This paper presents the dimension split element-free Galerkin (DSEFG) method for three-dimensional potential problems, and the corresponding formulae are obtained. The main idea of the DSEFG method is that a three-dimensional potential problem can be transformed into a series of two-dimensional problems. For these two-dimensional problems, the improved moving least-squares (IMLS) approximation is applied to construct the shape function, which uses an orthogonal function system with a weight function as the basis functions. The Galerkin weak form is applied to obtain a discretized system equation, and the penalty method is employed to impose the essential boundary condition. The finite difference method is selected in the splitting direction. For the purposes of demonstration, some selected numerical examples are solved using the DSEFG method. The convergence study and error analysis of the DSEFG method are presented. The numerical examples show that the DSEFG method has greater computational precision and computational efficiency than the IEFG method.
International Nuclear Information System (INIS)
Shestakov, A.I.; Mirin, A.A.
1984-01-01
A numerical method based on Fourier expansions and finite differences is presented. The method is demonstrated by solving a scalar, three-dimensional elliptic equation arising in MFE research, but has applicability to a wider class of problems. The scheme solves equations whose solutions are expected to be periodic in one or more of the independent variables
Computational Methods for Inviscid and Viscous Two-and-Three-Dimensional Flow Fields.
1975-01-01
Difference Equations Over a Network, Watson Sei. Comput. Lab. Report, 19U9. 173- Isaacson, E. and Keller, H. B., Analaysis of Numerical Methods...element method has given a new impulse to the old mathematical theory of multivariate interpolation. We first study the one-dimensional case, which
Buisman, Wijnand J; van Herwaarden-Lindeboom, MYA; Mauritz, Femke A; El Ouamari, Mourad; Hausken, Trygve; Olafsdottir, Edda J; van der Zee, David C; Gilja, Odd Helge
OBJECTIVES: A novel automated 3-dimensional (3D) sonographic method has been developed for measuring gastric volumes. This study aimed to validate and assess the reliability of this novel 3D sonographic method compared to the reference standard in 3D gastric sonography: freehand magneto-based 3D
A finite element method for calculating the 3-dimensional magnetic fields of cyclotron
International Nuclear Information System (INIS)
Zhao Xiaofeng
1986-01-01
A series of formula of the finite element method (scalar potential) for calculating the three-dimensional magnetic field of the main magnet of a sector focused cyclotron, and the realization method of the periodic boundary conditions in the code are given
Homotopy decomposition method for solving one-dimensional time-fractional diffusion equation
Abuasad, Salah; Hashim, Ishak
2018-04-01
In this paper, we present the homotopy decomposition method with a modified definition of beta fractional derivative for the first time to find exact solution of one-dimensional time-fractional diffusion equation. In this method, the solution takes the form of a convergent series with easily computable terms. The exact solution obtained by the proposed method is compared with the exact solution obtained by using fractional variational homotopy perturbation iteration method via a modified Riemann-Liouville derivative.
Knowledge Reduction Based on Divide and Conquer Method in Rough Set Theory
Directory of Open Access Journals (Sweden)
Feng Hu
2012-01-01
Full Text Available The divide and conquer method is a typical granular computing method using multiple levels of abstraction and granulations. So far, although some achievements based on divided and conquer method in the rough set theory have been acquired, the systematic methods for knowledge reduction based on divide and conquer method are still absent. In this paper, the knowledge reduction approaches based on divide and conquer method, under equivalence relation and under tolerance relation, are presented, respectively. After that, a systematic approach, named as the abstract process for knowledge reduction based on divide and conquer method in rough set theory, is proposed. Based on the presented approach, two algorithms for knowledge reduction, including an algorithm for attribute reduction and an algorithm for attribute value reduction, are presented. Some experimental evaluations are done to test the methods on uci data sets and KDDCUP99 data sets. The experimental results illustrate that the proposed approaches are efficient to process large data sets with good recognition rate, compared with KNN, SVM, C4.5, Naive Bayes, and CART.
Park, W S; Kim, K D; Shin, H K; Lee, S H
2007-01-01
Metal Artifact still remains one of the main drawbacks in craniofacial Three-Dimensional Computed Tomography (3D CT). In this study, we tried to test the efficacy of additional silicone dental impression materials as a "tooth shield" for the reduction of metal artifact caused by metal restorations and orthodontic appliances. 6 phantoms with 4 teeth were prepared for this in vitro study. Orthodontic bracket, bands and amalgam restorations were placed in each tooth to reproduce various intraoral conditions. Standardized silicone shields were fabricated and placed around the teeth. CT image acquisition was performed with and without silicone shields. Maximum value, mean, and standard deviation of Hounsfield Units (HU) were compared with the presence of silicone shields. In every situation, metal artifacts were reduced in quality and quantity when silicone shields are used. Amalgam restoration made most serious metal artifact. Silicone shields made by dental impression material might be effective way to reduce the metal artifact caused by dental restoration and orthodontic appliances. This will help more excellent 3D image from 3D CT in craniofacial area.
Weckwerth, Wolfram
2008-02-01
In recent years, genomics has been extended to functional genomics. Toward the characterization of organisms or species on the genome level, changes on the metabolite and protein level have been shown to be essential to assign functions to genes and to describe the dynamic molecular phenotype. Gas chromatography (GC) and liquid chromatography coupled to mass spectrometry (GC- and LC-MS) are well suited for the fast and comprehensive analysis of ultracomplex metabolite samples. For the integration of metabolite profiles with quantitative protein profiles, a high throughput (HTP) shotgun proteomics approach using LC-MS and label-free quantification of unique proteins in a complex protein digest is described. Multivariate statistics are applied to examine sample pattern recognition based on data-dimensionality reduction and biomarker identification in plant systems biology. The integration of the data reveal multiple correlative biomarkers providing evidence for an increase of information in such holistic approaches. With computational simulation of metabolic networks and experimental measurements, it can be shown that biochemical regulation is reflected by metabolite network dynamics measured in a metabolomics approach. Examples in molecular plant physiology are presented to substantiate the integrative approach.
A new analytical method to solve the heat equation for a multi-dimensional composite slab
International Nuclear Information System (INIS)
Lu, X; Tervola, P; Viljanen, M
2005-01-01
A novel analytical approach has been developed for heat conduction in a multi-dimensional composite slab subject to time-dependent boundary changes of the first kind. Boundary temperatures are represented as Fourier series. Taking advantage of the periodic properties of boundary changes, the analytical solution is obtained and expressed explicitly. Nearly all the published works necessitate searching for associated eigenvalues in solving such a problem even for a one-dimensional composite slab. In this paper, the proposed method involves no iterative computation such as numerically searching for eigenvalues and no residue evaluation. The adopted method is simple which represents an extension of the novel analytical approach derived for the one-dimensional composite slab. Moreover, the method of 'separation of variables' employed in this paper is new. The mathematical formula for solutions is concise and straightforward. The physical parameters are clearly shown in the formula. Further comparison with numerical calculations is presented
Biomedical applications of two- and three-dimensional deterministic radiation transport methods
International Nuclear Information System (INIS)
Nigg, D.W.
1992-01-01
Multidimensional deterministic radiation transport methods are routinely used in support of the Boron Neutron Capture Therapy (BNCT) Program at the Idaho National Engineering Laboratory (INEL). Typical applications of two-dimensional discrete-ordinates methods include neutron filter design, as well as phantom dosimetry. The epithermal-neutron filter for BNCT that is currently available at the Brookhaven Medical Research Reactor (BMRR) was designed using such methods. Good agreement between calculated and measured neutron fluxes was observed for this filter. Three-dimensional discrete-ordinates calculations are used routinely for dose-distribution calculations in three-dimensional phantoms placed in the BMRR beam, as well as for treatment planning verification for live canine subjects. Again, good agreement between calculated and measured neutron fluxes and dose levels is obtained
A GPU-based calculation using the three-dimensional FDTD method for electromagnetic field analysis.
Nagaoka, Tomoaki; Watanabe, Soichi
2010-01-01
Numerical simulations with the numerical human model using the finite-difference time domain (FDTD) method have recently been performed frequently in a number of fields in biomedical engineering. However, the FDTD calculation runs too slowly. We focus, therefore, on general purpose programming on the graphics processing unit (GPGPU). The three-dimensional FDTD method was implemented on the GPU using Compute Unified Device Architecture (CUDA). In this study, we used the NVIDIA Tesla C1060 as a GPGPU board. The performance of the GPU is evaluated in comparison with the performance of a conventional CPU and a vector supercomputer. The results indicate that three-dimensional FDTD calculations using a GPU can significantly reduce run time in comparison with that using a conventional CPU, even a native GPU implementation of the three-dimensional FDTD method, while the GPU/CPU speed ratio varies with the calculation domain and thread block size.
Minezawa, Noriyuki; Kato, Shigeki
2007-02-07
The authors present an implementation of the three-dimensional reference interaction site model self-consistent-field (3D-RISM-SCF) method. First, they introduce a robust and efficient algorithm for solving the 3D-RISM equation. The algorithm is a hybrid of the Newton-Raphson and Picard methods. The Jacobian matrix is analytically expressed in a computationally useful form. Second, they discuss the solute-solvent electrostatic interaction. For the solute to solvent route, the electrostatic potential (ESP) map on a 3D grid is constructed directly from the electron density. The charge fitting procedure is not required to determine the ESP. For the solvent to solute route, the ESP acting on the solute molecule is derived from the solvent charge distribution obtained by solving the 3D-RISM equation. Matrix elements of the solute-solvent interaction are evaluated by the direct numerical integration. A remarkable reduction in the computational time is observed in both routes. Finally, the authors implement the first derivatives of the free energy with respect to the solute nuclear coordinates. They apply the present method to "solute" water and formaldehyde in aqueous solvent using the simple point charge model, and the results are compared with those from other methods: the six-dimensional molecular Ornstein-Zernike SCF, the one-dimensional site-site RISM-SCF, and the polarizable continuum model. The authors also calculate the solvatochromic shifts of acetone, benzonitrile, and nitrobenzene using the present method and compare them with the experimental and other theoretical results.
A three-dimensional correlation method for registration of medical images in radiology
Energy Technology Data Exchange (ETDEWEB)
Georgiou, Michalakis; Sfakianakis, George N [Department of Radiology, University of Miami, Jackson Memorial Hospital, Miami, FL 33136 (United States); Nagel, Joachim H [Institute of Biomedical Engineering, University of Stuttgart, Stuttgart 70174 (Germany)
1999-12-31
The availability of methods to register multi-modality images in order to `fuse` them to correlate their information is increasingly becoming an important requirement for various diagnostic and therapeutic procedures. A variety of image registration methods have been developed but they remain limited to specific clinical applications. Assuming rigid body transformation, two images can be registered if their differences are calculated in terms of translation, rotation and scaling. This paper describes the development and testing of a new correlation based approach for three-dimensional image registration. First, the scaling factors introduced by the imaging devices are calculated and compensated for. Then, the two images become translation invariant by computing their three-dimensional Fourier magnitude spectra. Subsequently, spherical coordinate transformation is performed and then the three-dimensional rotation is computed using a novice approach referred to as {sup p}olar Shells{sup .} The method of polar shells maps the three angles of rotation into one rotation and two translations of a two-dimensional function and then proceeds to calculate them using appropriate transformations based on the Fourier invariance properties. A basic assumption in the method is that the three-dimensional rotation is constrained to one large and two relatively small angles. This assumption is generally satisfied in normal clinical settings. The new three-dimensional image registration method was tested with simulations using computer generated phantom data as well as actual clinical data. Performance analysis and accuracy evaluation of the method using computer simulations yielded errors in the sub-pixel range. (authors) 6 refs., 3 figs.
Method of reduction of nitroaromatics by enzymatic reaction with redox enzymes
Shah, Manish M.
2000-01-01
A method for the controlled reduction of nitroaromatic compounds such as nitrobenzene and 2,4,6-trinitrotoluene by enzymatic reaction with redox enzymes, such as Oxyrase (Trademark of Oxyrase, Inc., Mansfield, Ohio).
A two-dimensional adaptive numerical grids generation method and its realization
International Nuclear Information System (INIS)
Xu Tao; Shui Hongshou
1998-12-01
A two-dimensional adaptive numerical grids generation method and its particular realization is discussed. This method is effective and easy to realize if the control functions are given continuously, and the grids for some regions is showed in this case. For Computational Fluid Dynamics, because the control values of adaptive grids-numerical solution is given in dispersed form, it is needed to interpolate these values to get the continuous control functions. These interpolation techniques are discussed, and some efficient adaptive grids are given. A two-dimensional fluid dynamics example was also given
International Nuclear Information System (INIS)
Sanchez, Richard.
1980-11-01
This work is divided into two part the first part (note CEA-N-2165) deals with the solution of complex two-dimensional transport problems, the second one treats the critically mixed methods of resolution. These methods are applied for one-dimensional geometries with highly anisotropic scattering. In order to simplify the set of integral equation provided by the integral transport equation, the integro-differential equation is used to obtain relations that allow to lower the number of integral equation to solve; a general mathematical and numerical study is presented [fr
Shigetoh, Keisuke; Horibuchi, Kayo; Nakamura, Daisuke
2017-11-01
Owing to the large differences in the chemical properties between Al and N polarities in aluminum nitride (AlN), the choice of the polar direction for crystal growth strongly affects not only the quality but also the shape (facet formation) of the grown crystal. In particular, N-polar (0 0 0 -1) has been considered to be a more preferable direction than Al-polar (0 0 0 1) for sublimation growth because compared to Al-polar (0 0 0 1), N-polar (0 0 0 -1) exhibits better stability at high growth rate (high supersaturation) conditions and enables easier lateral enlargement of the crystal. However, some critical growth conditions induce polarity inversion and hinder stable N-polar growth. Furthermore, the origin of the polarity inversion in AlN growth by the sublimation method is still unclear. To ensure stable N-polar growth without polarity inversion, the formation mechanism of the inversion domain during AlN sublimation growth must be elucidated. Therefore, herein, we demonstrate homoepitaxial growth on an N-polar seed and carefully investigate the obtained crystal that shows polarity inversion. Annular bright-field scanning transmission electron microscopy reveals that polarity is completely converted to the Al polarity via the formation of a 30 nm thick mixed polar layer (MPL) just above the seed. Moreover, three-dimensional atom probe tomography shows the segregation of the oxygen impurities in the MPL with a high concentration of about 3 atom%. Finally, by avoiding the incorporation of oxygen impurity into the crystal at the initial stage of the growth, we demonstrate an effective reduction (seven orders of magnitude) of the inversion domain boundary formation.
