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)

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.

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

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

Science.gov (United States)

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.

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.)

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

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

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.).

A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

OpenAIRE

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 ...

Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

Science.gov (United States)

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 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.

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.)

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 LLE’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.

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.)

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

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

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.

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.

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.)

Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

Science.gov (United States)

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.

Reduced order methods for modeling and computational reduction

CERN Document Server

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...

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.

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.)

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

Science.gov (United States)

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.

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

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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.

Lie symmetry analysis and reduction for exact solution of (2+1)-dimensional Bogoyavlensky-Konopelchenko equation by geometric approach

Science.gov (United States)

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.

Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

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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.

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

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)

Three-dimensional assemblies of graphene prepared by a novel chemical reduction-induced self-assembly method

KAUST Repository

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.

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

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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.

Science.gov (United States)

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

Three-dimensional assessment of unilateral subcondylar fracture using computed tomography after open reduction

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

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

Supervised linear dimensionality reduction with robust margins for object recognition

Science.gov (United States)

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.

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.)

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

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

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.

TPSLVM: a dimensionality reduction algorithm based on thin plate splines.

Science.gov (United States)

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.

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

The (2+1)-dimensional axial universes—solutions to the Einstein equations, dimensional reduction points and Klein–Fock–Gordon waves

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)

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.

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

Science.gov (United States)

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.

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

Science.gov (United States)

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.

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)

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

Science.gov (United States)

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.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

Science.gov (United States)

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.

Simulation of multivariate stationary stochastic processes using dimension-reduction representation methods

Science.gov (United States)

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.

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

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

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Science.gov (United States)

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

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

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

Center-vortex dominance after dimensional reduction of SU(2) lattice gauge theory

OpenAIRE

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%.

Dimensionality Reduction for Hyperspectral Data Based on Class-Aware Tensor Neighborhood Graph and Patch Alignment.

Science.gov (United States)

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 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.

Chaotic oscillator containing memcapacitor and meminductor and its dimensionality reduction analysis.

Science.gov (United States)

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.

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

Science.gov (United States)

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.

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.

Comparison of dimensionality reduction techniques for the fault diagnosis of mono block centrifugal pump using vibration signals

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.

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.

Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

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.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

Science.gov (United States)

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.

Multichannel transfer function with dimensionality reduction

KAUST Repository

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

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)

Modern Reduction Methods

CERN Document Server

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.

Iterative methods for dose reduction and image enhancement in tomography

Science.gov (United States)

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.

Three-dimensional display by computer graphics method of hepatocellular carcinoma using seen with the hepatic arteriogram

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)

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)

New exact solutions of (2 + 1)-dimensional Gardner equation via the new sine-Gordon equation expansion method

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

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

Development of a two-dimensional high-performance liquid chromatography system coupled with on-line reduction as a new efficient analytical method of 3-nitrobenzanthrone, a potential human carcinogen.

Science.gov (United States)

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.

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

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

Science.gov (United States)

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.

QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION.

Science.gov (United States)

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.

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.)

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.

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

Science.gov (United States)

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.

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices and its application in brain-computer interfaces

Science.gov (United States)

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.

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)

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.

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.)

Relation between the pole and the minimally subtracted mass in dimensional regularization and dimensional reduction to three-loop order

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.)

Quantification of Artifact Reduction With Real-Time Cine Four-Dimensional Computed Tomography Acquisition Methods

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.

Analysis and application of a novel three-dimensional energy-saving and emission-reduction dynamic evolution system

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.

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

Science.gov (United States)

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

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

Effect of Intraoperative Three-Dimensional Imaging During the Reduction and Fixation of Displaced Calcaneal Fractures on Articular Congruence and Implant Fixation

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...

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.

A principled dimension-reduction method for the population density approach to modeling networks of neurons with synaptic dynamics.

Science.gov (United States)

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.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.

Science.gov (United States)

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.

M-Isomap: Orthogonal Constrained Marginal Isomap for Nonlinear Dimensionality Reduction.

Science.gov (United States)

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.

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.

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

Features in chemical kinetics. I. Signatures of self-emerging dimensional reduction from a general format of the evolution law.

Science.gov (United States)

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

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 Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

OpenAIRE

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...

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

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.

Neural networks for the dimensionality reduction of GOME measurement vector in the estimation of ozone profiles

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

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)

Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control.

Science.gov (United States)

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

Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control.

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

Dual Dimensionality Reduction Reveals Independent Encoding of Motor Features in a Muscle Synergy for Insect Flight Control

Science.gov (United States)

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

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)

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals.

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.

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

Machine Learning Based Dimensionality Reduction Facilitates Ligand Diffusion Paths Assessment: A Case of Cytochrome P450cam.

Science.gov (United States)

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.

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)

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

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)

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

Science.gov (United States)

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.

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.)

Denoising and dimensionality reduction of genomic data

Science.gov (United States)

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

Water-Induced Dimensionality Reduction in Metal-Halide Perovskites

KAUST Repository

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.

Exploring the effects of dimensionality reduction in deep networks for force estimation in robotic-assisted surgery

Science.gov (United States)

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.

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.

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.)

Computational methods for three-dimensional microscopy reconstruction

CERN Document Server

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.

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)

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

A Corresponding Lie Algebra of a Reductive homogeneous Group and Its Applications

International Nuclear Information System (INIS)

Zhang Yu-Feng; Rui Wen-Juan; Wu Li-Xin

2015-01-01

With the help of a Lie algebra of a reductive homogeneous space G/K, where G is a Lie group and K is a resulting isotropy group, we introduce a Lax pair for which an expanding (2+1)-dimensional integrable hierarchy is obtained by applying the binormial-residue representation (BRR) method, whose Hamiltonian structure is derived from the trace identity for deducing (2+1)-dimensional integrable hierarchies, which was proposed by Tu, et al. We further consider some reductions of the expanding integrable hierarchy obtained in the paper. The first reduction is just right the (2+1)-dimensional AKNS hierarchy, the second-type reduction reveals an integrable coupling of the (2+1)-dimensional AKNS equation (also called the Davey-Stewartson hierarchy), a kind of (2+1)-dimensional Schrödinger equation, which was once reobtained by Tu, Feng and Zhang. It is interesting that a new (2+1)-dimensional integrable nonlinear coupled equation is generated from the reduction of the part of the (2+1)-dimensional integrable coupling, which is further reduced to the standard (2+1)-dimensional diffusion equation along with a parameter. In addition, the well-known (1+1)-dimensional AKNS hierarchy, the (1+1)-dimensional nonlinear Schrödinger equation are all special cases of the (2+1)-dimensional expanding integrable hierarchy. Finally, we discuss a few discrete difference equations of the diffusion equation whose stabilities are analyzed by making use of the von Neumann condition and the Fourier method. Some numerical solutions of a special stationary initial value problem of the (2+1)-dimensional diffusion equation are obtained and the resulting convergence and estimation formula are investigated. (paper)

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.

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”.

Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern–Simons theory

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)

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.)

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

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

Science.gov (United States)

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

A modal-based reduction method for sound absorbing porous materials in poro-acoustic finite element models.

Science.gov (United States)

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.

Three-dimensional porous hollow fibre copper electrodes for efficient and high-rate electrochemical carbon dioxide reduction

NARCIS (Netherlands)

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,

Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern-Simons theory

Science.gov (United States)

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.

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

System reduction for nanoscale IC design

CERN Document Server

2017-01-01

This book describes the computational challenges posed by the progression toward nanoscale electronic devices and increasingly short design cycles in the microelectronics industry, and proposes methods of model reduction which facilitate circuit and device simulation for specific tasks in the design cycle. The goal is to develop and compare methods for system reduction in the design of high dimensional nanoelectronic ICs, and to test these methods in the practice of semiconductor development. Six chapters describe the challenges for numerical simulation of nanoelectronic circuits and suggest model reduction methods for constituting equations. These include linear and nonlinear differential equations tailored to circuit equations and drift diffusion equations for semiconductor devices. The performance of these methods is illustrated with numerical experiments using real-world data. Readers will benefit from an up-to-date overview of the latest model reduction methods in computational nanoelectronics.

New treatment method for developmental dysplasia of the hips after walking age. Arthroscopic reduction with limboplasty based on the findings of preoperative imaging

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

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

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.)

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 ...

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

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

Model reduction of parametrized systems

CERN Document Server

Ohlberger, Mario; Patera, Anthony; Rozza, Gianluigi; Urban, Karsten

2017-01-01

The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems. The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor t, carried out over the last 12 years, to build a growing research community in this field. Though not a textbook, some of the chapters ca...

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)

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)

van Manen's method and reduction in a phenomenological hermeneutic study.

Science.gov (United States)

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.

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)

Explicit formulation of a nodal transport method for discrete ordinates calculations in two-dimensional fixed-source problems

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.)

Transformative piezoelectric enhancement of P(VDF-TrFE) synergistically driven by nanoscale dimensional reduction and thermal treatment.

Science.gov (United States)

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.

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

The dimension split element-free Galerkin method for three-dimensional potential problems

Science.gov (United States)

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.

ldr: An R Software Package for Likelihood-Based Su?cient Dimension Reduction

Directory of Open Access Journals (Sweden)

Kofi Placid Adragni

2014-11-01

Full Text Available In regression settings, a su?cient dimension reduction (SDR method seeks the core information in a p-vector predictor that completely captures its relationship with a response. The reduced predictor may reside in a lower dimension d < p, improving ability to visualize data and predict future observations, and mitigating dimensionality issues when carrying out further analysis. We introduce ldr, a new R software package that implements three recently proposed likelihood-based methods for SDR: covariance reduction, likelihood acquired directions, and principal fitted components. All three methods reduce the dimensionality of the data by pro jection into lower dimensional subspaces. The package also implements a variable screening method built upon principal ?tted components which makes use of ?exible basis functions to capture the dependencies between the predictors and the response. Examples are given to demonstrate likelihood-based SDR analyses using ldr, including estimation of the dimension of reduction subspaces and selection of basis functions. The ldr package provides a framework that we hope to grow into a comprehensive library of likelihood-based SDR methodologies.

Dimensional degression in AdSd

International Nuclear Information System (INIS)

Artsukevich, A. Yu.; Vasiliev, M. A.

2009-01-01

We analyze the pattern of fields in (d+1)-dimensional anti-de Sitter space in terms of those in d-dimensional anti-de Sitter space. The procedure, which is neither dimensional reduction nor dimensional compactification, is called dimensional degression. The analysis is performed group theoretically for all totally symmetric bosonic and fermionic representations of the anti-de Sitter algebra. The field-theoretical analysis is done for a massive scalar field in AdS d+d ' and massless spin-one-half, spin-one, and spin-two fields in AdS d+1 . The mass spectra of the resulting towers of fields in AdS d are found. For the scalar field case, the obtained results extend to the shadow sector those obtained by Metsaev [Nucl. Phys. B, Proc. Suppl. 102, 100 (2001)] by a different method.