Development of three-dimensional individual bubble-velocity measurement method by bubble tracking
International Nuclear Information System (INIS)
Kanai, Taizo; Furuya, Masahiro; Arai, Takahiro; Shirakawa, Kenetsu; Nishi, Yoshihisa
2012-01-01
A gas-liquid two-phase flow in a large diameter pipe exhibits a three-dimensional flow structure. Wire-Mesh Sensor (WMS) consists of a pair of parallel wire layers located at the cross section of a pipe. Both the parallel wires cross at 90o with a small gap and each intersection acts as an electrode. The WMS allows the measurement of the instantaneous two-dimensional void-fraction distribution over the cross-section of a pipe, based on the difference between the local instantaneous conductivity of the two-phase flow. Furthermore, the WMS can acquire a phasic-velocity on the basis of the time lag of void signals between two sets of WMS. Previously, the acquired phasic velocity was one-dimensional with time-averaged distributions. The authors propose a method to estimate the three-dimensional bubble-velocity individually WMS data. The bubble velocity is determined by the tracing method. In this tracing method, each bubble is separated from WMS signal, volume and center coordinates of the bubble is acquired. Two bubbles with near volume at two WMS are considered as the same bubble and bubble velocity is estimated from the displacement of the center coordinates of the two bubbles. The validity of this method is verified by a swirl flow. The proposed method can successfully visualize a swirl flow structure and the results of this method agree with the results of cross-correlation analysis. (author)
Correlation based method for comparing and reconstructing quasi-identical two-dimensional structures
International Nuclear Information System (INIS)
Mejia-Barbosa, Y.
2000-03-01
We show a method for comparing and reconstructing two similar amplitude-only structures, which are composed by the same number of identical apertures. The structures are two-dimensional and differ only in the location of one of the apertures. The method is based on a subtraction algorithm, which involves the auto-correlations and cross-correlation functions of the compared structures. Experimental results illustrate the feasibility of the method. (author)
Semi-implicit method for three-dimensional compressible MHD simulation
International Nuclear Information System (INIS)
Harned, D.S.; Kerner, W.
1984-03-01
A semi-implicit method for solving the full compressible MHD equations in three dimensions is presented. The method is unconditionally stable with respect to the fast compressional modes. The time step is instead limited by the slower shear Alfven motion. The computing time required for one time step is essentially the same as for explicit methods. Linear stability limits are derived and verified by three-dimensional tests on linear waves in slab geometry. (orig.)
International Nuclear Information System (INIS)
Paixao, S.B.; Marzo, M.A.S.; Alvim, A.C.M.
1986-01-01
The calculation method used in WIGLE code is studied. Because of the non availability of such a praiseworthy solution, expounding the method minutely has been tried. This developed method has been applied for the solution of the one-dimensional, two-group, diffusion equations in slab, axial analysis, including non-boiling heat transfer, accountig for feedback. A steady-state program (CITER-1D), written in FORTRAN 4, has been implemented, providing excellent results, ratifying the developed work quality. (Author) [pt
A study on three dimensional layout design by the simulated annealing method
International Nuclear Information System (INIS)
Jang, Seung Ho
2008-01-01
Modern engineered products are becoming increasingly complicated and most consumers prefer compact designs. Layout design plays an important role in many engineered products. The objective of this study is to suggest a method to apply the simulated annealing method to the arbitrarily shaped three-dimensional component layout design problem. The suggested method not only optimizes the packing density but also satisfies constraint conditions among the components. The algorithm and its implementation as suggested in this paper are extendable to other research objectives
Development of three-dimensional transport code by the double finite element method
International Nuclear Information System (INIS)
Fujimura, Toichiro
1985-01-01
Development of a three-dimensional neutron transport code by the double finite element method is described. Both of the Galerkin and variational methods are adopted to solve the problem, and then the characteristics of them are compared. Computational results of the collocation method, developed as a technique for the vaviational one, are illustrated in comparison with those of an Ssub(n) code. (author)
A novel three-dimensional mesh deformation method based on sphere relaxation
International Nuclear Information System (INIS)
Zhou, Xuan; Li, Shuixiang
2015-01-01
In our previous work (2013) [19], we developed a disk relaxation based mesh deformation method for two-dimensional mesh deformation. In this paper, the idea of the disk relaxation is extended to the sphere relaxation for three-dimensional meshes with large deformations. We develop a node based pre-displacement procedure to apply initial movements on nodes according to their layer indices. Afterwards, the nodes are moved locally by the improved sphere relaxation algorithm to transfer boundary deformations and increase the mesh quality. A three-dimensional mesh smoothing method is also adopted to prevent the occurrence of the negative volume of elements, and further improve the mesh quality. Numerical applications in three-dimension including the wing rotation, bending beam and morphing aircraft are carried out. The results demonstrate that the sphere relaxation based approach generates the deformed mesh with high quality, especially regarding complex boundaries and large deformations
A novel three-dimensional mesh deformation method based on sphere relaxation
Energy Technology Data Exchange (ETDEWEB)
Zhou, Xuan [Department of Mechanics & Engineering Science, College of Engineering, Peking University, Beijing, 100871 (China); Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China); Li, Shuixiang, E-mail: lsx@pku.edu.cn [Department of Mechanics & Engineering Science, College of Engineering, Peking University, Beijing, 100871 (China)
2015-10-01
In our previous work (2013) [19], we developed a disk relaxation based mesh deformation method for two-dimensional mesh deformation. In this paper, the idea of the disk relaxation is extended to the sphere relaxation for three-dimensional meshes with large deformations. We develop a node based pre-displacement procedure to apply initial movements on nodes according to their layer indices. Afterwards, the nodes are moved locally by the improved sphere relaxation algorithm to transfer boundary deformations and increase the mesh quality. A three-dimensional mesh smoothing method is also adopted to prevent the occurrence of the negative volume of elements, and further improve the mesh quality. Numerical applications in three-dimension including the wing rotation, bending beam and morphing aircraft are carried out. The results demonstrate that the sphere relaxation based approach generates the deformed mesh with high quality, especially regarding complex boundaries and large deformations.
Pseudo three-dimensional modeling of particle-fuel packing using distinct element method
International Nuclear Information System (INIS)
Yuki, Daisuke; Takata, Takashi; Yamaguchi, Akira
2007-01-01
Vibration-based packing of sphere-pac fuel is a key technology in a nuclear fuel manufacturing. In the production process of sphere-pac fuel, a Mixed Oxide (MOX) fuel is formed to spherical form and is packed in a cladding tube by adding a vibration force. In the present study, we have developed a numerical simulation method to investigate the behavior of the particles in a vibrated tube using the Distinct Element Method (DEM). In general, the DEM requires a significant computational cost. Therefore we propose a new approach in which a small particle can move through the space between three larger particles even in the two-dimensional simulation. We take into account an equivalent three-dimensional effect in the equations of motion. Thus it is named pseudo three-dimensional modeling. (author)
Directory of Open Access Journals (Sweden)
Beretta Lorenzo
2010-08-01
Full Text Available Abstract Background Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. Results The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%. The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the FcγRIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Conclusions Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/
Finite element method for radiation heat transfer in multi-dimensional graded index medium
International Nuclear Information System (INIS)
Liu, L.H.; Zhang, L.; Tan, H.P.
2006-01-01
In graded index medium, ray goes along a curved path determined by Fermat principle, and curved ray-tracing is very difficult and complex. To avoid the complicated and time-consuming computation of curved ray trajectories, a finite element method based on discrete ordinate equation is developed to solve the radiative transfer problem in a multi-dimensional semitransparent graded index medium. Two particular test problems of radiative transfer are taken as examples to verify this finite element method. The predicted dimensionless net radiative heat fluxes are determined by the proposed method and compared with the results obtained by finite volume method. The results show that the finite element method presented in this paper has a good accuracy in solving the multi-dimensional radiative transfer problem in semitransparent graded index medium
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang
2017-09-27
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-09-21
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-01-01
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series
Directory of Open Access Journals (Sweden)
Keke Zhang
2018-01-01
Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.
Griebler, C; Slezak, D
2001-01-01
A new method to determine microbial (bacterial and fungal) activity in various freshwater habitats is described. Based on microbial reduction of dimethyl sulfoxide (DMSO) to dimethyl sulfide (DMS), our DMSO reduction method allows measurement of the respiratory activity in interstitial water, as well as in the water column. DMSO is added to water samples at a concentration (0.75% [vol/vol] or 106 mM) high enough to compete with other naturally occurring electron acceptors, as determined with oxygen and nitrate, without stimulating or inhibiting microbial activity. Addition of NaN(3), KCN, and formaldehyde, as well as autoclaving, inhibited the production of DMS, which proves that the reduction of DMSO is a biotic process. DMSO reduction is readily detectable via the formation of DMS even at low microbial activities. All water samples showed significant DMSO reduction over several hours. Microbially reduced DMSO is recovered in the form of DMS from water samples by a purge and trap system and is quantified by gas chromatography and detection with a flame photometric detector. The DMSO reduction method was compared with other methods commonly used for assessment of microbial activity. DMSO reduction activity correlated well with bacterial production in predator-free batch cultures. Cell-production-specific DMSO reduction rates did not differ significantly in batch cultures with different nutrient regimes but were different in different growth phases. Overall, a cell-production-specific DMSO reduction rate of 1.26 x 10(-17) +/- 0. 12 x 10(-17) mol of DMS per produced cell (mean +/- standard error; R(2) = 0.78) was calculated. We suggest that the relationship of DMSO reduction rates to thymidine and leucine incorporation is linear (the R(2) values ranged from 0.783 to 0.944), whereas there is an exponential relationship between DMSO reduction rates and glucose uptake, as well as incorporation (the R(2) values ranged from 0.821 to 0.931). Based on our results, we
Scintigraphic method for evaluating reductions in local blood volumes in human extremities
DEFF Research Database (Denmark)
Blønd, L; Madsen, Jan Lysgård
2000-01-01
in the experiment. Evaluation of one versus two scintigraphic projections, trials for assessment of the reproducibility, a comparison of the scintigraphic method with a water-plethysmographic method and registration of the fractional reduction in blood volume caused by exsanguination as a result of simple elevation......% in the lower limb experiment and 6% in the upper limb experiment. We found a significant relation (r = 0.42, p = 0.018) between the results obtained by the scintigraphic method and the plethysmographic method. In fractions, a mean reduction in blood volume of 0.49+0.14 (2 SD) was found after 1 min of elevation......We introduce a new method for evaluating reductions in local blood volumes in extremities, based on the combined use of autologue injection of 99mTc-radiolabelled erythrocytes and clamping of the limb blood flow by the use of a tourniquet. Twenty-two healthy male volunteers participated...
A New Ensemble Method with Feature Space Partitioning for High-Dimensional Data Classification
Directory of Open Access Journals (Sweden)
Yongjun Piao
2015-01-01
Full Text Available Ensemble data mining methods, also known as classifier combination, are often used to improve the performance of classification. Various classifier combination methods such as bagging, boosting, and random forest have been devised and have received considerable attention in the past. However, data dimensionality increases rapidly day by day. Such a trend poses various challenges as these methods are not suitable to directly apply to high-dimensional datasets. In this paper, we propose an ensemble method for classification of high-dimensional data, with each classifier constructed from a different set of features determined by partitioning of redundant features. In our method, the redundancy of features is considered to divide the original feature space. Then, each generated feature subset is trained by a support vector machine, and the results of each classifier are combined by majority voting. The efficiency and effectiveness of our method are demonstrated through comparisons with other ensemble techniques, and the results show that our method outperforms other methods.
A two-dimensional, semi-analytic expansion method for nodal calculations
International Nuclear Information System (INIS)
Palmtag, S.P.
1995-08-01
Most modern nodal methods used today are based upon the transverse integration procedure in which the multi-dimensional flux shape is integrated over the transverse directions in order to produce a set of coupled one-dimensional flux shapes. The one-dimensional flux shapes are then solved either analytically or by representing the flux shape by a finite polynomial expansion. While these methods have been verified for most light-water reactor applications, they have been found to have difficulty predicting the large thermal flux gradients near the interfaces of highly-enriched MOX fuel assemblies. A new method is presented here in which the neutron flux is represented by a non-seperable, two-dimensional, semi-analytic flux expansion. The main features of this method are (1) the leakage terms from the node are modeled explicitly and therefore, the transverse integration procedure is not used, (2) the corner point flux values for each node are directly edited from the solution method, and a corner-point interpolation is not needed in the flux reconstruction, (3) the thermal flux expansion contains hyperbolic terms representing analytic solutions to the thermal flux diffusion equation, and (4) the thermal flux expansion contains a thermal to fast flux ratio term which reduces the number of polynomial expansion functions needed to represent the thermal flux. This new nodal method has been incorporated into the computer code COLOR2G and has been used to solve a two-dimensional, two-group colorset problem containing uranium and highly-enriched MOX fuel assemblies. The results from this calculation are compared to the results found using a code based on the traditional transverse integration procedure
Ince, Elif; Kirbaslar, Fatma Gulay; Yolcu, Ergun; Aslan, Ayse Esra; Kayacan, Zeynep Cigdem; Alkan Olsson, Johanna; Akbasli, Ayse Ceylan; Aytekin, Mesut; Bauer, Thomas; Charalambis, Dimitris; Gunes, Zeliha Ozsoy; Kandemir, Ceyhan; Sari, Umit; Turkoglu, Suleyman; Yaman, Yavuz; Yolcu, Ozgu
2014-01-01
The purpose of this study is to develop a 3-dimensional interactive multi-user and multi-admin IUVIRLAB featuring active learning methods and techniques for university students and to introduce the Virtual Laboratory of Istanbul University and to show effects of IUVIRLAB on students' attitudes on communication skills and IUVIRLAB. Although there…
Newton-sor iterative method for solving the two-dimensional porous ...
African Journals Online (AJOL)
In this paper, we consider the application of the Newton-SOR iterative method in obtaining the approximate solution of the two-dimensional porous medium equation (2D PME). The nonlinear finite difference approximation equation to the 2D PME is derived by using the implicit finite difference scheme. The developed ...
A greedy method for reconstructing polycrystals from three-dimensional X-ray diffraction data
DEFF Research Database (Denmark)
Kulshreshth, Arun Kumar; Alpers, Andreas; Herman, Gabor T.
2009-01-01
An iterative search method is proposed for obtaining orientation maps inside polycrystals from three-dimensional X-ray diffraction (3DXRD) data. In each step, detector pixel intensities are calculated by a forward model based on the current estimate of the orientation map. The pixel at which...
Multisymplectic Structure-Preserving in Simple Finite Element Method in High Dimensional Case
Institute of Scientific and Technical Information of China (English)
BAI Yong-Qiang; LIU Zhen; PEI Ming; ZHENG Zhu-Jun
2003-01-01
In this paper, we study a finite element scheme of some semi-linear elliptic boundary value problems inhigh-dimensional space. With uniform mesh, we find that, the numerical scheme derived from finite element method cankeep a preserved multisymplectic structure.
Improving the accuracy of CT dimensional metrology by a novel beam hardening correction method
International Nuclear Information System (INIS)
Zhang, Xiang; Li, Lei; Zhang, Feng; Xi, Xiaoqi; Deng, Lin; Yan, Bin
2015-01-01
Its powerful nondestructive characteristics are attracting more and more research into the study of computed tomography (CT) for dimensional metrology, which offers a practical alternative to the common measurement methods. However, the inaccuracy and uncertainty severely limit the further utilization of CT for dimensional metrology due to many factors, among which the beam hardening (BH) effect plays a vital role. This paper mainly focuses on eliminating the influence of the BH effect in the accuracy of CT dimensional metrology. To correct the BH effect, a novel exponential correction model is proposed. The parameters of the model are determined by minimizing the gray entropy of the reconstructed volume. In order to maintain the consistency and contrast of the corrected volume, a punishment term is added to the cost function, enabling more accurate measurement results to be obtained by the simple global threshold method. The proposed method is efficient, and especially suited to the case where there is a large difference in gray value between material and background. Different spheres with known diameters are used to verify the accuracy of dimensional measurement. Both simulation and real experimental results demonstrate the improvement in measurement precision. Moreover, a more complex workpiece is also tested to show that the proposed method is of general feasibility. (paper)
Yin, Zhifu; Sun, Lei; Zou, Helin; Cheng, E.
2015-05-01
A method for obtaining a low-cost and high-replication precision two-dimensional (2D) nanofluidic device with a polymethyl methacrylate (PMMA) sheet is proposed. To improve the replication precision of the 2D PMMA nanochannels during the hot embossing process, the deformation of the PMMA sheet was analyzed by a numerical simulation method. The constants of the generalized Maxwell model used in the numerical simulation were calculated by experimental compressive creep curves based on previously established fitting formula. With optimized process parameters, 176 nm-wide and 180 nm-deep nanochannels were successfully replicated into the PMMA sheet with a replication precision of 98.2%. To thermal bond the 2D PMMA nanochannels with high bonding strength and low dimensional loss, the parameters of the oxygen plasma treatment and thermal bonding process were optimized. In order to measure the dimensional loss of 2D nanochannels after thermal bonding, a dimension loss evaluating method based on the nanoindentation experiments was proposed. According to the dimension loss evaluating method, the total dimensional loss of 2D nanochannels was 6 nm and 21 nm in width and depth, respectively. The tensile bonding strength of the 2D PMMA nanofluidic device was 0.57 MPa. The fluorescence images demonstrate that there was no blocking or leakage over the entire microchannels and nanochannels.
Geotechnical applications of a two-dimensional elastodynamic displacement discontinuity method
CSIR Research Space (South Africa)
Siebrits, E
1993-12-01
Full Text Available A general two-dimensional elastodynamic displacement discontinuity method is used to model a variety of application problems. The plane strain problems are: the elastodynamic motions induced on a cavity by shear slip on a nearby crack; the dynamic...
Numerical comparison of robustness of some reduction methods in rough grids
Hou, Jiangyong
2014-04-09
In this article, we present three nonsymmetric mixed hybrid RT 1 2 methods and compare with some recently developed reduction methods which are suitable for the single-phase Darcy flow problem with full anisotropic and highly heterogeneous permeability on general quadrilateral grids. The methods reviewed are multipoint flux approximation (MPFA), multipoint flux mixed finite element method, mixed-finite element with broken RT 1 2 method, MPFA-type mimetic finite difference method, and symmetric mixed-hybrid finite element method. The numerical experiments of these methods on different distorted meshes are compared, as well as their differences in performance of fluxes are discussed. © 2014 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Muhammad Aslam Noor
2008-01-01
Full Text Available We suggest and analyze a technique by combining the variational iteration method and the homotopy perturbation method. This method is called the variational homotopy perturbation method (VHPM. We use this method for solving higher dimensional initial boundary value problems with variable coefficients. The developed algorithm is quite efficient and is practically well suited for use in these problems. The proposed scheme finds the solution without any discritization, transformation, or restrictive assumptions and avoids the round-off errors. Several examples are given to check the reliability and efficiency of the proposed technique.
International Nuclear Information System (INIS)
Wang Qi; Chen Yong; Zhang Hongqing
2005-01-01
In this paper, we present a new Riccati equation rational expansion method to uniformly construct a series of exact solutions for nonlinear evolution equations. Compared with most existing tanh methods and other sophisticated methods, the proposed method not only recover some known solutions, but also find some new and general solutions. The solutions obtained in this paper include rational triangular periodic wave solutions, rational solitary wave solutions and rational wave solutions. The efficiency of the method can be demonstrated on (2 + 1)-dimensional Burgers equation
International Nuclear Information System (INIS)
Park, Jai Hak
2009-01-01
SGBEM(Symmetric Galerkin Boundary Element Method)-FEM alternating method has been proposed by Nikishkov, Park and Atluri. In the proposed method, arbitrarily shaped three-dimensional crack problems can be solved by alternating between the crack solution in an infinite body and the finite element solution without a crack. In the previous study, the SGBEM-FEM alternating method was extended further in order to solve elastic-plastic crack problems and to obtain elastic-plastic stress fields. For the elastic-plastic analysis the algorithm developed by Nikishkov et al. is used after modification. In the algorithm, the initial stress method is used to obtain elastic-plastic stress and strain fields. In this paper, elastic-plastic J integrals for three-dimensional cracks are obtained using the method. For that purpose, accurate values of displacement gradients and stresses are necessary on an integration path. In order to improve the accuracy of stress near crack surfaces, coordinate transformation and partitioning of integration domain are used. The coordinate transformation produces a transformation Jacobian, which cancels the singularity of the integrand. Using the developed program, simple three-dimensional crack problems are solved and elastic and elastic-plastic J integrals are obtained. The obtained J integrals are compared with the values obtained using a handbook solution. It is noted that J integrals obtained from the alternating method are close to the values from the handbook
Casimir effect in a d-dimensional flat spacetime and the cut-off method
International Nuclear Information System (INIS)
Svaiter, N.F.; Svaiter, B.F.
1989-01-01
The CasiMir efeect in a D-dimensional spacetime produced by a Hermitian massless scalar field in the presence of a pair of perfectly reflecting parallel flat plates is discussed. The exponential cut-off regularization method is employed. The regularized vacuum energy and the Casimir energy of this field are evaluated and a detailed analysis of the divergent terms in the regularized vacuum energy is carried out. The two-dimensional version of the Casimir effect is discussed by means of the same cut-off method. A comparison between the above method and the zeta function regularization procedure is presented in a way which gives the unification between these two methods in the present case. (author) [pt
Directory of Open Access Journals (Sweden)
Wei Tian
2015-01-01
Full Text Available Background: The treatment of high-grade developmental spondylolisthesis (HGDS is still challenging and controversial. In this study, we investigated the efficacy of the posterior reduction and monosegmental fusion assisted by intraoperative three-dimensional (3D navigation system in managing the HGDS. Methods: Thirteen consecutive HGDS patients were treated with posterior decompression, reduction and monosegmental fusion of L5/S1, assisted by intraoperative 3D navigation system. The clinical and radiographic outcomes were evaluated, with a minimum follow-up of 2 years. The differences between the pre- and post-operative measures were statistically analyzed using a two-tailed, paired t-test. Results: At most recent follow-up, 12 patients were pain-free. Only 1 patient had moderate pain. There were no permanent neurological complications or pseudarthrosis. The magnetic resonance imaging showed that there was no obvious disc degeneration in the adjacent segment. All radiographic parameters were improved. Mean slippage improved from 63.2% before surgery to 12.2% after surgery and 11.0% at latest follow-up. Lumbar lordosis changed from preoperative 34.9 ± 13.3° to postoperative 50.4 ± 9.9°, and 49.3 ± 7.8° at last follow-up. L5 incidence improved from 71.0 ± 11.3° to 54.0 ± 11.9° and did not change significantly at the last follow-up 53.1 ± 15.4°. While pelvic incidence remained unchanged, sacral slip significantly decreased from preoperative 32.7 ± 12.5° to postoperative 42.6 ± 9.8°and remained constant to the last follow-up 44.4 ± 6.9°. Pelvic tilt significantly decreased from 38.4 ± 12.5° to 30.9 ± 8.1° and remained unchanged at the last follow-up 28.1 ± 11.2°. Conclusions: Posterior reduction and monosegmental fusion of L5/S1 assisted by intraoperative 3D navigation are an effective technique for managing high-grade dysplastic spondylolisthesis. A complete reduction of local deformity and excellent correction of overall
Energy Technology Data Exchange (ETDEWEB)
Tres, Anderson [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Matematica Aplicada; Becker Picoloto, Camila [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica; Prolo Filho, Joao Francisco [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Inst de Matematica, Estatistica e Fisica; Dias da Cunha, Rudnei; Basso Barichello, Liliane [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Inst de Matematica
2014-04-15
In this work a study of two-dimensional fixed-source neutron transport problems, in Cartesian geometry, is reported. The approach reduces the complexity of the multidimensional problem using a combination of nodal schemes and the Analytical Discrete Ordinates Method (ADO). The unknown leakage terms on the boundaries that appear from the use of the derivation of the nodal scheme are incorporated to the problem source term, such as to couple the one-dimensional integrated solutions, made explicit in terms of the x and y spatial variables. The formulation leads to a considerable reduction of the order of the associated eigenvalue problems when combined with the usual symmetric quadratures, thereby providing solutions that have a higher degree of computational efficiency. Reflective-type boundary conditions are introduced to represent the domain on a simpler form than that previously considered in connection with the ADO method. Numerical results obtained with the technique are provided and compared to those present in the literature. (orig.)
Moving Least Squares Method for a One-Dimensional Parabolic Inverse Problem
Directory of Open Access Journals (Sweden)
Baiyu Wang
2014-01-01
Full Text Available This paper investigates the numerical solution of a class of one-dimensional inverse parabolic problems using the moving least squares approximation; the inverse problem is the determination of an unknown source term depending on time. The collocation method is used for solving the equation; some numerical experiments are presented and discussed to illustrate the stability and high efficiency of the method.
Image-Based Compression Method of Three-Dimensional Range Data with Texture
Chen, Xia; Bell, Tyler; Zhang, Song
2017-01-01
Recently, high speed and high accuracy three-dimensional (3D) scanning techniques and commercially available 3D scanning devices have made real-time 3D shape measurement and reconstruction possible. The conventional mesh representation of 3D geometry, however, results in large file sizes, causing difficulties for its storage and transmission. Methods for compressing scanned 3D data therefore become desired. This paper proposes a novel compression method which stores 3D range data within the c...
Shintani, Kenichirou; Yoshitomi, Shinta; Takewaki, Izuru
2017-01-01
A method of physical parameter system identification (SI) is proposed here for three-dimensional (3D) building structures with in-plane rigid floors in which the stiffness and damping coefficients of each structural frame in the 3D building structure are identified from the measured floor horizontal accelerations. A batch processing least-squares estimation method for many discrete time domain measured data is proposed for the direct identification of the stiffness and damping coefficients of...
International Nuclear Information System (INIS)
Yasuk, F.; Tekin, S.; Boztosun, I.