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

Three-dimensional compound comparison methods and their application in drug discovery.

Science.gov (United States)

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 image signals: processing methods

Science.gov (United States)

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.

Unlocking the Electrocatalytic Activity of Antimony for CO2 Reduction by Two-Dimensional Engineering of the Bulk Material.

Science.gov (United States)

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.

Reduction of Large Dynamical Systems by Minimization of Evolution Rate

Science.gov (United States)

Girimaji, Sharath S.

1999-01-01

Reduction of a large system of equations to a lower-dimensional system of similar dynamics is investigated. For dynamical systems with disparate timescales, a criterion for determining redundant dimensions and a general reduction method based on the minimization of evolution rate are proposed.

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

Efficient implementation of three-dimensional reference interaction site model self-consistent-field method: application to solvatochromic shift calculations.

Science.gov (United States)

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.

AN EFFECTIVE MULTI-CLUSTERING ANONYMIZATION APPROACH USING DISCRETE COMPONENT TASK FOR NON-BINARY HIGH DIMENSIONAL DATA SPACES

Directory of Open Access Journals (Sweden)

L.V. Arun Shalin

2016-01-01

Full Text Available Clustering is a process of grouping elements together, designed in such a way that the elements assigned to similar data points in a cluster are more comparable to each other than the remaining data points in a cluster. During clustering certain difficulties related when dealing with high dimensional data are ubiquitous and abundant. Works concentrated using anonymization method for high dimensional data spaces failed to address the problem related to dimensionality reduction during the inclusion of non-binary databases. In this work we study methods for dimensionality reduction for non-binary database. By analyzing the behavior of dimensionality reduction for non-binary database, results in performance improvement with the help of tag based feature. An effective multi-clustering anonymization approach called Discrete Component Task Specific Multi-Clustering (DCTSM is presented for dimensionality reduction on non-binary database. To start with we present the analysis of attribute in the non-binary database and cluster projection identifies the sparseness degree of dimensions. Additionally with the quantum distribution on multi-cluster dimension, the solution for relevancy of attribute and redundancy on non-binary data spaces is provided resulting in performance improvement on the basis of tag based feature. Multi-clustering tag based feature reduction extracts individual features and are correspondingly replaced by the equivalent feature clusters (i.e. tag clusters. During training, the DCTSM approach uses multi-clusters instead of individual tag features and then during decoding individual features is replaced by corresponding multi-clusters. To measure the effectiveness of the method, experiments are conducted on existing anonymization method for high dimensional data spaces and compared with the DCTSM approach using Statlog German Credit Data Set. Improved tag feature extraction and minimum error rate compared to conventional anonymization

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.

Unitarity cuts and Reduction to master integrals in d dimensions for one-loop amplitudes

CERN Document Server

Anastasiou, C; Feng, B; Kunszt, Z; Mastrolia, Pierpaolo; Anastasiou, Charalampos; Britto, Ruth; Feng, Bo; Kunszt, Zoltan; Mastrolia, Pierpaolo

2007-01-01

We present an alternative reduction to master integrals for one-loop amplitudes using a unitarity cut method in arbitrary dimensions. We carry out the reduction in two steps. The first step is a pure four-dimensional cut-integration of tree amplitudes with a mass parameter, and the second step is applying dimensional shift identities to master integrals. This reduction is performed at the integrand level, so that coefficients can be read out algebraically.

Study of the X-Ray Diagnosis of Unstable Pelvic Fracture Displacements in Three-Dimensional Space and its Application in Closed Reduction.

Science.gov (United States)

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.

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

Direct Linear Transformation Method for Three-Dimensional Cinematography

Science.gov (United States)

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)

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.)

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...

Solution of the two-dimensional space-time reactor kinetics equation by a locally one-dimensional method

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

Water-Induced Dimensionality Reduction in Metal-Halide Perovskites

KAUST Repository

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

Improved non-dimensional dynamic influence function method based on tow-domain method for vibration analysis of membranes

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.

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.

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)

The stress analysis method for three-dimensional composite materials

Science.gov (United States)

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.

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

Using a Feature Subset Selection method and Support Vector Machine to address curse of dimensionality and redundancy in Hyperion hyperspectral data classification

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

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)

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.

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

Energy Technology Data Exchange (ETDEWEB)

Choi, Youngsoo [Sandia National Laboratories (SNL-CA), Livermore, CA (United States). Extreme-scale Data Science and Analytics Dept.; Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Carlberg, Kevin Thomas [Sandia National Laboratories (SNL-CA), Livermore, CA (United States). Extreme-scale Data Science and Analytics Dept.

2017-09-01

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ²-norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.

Facile Synthesis of Quasi-One-Dimensional Au/PtAu Heterojunction Nanotubes and Their Application as Catalysts in an Oxygen-Reduction Reaction.

Science.gov (United States)

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.

Dimensional analysis and self-similarity methods for engineers and scientists

CERN Document Server

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

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)

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.

Irregular grid methods for pricing high-dimensional American options

NARCIS (Netherlands)

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

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.

Global sensitivity analysis by polynomial dimensional decomposition

Energy Technology Data Exchange (ETDEWEB)

Rahman, Sharif, E-mail: rahman@engineering.uiowa.ed [College of Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

2011-07-15

This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol's method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent.

Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons

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.

Fast Reduction Method in Dominance-Based Information Systems

Science.gov (United States)

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.

Recursions of Symmetry Orbits and Reduction without Reduction

Directory of Open Access Journals (Sweden)

Andrei A. Malykh

2011-04-01

Full Text Available We consider a four-dimensional PDE possessing partner symmetries mainly on the example of complex Monge-Ampère equation (CMA. We use simultaneously two pairs of symmetries related by a recursion relation, which are mutually complex conjugate for CMA. For both pairs of partner symmetries, using Lie equations, we introduce explicitly group parameters as additional variables, replacing symmetry characteristics and their complex conjugates by derivatives of the unknown with respect to group parameters. We study the resulting system of six equations in the eight-dimensional space, that includes CMA, four equations of the recursion between partner symmetries and one integrability condition of this system. We use point symmetries of this extended system for performing its symmetry reduction with respect to group parameters that facilitates solving the extended system. This procedure does not imply a reduction in the number of physical variables and hence we end up with orbits of non-invariant solutions of CMA, generated by one partner symmetry, not used in the reduction. These solutions are determined by six linear equations with constant coefficients in the five-dimensional space which are obtained by a three-dimensional Legendre transformation of the reduced extended system. We present algebraic and exponential examples of such solutions that govern Legendre-transformed Ricci-flat Kähler metrics with no Killing vectors. A similar procedure is briefly outlined for Husain equation.

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

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

Theories to support method development in comprehensive two-dimensional liquid chromatography - A review

NARCIS (Netherlands)

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

Research on a Rotating Machinery Fault Prognosis Method Using Three-Dimensional Spatial Representations

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.

Two-dimensional mapping of three-dimensional SPECT data: a preliminary step to the quantitation of thallium myocardial perfusion single photon emission tomography

International Nuclear Information System (INIS)

Goris, M.L.; Boudier, S.; Briandet, P.A.

1987-01-01

A method is presented by which tomographic myocardial perfusion data are prepared for quantitative analysis. The method is characterized by an interrogation of the original data, which results in a size and shape normalization. The method is analogous to the circumferential profile methods used in planar scintigraphy but requires a polar-to-cartesian transformation from three to two dimensions. As was the case in the planar situation, centering and reorientation are explicit. The degree of data reduction is evaluated by reconstructing idealized three-dimensional data from the two-dimensional sampling vectors. The method differs from previously described approaches by the absence in the resulting vector of a coordinate reflecting cartesian coordinate in the original data (slice number)

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.

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

Active sound reduction system and method

NARCIS (Netherlands)

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

Facile preparation of three-dimensional Co1-xS/sulfur and nitrogen-codoped graphene/carbon foam for highly efficient oxygen reduction reaction

Science.gov (United States)

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.

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

Three-dimensional iron, nitrogen-doped carbon foams as efficient electrocatalysts for oxygen reduction reaction in alkaline solution

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

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.

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.

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

Effective Hamiltonian for 2-dimensional arbitrary spin Ising model

International Nuclear Information System (INIS)

Sznajd, J.; Polska Akademia Nauk, Wroclaw. Inst. Niskich Temperatur i Badan Strukturalnych)

1983-08-01

The method of the reduction of the generalized arbitrary-spin 2-dimensional Ising model to spin-half Ising model is presented. The method is demonstrated in detail by calculating the effective interaction constants to the third order in cumulant expansion for the triangular spin-1 Ising model (the Blume-Emery-Griffiths model). (author)

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.

Hidden symmetries in five-dimensional supergravity

International Nuclear Information System (INIS)

Poessel, M.

2003-05-01

This thesis is concerned with the study of hidden symmetries in supergravity, which play an important role in the present picture of supergravity and string theory. Concretely, the appearance of a hidden G 2(+2) /SO(4) symmetry is studied in the dimensional reduction of d=5, N=2 supergravity to three dimensions - a parallel model to the more famous E 8(+8) /SO(16) case in eleven-dimensional supergravity. Extending previous partial results for the bosonic part, I give a derivation that includes fermionic terms. This sheds new light on the appearance of the local hidden symmetry SO(4) in the reduction, and shows up an unusual feature which follows from an analysis of the R-symmetry associated with N=4 supergravity and of the supersymmetry variations, and which has no parallel in the eleven-dimensional case: The emergence of an additional SO(3) as part of the enhanced local symmetry, invisible in the dimensional reduction of the gravitino, and corresponding to the fact that, of the SO(4) used in the coset model, only the diagonal SO(3) is visible immediately upon dimensional reduction. The uncovering of the hidden symmetries proceeds via the construction of the proper coset gravity in three dimensions, and matching it with the Lagrangian obtained from the reduction. (orig.)

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

Speckle reduction methods in laser-based picture projectors

Science.gov (United States)

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.

The Topology Optimization of Three-dimensional Cooling Fins by the Internal Element Connectivity Parameterization Method

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

Symmetry Analysis and Exact Solutions of (2+1)-Dimensional Sawada-Kotera Equation

International Nuclear Information System (INIS)

Zhi Hongyan; Zhang Hongqing

2008-01-01

Based on the symbolic computation system Maple, the infinite-dimensional symmetry group of the (2+1)-dimensional Sawada-Kotera equation is found by the classical Lie group method and the characterization of the group properties is given. The symmetry groups are used to perform the symmetry reduction. Moreover, with Lou's direct method that is based on Lax pairs, we obtain the symmetry transformations of the Sawada-Kotera and Konopelchenko-Dubrovsky equations, respectively.