2010-01-01
In this study, the exact solutions of the d-dimensional Schroedinger equation with a position-dependent mass m(r)=1/(1+ζ 2 r 2 ) is presented for a free particle, V(r)=0, by using the method of point canonical transformations. The energy eigenvalues and corresponding wavefunctions for the effective potential which is to be a generalized Poeschl-Teller potential are obtained within the framework of the asymptotic iteration method.
One-Dimensional Finite Elements An Introduction to the FE Method
Öchsner, Andreas
2013-01-01
This textbook presents finite element methods using exclusively one-dimensional elements. The aim is to present the complex methodology in an easily understandable but mathematically correct fashion. The approach of one-dimensional elements enables the reader to focus on the understanding of the principles of basic and advanced mechanical problems. The reader easily understands the assumptions and limitations of mechanical modeling as well as the underlying physics without struggling with complex mathematics. But although the description is easy it remains scientifically correct. The approach using only one-dimensional elements covers not only standard problems but allows also for advanced topics like plasticity or the mechanics of composite materials. Many examples illustrate the concepts and problems at the end of every chapter help to familiarize with the topics.
Frahm, Jan-Michael; Pollefeys, Marc Andre Leon; Gallup, David Robert
2015-12-08
Methods of generating a three dimensional representation of an object in a reference plane from a depth map including distances from a reference point to pixels in an image of the object taken from a reference point. Weights are assigned to respective voxels in a three dimensional grid along rays extending from the reference point through the pixels in the image based on the distances in the depth map from the reference point to the respective pixels, and a height map including an array of height values in the reference plane is formed based on the assigned weights. An n-layer height map may be constructed by generating a probabilistic occupancy grid for the voxels and forming an n-dimensional height map comprising an array of layer height values in the reference plane based on the probabilistic occupancy grid.
An axial calculation method for accurate two-dimensional PWR core simulation
International Nuclear Information System (INIS)
Grimm, P.
1985-02-01
An axial calculation method, which improves the agreement of the multiplication factors determined by two- and three-dimensional PWR neutronic calculations, is presented. The axial buckling is determined at each time point so as to reproduce the increase of the leakage due to the flattening of the axial power distribution and the effect of the axial variation of the group constants of the fuel on the reactivity is taken into account. The results of a test example show that the differences of k-eff and cycle length between two- and three-dimensional calculations, which are unsatisfactorily large if a constant buckling is used, become negligible if the results of the axial calculation are used in the two-dimensional core simulation. (Auth.)
Application of advanced data reduction methods to gas turbine dynamic analysis
International Nuclear Information System (INIS)
Juhl, P.B.
1978-01-01
This paper discusses the application of advanced data reduction methods to the evaluation of dynamic data from gas turbines and turbine components. The use of the Fast Fourier Transform and of real-time spectrum analyzers is discussed. The use of power spectral density and probability density functions for analyzing random data is discussed. Examples of the application of these modern techniques to gas turbine testing are presented. The use of the computer to automate the data reduction procedures is discussed. (orig.) [de
ULTRACAVITATION METHOD OF EVALUATION IN THE REDUCTION OF LOCALIZED FAT IN WOMEN
L. Petraglia; D. R. X. O. Crege; J. L. Dullius; A. E. Bighetti
2017-01-01
This study evaluated cosmetic fat reduction methods that cause localized lipolysis and that are not invasive. The use of a differentiated ultrasound called Ultracavitation was evaluated, it causes reduction of localized fat in the infra abdominal region. 30 women aged 30-45 years old, healthy, sedentary were evaluated; they were separated into two groups subjected to 12 treatment sessions in infra abdominal region, once a week, alone or combined with aerobic exercise. Photographic recording w...
Research on numerical method for multiple pollution source discharge and optimal reduction program
Li, Mingchang; Dai, Mingxin; Zhou, Bin; Zou, Bin
2018-03-01
In this paper, the optimal method for reduction program is proposed by the nonlinear optimal algorithms named that genetic algorithm. The four main rivers in Jiangsu province, China are selected for reducing the environmental pollution in nearshore district. Dissolved inorganic nitrogen (DIN) is studied as the only pollutant. The environmental status and standard in the nearshore district is used to reduce the discharge of multiple river pollutant. The research results of reduction program are the basis of marine environmental management.
A general mixed boundary model reduction method for component mode synthesis
Voormeeren, S.N.; Van der Valk, P.L.C.; Rixen, D.J.
2010-01-01
A classic issue in component mode synthesis (CMS) methods is the choice for fixed or free boundary conditions at the interface degrees of freedom (DoF) and the associated vibration modes in the components reduction base. In this paper, a novel mixed boundary CMS method called the “Mixed
A new uncertainty reduction method for PWR cores with erbia bearing fuel
International Nuclear Information System (INIS)
Takeda, Toshikazu; Sano, Tadafumi; Kitada, Takanori; Kuroishi, Takeshi; Yamasaki, Masatoshi; Unesaki, Hironobu
2008-01-01
The concept of a PWR with erbia bearing high burnup fuel has been proposed. The erbia is added to all fuel with over 5% 235 U enrichment to retain the neutronics characteristics to that within 5% 235 U enrichment. There is a problem of the prediction accuracy of the neutronics characteristics with erbia bearing fuel because of the short of experimental data of erbia bearing fuel. The purpose of the present work is to reduce the uncertainty. A new method has been proposed by combining the bias factor method and the cross section adjustment method. For the PWR core, the uncertainty reduction, which shows the rate of reduction of uncertainty, of the k eff is 0.865 by the present method and 0.801 by the conventional bias factor method. Thus the prediction uncertainties are reduced by the present method compared to the bias factor method. (authors)
Levels of reduction in van Manen's phenomenological hermeneutic method: an empirical example.
Heinonen, Kristiina
2015-05-01
To describe reduction as a method using van Manen's phenomenological hermeneutic research approach. Reduction involves several levels that can be distinguished for their methodological usefulness. Researchers can use reduction in different ways and dimensions for their methodological needs. A study of Finnish multiple-birth families in which open interviews (n=38) were conducted with public health nurses, family care workers and parents of twins. A systematic literature and knowledge review showed there were no articles on multiple-birth families that used van Manen's method. Discussion The phenomena of the 'lifeworlds' of multiple-birth families consist of three core essential themes as told by parents: 'a state of constant vigilance', 'ensuring that they can continue to cope' and 'opportunities to share with other people'. Reduction provides the opportunity to carry out in-depth phenomenological hermeneutic research and understand people's lives. It helps to keep research stages separate but also enables a consolidated view. Social care and healthcare professionals have to hear parents' voices better to comprehensively understand their situation; they need further tools and training to be able to empower parents of twins. This paper adds an empirical example to the discussion of phenomenology, hermeneutic study and reduction as a method. It opens up reduction for researchers to exploit.
International Nuclear Information System (INIS)
Niki, Noboru; Mizutani, Toshio; Takahashi, Yoshizo; Inouye, Tamon.
1983-01-01
The nescessity for developing real-time computerized tomography (CT) aiming at the dynamic observation of organs such as hearts has lately been advocated. It is necessary for its realization to reconstruct the images which are markedly faster than present CTs. Although various reconstructing methods have been proposed so far, the method practically employed at present is the filtered backprojection (FBP) method only, which can give high quality image reconstruction, but takes much computing time. In the past, the two-dimensional Fourier transform (TFT) method was regarded as unsuitable to practical use because the quality of images obtained was not good, in spite of the promising method for high speed reconstruction because of its less computing time. However, since it was revealed that the image quality by TFT method depended greatly on interpolation accuracy in two-dimensional Fourier space, the authors have developed a high-speed calculation algorithm that can obtain high quality images by pursuing the relationship between the image quality and the interpolation method. In this case, radial data sampling points in Fourier space are increased to β-th power of 2 times, and the linear or spline interpolation is used. Comparison of this method with the present FBP method resulted in the conclusion that the image quality is almost the same in practical image matrix, the computational time by TFT method becomes about 1/10 of FBP method, and the memory capacity also reduces by about 20 %. (Wakatsuki, Y.)
Modified Splitting FDTD Methods for Two-Dimensional Maxwell’s Equations
Directory of Open Access Journals (Sweden)
Liping Gao
2017-01-01
Full Text Available In this paper, we develop a new method to reduce the error in the splitting finite-difference method of Maxwell’s equations. By this method two modified splitting FDTD methods (MS-FDTDI, MS-FDTDII for the two-dimensional Maxwell equations are proposed. It is shown that the two methods are second-order accurate in time and space and unconditionally stable by Fourier methods. By energy method, it is proved that MS-FDTDI is second-order convergent. By deriving the numerical dispersion (ND relations, we prove rigorously that MS-FDTDI has less ND errors than the ADI-FDTD method and the ND errors of ADI-FDTD are less than those of MS-FDTDII. Numerical experiments for computing ND errors and simulating a wave guide problem and a scattering problem are carried out and the efficiency of the MS-FDTDI and MS-FDTDII methods is confirmed.
International Nuclear Information System (INIS)
Ravi Kanth, A.S.V.; Aruna, K.
2009-01-01
In this paper, we propose a reliable algorithm to develop exact and approximate solutions for the linear and nonlinear Schroedinger equations. The approach rest mainly on two-dimensional differential transform method which is one of the approximate methods. The method can easily be applied to many linear and nonlinear problems and is capable of reducing the size of computational work. Exact solutions can also be achieved by the known forms of the series solutions. Several illustrative examples are given to demonstrate the effectiveness of the present method.
Development of a three dimensional circulation model based on fractional step method
Directory of Open Access Journals (Sweden)
Mazen Abualtayef
2010-03-01
Full Text Available A numerical model was developed for simulating a three-dimensional multilayer hydrodynamic and thermodynamic model in domains with irregular bottom topography. The model was designed for examining the interactions between flow and topography. The model was based on the three-dimensional Navier-Stokes equations and was solved using the fractional step method, which combines the finite difference method in the horizontal plane and the finite element method in the vertical plane. The numerical techniques were described and the model test and application were presented. For the model application to the northern part of Ariake Sea, the hydrodynamic and thermodynamic results were predicted. The numerically predicted amplitudes and phase angles were well consistent with the field observations.
Multi-GPU accelerated three-dimensional FDTD method for electromagnetic simulation.
Nagaoka, Tomoaki; Watanabe, Soichi
2011-01-01
Numerical simulation with a numerical human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the numerical human model, we adapt three-dimensional FDTD code to a multi-GPU environment using Compute Unified Device Architecture (CUDA). In this study, we used NVIDIA Tesla C2070 as GPGPU boards. The performance of multi-GPU is evaluated in comparison with that of a single GPU and vector supercomputer. The calculation speed with four GPUs was approximately 3.5 times faster than with a single GPU, and was slightly (approx. 1.3 times) slower than with the supercomputer. Calculation speed of the three-dimensional FDTD method using GPUs can significantly improve with an expanding number of GPUs.
International Nuclear Information System (INIS)
Chen, G.S.
1997-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used. TFQMR (transpose free quasi-minimal residual algorithm), CGS (conjuage gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These sub-routines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. (author)
Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J
2017-07-01
Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.
Ülger, Fatma Esra Bahadır; Ülger, Aykut; Karakaya, Ali Erdal; Tüten, Fatih; Katı, Ömer; Çolak, Mustafa
2014-03-01
Intussusception is one of the important causes of intestinal obstruction in children. Hydrostatic reduction under ultrasound guidance is a popular treatment method for intussusception. In the present study, we aimed to explain the demographic characteristics of and treatment approaches in patients diagnosed with intussusception by ultrasound. Forty-one patients diagnosed with intussusception by ultrasound between August 2011 and May 2013 were retrospectively analyzed. Twenty-four of these patients who had no contraindications had been treated with ultrasound-guided hydrostatic reduction. Twenty-four of the patients were male and 17 were female, a 1.4/1 male-to-female ratio. The majority of the patients were between the ages of 6-24 months and 2-5 years. The mean age was 31.12±26.32 months (range 3-125). Patients were more frequently diagnosed in April and May. Seventeen patients who had clinical contraindications enrolled directly for surgery. In 20 of the 24 patients who underwent ultrasound-guided hydrostatic reduction, reduction was achieved. Three experienced recurrence. In two of these patients, successful reduction was achieved with the second attempt. The remaining patient was enrolled for surgery. Hydrostatic reduction was performed 26 times on these 24 patients, and in 22, success was achieved (84.6%). No procedure-related complications occurred in the patients. Ultrasound-guided hydrostatic reduction, with its high success rates and lack of radiation risk, should be the first choice therapeutic approach for children diagnosed with intussusception.
Laguda, Edcer Jerecho
Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient's medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method. Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three
Chen, Hui; Deng, Ju-Zhi; Yin, Min; Yin, Chang-Chun; Tang, Wen-Wu
2017-03-01
To speed up three-dimensional (3D) DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method (AGMG). We first discretize the differential equation of the secondary potential field with mixed boundary conditions by using a seven-point finite-difference method to obtain a large sparse system of linear equations. Then, we introduce the theory behind the pairwise aggregation algorithms for AGMG and use the conjugate-gradient method with the V-cycle AGMG preconditioner (AGMG-CG) to solve the linear equations. We use typical geoelectrical models to test the proposed AGMG-CG method and compare the results with analytical solutions and the 3DDCXH algorithm for 3D DC modeling (3DDCXH). In addition, we apply the AGMG-CG method to different grid sizes and geoelectrical models and compare it to different iterative methods, such as ILU-BICGSTAB, ILU-GCR, and SSOR-CG. The AGMG-CG method yields nearly linearly decreasing errors, whereas the number of iterations increases slowly with increasing grid size. The AGMG-CG method is precise and converges fast, and thus can improve the computational efficiency in forward modeling of three-dimensional DC resistivity.