Topological aspects of classical and quantum (2+1)-dimensional gravity

International Nuclear Information System (INIS)

Soda, Jiro.

1990-03-01

In order to understand (3+1)-dimensional gravity, (2+1)-dimensional gravity is studied as a toy model. Our emphasis is on its topological aspects, because (2+1)-dimensional gravity without matter fields has no local dynamical degrees of freedom. Starting from a review of the canonical ADM formalism and York's formalism for the initial value problem, we will solve the evolution equations of (2+1)-dimensional gravity with a cosmological constant in the case of g=0 and g=1, where g is the genus of Riemann surface. The dynamics of it is understood as the geodesic motion in the moduli space. This remarkable fact is the same with the case of (2+1)-dimensional pure gravity and seen more apparently from the action level. Indeed we will show the phase space reduction of (2+1)-dimensional gravity in the case of g=1. For g ≥ 2, unfortunately we are not able to explicitly perform the phase space reduction of (2+1)-dimensional gravity due to the complexity of the Hamiltonian constraint equation. Based on this result, we will attempt to incorporate matter fields into (2+1)-dimensional pure gravity. The linearization and mini-superspace methods are used for this purpose. By using the linearization method, we conclude that the transverse-traceless part of the energy-momentum tensor affects the geodesic motion. In the case of the Einstein-Maxwell theory, we observe that the Wilson lines interact with the geometry to bend the geodesic motion. We analyze the mini-superspace model of (2+1)-dimensional gravity with the matter fields in the case of g=0 and g=1. For g=0, a wormhole solution is found but for g=1 we can not find an analogous solution. Quantum gravity is also considered and we succeed to perform the phase space reduction of (2+1)-dimensional gravity in the case of g=1 at the quantum level. From this analysis we argue that the conformal rotation is not necessary in the sense that the Euclidean quantum gravity is inappropriate for the full gravity. (author)

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

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)

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.)

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

OpenAIRE

Cowley, Benjamin R.; Kaufman, Matthew T.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2012-01-01

The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data)...

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.)

High dimensional model representation method for fuzzy structural dynamics

Science.gov (United States)

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.

An adaptive proper orthogonal decomposition method for model order reduction of multi-disc rotor system

Science.gov (United States)

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.

Multi-GPU accelerated three-dimensional FDTD method for electromagnetic simulation.

Science.gov (United States)

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.

A simple three dimensional wide-angle beam propagation method

Science.gov (United States)

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.

Euclidean D-branes and higher-dimensional gauge theory

International Nuclear Information System (INIS)

Acharya, B.S.; Figueroa-O'Farrill, J.M.; Spence, B.; O'Loughlin, M.

1997-07-01

We consider euclidean D-branes wrapping around manifolds of exceptional holonomy in dimensions seven and eight. The resulting theory on the D-brane-that is, the dimensional reduction of 10-dimensional supersymmetric Yang-Mills theory-is a cohomological field theory which describes the topology of the moduli space of instantons. The 7-dimensional theory is an N T =2 (or balanced) cohomological theory given by an action potential of Chern-Simons type. As a by-product of this method, we construct a related cohomological field theory which describes the monopole moduli space on a 7-manifold of G 2 holonomy. (author). 22 refs, 3 tabs

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

Measurement of cardiac ventricular volumes using multidetector row computed tomography: comparison of two- and three-dimensional methods

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.)

Variance Reduction Techniques in Monte Carlo Methods

NARCIS (Netherlands)

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

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

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

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 Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

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.

Science.gov (United States)

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 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.

Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

KAUST Repository

Ghasemi, Mohammadreza

2015-02-23

In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.

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.

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

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.

Canonical reduction of self-dual Yang-Mills equations to Fitzhugh-Nagumo equation and exact solutions

International Nuclear Information System (INIS)

Sayed, S.M.; Gharib, G.M.

2009-01-01

The (constrained) canonical reduction of four-dimensional self-dual Yang-Mills theory to two-dimensional Fitzhugh-Nagumo and the real Newell-Whitehead equations are considered. On the other hand, other methods and transformations are developed to obtain exact solutions for the original two-dimensional Fitzhugh-Nagumo and Newell-Whitehead equations. The corresponding gauge potential A μ and the gauge field strengths F μν are also obtained. New explicit and exact traveling wave and solitary solutions (for Fitzhugh-Nagumo and Newell-Whitehead equations) are obtained by using an improved sine-cosine method and the Wu's elimination method with the aid of Mathematica.

Low-Dimensional Feature Representation for Instrument Identification

Science.gov (United States)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Hypergraph-based anomaly detection of high-dimensional co-occurrences.

Science.gov (United States)

Silva, Jorge; Willett, Rebecca

2009-03-01

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.

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)

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 Statistical Method to Analyze Three-Dimensional Landmark Configurations Obtained with Cone-Beam CT: Basic Features and Clinical Application for Rapid Maxillary Expansion

Energy Technology Data Exchange (ETDEWEB)

Gamble, Jennifer; Lagravere, Manuel O.; Major, Paul W.; Heo, Giseon [University of Alberta, Edmonton (Canada)

2012-03-15

To describe a statistical method of three-dimensional landmark configuration data and apply it to an orthodontic data set comparing two types of rapid maxillary expansion (RME) treatments. Landmark configurations obtained from cone beam CT scans were used to represent patients in two types (please describe what were two types) of RME groups and a control group over four time points. A method using tools from persistent homology and dimensionality reduction is presented and used to identify variability between the subjects. The analysis was in agreement with previous results using conventional methods, which found significant differences between treatment groups and the control, but no distinction between the types of treatment. Additionally, it was found that second molar eruption varied considerably between the subjects, and this has not been evaluated in previous analyses. This method of analysis allows entire configurations to be considered as a whole, and does not require specific inter-landmark distances or angles to be selected. Sources of variability present themselves, without having to be individually sought after. This method is suggested as an additional tool for the analysis of landmark configuration data.

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.

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

Science.gov (United States)

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.

A Comparative Study of 3-Dimensional Titanium Versus 2-Dimensional Titanium Miniplates for Open Reduction and Fixation of Mandibular Parasymphysis Fracture.

Science.gov (United States)

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.

Analysis of wave motion in one-dimensional structures through fast-Fourier-transform-based wavelet finite element method

Science.gov (United States)

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.

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.

One-Dimensional Finite Elements An Introduction to the FE Method

CERN Document Server

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.

Three dimensional wavefield modeling using the pseudospectral method; Pseudospectral ho ni yoru sanjigen hadoba modeling

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.

Assessment of the reduction methods used to develop chemical schemes: building of a new chemical scheme for VOC oxidation suited to three-dimensional multiscale HOx-NOx-VOC chemistry simulations

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.

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.

Canonical reduction of self-dual Yang-Mills equations to Fitzhugh-Nagumo equation and exact solutions

Energy Technology Data Exchange (ETDEWEB)

Sayed, S.M. [Mathematics Department, Faculty of Science, Beni-Suef University, Beni-Suef (Egypt); Mathematics Department, P.O. Box 1144, Tabouk Teacher College, Ministry of Education (Saudi Arabia)], E-mail: eaashour@lycos.com; Gharib, G.M. [Mathematics Department, P.O. Box 1144, Tabouk Teacher College, Ministry of Education (Saudi Arabia)

2009-01-30

The (constrained) canonical reduction of four-dimensional self-dual Yang-Mills theory to two-dimensional Fitzhugh-Nagumo and the real Newell-Whitehead equations are considered. On the other hand, other methods and transformations are developed to obtain exact solutions for the original two-dimensional Fitzhugh-Nagumo and Newell-Whitehead equations. The corresponding gauge potential A{sub {mu}} and the gauge field strengths F{sub {mu}}{sub {nu}} are also obtained. New explicit and exact traveling wave and solitary solutions (for Fitzhugh-Nagumo and Newell-Whitehead equations) are obtained by using an improved sine-cosine method and the Wu's elimination method with the aid of Mathematica.

Vibration of carbon nanotubes with defects: order reduction methods

Science.gov (United States)

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.

One-dimensional reduction of viscous jets. I. Theory

Science.gov (United States)

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].

Four-Dimensional Data Assimilation Using the Adjoint Method

Science.gov (United States)

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.

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...

Method for the manufacture of a thin-layer battery stack on a three-dimensional substrate

NARCIS (Netherlands)

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

Wave field restoration using three-dimensional Fourier filtering method.

Science.gov (United States)

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.

The Chimera Method of Simulation for Unsteady Three-Dimensional Viscous Flow

Science.gov (United States)

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.

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

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.)

The analysis of carbohydrates in milk powder by a new "heart-cutting" two-dimensional liquid chromatography method.

Science.gov (United States)

Ma, Jing; Hou, Xiaofang; Zhang, Bing; Wang, Yunan; He, Langchong

2014-03-01

In this study, a new"heart-cutting" two-dimensional liquid chromatography method for the simultaneous determination of carbohydrate contents in milk powder was presented. In this two dimensional liquid chromatography system, a Venusil XBP-C4 analysis column was used in the first dimension ((1)D) as a pre-separation column, a ZORBAX carbohydrates analysis column was used in the second dimension ((2)D) as a final-analysis column. The whole process was completed in less than 35min without a particular sample preparation procedure. The capability of the new two dimensional HPLC method was demonstrated in the determination of carbohydrates in various brands of milk powder samples. A conventional one dimensional chromatography method was also proposed. The two proposed methods were both validated in terms of linearity, limits of detection, accuracy and precision. The comparison between the results obtained with the two methods showed that the new and completely automated two dimensional liquid chromatography method is more suitable for milk powder sample because of its online cleanup effect involved. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

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

State-space dimensionality in short-memory hidden-variable theories

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

Recently we have presented a hidden-variable model of measurements for a qubit where the hidden-variable state-space dimension is one-half the quantum-state manifold dimension. The absence of a short memory (Markov) dynamics is the price paid for this dimensional reduction. The conflict between having the Markov property and achieving the dimensional reduction was proved by Montina [A. Montina, Phys. Rev. A 77, 022104 (2008)] using an additional hypothesis of trajectory relaxation. Here we analyze in more detail this hypothesis introducing the concept of invertible process and report a proof that makes clearer the role played by the topology of the hidden-variable space. This is accomplished by requiring suitable properties of regularity of the conditional probability governing the dynamics. In the case of minimal dimension the set of continuous hidden variables is identified with an object living an N-dimensional Hilbert space whose dynamics is described by the Schroedinger equation. A method for generating the economical non-Markovian model for the qubit is also presented.

Comparison of Rigid and Adaptive Methods of Propagating Gross Tumor Volume Through Respiratory Phases of Four-Dimensional Computed Tomography Image Data Set

International Nuclear Information System (INIS)

Ezhil, Muthuveni; Choi, Bum; Starkschall, George; Bucci, M. Kara; Vedam, Sastry; Balter, Peter

2008-01-01

Purpose: To compare three different methods of propagating the gross tumor volume (GTV) through the respiratory phases that constitute a four-dimensional computed tomography image data set. Methods and Materials: Four-dimensional computed tomography data sets of 20 patients who had undergone definitive hypofractionated radiotherapy to the lung were acquired. The GTV regions of interest (ROIs) were manually delineated on each phase of the four-dimensional computed tomography data set. The ROI from the end-expiration phase was propagated to the remaining nine phases of respiration using the following three techniques: (1) rigid-image registration using in-house software, (2) rigid image registration using research software from a commercial radiotherapy planning system vendor, and (3) rigid-image registration followed by deformable adaptation originally intended for organ-at-risk delineation using the same software. The internal GTVs generated from the various propagation methods were compared with the manual internal GTV using the normalized Dice similarity coefficient (DSC) index. Results: The normalized DSC index of 1.01 ± 0.06 (SD) for rigid propagation using the in-house software program was identical to the normalized DSC index of 1.01 ± 0.06 for rigid propagation achieved with the vendor's research software. Adaptive propagation yielded poorer results, with a normalized DSC index of 0.89 ± 0.10 (paired t test, p <0.001). Conclusion: Propagation of the GTV ROIs through the respiratory phases using rigid- body registration is an acceptable method within a 1-mm margin of uncertainty. The adaptive organ-at-risk propagation method was not applicable to propagating GTV ROIs, resulting in an unacceptable reduction of the volume and distortion of the ROIs

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

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 simple method for in vivo measurement of implant rod three-dimensional geometry during scoliosis surgery.

Science.gov (United States)

Salmingo, Remel A; Tadano, Shigeru; Fujisaki, Kazuhiro; Abe, Yuichiro; Ito, Manabu

2012-05-01

Scoliosis is defined as a spinal pathology characterized as a three-dimensional deformity of the spine combined with vertebral rotation. Treatment for severe scoliosis is achieved when the scoliotic spine is surgically corrected and fixed using implanted rods and screws. Several studies performed biomechanical modeling and corrective forces measurements of scoliosis correction. These studies were able to predict the clinical outcome and measured the corrective forces acting on screws, however, they were not able to measure the intraoperative three-dimensional geometry of the spinal rod. In effect, the results of biomechanical modeling might not be so realistic and the corrective forces during the surgical correction procedure were intra-operatively difficult to measure. Projective geometry has been shown to be successful in the reconstruction of a three-dimensional structure using a series of images obtained from different views. In this study, we propose a new method to measure the three-dimensional geometry of an implant rod using two cameras. The reconstruction method requires only a few parameters, the included angle θ between the two cameras, the actual length of the rod in mm, and the location of points for curve fitting. The implant rod utilized in spine surgery was used to evaluate the accuracy of the current method. The three-dimensional geometry of the rod was measured from the image obtained by a scanner and compared to the proposed method using two cameras. The mean error in the reconstruction measurements ranged from 0.32 to 0.45 mm. The method presented here demonstrated the possibility of intra-operatively measuring the three-dimensional geometry of spinal rod. The proposed method could be used in surgical procedures to better understand the biomechanics of scoliosis correction through real-time measurement of three-dimensional implant rod geometry in vivo.

Two-dimensional semi-analytic nodal method for multigroup pin power reconstruction

International Nuclear Information System (INIS)

Seung Gyou, Baek; Han Gyu, Joo; Un Chul, Lee

2007-01-01

A pin power reconstruction method applicable to multigroup problems involving square fuel assemblies is presented. The method is based on a two-dimensional semi-analytic nodal solution which consists of eight exponential terms and 13 polynomial terms. The 13 polynomial terms represent the particular solution obtained under the condition of a 2-dimensional 13 term source expansion. In order to achieve better approximation of the source distribution, the least square fitting method is employed. The 8 exponential terms represent a part of the analytically obtained homogeneous solution and the 8 coefficients are determined by imposing constraints on the 4 surface average currents and 4 corner point fluxes. The surface average currents determined from a transverse-integrated nodal solution are used directly whereas the corner point fluxes are determined during the course of the reconstruction by employing an iterative scheme that would realize the corner point balance condition. The outgoing current based corner point flux determination scheme is newly introduced. The accuracy of the proposed method is demonstrated with the L336C5 benchmark problem. (authors)

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)

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

A novel forward projection-based metal artifact reduction method for flat-detector computed tomography

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))

A novel forward projection-based metal artifact reduction method for flat-detector computed tomography

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)).

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

One New Method to Generate 3-Dimensional Virtual Mannequin

Science.gov (United States)

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.

Homotopy decomposition method for solving one-dimensional time-fractional diffusion equation

Science.gov (United States)

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.

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...

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.

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)

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

Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients

KAUST Repository

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

A new method for information retrieval in two-dimensional grating-based X-ray phase contrast imaging

International Nuclear Information System (INIS)

Wang Zhi-Li; Gao Kun; Chen Jian; Ge Xin; Tian Yang-Chao; Wu Zi-Yu; Zhu Pei-Ping

2012-01-01

Grating-based X-ray phase contrast imaging has been demonstrated to be an extremely powerful phase-sensitive imaging technique. By using two-dimensional (2D) gratings, the observable contrast is extended to two refraction directions. Recently, we have developed a novel reverse-projection (RP) method, which is capable of retrieving the object information efficiently with one-dimensional (1D) grating-based phase contrast imaging. In this contribution, we present its extension to the 2D grating-based X-ray phase contrast imaging, named the two-dimensional reverse-projection (2D-RP) method, for information retrieval. The method takes into account the nonlinear contributions of two refraction directions and allows the retrieval of the absorption, the horizontal and the vertical refraction images. The obtained information can be used for the reconstruction of the three-dimensional phase gradient field, and for an improved phase map retrieval and reconstruction. Numerical experiments are carried out, and the results confirm the validity of the 2D-RP method

Levels of reduction in van Manen's phenomenological hermeneutic method: an empirical example.

Science.gov (United States)

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.

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...

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

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...

Higher-dimensional Bianchi type-VIh cosmologies

Science.gov (United States)

Lorenz-Petzold, D.

1985-09-01

The higher-dimensional perfect fluid equations of a generalization of the (1 + 3)-dimensional Bianchi type-VIh space-time are discussed. Bianchi type-V and Bianchi type-III space-times are also included as special cases. It is shown that the Chodos-Detweiler (1980) mechanism of cosmological dimensional-reduction is possible in these cases.

A GPU-based calculation using the three-dimensional FDTD method for electromagnetic field analysis.

Science.gov (United States)

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.

New method of 2-dimensional metrology using mask contouring

Science.gov (United States)

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.

Computational Methods for Inviscid and Viscous Two-and-Three-Dimensional Flow Fields.

Science.gov (United States)

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

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 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

Study of reduction methods for irradiation on oral mucositis. The examination of reduction methods for mucosal failure

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)

Development of 2-D/1-D fusion method for three-dimensional whole-core heterogeneous neutron transport calculations

International Nuclear Information System (INIS)

Lee, Gil Soo

2006-02-01

To describe power distribution and multiplication factor of a reactor core accurately, it is necessary to perform calculations based on neutron transport equation considering heterogeneous geometry and scattering angles. These calculations require very heavy calculations and were nearly impossible with computers of old days. From the limitation of computing power, traditional approach of reactor core design consists of heterogeneous transport calculation in fuel assembly level and whole core diffusion nodal calculation with assembly homogenized properties, resulting from fuel assembly transport calculation. This approach may be effective in computation time, but it gives less accurate results for highly heterogeneous problems. As potential for whole core heterogeneous transport calculation became more feasible owing to rapid development of computing power during last several years, the interests in two and three dimensional whole core heterogeneous transport calculations by deterministic method are increased. For two dimensional calculation, there were several successful approaches using even parity transport equation with triangular meshes, S N method with refined rectangular meshes, the method of characteristics (MOC) with unstructured meshes, and so on. The work in this thesis originally started from the two dimensional whole core heterogeneous transport calculation by using MOC. After successful achievement in two dimensional calculation, there were efforts in three-dimensional whole-core heterogeneous transport calculation using MOC. Since direct extension to three dimensional calculation of MOC requires too much computing power, indirect approach to three dimensional calculation was considered.Thus, 2D/1D fusion method for three dimensional heterogeneous transport calculation was developed and successfully implemented in a computer code. The 2D/1D fusion method is synergistic combination of the MOC for radial 2-D calculation and S N -like methods for axial 1

Method for simulating dose reduction in digital mammography using the Anscombe transformation

OpenAIRE

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...

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)

A Monte Carlo Green's function method for three-dimensional neutron transport

International Nuclear Information System (INIS)

Gamino, R.G.; Brown, F.B.; Mendelson, M.R.

1992-01-01

This paper describes a Monte Carlo transport kernel capability, which has recently been incorporated into the RACER continuous-energy Monte Carlo code. The kernels represent a Green's function method for neutron transport from a fixed-source volume out to a particular volume of interest. This method is very powerful transport technique. Also, since kernels are evaluated numerically by Monte Carlo, the problem geometry can be arbitrarily complex, yet exact. This method is intended for problems where an ex-core neutron response must be determined for a variety of reactor conditions. Two examples are ex-core neutron detector response and vessel critical weld fast flux. The response is expressed in terms of neutron transport kernels weighted by a core fission source distribution. In these types of calculations, the response must be computed for hundreds of source distributions, but the kernels only need to be calculated once. The advance described in this paper is that the kernels are generated with a highly accurate three-dimensional Monte Carlo transport calculation instead of an approximate method such as line-of-sight attenuation theory or a synthesized three-dimensional discrete ordinates solution

Three-dimensional protein structure prediction: Methods and computational strategies.

Science.gov (United States)

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.