Chen, Tao; Clauser, Christoph; Marquart, Gabriele; Willbrand, Karen; Hiller, Thomas
2018-02-01
Upscaling permeability of grid blocks is crucial for groundwater models. A novel upscaling method for three-dimensional fractured porous rocks is presented. The objective of the study was to compare this method with the commonly used Oda upscaling method and the volume averaging method. First, the multiple boundary method and its computational framework were defined for three-dimensional stochastic fracture networks. Then, the different upscaling methods were compared for a set of rotated fractures, for tortuous fractures, and for two discrete fracture networks. The results computed by the multiple boundary method are comparable with those of the other two methods and fit best the analytical solution for a set of rotated fractures. The errors in flow rate of the equivalent fracture model decrease when using the multiple boundary method. Furthermore, the errors of the equivalent fracture models increase from well-connected fracture networks to poorly connected ones. Finally, the diagonal components of the equivalent permeability tensors tend to follow a normal or log-normal distribution for the well-connected fracture network model with infinite fracture size. By contrast, they exhibit a power-law distribution for the poorly connected fracture network with multiple scale fractures. The study demonstrates the accuracy and the flexibility of the multiple boundary upscaling concept. This makes it attractive for being incorporated into any existing flow-based upscaling procedures, which helps in reducing the uncertainty of groundwater models.
Irges, Nikos; Zoupanos, George
2011-01-01
We present an extension of the Standard Model inspired by the E_8 x E_8 Heterotic String. In order that a reasonable effective Lagrangian is presented we neglect everything else other than the ten-dimensional N=1 supersymmetric Yang-Mills sector associated with one of the gauge factors and certain couplings necessary for anomaly cancellation. We consider a compactified space-time M_4 x B_0 / Z_3, where B_0 is the nearly-Kaehler manifold SU(3)/U(1) x U(1) and Z_3 is a freely acting discrete group on B_0. Then we reduce dimensionally the E_8 on this manifold and we employ the Wilson flux mechanism leading in four dimensions to an SU(3)^3 gauge theory with the spectrum of a N=1 supersymmetric theory. We compute the effective four-dimensional Lagrangian and demonstrate that an extension of the Standard Model is obtained with interesting features including a conserved baryon number and fixed tree level Yukawa couplings and scalar potential. The spectrum contains new states such as right handed neutrinos and heavy ...
Advanced numerical methods for three dimensional two-phase flow calculations
Energy Technology Data Exchange (ETDEWEB)
Toumi, I. [Laboratoire d`Etudes Thermiques des Reacteurs, Gif sur Yvette (France); Caruge, D. [Institut de Protection et de Surete Nucleaire, Fontenay aux Roses (France)
1997-07-01
This paper is devoted to new numerical methods developed for both one and three dimensional two-phase flow calculations. These methods are finite volume numerical methods and are based on the use of Approximate Riemann Solvers concepts to define convective fluxes versus mean cell quantities. The first part of the paper presents the numerical method for a one dimensional hyperbolic two-fluid model including differential terms as added mass and interface pressure. This numerical solution scheme makes use of the Riemann problem solution to define backward and forward differencing to approximate spatial derivatives. The construction of this approximate Riemann solver uses an extension of Roe`s method that has been successfully used to solve gas dynamic equations. As far as the two-fluid model is hyperbolic, this numerical method seems very efficient for the numerical solution of two-phase flow problems. The scheme was applied both to shock tube problems and to standard tests for two-fluid computer codes. The second part describes the numerical method in the three dimensional case. The authors discuss also some improvements performed to obtain a fully implicit solution method that provides fast running steady state calculations. Such a scheme is not implemented in a thermal-hydraulic computer code devoted to 3-D steady-state and transient computations. Some results obtained for Pressurised Water Reactors concerning upper plenum calculations and a steady state flow in the core with rod bow effect evaluation are presented. In practice these new numerical methods have proved to be stable on non staggered grids and capable of generating accurate non oscillating solutions for two-phase flow calculations.
Advanced numerical methods for three dimensional two-phase flow calculations
International Nuclear Information System (INIS)
Toumi, I.; Caruge, D.
1997-01-01
This paper is devoted to new numerical methods developed for both one and three dimensional two-phase flow calculations. These methods are finite volume numerical methods and are based on the use of Approximate Riemann Solvers concepts to define convective fluxes versus mean cell quantities. The first part of the paper presents the numerical method for a one dimensional hyperbolic two-fluid model including differential terms as added mass and interface pressure. This numerical solution scheme makes use of the Riemann problem solution to define backward and forward differencing to approximate spatial derivatives. The construction of this approximate Riemann solver uses an extension of Roe's method that has been successfully used to solve gas dynamic equations. As far as the two-fluid model is hyperbolic, this numerical method seems very efficient for the numerical solution of two-phase flow problems. The scheme was applied both to shock tube problems and to standard tests for two-fluid computer codes. The second part describes the numerical method in the three dimensional case. The authors discuss also some improvements performed to obtain a fully implicit solution method that provides fast running steady state calculations. Such a scheme is not implemented in a thermal-hydraulic computer code devoted to 3-D steady-state and transient computations. Some results obtained for Pressurised Water Reactors concerning upper plenum calculations and a steady state flow in the core with rod bow effect evaluation are presented. In practice these new numerical methods have proved to be stable on non staggered grids and capable of generating accurate non oscillating solutions for two-phase flow calculations
Two-Dimensional Space-Time Dependent Multi-group Diffusion Equation with SLOR Method
International Nuclear Information System (INIS)
Yulianti, Y.; Su'ud, Z.; Waris, A.; Khotimah, S. N.
2010-01-01
The research of two-dimensional space-time diffusion equations with SLOR (Successive-Line Over Relaxation) has been done. SLOR method is chosen because this method is one of iterative methods that does not required to defined whole element matrix. The research is divided in two cases, homogeneous case and heterogeneous case. Homogeneous case has been inserted by step reactivity. Heterogeneous case has been inserted by step reactivity and ramp reactivity. In general, the results of simulations are agreement, even in some points there are differences.
Application of the Green's function method for 2- and 3-dimensional steady transonic flows
Tseng, K.
1984-01-01
A Time-Domain Green's function method for the nonlinear time-dependent three-dimensional aerodynamic potential equation is presented. The Green's theorem is being used to transform the partial differential equation into an integro-differential-delay equation. Finite-element and finite-difference methods are employed for the spatial and time discretizations to approximate the integral equation by a system of differential-delay equations. Solution may be obtained by solving for this nonlinear simultaneous system of equations in time. This paper discusses the application of the method to the Transonic Small Disturbance Equation and numerical results for lifting and nonlifting airfoils and wings in steady flows are presented.
International Nuclear Information System (INIS)
Ren Dan; Ren Zhuoxiang; Qu Hui; Xu Xiaoyu
2015-01-01
Capacitance extraction is one of the key issues in integrated circuits and also a typical electrostatic problem. The dual discrete geometric method (DGM) is investigated to provide relative solutions in two-dimensional unstructured mesh space. The energy complementary characteristic and quick field energy computation thereof based on it are emphasized. Contrastive analysis between the dual finite element methods and the dual DGMs are presented both from theoretical derivation and through case studies. The DGM, taking the scalar potential as unknown on dual interlocked meshes, with simple form and good accuracy, is expected to be one of the mainstreaming methods in associated areas. (paper)
International Nuclear Information System (INIS)
Xi Li-Ying; Chen Huan-Ming; Zheng Fu; Gao Hua; Tong Yang; Ma Zhi
2015-01-01
Three-dimensional simulations of ferroelectric hysteresis and butterfly loops are carried out based on solving the time dependent Ginzburg–Landau equations using a finite volume method. The influence of externally mechanical loadings with a tensile strain and a compressive strain on the hysteresis and butterfly loops is studied numerically. Different from the traditional finite element and finite difference methods, the finite volume method is applicable to simulate the ferroelectric phase transitions and properties of ferroelectric materials even for more realistic and physical problems. (paper)
An improved method for computer generation of three-dimensional digital holography
International Nuclear Information System (INIS)
Hu, Yanlei; Chen, Yuhang; Li, Jiawen; Huang, Wenhao; Chu, Jiaru; Ma, Jianqiang
2013-01-01
A novel method is proposed for designing optimized three-dimensional computer-generated holograms (CGHs). A series of spherical wave factors are introduced into the conventional optimal rotation angle (ORA) algorithm to achieve a varying amount of defocus along the optical axis, and the distraction terms are minimized during the iterative process. Both numerical simulation and experimental reconstructions are presented to demonstrate that this method is able to yield excellent multilayer patterns with high uniformity and signal-to-noise ratio (SNR). This method is significant for applications in laser 3D printing and multilayer data recording. (paper)
A new method for three-dimensional laparoscopic ultrasound model reconstruction
DEFF Research Database (Denmark)
Fristrup, C W; Pless, T; Durup, J
2004-01-01
BACKGROUND: Laparoscopic ultrasound is an important modality in the staging of gastrointestinal tumors. Correct staging depends on good spatial understanding of the regional tumor infiltration. Three-dimensional (3D) models may facilitate the evaluation of tumor infiltration. The aim of the study...... accuracy of the new method was tested ex vivo, and the clinical feasibility was tested on a small series of patients. RESULTS: Both electromagnetic tracked reconstructions and the new 3D method gave good volumetric information with no significant difference. Clinical use of the new 3D method showed...
The discrete cones method for two-dimensional neutron transport calculations
International Nuclear Information System (INIS)
Watanabe, Y.; Maynard, C.W.
1986-01-01
A novel method, the discrete cones method (DC/sub N/), is proposed as an alternative to the discrete ordinates method (S/sub N/) for solutions of the two-dimensional neutron transport equation. The new method utilizes a new concept, discrete cones, which are made by partitioning a unit spherical surface that the direction vector of particles covers. In this method particles in a cone are simultaneously traced instead of those in discrete directions so that an anomaly of the S/sub N/ method, the ray effects, can be eliminated. The DC/sub N/ method has been formulated for X-Y geometry and a program has been creaed by modifying the standard S/sub N/ program TWOTRAN-II. Our sample calculations demonstrate a strong mitigation of the ray effects without a computing cost penalty
The discrete cones methods for two-dimensional neutral particle transport problems with voids
International Nuclear Information System (INIS)
Watanabe, Y.; Maynard, C.W.
1983-01-01
One of the most widely applied deterministic methods for time-independent, two-dimensional neutron transport calculations is the discrete ordinates method (DSN). The DSN solution, however, fails to be accurate in a void due to the ray effect. In order to circumvent this drawback, the authors have been developing a novel approximation: the discrete cones method (DCN), where a group of particles in a cone are simultaneously traced instead of particles in discrete directions for the DSN method. Programs, which apply to the DSN method in a non-vacuum region and the DCN method in a void, have been written for transport calculations in X-Y coordinates. The solutions for test problems demonstrate mitigation of the ray effect in voids without loosing the computational efficiency of the DSN method
Method for the manufacture of a thin-layer battery stack on a three-dimensional substrate
2008-01-01
The invention relates to a method for the manufacture of a thin-layer battery stack on a three-dimensional substrate. The invention further relates to a thin-layer battery stack on a three-dimensional substrate obtainable by such a method. Moreover, the invention relates to a device comprising such
Development of the method for the dimensional measurement of the HANARO nuclear fuel
International Nuclear Information System (INIS)
Kim, Tae Yeon; Lee, K. S.; Park, D. G.; Choo, Y. S.; Ahn, S. B.
1998-06-01
Dimension of the nuclear fuel is altered in nuclear reactor because of the neutron exposure with high pressure water. If the deformation is overlarge, the severe problem in safety of the nuclear fuel and the reactor come about. Therefore the accurate dimensional data of the nuclear fuel in diameter and length is very important for the design of the nuclear fuel and the estimation of the nuclear safety. Measurement of diameter for the dummy HANARO fuel rod which has not filled with real fuel material was carried out in hot cell. And also the length of the HANARO fuel assembly and the rod are measured. Dimensional measuring method for the HANARO fuel was developed. The test result show our method is good enough to distinguish change in volume with statistical uncertainty of 0.6 %. (author). 2 refs., 7 tabs., 20 figs
International Nuclear Information System (INIS)
Kitano, Toshio; Morita, Mitsuaki; Nakagawa, Keisuke; Wada, Mayuko; Kuroda, Takaaki; Imai, Yuuki; Sakai, Toshiyuki; Eguchi, Yoshitaka
2010-01-01
What makes treatment choice for developmental dysplasia of the hips diagnosed after walking age difficult is the poor understanding of prereduction conditions that obstruct the reduction in spatial terms. To evaluate these problems, we employed subtraction three-dimensional imaging to search for the factors involved in intraarticular obstruction. On the basis of the findings of preoperative subtraction three-dimensional imaging from computed tomography, we developed a new method, a minimum invasive arthroscopic reduction with limboplasty, for reduction of developmental dysplasia of the hips after walking age. The purposes of this report were to: describe the technique of the arthroscopic procedure, and evaluate our new method using radiographic parameters. Ten patients with ten hips with developmental dysplasia after walking age treated by arthroscopic reduction with limboplasty were included in this study. The mean age of the patients at reduction was 22.6 months (range, 18.6-29.7 months); mean age at follow up was 7.2 years (range, 3.9-10.9 years); and mean follow up was 5.4 years (range, 1.7-9.0 years). These ten hips were evaluated using radiographic measurements. Moderate or severe avascular necrosis of the femoral head was not observed. Two hips that had a spherical-shaped head with minimal residual height loss or coxa magna were classified as Kalamchi and MacEwen grade 1. Additional surgery had been performed for two hips classified as Severin group 4 during the course of follow up. These two hips were classified as Severin group 1 at final examination. One more hip was classified as Severin group 4 at final examination, and additional surgery was recommended. The remaining seven hips (70%) therefore obtained good evaluations by arthroscopic reduction with limboplasty alone. We developed a new reduction method by using an arthroscopic procedure for the reduction of developmental dysplasia of the hips after walking age when this dysplasia failed to be reduced
Moment-based method for computing the two-dimensional discrete Hartley transform
Dong, Zhifang; Wu, Jiasong; Shu, Huazhong
2009-10-01
In this paper, we present a fast algorithm for computing the two-dimensional (2-D) discrete Hartley transform (DHT). By using kernel transform and Taylor expansion, the 2-D DHT is approximated by a linear sum of 2-D geometric moments. This enables us to use the fast algorithms developed for computing the 2-D moments to efficiently calculate the 2-D DHT. The proposed method achieves a simple computational structure and is suitable to deal with any sequence lengths.