A fast semi-discrete Kansa method to solve the two-dimensional spatiotemporal fractional diffusion equation

Science.gov (United States)

Sun, HongGuang; Liu, Xiaoting; Zhang, Yong; Pang, Guofei; Garrard, Rhiannon

2017-09-01

Fractional-order diffusion equations (FDEs) extend classical diffusion equations by quantifying anomalous diffusion frequently observed in heterogeneous media. Real-world diffusion can be multi-dimensional, requiring efficient numerical solvers that can handle long-term memory embedded in mass transport. To address this challenge, a semi-discrete Kansa method is developed to approximate the two-dimensional spatiotemporal FDE, where the Kansa approach first discretizes the FDE, then the Gauss-Jacobi quadrature rule solves the corresponding matrix, and finally the Mittag-Leffler function provides an analytical solution for the resultant time-fractional ordinary differential equation. Numerical experiments are then conducted to check how the accuracy and convergence rate of the numerical solution are affected by the distribution mode and number of spatial discretization nodes. Applications further show that the numerical method can efficiently solve two-dimensional spatiotemporal FDE models with either a continuous or discrete mixing measure. Hence this study provides an efficient and fast computational method for modeling super-diffusive, sub-diffusive, and mixed diffusive processes in large, two-dimensional domains with irregular shapes.

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 fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space

Science.gov (United States)

Wang, S.; Huang, G. H.; Huang, W.; Fan, Y. R.; Li, Z.

2015-10-01

In this study, a fractional factorial probabilistic collocation method is proposed to reveal statistical significance of hydrologic model parameters and their multi-level interactions affecting model outputs, facilitating uncertainty propagation in a reduced dimensional space. The proposed methodology is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability, as well as its capability of revealing complex and dynamic parameter interactions. A set of reduced polynomial chaos expansions (PCEs) only with statistically significant terms can be obtained based on the results of factorial analysis of variance (ANOVA), achieving a reduction of uncertainty in hydrologic predictions. The predictive performance of reduced PCEs is verified by comparing against standard PCEs and the Monte Carlo with Latin hypercube sampling (MC-LHS) method in terms of reliability, sharpness, and Nash-Sutcliffe efficiency (NSE). Results reveal that the reduced PCEs are able to capture hydrologic behaviors of the Xiangxi River watershed, and they are efficient functional representations for propagating uncertainties in hydrologic predictions.

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

Science.gov (United States)

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.

Isostable reduction with applications to time-dependent partial differential equations.

Science.gov (United States)

Wilson, Dan; Moehlis, Jeff

2016-07-01

Isostables and isostable reduction, analogous to isochrons and phase reduction for oscillatory systems, are useful in the study of nonlinear equations which asymptotically approach a stationary solution. In this work, we present a general method for isostable reduction of partial differential equations, with the potential power to reduce the dimensionality of a nonlinear system from infinity to 1. We illustrate the utility of this reduction by applying it to two different models with biological relevance. In the first example, isostable reduction of the Fokker-Planck equation provides the necessary framework to design a simple control strategy to desynchronize a population of pathologically synchronized oscillatory neurons, as might be relevant to Parkinson's disease. Another example analyzes a nonlinear reaction-diffusion equation with relevance to action potential propagation in a cardiac system.

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

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.

Noise-based tube current reduction method with iterative reconstruction for reduction of radiation exposure in coronary CT angiography

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

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

Review of noise reduction methods for centrifugal fans

Science.gov (United States)

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.

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

Efficient two-dimensional compressive sensing in MIMO radar

Science.gov (United States)

Shahbazi, Nafiseh; Abbasfar, Aliazam; Jabbarian-Jahromi, Mohammad

2017-12-01

Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed received signals and then we propose a new measurement matrix design for our 2D compressive sensing model that is based on minimizing the coherence of sensing matrix using gradient descent algorithm. The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.

Three-dimensional MRI Analysis of Femoral Head Remodeling After Reduction in Patients With Developmental Dysplasia of the Hip.

Science.gov (United States)

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

Four-dimensional Hall mechanics as a particle on CP3

International Nuclear Information System (INIS)

Bellucci, Stefano; Casteill, Pierre-Yves; Nersessian, Armen

2003-01-01

In order to establish an explicit connection between four-dimensional Hall effect on S 4 and six-dimensional Hall effect on CP 3 , we perform the Hamiltonian reduction of a particle moving on CP 3 in a constant magnetic field to the four-dimensional Hall mechanics (i.e., a-bar particle on S 4 in a SU(2) instanton field). This reduction corresponds to fixing the isospin of the latter system

Analysis and Reduction of Complex Networks Under Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Knio, Omar M

2014-04-09

This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

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.

Kaluza-Klein cosmology from five-dimensional Lovelock-Cartan theory

Science.gov (United States)

Castillo-Felisola, Oscar; Corral, Cristóbal; del Pino, Simón; Ramírez, Francisca

2016-12-01

We study the Kaluza-Klein dimensional reduction of the Lovelock-Cartan theory in five-dimensional spacetime, with a compact dimension of S1 topology. We find cosmological solutions of the Friedmann-Robertson-Walker class in the reduced spacetime. The torsion and the fields arising from the dimensional reduction induce a nonvanishing energy-momentum tensor in four dimensions. We find solutions describing expanding, contracting, and bouncing universes. The model shows a dynamical compactification of the extra dimension in some regions of the parameter space.

The interpolation method based on endpoint coordinate for CT three-dimensional image

International Nuclear Information System (INIS)

Suto, Yasuzo; Ueno, Shigeru.

1997-01-01

Image interpolation is frequently used to improve slice resolution to reach spatial resolution. Improved quality of reconstructed three-dimensional images can be attained with this technique as a result. Linear interpolation is a well-known and widely used method. The distance-image method, which is a non-linear interpolation technique, is also used to convert CT value images to distance images. This paper describes a newly developed method that makes use of end-point coordinates: CT-value images are initially converted to binary images by thresholding them and then sequences of pixels with 1-value are arranged in vertical or horizontal directions. A sequence of pixels with 1-value is defined as a line segment which has starting and end points. For each pair of adjacent line segments, another line segment was composed by spatial interpolation of the start and end points. Binary slice images are constructed from the composed line segments. Three-dimensional images were reconstructed from clinical X-ray CT images, using three different interpolation methods and their quality and processing speed were evaluated and compared. (author)

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)

A hybrid method for quasi-three-dimensional slope stability analysis in a municipal solid waste landfill

International Nuclear Information System (INIS)

Yu, L.; Batlle, F.

2011-01-01

Highlights: → A quasi-three-dimensional slope stability analysis method was proposed. → The proposed method is a good engineering tool for 3D slope stability analysis. → Factor of safety from 3D analysis is higher than from 2D analysis. → 3D analysis results are more sensitive to cohesion than 2D analysis. - Abstract: Limited space for accommodating the ever increasing mounds of municipal solid waste (MSW) demands the capacity of MSW landfill be maximized by building landfills to greater heights with steeper slopes. This situation has raised concerns regarding the stability of high MSW landfills. A hybrid method for quasi-three-dimensional slope stability analysis based on the finite element stress analysis was applied in a case study at a MSW landfill in north-east Spain. Potential slides can be assumed to be located within the waste mass due to the lack of weak foundation soils and geosynthetic membranes at the landfill base. The only triggering factor of deep-seated slope failure is the higher leachate level and the relatively high and steep slope in the front. The valley-shaped geometry and layered construction procedure at the site make three-dimensional slope stability analyses necessary for this landfill. In the finite element stress analysis, variations of leachate level during construction and continuous settlement of the landfill were taken into account. The 'equivalent' three-dimensional factor of safety (FoS) was computed from the individual result of the two-dimensional analysis for a series of evenly spaced cross sections within the potential sliding body. Results indicate that the hybrid method for quasi-three-dimensional slope stability analysis adopted in this paper is capable of locating roughly the spatial position of the potential sliding mass. This easy to manipulate method can serve as an engineering tool in the preliminary estimate of the FoS as well as the approximate position and extent of the potential sliding mass. The result that

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)

Dimensional reduction of a general advection–diffusion equation in 2D channels

Science.gov (United States)

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.

Two-dimensional simulation of broad-band ferrite electromagnetic wave absorbers by using the FDTD method

Energy Technology Data Exchange (ETDEWEB)

Yoon, Hyun Jin; Kim, Dong Il [Korea Maritime University, Busan (Korea, Republic of)

2004-10-15

The purpose of this simulation study is to design and fabricate an electromagnetic (EM) wave absorber in order to develop a wide-band absorber. We have proposed and modeled a bird-eye-type and cutting-cone-type EM wave absorber by using the equivalent material constants method (EMCM), and we simulated them by using a finite-difference time-domain (FDTD) method. A two or a three-dimensional simulation would be desirable to analyze the EM wave absorber characteristics and to develop new structures. The two-dimensional FDTD simulation requires less computer resources than a three-dimensional simulation to consider the structural effects of the EM wave absorbers. The numerical simulation by using the FDTD method shows propagating EM waves in various types of periodic structure EM wave absorbers. Simultaneously, a Fourier analysis is used to characterize the input pulse and the reflected EM waves for ferrite absorbers with various structures. The results have a wide-band reflection-reducing characteristic. The validity of the proposed model was confirmed by comparing the two-dimensional simulation with the experimental results. The simulations were carried out in the frequency band from 30 MHz to 10 GHz.

Two-dimensional simulation of broad-band ferrite electromagnetic wave absorbers by using the FDTD method

International Nuclear Information System (INIS)

Yoon, Hyun Jin; Kim, Dong Il

2004-01-01

The purpose of this simulation study is to design and fabricate an electromagnetic (EM) wave absorber in order to develop a wide-band absorber. We have proposed and modeled a bird-eye-type and cutting-cone-type EM wave absorber by using the equivalent material constants method (EMCM), and we simulated them by using a finite-difference time-domain (FDTD) method. A two or a three-dimensional simulation would be desirable to analyze the EM wave absorber characteristics and to develop new structures. The two-dimensional FDTD simulation requires less computer resources than a three-dimensional simulation to consider the structural effects of the EM wave absorbers. The numerical simulation by using the FDTD method shows propagating EM waves in various types of periodic structure EM wave absorbers. Simultaneously, a Fourier analysis is used to characterize the input pulse and the reflected EM waves for ferrite absorbers with various structures. The results have a wide-band reflection-reducing characteristic. The validity of the proposed model was confirmed by comparing the two-dimensional simulation with the experimental results. The simulations were carried out in the frequency band from 30 MHz to 10 GHz.

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)

Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model

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

A Feature Subset Selection Method Based On High-Dimensional Mutual Information

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Chee Keong Kwoh

2011-04-01

Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.

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

Modified Splitting FDTD Methods for Two-Dimensional Maxwell’s Equations

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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.

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

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

Science.gov (United States)

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.

New Traveling Wave Solutions of the Higher Dimensional Nonlinear Partial Differential Equation by the Exp-Function Method

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Hasibun Naher

2012-01-01

Full Text Available We construct new analytical solutions of the (3+1-dimensional modified KdV-Zakharov-Kuznetsev equation by the Exp-function method. Plentiful exact traveling wave solutions with arbitrary parameters are effectively obtained by the method. The obtained results show that the Exp-function method is effective and straightforward mathematical tool for searching analytical solutions with arbitrary parameters of higher-dimensional nonlinear partial differential equation.

Numerical comparison of robustness of some reduction methods in rough grids

KAUST Repository

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

A simplified method for rapid quantification of intracellular nucleoside triphosphates by one-dimensional thin-layer chromatography

DEFF Research Database (Denmark)

Jendresen, Christian Bille; Kilstrup, Mogens; Martinussen, Jan

2011-01-01

-pyrophosphate (PRPP), and inorganic pyrophosphate (PPi) in cell extracts. The method uses one-dimensional thin-layer chromatography (TLC) and radiolabeled biological samples. Nucleotides are resolved at the level of ionic charge in an optimized acidic ammonium formate and chloride solvent, permitting...... quantification of NTPs. The method is significantly simpler and faster than both current two-dimensional methods and high-performance liquid chromatography (HPLC)-based procedures, allowing a higher throughput while common sources of inaccuracies and technical problems are avoided. For determination of PPi...

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.

Posterior Reduction and Monosegmental Fusion with Intraoperative Three-dimensional Navigation System in the Treatment of High-grade Developmental Spondylolisthesis

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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

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)

Three-dimensional quantum electrodynamics as an effective interaction

International Nuclear Information System (INIS)

Abdalla, E.; Carvalho Filho, F.M. de

1995-10-01

We obtain a Quantum Electrodynamics in 2 + 1 dimensions by applying a Kaluza-Klein type method of dimensional reduction to Quantum Electrodynamics in 3 + 1 dimensions rendering the model more realistic to application in solid-state systems, invariant under translations in one direction. We show that the model obtained leads to an effective action exhibiting an interesting phase structure and that the generated Chern-Simons term survives only in the broken phase. (author). 20 refs

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 method for three-dimensional quantitative observation of the microstructure of biological samples

Science.gov (United States)

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.

Supersymmetric dimensional regularization

International Nuclear Information System (INIS)

Siegel, W.; Townsend, P.K.; van Nieuwenhuizen, P.

1980-01-01

There is a simple modification of dimension regularization which preserves supersymmetry: dimensional reduction to real D < 4, followed by analytic continuation to complex D. In terms of component fields, this means fixing the ranges of all indices on the fields (and therefore the numbers of Fermi and Bose components). For superfields, it means continuing in the dimensionality of x-space while fixing the dimensionality of theta-space. This regularization procedure allows the simple manipulation of spinor derivatives in supergraph calculations. The resulting rules are: (1) First do all algebra exactly as in D = 4; (2) Then do the momentum integrals as in ordinary dimensional regularization. This regularization procedure needs extra rules before one can say that it is consistent. Such extra rules needed for superconformal anomalies are discussed. Problems associated with renormalizability and higher order loops are also discussed

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

Variational Homotopy Perturbation Method for Solving Higher Dimensional Initial Boundary Value Problems

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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.

TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

International Nuclear Information System (INIS)

Liu, W; Sawant, A; Ruan, D

2016-01-01

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction

An analytical approach for a nodal scheme of two-dimensional neutron transport problems

International Nuclear Information System (INIS)

Barichello, L.B.; Cabrera, L.C.; Prolo Filho, J.F.

2011-01-01

Research highlights: → Nodal equations for a two-dimensional neutron transport problem. → Analytical Discrete Ordinates Method. → Numerical results compared with the literature. - Abstract: In this work, a solution for a two-dimensional neutron transport problem, in cartesian geometry, is proposed, on the basis of nodal schemes. In this context, one-dimensional equations are generated by an integration process of the multidimensional problem. Here, the integration is performed for the whole domain such that no iterative procedure between nodes is needed. The ADO method is used to develop analytical discrete ordinates solution for the one-dimensional integrated equations, such that final solutions are analytical in terms of the spatial variables. The ADO approach along with a level symmetric quadrature scheme, lead to a significant order reduction of the associated eigenvalues problems. Relations between the averaged fluxes and the unknown fluxes at the boundary are introduced as the usually needed, in nodal schemes, auxiliary equations. Numerical results are presented and compared with test problems.

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.

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

Science.gov (United States)

Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

2015-11-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

New results for algebraic tensor reduction of Feynman integrals

Energy Technology Data Exchange (ETDEWEB)

Fleischer, Jochem [Bielefeld Univ. (Germany). Fakultaet fuer Physik; Riemann, Tord [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Yundin, Valery [Copenhagen Univ. (Denmark). Niels Bohr International Academy and Discovery Center

2012-02-15

We report on some recent developments in algebraic tensor reduction of one-loop Feynman integrals. For 5-point functions, an efficient tensor reduction was worked out recently and is now available as numerical C++ package, PJFry, covering tensor ranks until five. It is free of inverse 5- point Gram determinants and inverse small 4-point Gram determinants are treated by expansions in higher-dimensional 3-point functions. By exploiting sums over signed minors, weighted with scalar products of chords (or, equivalently, external momenta), extremely efficient expressions for tensor integrals contracted with external momenta were derived. The evaluation of 7-point functions is discussed. In the present approach one needs for the reductions a (d +2)-dimensional scalar 5-point function in addition to the usual scalar basis of 1- to 4-point functions in the generic dimension d=4-2{epsilon}. When exploiting the four-dimensionality of the kinematics, this basis is sufficient. We indicate how the (d+2)-dimensional 5-point function can be evaluated. (orig.)

New results for algebraic tensor reduction of Feynman integrals

International Nuclear Information System (INIS)

Fleischer, Jochem; Yundin, Valery

2012-02-01

We report on some recent developments in algebraic tensor reduction of one-loop Feynman integrals. For 5-point functions, an efficient tensor reduction was worked out recently and is now available as numerical C++ package, PJFry, covering tensor ranks until five. It is free of inverse 5- point Gram determinants and inverse small 4-point Gram determinants are treated by expansions in higher-dimensional 3-point functions. By exploiting sums over signed minors, weighted with scalar products of chords (or, equivalently, external momenta), extremely efficient expressions for tensor integrals contracted with external momenta were derived. The evaluation of 7-point functions is discussed. In the present approach one needs for the reductions a (d +2)-dimensional scalar 5-point function in addition to the usual scalar basis of 1- to 4-point functions in the generic dimension d=4-2ε. When exploiting the four-dimensionality of the kinematics, this basis is sufficient. We indicate how the (d+2)-dimensional 5-point function can be evaluated. (orig.)

Image-Based Compression Method of Three-Dimensional Range Data with Texture

OpenAIRE

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...

Topology optimization for three-dimensional electromagnetic waves using an edge element-based finite-element method.

Science.gov (United States)

Deng, Yongbo; Korvink, Jan G

2016-05-01

This paper develops a topology optimization procedure for three-dimensional electromagnetic waves with an edge element-based finite-element method. In contrast to the two-dimensional case, three-dimensional electromagnetic waves must include an additional divergence-free condition for the field variables. The edge element-based finite-element method is used to both discretize the wave equations and enforce the divergence-free condition. For wave propagation described in terms of the magnetic field in the widely used class of non-magnetic materials, the divergence-free condition is imposed on the magnetic field. This naturally leads to a nodal topology optimization method. When wave propagation is described using the electric field, the divergence-free condition must be imposed on the electric displacement. In this case, the material in the design domain is assumed to be piecewise homogeneous to impose the divergence-free condition on the electric field. This results in an element-wise topology optimization algorithm. The topology optimization problems are regularized using a Helmholtz filter and a threshold projection method and are analysed using a continuous adjoint method. In order to ensure the applicability of the filter in the element-wise topology optimization version, a regularization method is presented to project the nodal into an element-wise physical density variable.

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.

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.

Right ventricular volume determination by two-dimensional echocardiography and radiography in model hearts using a subtraction method

International Nuclear Information System (INIS)

Krebs, W.; Erbel, R.; Schweizer, P.; Richter, H.A.; Massberg, I.; Meyer, J.; Effert, S.; Henn, G.

1982-01-01

The irregularity and complexity of the right ventricle is the reason why no accurate method for right ventricular volume determination exists. A new method for right ventricular volume determination particularly for two-dimensional echocardiography was developed - it is called subtraction method - and was compared with the pyramid and Simpson's methods. The partial volume of the left ventricle and septum was subtracted from total volume of right and left ventricle including interventricular septum. Thus right ventricular volume resulted. Total and partial volume were computer-assisted calculated by use of biplane methods, preferably Simpson's rule. The method was proved with thinwall silicon-rubber model hearts of the left and right ventricle. Two orthogonal planes in the long-axis were filmed by radiography or scanned in a water bath by two-dimensional echocardiography equivalent to RAO and LAO-projections of cineangiocardiograms or to four- and two-chamber views of apical two-dimensional echocardiograms. For calculation of the major axes of the elliptical sections, summed up by Simpson's rule, they were derived from the LAO-projection and the four-chamber view, respectively, the minor axis approximated from the RAO-projection and the two-chamber view. For comparison of direct-measured volume and two-dimensional echocardiographically determined volume, regression equation was given by y = 1.01 x - 3.2, correlation-coefficient, r = 0.977, and standard error of estimate (SEE) +-10.5 ml. For radiography, regression equation was y = 0.909 x + 13.3, r = 0.983, SEE = +-8.0 ml. For pyramid method and Simpson's rule, higher standard errors and lower correlation coefficients were found. Between radiography and two-dimensional echocardiography a mean difference of 4.3 +- 13.2 ml, using subtraction method, and -10.2 +- 22.9 ml, using pyramid method, as well as -0.6 +- 18.5 ml, using Simpson's rule, were calculated for right ventricular volume measurements. (orig./APR) [de

Extended supersymmetry in four-dimensional Euclidean space

International Nuclear Information System (INIS)

McKeon, D.G.C.; Sherry, T.N.

2000-01-01

Since the generators of the two SU(2) groups which comprise SO(4) are not Hermitian conjugates of each other, the simplest supersymmetry algebra in four-dimensional Euclidean space more closely resembles the N=2 than the N=1 supersymmetry algebra in four-dimensional Minkowski space. An extended supersymmetry algebra in four-dimensional Euclidean space is considered in this paper; its structure resembles that of N=4 supersymmetry in four-dimensional Minkowski space. The relationship of this algebra to the algebra found by dimensionally reducing the N=1 supersymmetry algebra in ten-dimensional Euclidean space to four-dimensional Euclidean space is examined. The dimensional reduction of N=1 super Yang-Mills theory in ten-dimensional Minkowski space to four-dimensional Euclidean space is also considered

Exact rebinning methods for three-dimensional PET.

Science.gov (United States)

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.