DEFF Research Database (Denmark)
Yoon, Gil Ho; Joung, Young Soo; Kim, Yoon Young
2005-01-01
The topology design optimization of “three-dimensional geometrically-nonlinear” continuum structures is still a difficult problem not only because of its problem size but also the occurrence of unstable continuum finite elements during the design optimization. To overcome this difficulty, the ele......) stiffness matrix of continuum finite elements. Therefore, any finite element code, including commercial codes, can be readily used for the ECP implementation. The key ideas and characteristics of these methods will be presented in this paper....
Soliton solutions of the two-dimensional KdV-Burgers equation by homotopy perturbation method
International Nuclear Information System (INIS)
Molabahrami, A.; Khani, F.; Hamedi-Nezhad, S.
2007-01-01
In this Letter, the He's homotopy perturbation method (HPM) to finding the soliton solutions of the two-dimensional Korteweg-de Vries Burgers' equation (tdKdVB) for the initial conditions was applied. Numerical solutions of the equation were obtained. The obtained solutions, in comparison with the exact solutions admit a remarkable accuracy. The results reveal that the HPM is very effective and simple
Semiconductor/metal nanocomposites formed by in situ reduction method in multilayer thin films
International Nuclear Information System (INIS)
Song Yanli; Wang Enbo; Tian Chungui; Mao Baodong; Wang Chunlei
2009-01-01
A layer-by-layer adsorption and in situ reduction method was adopted for synthesizing semiconductor/metal nanocomposites in multilayer ultra-thin films. Alternate adsorption of ZnO nanoparticles modified with poly(ethyleneimine), hydrogentetrachloroaurate and poly(styrenesulfonate) sodium results in the formation of ZnO/AuCl 4 - -loaded multilayer films. In situ reduction of the incorporated metal ions by heating yields ZnO/Au nanocomposites in the films. UV-vis absorption spectroscopy and X-ray photoelectron spectroscopy were used to characterize the components of the composite films. UV-vis spectra indicate regular growth of the films. The electrochemistry behavior of the multilayer films was studied in detail on indium tin oxide electrode. The combined results suggest that the layer-by-layer adsorption and subsequent reduction method used here provides an effective way to synthesize ZnO/Au nanocomposites in the polymer matrix
Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?
Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W
2018-03-01
The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.
International Nuclear Information System (INIS)
Rabrait, C.
2007-11-01
Echo Planar Imaging is widely used to perform data acquisition in functional neuroimaging. This sequence allows the acquisition of a set of about 30 slices, covering the whole brain, at a spatial resolution ranging from 2 to 4 mm, and a temporal resolution ranging from 1 to 2 s. It is thus well adapted to the mapping of activated brain areas but does not allow precise study of the brain dynamics. Moreover, temporal interpolation is needed in order to correct for inter-slices delays and 2-dimensional acquisition is subject to vascular in flow artifacts. To improve the estimation of the hemodynamic response functions associated with activation, this thesis aimed at developing a 3-dimensional high temporal resolution acquisition method. To do so, Echo Volume Imaging was combined with reduced field-of-view acquisition and parallel imaging. Indeed, E.V.I. allows the acquisition of a whole volume in Fourier space following a single excitation, but it requires very long echo trains. Parallel imaging and field-of-view reduction are used to reduce the echo train durations by a factor of 4, which allows the acquisition of a 3-dimensional brain volume with limited susceptibility-induced distortions and signal losses, in 200 ms. All imaging parameters have been optimized in order to reduce echo train durations and to maximize S.N.R., so that cerebral activation can be detected with a high level of confidence. Robust detection of brain activation was demonstrated with both visual and auditory paradigms. High temporal resolution hemodynamic response functions could be estimated through selective averaging of the response to the different trials of the stimulation. To further improve S.N.R., the matrix inversions required in parallel reconstruction were regularized, and the impact of the level of regularization on activation detection was investigated. Eventually, potential applications of parallel E.V.I. such as the study of non-stationary effects in the B.O.L.D. response
International Nuclear Information System (INIS)
Tang, Sheng; Zhou, Xuejun; Xu, Nengneng; Bai, Zhengyu; Qiao, Jinli; Zhang, Jiujun
2016-01-01
Highlights: • 3-D porous N-doped graphene was prepared using one-step silica template-free method. • High specific surface area of 920 m 2 g −1 was achieved for 3-D porous N-doped graphene. • Much higher ORR activity was observed for N-doped graphene than S-doped one in 0.1 M KOH. • The as-prepared catalyst gave a peak power density of 275 mW cm −2 as zinc–air battery cathode. - Abstract: Three-dimensional nanoporous nitrogen-doped graphene (3D-PNG) has been synthesized through a facial one-step synthesis method without additional silica template. The as-prepared 3D-PNGwas used as an electrocatalyst for the oxygen reduction reaction (ORR), which shows excellent electrochemistry performance, demonstrated by half-cell electrochemical evaluation in 0.1 M KOH including prominent ORR activity, four electron-selectivity and remarkable methanol poisoning stability compared to commercial 20%Pt/C catalyst. The physical and surface properties of 3D-PNG catalyst were characterized by scanning electron microscopy (SEM), high-resolution transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and BET surface area analysis. The experiments show that 3D-PNG catalyst possesses super-large specific surface area reaching 920 m 2 g −1 , which is superior to our most recently reported 3D-PNG synthesized by silica template (670 m 2 g −1 ) and other doped graphene catalysts in literature. When used for constructing a zinc–air battery cathode, such an 3D-PNG catalyst can give a discharge peak power density of 275 mW cm −2 . All the results announce a unique procedure to product high-efficiency graphene-based non-noble metal catalyst materials for electrochemical energy devices including both fuel cells and metal–air batteries.
Brooks–Corey Modeling by One-Dimensional Vertical Infiltration Method
Directory of Open Access Journals (Sweden)
Xuguang Xing
2018-05-01
Full Text Available The laboratory methods used for the soil water retention curve (SWRC construction and parameter estimation is time-consuming. A vertical infiltration method was proposed to estimate parameters α and n and to further construct the SWRC. In the present study, the relationships describing the cumulative infiltration and infiltration rate with the depth of the wetting front were established, and simplified expressions for estimating α and n parameters were proposed. The one-dimensional vertical infiltration experiments of four soils were conducted to verify if the proposed method would accurately estimate α and n. The fitted values of α and n, obtained from the RETC software, were consistent with the calculated values obtained from the infiltration method. The comparison between the measured SWRCs obtained from the centrifuge method and the calculated SWRCs that were based on the infiltration method displayed small values of root mean square error (RMSE, mean absolute percentage error (MAPE, and mean absolute error. SWMS_2D-based simulations of cumulative infiltration, based on the calculated α and n, remained consistent with the measured values due to small RMSE and MAPE values. The experiments verified the proposed one-dimensional vertical infiltration method, which has applications in field hydraulic parameter estimation.
Advanced numerical methods for three dimensional two-phase flow calculations in PWR
International Nuclear Information System (INIS)
Toumi, I.; Gallo, D.; Royer, E.
1997-01-01
This paper is devoted to new numerical methods developed for three dimensional two-phase flow calculations. These methods are finite volume numerical methods. They are based on an extension of Roe's approximate Riemann solver to define convective fluxes versus mean cell quantities. To go forward in time, a linearized conservative implicit integrating step is used, together with a Newton iterative method. We also present here some improvements performed to obtain a fully implicit solution method that provides fast running steady state calculations. This kind of numerical method, which is widely used for fluid dynamic calculations, is proved to be very efficient for the numerical solution to two-phase flow problems. This numerical method has been implemented for the three dimensional thermal-hydraulic code FLICA-4 which is mainly dedicated to core thermal-hydraulic transient and steady-state analysis. Hereafter, we will also find some results obtained for the EPR reactor running in a steady-state at 60% of nominal power with 3 pumps out of 4, and a thermal-hydraulic core analysis for a 1300 MW PWR at low flow steam-line-break conditions. (author)
High-speed fan-beam reconstruction using direct two-dimensional Fourier transform method
International Nuclear Information System (INIS)
Niki, Noboru; Mizutani, Toshio; Takahashi, Yoshizo; Inouye, Tamon.
1984-01-01
Since the first development of X-ray computer tomography (CT), various efforts have been made to obtain high quality of high-speed image. However, the development of high resolution CT and the ultra-high speed CT to be applied to hearts is still desired. The X-ray beam scanning method was already changed from the parallel beam system to the fan-beam system in order to greatly shorten the scanning time. Also, the filtered back projection (DFBP) method has been employed to directly processing fan-beam projection data as reconstruction method. Although the two-dimensional Fourier transform (TFT) method significantly faster than FBP method was proposed, it has not been sufficiently examined for fan-beam projection data. Thus, the ITFT method was investigated, which first executes rebinning algorithm to convert the fan-beam projection data to the parallel beam projection data, thereafter, uses two-dimensional Fourier transform. By this method, although high speed is expected, the reconstructed images might be degraded due to the adoption of rebinning algorithm. Therefore, the effect of the interpolation error of rebinning algorithm on the reconstructed images has been analyzed theoretically, and finally, the result of the employment of spline interpolation which allows the acquisition of high quality images with less errors has been shown by the numerical and visual evaluation based on simulation and actual data. Computation time was reduced to 1/15 for the image matrix of 512 and to 1/30 for doubled matrix. (Wakatsuki, Y.)
International Nuclear Information System (INIS)
Montaudon, M.; Laffon, E.; Berger, P.; Corneloup, O.; Latrabe, V.; Laurent, F.
2006-01-01
This study compared a three-dimensional volumetric threshold-based method to a two-dimensional Simpson's rule based short-axis multiplanar method for measuring right (RV) and left ventricular (LV) volumes, stroke volumes, and ejection fraction using electrocardiography-gated multidetector computed tomography (MDCT) data sets. End-diastolic volume (EDV) and end-systolic volume (ESV) of RV and LV were measured independently and blindly by two observers from contrast-enhanced MDCT images using commercial software in 18 patients. For RV and LV the three-dimensionally calculated EDV and ESV values were smaller than those provided by two-dimensional short axis (10%, 5%, 15% and 26% differences respectively). Agreement between the two methods was found for LV (EDV/ESV: r=0.974/0.910, ICC=0.905/0.890) but not for RV (r=0.882/0.930, ICC=0.663/0.544). Measurement errors were significant only for EDV of LV using the two-dimensional method. Similar reproducibility was found for LV measurements, but the three-dimensional method provided greater reproducibility for RV measurements than the two-dimensional. The threshold value supported three-dimensional method provides reproducible cardiac ventricular volume measurements, comparable to those obtained using the short-axis Simpson based method. (orig.)
Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
Efendiev, Yalchin R.; Presho, Michael
2015-01-01
In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.
A new approach to passivity preserving model reduction : the dominant spectral zero method
Ionutiu, R.; Rommes, J.; Antoulas, A.C.; Roos, J.; Costa, L.R.J.
2010-01-01
A new model reduction method for circuit simulation is presented, which preserves passivity by interpolating dominant spectral zeros. These are computed as poles of an associated Hamiltonian system, using an iterative solver: the subspace accelerated dominant pole algorithm (SADPA). Based on a
Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
Efendiev, Yalchin R.
2015-09-02
In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.
The Induced Dimension Reduction method applied to convection-diffusion-reaction problems
Astudillo, R.; Van Gijzen, M.B.
2016-01-01
Discretization of (linearized) convection-diffusion-reaction problems yields a large and sparse non symmetric linear system of equations, Ax = b. (1) In this work, we compare the computational behavior of the Induced Dimension Reduction method (IDR(s)) [10], with other short-recurrences Krylov
The induced dimension reduction method applied to convection-diffusion-reaction problems
Astudillo Rengifo, R.A.; van Gijzen, M.B.
2016-01-01
Discretization of (linearized) convection-diusion-reaction problems yields
a large and sparse non symmetric linear system of equations,
Ax = b: (1)
In this work, we compare the computational behavior of the Induced Dimension
Reduction method (IDR(s)) [10], with other
The homeowner view of thinning methods for fire hazard reduction: more positive than many think
Sarah McCaffrey
2008-01-01
With the focus of the National Fire Plan on decreasing fire risk in the wildland-urban interface, fire managers are increasingly tasked with reducing the fuel load in areas where mixed public and private ownership and a growing number of homes can make most fuel reduction methods problematic at best. In many of these intermix areas, use of prescribed burning will be...