The ADO-nodal method for solving two-dimensional discrete ordinates transport problems

International Nuclear Information System (INIS)

Barichello, L.B.; Picoloto, C.B.; Cunha, R.D. da

2017-01-01

Highlights: • Two-dimensional discrete ordinates neutron transport. • Analytical Discrete Ordinates (ADO) nodal method. • Heterogeneous media fixed source problems. • Local solutions. - Abstract: In this work, recent results on the solution of fixed-source two-dimensional transport problems, in Cartesian geometry, are reported. Homogeneous and heterogeneous media problems are considered in order to incorporate the idea of arbitrary number of domain division into regions (nodes) when applying the ADO method, which is a method of analytical features, to those problems. The ADO-nodal formulation is developed, for each node, following previous work devoted to heterogeneous media problem. Here, however, the numerical procedure is extended to higher number of domain divisions. Such extension leads, in some cases, to the use of an iterative method for solving the general linear system which defines the arbitrary constants of the general solution. In addition to solve alternative heterogeneous media configurations than reported in previous works, the present approach allows comparisons with results provided by other metodologies generated with refined meshes. Numerical results indicate the ADO solution may achieve a prescribed accuracy using coarser meshes than other schemes.

Experimental study on two-dimensional film flow with local measurement methods

Energy Technology Data Exchange (ETDEWEB)

Yang, Jin-Hwa, E-mail: evo03@snu.ac.kr [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Cho, Hyoung-Kyu [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Kim, Seok [Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Euh, Dong-Jin, E-mail: djeuh@kaeri.re.kr [Korea Atomic Energy Research Institute, 989-111, Daedeok-daero, Yuseong-gu, Daejeon 305-600 (Korea, Republic of); Park, Goon-Cherl [Nuclear Thermal-Hydraulic Engineering Laboratory, Seoul National University, Gwanak 599, Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of)

2015-12-01

Highlights: • An experimental study on the two-dimensional film flow with lateral air injection was performed. • The ultrasonic thickness gauge was used to measure the local liquid film thickness. • The depth-averaged PIV (Particle Image Velocimetry) method was applied to measure the local liquid film velocity. • The uncertainty of the depth-averaged PIV was quantified with a validation experiment. • Characteristics of two-dimensional film flow were classified following the four different flow patterns. - Abstract: In an accident condition of a nuclear reactor, multidimensional two-phase flows may occur in the reactor vessel downcomer and reactor core. Therefore, those have been regarded as important issues for an advanced thermal-hydraulic safety analysis. In particular, the multi-dimensional two-phase flow in the upper downcomer during the reflood phase of large break loss of coolant accident appears with an interaction between a downward liquid and a transverse gas flow, which determines the bypass flow rate of the emergency core coolant and subsequently, the reflood coolant flow rate. At present, some thermal-hydraulic analysis codes incorporate multidimensional modules for the nuclear reactor safety analysis. However, their prediction capability for the two-phase cross flow in the upper downcomer has not been validated sufficiently against experimental data based on local measurements. For this reason, an experimental study was carried out for the two-phase cross flow to clarify the hydraulic phenomenon and provide local measurement data for the validation of the computational tools. The experiment was performed in a 1/10 scale unfolded downcomer of Advanced Power Reactor 1400 (APR1400). Pitot tubes, a depth-averaged PIV method and ultrasonic thickness gauge were applied for local measurement of the air velocity, the liquid film velocity and the liquid film thickness, respectively. The uncertainty of the depth-averaged PIV method for the averaged

Experimental study on two-dimensional film flow with local measurement methods

International Nuclear Information System (INIS)

Yang, Jin-Hwa; Cho, Hyoung-Kyu; Kim, Seok; Euh, Dong-Jin; Park, Goon-Cherl

2015-01-01

Highlights: • An experimental study on the two-dimensional film flow with lateral air injection was performed. • The ultrasonic thickness gauge was used to measure the local liquid film thickness. • The depth-averaged PIV (Particle Image Velocimetry) method was applied to measure the local liquid film velocity. • The uncertainty of the depth-averaged PIV was quantified with a validation experiment. • Characteristics of two-dimensional film flow were classified following the four different flow patterns. - Abstract: In an accident condition of a nuclear reactor, multidimensional two-phase flows may occur in the reactor vessel downcomer and reactor core. Therefore, those have been regarded as important issues for an advanced thermal-hydraulic safety analysis. In particular, the multi-dimensional two-phase flow in the upper downcomer during the reflood phase of large break loss of coolant accident appears with an interaction between a downward liquid and a transverse gas flow, which determines the bypass flow rate of the emergency core coolant and subsequently, the reflood coolant flow rate. At present, some thermal-hydraulic analysis codes incorporate multidimensional modules for the nuclear reactor safety analysis. However, their prediction capability for the two-phase cross flow in the upper downcomer has not been validated sufficiently against experimental data based on local measurements. For this reason, an experimental study was carried out for the two-phase cross flow to clarify the hydraulic phenomenon and provide local measurement data for the validation of the computational tools. The experiment was performed in a 1/10 scale unfolded downcomer of Advanced Power Reactor 1400 (APR1400). Pitot tubes, a depth-averaged PIV method and ultrasonic thickness gauge were applied for local measurement of the air velocity, the liquid film velocity and the liquid film thickness, respectively. The uncertainty of the depth-averaged PIV method for the averaged

Hamiltonian reduction and supersymmetric mechanics with Dirac monopole

International Nuclear Information System (INIS)

Bellucci, Stefano; Nersessian, Armen; Yeranyan, Armen

2006-01-01

We apply the technique of Hamiltonian reduction for the construction of three-dimensional N=4 supersymmetric mechanics specified by the presence of a Dirac monopole. For this purpose we take the conventional N=4 supersymmetric mechanics on the four-dimensional conformally-flat spaces and perform its Hamiltonian reduction to three-dimensional system. We formulate the final system in the canonical coordinates, and present, in these terms, the explicit expressions of the Hamiltonian and supercharges. We show that, besides a magnetic monopole field, the resulting system is specified by the presence of a spin-orbit coupling term. A comparision with previous work is also carried out

Two-dimensional filtering of SPECT images using the Metz and Wiener filters

International Nuclear Information System (INIS)

King, M.A.; Schwinger, R.B.; Penney, B.C.; Doherty, P.W.

1984-01-01

Presently, single photon emission computed tomographic (SPECT) images are usually reconstructed by arbitrarily selecting a one-dimensional ''window'' function for use in reconstruction. A better method would be to automatically choose among a family of two-dimensional image restoration filters in such a way as to produce ''optimum'' image quality. Two-dimensional image processing techniques offer the advantages of a larger statistical sampling of the data for better noise reduction, and two-dimensional image deconvolution to correct for blurring during acquisition. An investigation of two such ''optimal'' digital image restoration techniques (the count-dependent Metz filter and the Wiener filter) was made. They were applied both as two-dimensional ''window'' functions for preprocessing SPECT images, and for filtering reconstructed images. Their performance was compared by measuring image contrast and per cent fractional standard deviation (% FSD) in multiple-acquisitions of the Jaszczak SPECT phantom at two different count levels. A statistically significant increase in image contrast and decrease in % FSD was observed with these techniques when compared to the results of reconstruction with a ramp filter. The adaptability of the techniques was manifested in a lesser % reduction in % FSD at the high count level coupled with a greater enhancement in image contrast. Using an array processor, processing time was 0.2 sec per image for the Metz filter and 3 sec for the Wiener filter. It is concluded that two-dimensional digital image restoration with these techniques can produce a significant increase in SPECT image quality

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)

Improved non-dimensional dynamic influence function method for vibration analysis of arbitrarily shaped plates with clamped edges

Directory of Open Access Journals (Sweden)

Sang-Wook Kang

2016-03-01

Full Text Available A new formulation for the non-dimensional dynamic influence function method, which was developed by the authors, is proposed to efficiently extract eigenvalues and mode shapes of clamped plates with arbitrary shapes. Compared with the finite element and boundary element methods, the non-dimensional dynamic influence function method yields highly accurate solutions in eigenvalue analysis problems of plates and membranes including acoustic cavities. However, the non-dimensional dynamic influence function method requires the uneconomic procedure of calculating the singularity of a system matrix in the frequency range of interest for extracting eigenvalues because it produces a non-algebraic eigenvalue problem. This article describes a new approach that reduces the problem of free vibrations of clamped plates to an algebraic eigenvalue problem, the solution of which is straightforward. The validity and efficiency of the proposed method are illustrated through several numerical examples.

Shroud leakage flow models and a multi-dimensional coupling CFD (computational fluid dynamics) method for shrouded turbines

International Nuclear Information System (INIS)

Zou, Zhengping; Liu, Jingyuan; Zhang, Weihao; Wang, Peng

2016-01-01

Multi-dimensional coupling simulation is an effective approach for evaluating the flow and aero-thermal performance of shrouded turbines, which can balance the simulation accuracy and computing cost effectively. In this paper, 1D leakage models are proposed based on classical jet theories and dynamics equations, which can be used to evaluate most of the main features of shroud leakage flow, including the mass flow rate, radial and circumferential momentum, temperature and the jet width. Then, the 1D models are expanded to 2D distributions on the interface by using a multi-dimensional scaling method. Based on the models and multi-dimensional scaling, a multi-dimensional coupling simulation method for shrouded turbines is developed, in which, some boundary source and sink are set on the interface between the shroud and the main flow passage. To verify the precision, some simulations on the design point and off design points of a 1.5 stage turbine are conducted. It is indicated that the models and methods can give predictions with sufficient accuracy for most of the flow field features and will contribute to pursue deeper understanding and better design methods of shrouded axial turbines, which are the important devices in energy engineering. - Highlights: • Free and wall attached jet theories are used to model the leakage flow in shrouds. • Leakage flow rate is modeled by virtual labyrinth number and residual-energy factor. • A scaling method is applied to 1D model to obtain 2D distributions on interfaces. • A multi-dimensional coupling CFD method for shrouded turbines is proposed. • The proposed coupling method can give accurate predictions with low computing cost.

Reduction theories elucidate the origins of complex biological rhythms generated by interacting delay-induced oscillations.

Directory of Open Access Journals (Sweden)

Ikuhiro Yamaguchi

Full Text Available Time delay is known to induce sustained oscillations in many biological systems such as electroencephalogram (EEG activities and gene regulations. Furthermore, interactions among delay-induced oscillations can generate complex collective rhythms, which play important functional roles. However, due to their intrinsic infinite dimensionality, theoretical analysis of interacting delay-induced oscillations has been limited. Here, we show that the two primary methods for finite-dimensional limit cycles, namely, the center manifold reduction in the vicinity of the Hopf bifurcation and the phase reduction for weak interactions, can successfully be applied to interacting infinite-dimensional delay-induced oscillations. We systematically derive the complex Ginzburg-Landau equation and the phase equation without delay for general interaction networks. Based on the reduced low-dimensional equations, we demonstrate that diffusive (linearly attractive coupling between a pair of delay-induced oscillations can exhibit nontrivial amplitude death and multimodal phase locking. Our analysis provides unique insights into experimentally observed EEG activities such as sudden transitions among different phase-locked states and occurrence of epileptic seizures.

Analysis of Elastic-Plastic J Integrals for 3-Dimensional Cracks Using Finite Element Alternating Method

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

Four lectures on probabilistic methods for data science

OpenAIRE

Vershynin, Roman

2016-01-01

Methods of high-dimensional probability play a central role in applications for statistics, signal processing theoretical computer science and related fields. These lectures present a sample of particularly useful tools of high-dimensional probability, focusing on the classical and matrix Bernstein's inequality and the uniform matrix deviation inequality. We illustrate these tools with applications for dimension reduction, network analysis, covariance estimation, matrix comp...

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

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 coupled Eulerian/Lagrangian method for the solution of three-dimensional vortical flows

Science.gov (United States)

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.

Approximate solutions for the two-dimensional integral transport equation. The critically mixed methods of resolution

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

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

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

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

Microbial activity in aquatic environments measured by dimethyl sulfoxide reduction and intercomparison with commonly used methods.

Science.gov (United States)

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

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)

Registration and three-dimensional reconstruction of autoradiographic images by the disparity analysis method

International Nuclear Information System (INIS)

Zhao, Weizhao; Ginsberg, M.; Young, T.Y.

1993-01-01

Quantitative autoradiography is a powerful radio-isotopic-imaging method for neuroscientists to study local cerebral blood flow and glucose-metabolic rate at rest, in response to physiologic activation of the visual, auditory, somatosensory, and motor systems, and in pathologic conditions. Most autoradiographic studies analyze glucose utilization and blood flow in two-dimensional (2-D) coronal sections. With modern digital computer and image-processing techniques, a large number of closely spaced coronal sections can be stacked appropriately to form a three-dimensional (3-d) image. 3-D autoradiography allows investigators to observe cerebral sections and surfaces from any viewing angle. A fundamental problem in 3-D reconstruction is the alignment (registration) of the coronal sections. A new alignment method based on disparity analysis is presented which can overcome many of the difficulties encountered by previous methods. The disparity analysis method can deal with asymmetric, damaged, or tilted coronal sections under the same general framework, and it can be used to match coronal sections of different sizes and shapes. Experimental results on alignment and 3-D reconstruction are presented

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.)

Three-dimensional forward modeling of DC resistivity using the aggregation-based algebraic multigrid method

Science.gov (United States)

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.

A general mixed boundary model reduction method for component mode synthesis

NARCIS (Netherlands)

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

An indigenous method for closed reduction of pediatric mandibular parasymphysis fracture.

Science.gov (United States)

Kumar, Naresh; Singh, Akhilesh Kumar; Pandey, Arun; Verma, Vishal

2015-01-01

Mandibular fractures in children are very rare as compared to adults due to protected anatomic features of child and less exposure to road traffic accidents. Management becomes complicated due to inherent dynamic nature, instability of mixed dentition and fear of surgery. Conservative management can be done with the help of acrylic cap splints along with circum-mandibular wiring, intermaxillary fixation with eyelet wires, arch wires or open reduction and internal fixation with bio-resorbable plates. Different methods have various pros and cons. The choice of anesthesia is also very crucial sometimes. This case report describes a new method of closed reduction with 18 gauge needle simulated as an arch bar performed under local anaesthesia.

Application of a method for comparing one-dimensional and two-dimensional models of a ground-water flow system

International Nuclear Information System (INIS)

Naymik, T.G.

1978-01-01

To evaluate the inability of a one-dimensional ground-water model to interact continuously with surrounding hydraulic head gradients, simulations using one-dimensional and two-dimensional ground-water flow models were compared. This approach used two types of models: flow-conserving one-and-two dimensional models, and one-dimensional and two-dimensional models designed to yield two-dimensional solutions. The hydraulic conductivities of controlling features were varied and model comparison was based on the travel times of marker particles. The solutions within each of the two model types compare reasonably well, but a three-dimensional solution is required to quantify the comparison

Comparison of preconditioned generalized conjugate gradient methods to two-dimensional neutron and photon transport equation

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)

Upscaling permeability for three-dimensional fractured porous rocks with the multiple boundary method

Science.gov (United States)

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.

Sensor assembly method using silicon interposer with trenches for three-dimensional binocular range sensors

Science.gov (United States)

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.

Fourier method for three-dimensional partial differential equations in periodic geometry. Application: HELIAC

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

On the integrability of a Hamiltonian reduction of a 2+1-dimensional non-isothermal rotating gas cloud system

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

Two dimensional PMMA nanofluidic device fabricated by hot embossing and oxygen plasma assisted thermal bonding methods

Science.gov (United States)

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.

Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations

KAUST Repository

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

Beam shape coefficients calculation for an elliptical Gaussian beam with 1-dimensional quadrature and localized approximation methods

Science.gov (United States)

Wang, Wei; Shen, Jianqi

2018-06-01

The use of a shaped beam for applications relying on light scattering depends much on the ability to evaluate the beam shape coefficients (BSC) effectively. Numerical techniques for evaluating the BSCs of a shaped beam, such as the quadrature, the localized approximation (LA), the integral localized approximation (ILA) methods, have been developed within the framework of generalized Lorenz-Mie theory (GLMT). The quadrature methods usually employ the 2-/3-dimensional integrations. In this work, the expressions of the BSCs for an elliptical Gaussian beam (EGB) are simplified into the 1-dimensional integral so as to speed up the numerical computation. Numerical results of BSCs are used to reconstruct the beam field and the fidelity of the reconstructed field to the given beam field is estimated. It is demonstrated that the proposed method is much faster than the 2-dimensional integrations and it can acquire more accurate results than the LA method. Limitations of the quadrature method and also the LA method in the numerical calculation are analyzed in detail.

Comparison of two dimensional and three dimensional radiotherapy treatment planning in locally advanced non-small cell lung cancer treated with continuous hyperfractionated accelerated radiotherapy weekend less

International Nuclear Information System (INIS)

Wilson, Elena M.; Joy Williams, Frances; Ethan Lyn, Basil; Aird, Edwin G.A.

2005-01-01

Background and purpose: Patients with inoperable non-small cell lung cancer being treated with continuous hyperfractionated accelerated radiotherapy weekend less (CHARTWEL) were planned and treated with a three dimensional (3D) conformal protocol and comparison made with two dimensional (2D) planning, as used previously, to compare past practice and methods. Patients and methods: Twenty-four patients were planned initially using 3D and then replanned using a 2D system. The 2D plans were transferred onto the 3D system and recalculated. Dose volume histograms could then be constructed of planning target volumes for phases 1 and 2 (PTV 1 and 2, respectively), lung and spinal cord for the 2D plans and compared with the 3D plans. Results: There was a significantly lower absolute dose to the isocentre with 2D compared to 3D planning with dose reductions of 3.9% for phase 1, 4.4% for phase 2 and 4.7% for those treated with a single phase. Maximum dose to spinal cord was greater in 17 of the 24 2D plans with a median dose reduction of 0.82 Gy for 3D (P=0.04). The percentage volume of whole lung receiving ≥20 Gy (V 20 ) was greater in 16 of the 24 2D plans with a median reduction in V 20 of 2.4% for 3D (P=0.03). Conclusions: A lower dose to tumour was obtained using 2D planning due to the method of dose calculation and spinal cord and lung doses were significantly higher

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.

Three-dimensional ICT reconstruction

International Nuclear Information System (INIS)

Zhang Aidong; Li Ju; Chen Fa; Sun Lingxia

2005-01-01

The three-dimensional ICT reconstruction method is the hot topic of recent ICT technology research. In the context, qualified visual three-dimensional ICT pictures are achieved through multi-piece two-dimensional images accumulation by, combining with thresholding method and linear interpolation. Different direction and different position images of the reconstructed pictures are got by rotation and interception respectively. The convenient and quick method is significantly instructive to more complicated three-dimensional reconstruction of ICT images. (authors)

Three-dimensional ICT reconstruction

International Nuclear Information System (INIS)

Zhang Aidong; Li Ju; Chen Fa; Sun Lingxia

2004-01-01

The three-dimensional ICT reconstruction method is the hot topic of recent ICT technology research. In the context qualified visual three-dimensional ICT pictures are achieved through multi-piece two-dimensional images accumulation by order, combining with thresholding method and linear interpolation. Different direction and different position images of the reconstructed pictures are got by rotation and interception respectively. The convenient and quick method is significantly instructive to more complicated three-dimensional reconstruction of ICT images. (authors)

High index surfaces of Au-nanocrystals supported on one-dimensional MoO3-nanorod as a bi-functional electrocatalyst for ethanol oxidation and oxygen reduction

International Nuclear Information System (INIS)

Karuppasamy, L.; Chen, C.Y.; Anandan, S.; Wu, J.J.

2017-01-01

Highlights: •Synthesis of a new class of Au nanocrystals enclosed with high index surface supported on MoO 3 nanorods by ultrasonic probe method. •The role of supporting materials reduces the loading of Au and acts as a co-catalyst. •The as prepared electrocatalyst exhibits enhanced catalytic activity and stability towards both EOR and ORR. -- Abstract: The design of highly active electrocatalyst for ethanol electrooxidation (EOR) and oxygen reduction reaction (ORR) is of great significance for the improvement of efficient direct ethanol fuel cells (DEFCs). Therefore, creating high index facets nanocrystals with abundant catalytic active sites of stepped atoms is an effective way to enhance the electrocatalytic performance. In this article, we prepared the high index surface structures of Au nanocrystals supported on one-dimensional (1-D) MoO 3 nanorods by using two steps ultrasonic probe irradiation method. The size and physical properties of as electrocatalysts were studied by using field emission scanning electron microscopy (FE-SEM), high-resolution transmission electron microscopy (HR-TEM), and x-ray diffraction (XRD) instrumentation. Besides, the catalytic activity of as Au-MoO 3 electrocatalyst was determined by using cyclic voltammetry (CV), chronoamperometric (CA), electrochemical impedance spectroscopy (EIS), CO-stripping, and linear sweep voltammetry-rotating disk electrode (LSV-RDE). As a consequence, the Au-MoO 3 nanocomposites has been considered as an effective electrocatalyst for both ethanol oxidation and oxygen reduction reaction.