Asiri, Sharefa M.; Laleg-Kirati, Taous-Meriem
2016-01-01
In this paper, modulating functions-based method is proposed for estimating space–time-dependent unknowns in one-dimensional partial differential equations. The proposed method simplifies the problem into a system of algebraic equations linear
DEFF Research Database (Denmark)
Jepsen, Svend Erik; Krause, Michael; Grüttner, Henrik
1997-01-01
The increasing utilization of waste water sludge and source-separated organic household waste in agriculture has brought the quality aspects into focus, among others the hygienic aspects. In this study, the reducting effect on Fecal Streptococcus (FS) and Salmonella of different methods...... for stabilization and methods for further treatment of sludge and organic waste has been investigated. The most common methods for stabilization, i.e. aerobic and anaerobic stabilization, only reduce the indicator organisms by approximately 1 logarithmic decade. Methods for further treatment of sludge and organic......) significant reductions of Salmonella were found, while the die out at low temperatures (below 10°C) was limited. FS was not reduced systematically during storage, and therefore, FS is not usable as indicator organism for the hygienic properties of sludge during storage....
Zhang, Xuming; Li, Liu; Zhu, Fei; Hou, Wenguang; Chen, Xinjian
2014-06-01
Optical coherence tomography (OCT) images are usually degraded by significant speckle noise, which will strongly hamper their quantitative analysis. However, speckle noise reduction in OCT images is particularly challenging because of the difficulty in differentiating between noise and the information components of the speckle pattern. To address this problem, the spiking cortical model (SCM)-based nonlocal means method is presented. The proposed method explores self-similarities of OCT images based on rotation-invariant features of image patches extracted by SCM and then restores the speckled images by averaging the similar patches. This method can provide sufficient speckle reduction while preserving image details very well due to its effectiveness in finding reliable similar patches under high speckle noise contamination. When applied to the retinal OCT image, this method provides signal-to-noise ratio improvements of >16 dB with a small 5.4% loss of similarity.
Shen, Wei; Li, Dongsheng; Zhang, Shuaifang; Ou, Jinping
2017-07-01
This paper presents a hybrid method that combines the B-spline wavelet on the interval (BSWI) finite element method and spectral analysis based on fast Fourier transform (FFT) to study wave propagation in One-Dimensional (1D) structures. BSWI scaling functions are utilized to approximate the theoretical wave solution in the spatial domain and construct a high-accuracy dynamic stiffness matrix. Dynamic reduction on element level is applied to eliminate the interior degrees of freedom of BSWI elements and substantially reduce the size of the system matrix. The dynamic equations of the system are then transformed and solved in the frequency domain through FFT-based spectral analysis which is especially suitable for parallel computation. A comparative analysis of four different finite element methods is conducted to demonstrate the validity and efficiency of the proposed method when utilized in high-frequency wave problems. Other numerical examples are utilized to simulate the influence of crack and delamination on wave propagation in 1D rods and beams. Finally, the errors caused by FFT and their corresponding solutions are presented.
Nakajima, Kazuhiro; Yamamoto, Yuji; Arima, Yutaka
2018-04-01
To easily assemble a three-dimensional binocular range sensor, we devised an alignment method for two image sensors using a silicon interposer with trenches. The trenches were formed using deep reactive ion etching (RIE) equipment. We produced a three-dimensional (3D) range sensor using the method and experimentally confirmed that sufficient alignment accuracy was realized. It was confirmed that the alignment accuracy of the two image sensors when using the proposed method is more than twice that of the alignment assembly method on a conventional board. In addition, as a result of evaluating the deterioration of the detection performance caused by the alignment accuracy, it was confirmed that the vertical deviation between the corresponding pixels in the two image sensors is substantially proportional to the decrease in detection performance. Therefore, we confirmed that the proposed method can realize more than twice the detection performance of the conventional method. Through these evaluations, the effectiveness of the 3D binocular range sensor aligned by the silicon interposer with the trenches was confirmed.
Iterative methods used in overlap astrometric reduction techniques do not always converge
Rapaport, M.; Ducourant, C.; Colin, J.; Le Campion, J. F.
1993-04-01
In this paper we prove that the classical Gauss-Seidel type iterative methods used for the solution of the reduced normal equations occurring in overlapping reduction methods of astrometry do not always converge. We exhibit examples of divergence. We then analyze an alternative algorithm proposed by Wang (1985). We prove the consistency of this algorithm and verify that it can be convergent while the Gauss-Seidel method is divergent. We conjecture the convergence of Wang method for the solution of astrometric problems using overlap techniques.
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Directory of Open Access Journals (Sweden)
Jiang Feng
2010-12-01
Full Text Available Abstract Background Most genomic data have ultra-high dimensions with more than 10,000 genes (probes. Regularization methods with L1 and Lp penalty have been extensively studied in survival analysis with high-dimensional genomic data. However, when the sample size n ≪ m (the number of genes, directly identifying a small subset of genes from ultra-high (m > 10, 000 dimensional data is time-consuming and not computationally efficient. In current microarray analysis, what people really do is select a couple of thousands (or hundreds of genes using univariate analysis or statistical tests, and then apply the LASSO-type penalty to further reduce the number of disease associated genes. This two-step procedure may introduce bias and inaccuracy and lead us to miss biologically important genes. Results The accelerated failure time (AFT model is a linear regression model and a useful alternative to the Cox model for survival analysis. In this paper, we propose a nonlinear kernel based AFT model and an efficient variable selection method with adaptive kernel ridge regression. Our proposed variable selection method is based on the kernel matrix and dual problem with a much smaller n × n matrix. It is very efficient when the number of unknown variables (genes is much larger than the number of samples. Moreover, the primal variables are explicitly updated and the sparsity in the solution is exploited. Conclusions Our proposed methods can simultaneously identify survival associated prognostic factors and predict survival outcomes with ultra-high dimensional genomic data. We have demonstrated the performance of our methods with both simulation and real data. The proposed method performs superbly with limited computational studies.
International Nuclear Information System (INIS)
Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.
2015-01-01
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method
Reduction method for residual stress of welded joint using harmonic vibrational load
International Nuclear Information System (INIS)
Aoki, Shigeru; Nishimura, Tadashi; Hiroi, Tetsumaro; Hirai, Seiji
2007-01-01
Welding is widely used for construction of many structures. Since welding is a process using locally given heat, residual stress is generated near the bead. Tensile residual stress degrades fatigue strength. Some reduction methods of residual stress have been presented and, for example, heat treatment and shot peening are practically used. However, those methods need special tools and are time consuming. In this paper, a new method for reduction of residual stress using harmonic vibrational load during welding is proposed. The proposed method is examined experimentally for some conditions. Two thin plates are supported on the supporting device and butt-welded using an automatic CO 2 gas shielded arc welding machine. Residual stress in the direction of the bead is measured by using a paralleled beam X-ray diffractometer with scintillation counter after removing quenched scale chemically. First, the welding of rolled steel for general structure for some excitation frequencies is examined. Specimens are welded along the groove on both sides. For all frequencies, tensile residual stress near the bead is significantly reduced. Second, welding of the specimen made of high tensile strength steel is examined. In this case, tensile residual stress near the bead is also reduced. Finally, the proposed method is examined by an analytical method. An analytical model which consists of mass and preloaded springs with elasto-plastic characteristic is used. Reduction of residual stress is demonstrated using this model
This study develops contingent valuation methods for measuring the benefits of mortality and morbidity drinking water risk reductions. The major effort was devoted to developing and testing a survey instrument to value low-level risk reductions.
A general mixed boundary model reduction method for component mode synthesis
International Nuclear Information System (INIS)
Voormeeren, S N; Van der Valk, P L C; Rixen, D J
2010-01-01
A classic issue in component mode synthesis (CMS) methods is the choice for fixed or free boundary conditions at the interface degrees of freedom (DoF) and the associated vibration modes in the components reduction base. In this paper, a novel mixed boundary CMS method called the 'Mixed Craig-Bampton' method is proposed. The method is derived by dividing the substructure DoF into a set of internal DoF, free interface DoF and fixed interface DoF. To this end a simple but effective scheme is introduced that, for every pair of interface DoF, selects a free or fixed boundary condition for each DoF individually. Based on this selection a reduction basis is computed consisting of vibration modes, static constraint modes and static residual flexibility modes. In order to assemble the reduced substructures a novel mixed assembly procedure is developed. It is shown that this approach leads to relatively sparse reduced matrices, whereas other mixed boundary methods often lead to full matrices. As such, the Mixed Craig-Bampton method forms a natural generalization of the classic Craig-Bampton and more recent Dual Craig-Bampton methods. Finally, the method is applied to a finite element test model. Analysis reveals that the proposed method has comparable or better accuracy and superior versatility with respect to the existing methods.
International Nuclear Information System (INIS)
Chen, G.S.; Yang, D.Y.
1998-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used: TFQMR (transpose free quasi-minimal residual algorithm) CGS (conjugate gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These subroutines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. The reasons to choose the generalized conjugate gradient methods are that the methods have better residual (equivalent to error) control procedures in the computation and have better convergent rate. The pointwise incomplete LU factorization ILU, modified pointwise incomplete LU factorization MILU, block incomplete factorization BILU and modified blockwise incomplete LU factorization MBILU are the preconditioning techniques used in the several testing problems. In Bi-CGSTAB, CGS, TFQMR and QMRCGSTAB method, we find that either CGS or Bi-CGSTAB method combined with preconditioner MBILU is the most efficient algorithm in these methods in the several testing problems. The numerical solution of flux by preconditioned CGS and Bi-CGSTAB methods has the same result as those from Cray computer, obtained by either the point successive relaxation method or the line successive relaxation method combined with Gaussian elimination
Covariance Method of the Tunneling Radiation from High Dimensional Rotating Black Holes
Li, Hui-Ling; Han, Yi-Wen; Chen, Shuai-Ru; Ding, Cong
2018-04-01
In this paper, Angheben-Nadalini-Vanzo-Zerbini (ANVZ) covariance method is used to study the tunneling radiation from the Kerr-Gödel black hole and Myers-Perry black hole with two independent angular momentum. By solving the Hamilton-Jacobi equation and separating the variables, the radial motion equation of a tunneling particle is obtained. Using near horizon approximation and the distance of the proper pure space, we calculate the tunneling rate and the temperature of Hawking radiation. Thus, the method of ANVZ covariance is extended to the research of high dimensional black hole tunneling radiation.
Numerical method for solving the three-dimensional time-dependent neutron diffusion equation
International Nuclear Information System (INIS)
Khaled, S.M.; Szatmary, Z.
2005-01-01
A numerical time-implicit method has been developed for solving the coupled three-dimensional time-dependent multi-group neutron diffusion and delayed neutron precursor equations. The numerical stability of the implicit computation scheme and the convergence of the iterative associated processes have been evaluated. The computational scheme requires the solution of large linear systems at each time step. For this purpose, the point over-relaxation Gauss-Seidel method was chosen. A new scheme was introduced instead of the usual source iteration scheme. (author)
Modification of equivalent charge method for the Roben three-dimensional problem in electrostatics
International Nuclear Information System (INIS)
Barsukov, A.B.; Surenskij, A.V.
1989-01-01
The approach of the Roben problem solution for the calculation of the potential of intermediate electrode of accelerating structure with HFQ focusing is considered. The solution is constructed on the basis of variational formulation of the equivalent charge method, where electrostatic problem is reduced to equations of root-mean-square residuals on the system conductors. The technique presented permits to solve efficiently the three-dimensional problems of electrostatics for rather complicated from geometrical viewpoint systems of electrodes. Processing time is comparable with methods of integral equations. 5 refs.; 2 figs
Simulation of three-dimensional, time-dependent, incompressible flows by a finite element method
International Nuclear Information System (INIS)
Chan, S.T.; Gresho, P.M.; Lee, R.L.; Upson, C.D.
1981-01-01
A finite element model has been developed for simulating the dynamics of problems encountered in atmospheric pollution and safety assessment studies. The model is based on solving the set of three-dimensional, time-dependent, conservation equations governing incompressible flows. Spatial discretization is performed via a modified Galerkin finite element method, and time integration is carried out via the forward Euler method (pressure is computed implicitly, however). Several cost-effective techniques (including subcycling, mass lumping, and reduced Gauss-Legendre quadrature) which have been implemented are discussed. Numerical results are presented to demonstrate the applicability of the model
A method for three-dimensional structural analysis of reinforced concrete containment
International Nuclear Information System (INIS)
Kulak, R.F.; Fiala, C.
1989-01-01
A finite element method designed to assist reactor safety analysts in the three-dimensional numerical simulation of reinforced concrete containments to normal and off-normal mechanical loadings is presented. The development of a lined reinforced concrete plate element is described in detail, and the implementation of an empirical transverse shear failure criteria is discussed. The method is applied to the analysis of a 1/6th scale reinforced concrete containment model subjected to static internal pressurization. 11 refs., 14 figs., 1 tab
Directory of Open Access Journals (Sweden)
Fang Wang
2017-12-01
Full Text Available (FePt85Cu15 nanoparticles were successfully prepared by alternate reduction of metal salts in aqueous medium. Detailed investigations on the correlation between the magnetic and structural properties of these nanoparticles are presented as a function of annealing temperature. Both the X-ray diffraction patterns and the magnetic hysteresis loop measurements show the existence of L10-FePt phase at a relative low annealing temperature. It is proved that the Cu additive and alternate reduction are very effective methods in reducing the ordering temperature of FePt nanoparticles.
Directory of Open Access Journals (Sweden)
Amir Salimi
2018-04-01
Full Text Available The curse of dimensionality resulted from insufficient training samples and redundancy is considered as an important problem in the supervised classification of hyperspectral data. This problem can be handled by Feature Subset Selection (FSS methods and Support Vector Machine (SVM. The FSS methods can manage the redundancy by removing redundant spectral bands. Moreover, kernel based methods, especially SVM have a high ability to classify limited-sample data sets. This paper mainly aims to assess the capability of a FSS method and the SVM in curse of dimensional circumstances and to compare results with the Artificial Neural Network (ANN, when they are used to classify alteration zones of the Hyperion hyperspectral image acquired from the greatest Iranian porphyry copper complex. The results demonstrated that by decreasing training samples, the accuracy of SVM was just decreased 1.8% while the accuracy of ANN was highly reduced i.e. 14.01%. In addition, a hybrid FSS was applied to reduce the dimension of Hyperion. Accordingly, among the 165 useable spectral bands of Hyperion, 18 bands were only selected as the most important and informative bands. Although this dimensionality reduction could not intensively improve the performance of SVM, ANN revealed a significant improvement in the computational time and a slightly enhancement in the average accuracy. Therefore, SVM as a low-sensitive method respect to the size of training data set and feature space can be applied to classify the curse of dimensional problems. Also, the FSS methods can improve the performance of non-kernel based classifiers by eliminating redundant features. Keywords: Curse of dimensionality, Feature Subset Selection, Hydrothermal alteration, Hyperspectral, SVM
A method for three-dimensional quantitative observation of the microstructure of biological samples
Wang, Pengfei; Chen, Dieyan; Ma, Wanyun; Wu, Hongxin; Ji, Liang; Sun, Jialin; Lv, Danyu; Zhang, Lu; Li, Ying; Tian, Ning; Zheng, Jinggao; Zhao, Fengying
2009-07-01
Contemporary biology has developed into the era of cell biology and molecular biology, and people try to study the mechanism of all kinds of biological phenomena at the microcosmic level now. Accurate description of the microstructure of biological samples is exigent need from many biomedical experiments. This paper introduces a method for 3-dimensional quantitative observation on the microstructure of vital biological samples based on two photon laser scanning microscopy (TPLSM). TPLSM is a novel kind of fluorescence microscopy, which has excellence in its low optical damage, high resolution, deep penetration depth and suitability for 3-dimensional (3D) imaging. Fluorescent stained samples were observed by TPLSM, and afterward the original shapes of them were obtained through 3D image reconstruction. The spatial distribution of all objects in samples as well as their volumes could be derived by image segmentation and mathematic calculation. Thus the 3-dimensionally and quantitatively depicted microstructure of the samples was finally derived. We applied this method to quantitative analysis of the spatial distribution of chromosomes in meiotic mouse oocytes at metaphase, and wonderful results came out last.
Direct-coupled-ray method for design-oriented three-dimensional transport analysis
International Nuclear Information System (INIS)
Bucholz, J.A.; Poncelet, C.G.
1977-01-01
A fast three-dimensional design-oriented transport method has been developed for the solution of both neutron and gamma transport problems. It combines a nodal approach with analytic integral transport to achieve relative speed and accuracy. An analytic solution is obtained for the angular flux in each of the 14 directions defined by the six faces and eight corners of a cubic mesh block. The scheme used to accommodate high-order anisotropic scattering is based on the formulation of ray-to-ray scattering probabilities in an integral sense. A variable mesh approximation has also been introduced to provide greater flexibility. The details of a direct-coupled-ray (DCR) → P 1 conversion technique have been developed but not yet implemented. The DCR method, as implemented in the TRANS3 code, has been used in a number of liquid-metal fast breeder reactor shielding applications. These included a one-dimensional deep penetration configuration and one-, two-, and three dimensional representations of the lower axial shield of the Clinch River Breeder Reactor. Comparisons with ANISN and DOT-III solutions indicated good to excellent agreement in most situations
International Nuclear Information System (INIS)
Polivanskij, V.P.
1989-01-01
The method to solve two-dimensional equations of neutron transport using 4P 0 -approximation is presented. Previously such approach was efficiently used for the solution of one-dimensional problems. New an attempt is made to apply the approach to solution of two-dimensional problems. Algorithm of the solution is given, as well as results of test neutron-physical calculations. A considerable as compared with diffusion approximation is shown. 11 refs
Energy Technology Data Exchange (ETDEWEB)
Golbahar Haghighi, M.R.; Eghtesad, M. [Department of Mechanical Engineering, School of Engineering, Shiraz University, Shiraz 71348-51154 (Iran, Islamic Republic of); Malekzadeh, P. [Department of Mechanical Engineering, School of Engineering, Persian Gulf University, Boushehr 75169-13798 (Iran, Islamic Republic of)], E-mail: malekzadeh@pgu.ac.ir
2008-05-15
In this paper, a mixed finite element (FE) and differential quadrature (DQ) method as a simple, accurate and computationally efficient numerical tool for two dimensional transient heat transfer analysis of functionally graded materials (FGMs) is developed. The method benefits from the high accuracy, fast convergence behavior and low computational efforts of the DQ in conjunction with the advantages of the FE method in general geometry, loading and systematic boundary treatment. Also, the boundary conditions at the top and bottom surfaces of the domain can be implemented more precisely and in strong form. The temporal derivatives are discretized using an incremental DQ method (IDQM), whose numerical stability is not sensitive to time step size. The effects of non-uniform convective-radiative conditions on the boundaries are investigated. The accuracy of the proposed method is demonstrated by comparing its results with those available in the literature. It is shown that using few grid points, highly accurate results can be obtained.
International Nuclear Information System (INIS)
Kang, Jeong Hyun; Kim, Young Chul; Kim, Hyunki; Kim, Young Wan; Hur, Hyuk; Kim, Jin Soo; Min, Byung Soh; Kim, Hogeun; Lim, Joon Seok; Seong, Jinsil; Keum, Ki Chang; Kim, Nam Kyu
2010-01-01
Purpose: The aim of this study was to determine the correlation between tumor volume changes assessed by three-dimensional (3D) magnetic resonance (MR) volumetry and the histopathologic tumor response in rectal cancer patients undergoing preoperative chemoradiation therapy (CRT). Methods and Materials: A total of 84 patients who underwent preoperative CRT followed by radical surgery were prospectively enrolled in the study. The post-treatment tumor volume and tumor volume reduction ratio (% decrease ratio), as shown by 3D MR volumetry, were compared with the histopathologic response, as shown by T and N downstaging and the tumor regression grade (TRG). Results: There were no significant differences in the post-treatment tumor volume and the volume reduction ratio shown by 3D MR volumetry with respect to T and N downstaging and the tumor regression grade. In a multivariate analysis, the tumor volume reduction ratio was not significantly associated with T and N downstaging. The volume reduction ratio (>75%, p = 0.01) and the pretreatment carcinoembryonic antigen level (≤3 ng/ml, p = 0.01), but not the post-treatment volume shown by 3D MR (≤ 5ml), were, however, significantly associated with an increased pathologic complete response rate. Conclusion: More than 75% of the tumor volume reduction ratios were significantly associated with a high pathologic complete response rate. Therefore, limited treatment options such as local excision or simple observation might be considered after preoperative CRT in this patient population.
PARALLEL ALGORITHM FOR THREE-DIMENSIONAL STOKES FLOW SIMULATION USING BOUNDARY ELEMENT METHOD
Directory of Open Access Journals (Sweden)
D. G. Pribytok
2016-01-01
Full Text Available Parallel computing technique for modeling three-dimensional viscous flow (Stokes flow using direct boundary element method is presented. The problem is solved in three phases: sampling and construction of system of linear algebraic equations (SLAE, its decision and finding the velocity of liquid at predetermined points. For construction of the system and finding the velocity, the parallel algorithms using graphics CUDA cards programming technology have been developed and implemented. To solve the system of linear algebraic equations the implemented software libraries are used. A comparison of time consumption for three main algorithms on the example of calculation of viscous fluid motion in three-dimensional cavity is performed.
Three-Dimensional Computed Tomography as a Method for Finding Die Attach Voids in Diodes
Brahm, E. N.; Rolin, T. D.
2010-01-01
NASA analyzes electrical, electronic, and electromechanical (EEE) parts used in space vehicles to understand failure modes of these components. The diode is an EEE part critical to NASA missions that can fail due to excessive voiding in the die attach. Metallography, one established method for studying the die attach, is a time-intensive, destructive, and equivocal process whereby mechanical grinding of the diodes is performed to reveal voiding in the die attach. Problems such as die attach pull-out tend to complicate results and can lead to erroneous conclusions. The objective of this study is to determine if three-dimensional computed tomography (3DCT), a nondestructive technique, is a viable alternative to metallography for detecting die attach voiding. The die attach voiding in two- dimensional planes created from 3DCT scans was compared to several physical cross sections of the same diode to determine if the 3DCT scan accurately recreates die attach volumetric variability
Three-dimensional static and dynamic reactor calculations by the nodal expansion method
International Nuclear Information System (INIS)
Christensen, B.
1985-05-01
This report reviews various method for the calculation of the neutron-flux- and power distribution in an nuclear reactor. The nodal expansion method (NEM) is especially described in much detail. The nodal expansion method solves the diffusion equation. In this method the reactor core is divided into nodes, typically 10 to 20 cm in each direction, and the average flux in each node is calculated. To obtain the coupling between the nodes the local flux inside each node is expressed by use of a polynomial expansion. The expansion is one-dimensional, so inside each node such three expansions occur. To calculate the expansion coefficients it is necessary that the polynomial expansion is a solution to the one-dimensional diffusion equation. When the one-dimensional diffusion equation is established a term with the transversal leakage occur, and this term is expanded after the same polynomials. The resulting equation system with the expansion coefficients as the unknowns is solved with weigthed residual technique. The nodal expansion method is built into a computer program (also called NEM), which is divided into two parts, one part for steady-state calculations and one part for dynamic calculations. It is possible to take advantage of symmetry properties of the reactor core. The program is very flexible with regard to the number of energy groups, the node size, the flux expansion order and the transverse leakage expansion order. The boundary of the core is described by albedos. The program and input to it are described. The program is tested on a number of examples extending from small theoretical one up to realistic reactor cores. Many calculations are done on the wellknown IAEA benchmark case. The calculations have tested the accuracy and the computing time for various node sizes and polynomial expansions. In the dynamic examples various strategies for variation of the time step-length have been tested. (author)
A Generic multi-dimensional feature extraction method using multiobjective genetic programming.
Zhang, Yang; Rockett, Peter I
2009-01-01
In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.
International Nuclear Information System (INIS)
Ferri, A.A.
1986-01-01
Nodal methods applied in order to calculate the power distribution in a nuclear reactor core are presented. These methods have received special attention, because they yield accurate results in short computing times. Present nodal schemes contain several unknowns per node and per group. In the methods presented here, non linear feedback of the coupling coefficients has been applied to reduce this number to only one unknown per node and per group. The resulting algorithm is a 7- points formula, and the iterative process has proved stable in the response matrix scheme. The intranodal flux shape is determined by partial integration of the diffusion equations over two of the coordinates, leading to a set of three coupled one-dimensional equations. These can be solved by using a polynomial approximation or by integration (analytic solution). The tranverse net leakage is responsible for the coupling between the spatial directions, and two alternative methods are presented to evaluate its shape: direct parabolic approximation and local model expansion. Numerical results, which include the IAEA two-dimensional benchmark problem illustrate the efficiency of the developed methods. (M.E.L.) [es
A systematic way for the cost reduction of density fitting methods
International Nuclear Information System (INIS)
Kállay, Mihály
2014-01-01
We present a simple approach for the reduction of the size of auxiliary basis sets used in methods exploiting the density fitting (resolution of identity) approximation for electron repulsion integrals. Starting out of the singular value decomposition of three-center two-electron integrals, new auxiliary functions are constructed as linear combinations of the original fitting functions. The new functions, which we term natural auxiliary functions (NAFs), are analogous to the natural orbitals widely used for the cost reduction of correlation methods. The use of the NAF basis enables the systematic truncation of the fitting basis, and thereby potentially the reduction of the computational expenses of the methods, though the scaling with the system size is not altered. The performance of the new approach has been tested for several quantum chemical methods. It is demonstrated that the most pronounced gain in computational efficiency can be expected for iterative models which scale quadratically with the size of the fitting basis set, such as the direct random phase approximation. The approach also has the promise of accelerating local correlation methods, for which the processing of three-center Coulomb integrals is a bottleneck
An evaluation of three commercially available metal artifact reduction methods for CT imaging
International Nuclear Information System (INIS)
Huang, Jessie Y; Kerns, James R; Balter, Peter A; Followill, David S; Mirkovic, Dragan; Howell, Rebecca M; Kry, Stephen F; Nute, Jessica L; Liu, Xinming; Stingo, Francesco C
2015-01-01
Three commercial metal artifact reduction methods were evaluated for use in computed tomography (CT) imaging in the presence of clinically realistic metal implants: Philips O-MAR, GE’s monochromatic gemstone spectral imaging (GSI) using dual-energy CT, and GSI monochromatic imaging with metal artifact reduction software applied (MARs). Each method was evaluated according to CT number accuracy, metal size accuracy, and streak artifact severity reduction by using several phantoms, including three anthropomorphic phantoms containing metal implants (hip prosthesis, dental fillings and spinal fixation rods). All three methods showed varying degrees of success for the hip prosthesis and spinal fixation rod cases, while none were particularly beneficial for dental artifacts. Limitations of the methods were also observed. MARs underestimated the size of metal implants and introduced new artifacts in imaging planes beyond the metal implant when applied to dental artifacts, and both the O-MAR and MARs algorithms induced artifacts for spinal fixation rods in a thoracic phantom. Our findings suggest that all three artifact mitigation methods may benefit patients with metal implants, though they should be used with caution in certain scenarios. (paper)
Directory of Open Access Journals (Sweden)
Lubna Moin
2009-04-01
Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and